Exercise, Protein and Vitamin D for Type 2 Diabetes Mellitus

By

Eliza Grace Miller

Bachelor of Food Science and Nutrition (Honours)

School of Exercise and Nutrition Sciences

Faculty of Health

Deakin University

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

May 24, 2017

sfol

Retracted Stamp

sfol

Retracted Stamp

Acknowledgements

It is with utmost gratitude that I acknowledge the endless support, guidance and

patience of my principal supervisor, Professor Robin Daly. Without his wealth of

knowledge and experience this thesis would not have been possible. His belief and

confidence in not only me but all his students along with his resolve in fostering the

development of the next generation of researchers is to be commended. I consider it

a tremendous honour to have been fortunate enough to work with Professor Robin

Daly.

I am additionally indebted to my co-supervisors, Professor Caryl Nowson and

Professor David Dunstan for their academic support and willingness to provide

assistance when requested.

To Belinda De Ross, your invaluable assistance with the implementation and

management of REVAMP-IT along with data collection is greatly appreciated.

Further, to all the members of the Daly research team, my fellow PhD students, other

staff and colleagues within the School of Exercise and Nutrition Sciences, I am

thankful to all of you for your everlasting encouragement, friendship and guidance.

To the directors, practice managers and Exercise Physiologists and Scientists at

Kieser Training Australia your hard-work and diligence was crucial to the successful

completion of REVAMP-IT and I cannot thank-you enough for this effort.

Finally, thank-you to my greatest supporters and the most wonderful people in the

entire world- my parents Fiona and Robert Miller and my two younger sisters April

and Charlotte. There are simply not enough words for me to express my love and

gratitude for your eternal support, encouragement, love, friendship and the belief you

have in me that I can achieve anything I set out to in my life. Each of you inspire me

each day with the enthusiasm, dedication and commitment you show to your own

work/studies and life in its entirety.

List of Original Publications

Chapter 3

Miller. E.G., Sethi. P., Nowson. C.A., Dunstan. D.W., Daly. R.M. 2016 ‘Effects of

Progressive Resistance Training and Weight Loss versus Weight Loss alone on

Inflammatory and Endothelial Biomarkers in Older Adults with Type 2 Diabetes.’

European Journal of Applied Physiology. 117(8): 1669.

Chapter 4

Daly. R.M., Miller. E.G., Dunstan. D.W., Nowson. C.A., Kerr. D., Solah. V.,

Menzies. D. 2014 ‘The Effects of Progressive Resistance Training Combined with a

Whey-Protein Drink and Vitamin D Supplementation on Glycaemic Control, Body

Composition and Cardiometabolic Risk Factors in Older Adults with Type 2 Diabetes:

Study Protocol for a Randomised Controlled Trial.’ Trials. 15(1): 431.

Chapter 5

Miller. E.G., Dunstan. D.W., Nowson. C.A., Kerr. D., Solah. V., Menzies. D, Daly.

R.M, 2016 ‘Recruitment of older adults with type 2 diabetes into a community-based

exercise and nutrition randomised controlled trial.’ Trials. 17(1):467.

List of Accepted Conference Abstracts

September 2014

Challenges of Recruiting Type 2 Diabetes Mellitus Patients into a 6-Month

Randomised Controlled Trial

Deakin University Higher Degree by Research Symposium

Melbourne, Australia

September 2015

Exercise, Weight Loss and Inflammation in Older Adults with Type 2 Diabetes: A 12-

Month Randomised Controlled Trial

Deakin University Higher Degree by Research Symposium

Melbourne, Australia

June 2016

Effects of Progressive Resistance Training and Weight Loss versus Weight Loss

alone on Inflammatory and Endothelial Biomarkers in Older Adults with Type 2

Diabetes: A 12-month Randomised Controlled Trial

World Congress on Active Ageing

Melbourne, Australia

September 2016

Exercise Plus Protein and Vitamin D for Adults with Type 2 Diabetes

Deakin University Higher Degree by Research Symposium

Melbourne, Australia

Page | I

Table of Contents

Table of Contents I Abbreviations VII List of Tables X List of Figures XIV List of Appendices XXI

Chapter 1 Introduction

1.1 Research Problem 2 1.2 Thesis Aims 6 1.3 Thesis Hypothesis 7 1.4 Significance of this Research 7

Chapter 2 Review of the Literature

2.1 Type 2 Diabetes – A Global Health Problem 10 2.2 The Economic Burden of Type 2 Diabetes 12 2.3 Pathophysiology of Type 2 Diabetes 13 2.4 Defining Pre-Diabetes and Type 2 Diabetes 14 2.5 Risk Factors for the Development of Type 2 Diabetes 15 2.6 Prevention of Type 2 Diabetes 22 2.7 Exercise for the Management of Type 2 Diabetes 24

2.7.1 Aerobic Training and Type 2 Diabetes 25 2.7.2 Progressive Resistance Training and Type 2 Diabetes 25

2.7.2.1 Effects of PRT on Body Composition 26 2.7.2.2 Effects of PRT on Glycaemic and Insulinaemic Outcomes 35 2.7.2.3 Effects of PRT on Markers of Inflammation 38 2.7.2.4 Effects of PRT on Blood Pressure and Blood Lipids 40

2.7.3 Efficacy of Community-Based Resistance Training Programs 42 2.8 Nutrition for the Management of Type 2 Diabetes 44

2.8.1 High Protein Diets for the Management of Type 2 Diabetes 45

2.8.1.1 Effects of a High Protein Diet on Glycaemic and Insulinaemic Outcomes 45

2.8.1.2 Effects of a High Protein Diet on Body Composition 47

2.8.1.3 Effects of High Protein Diets on Lipids, Blood Pressure and Markers of Inflammation

49

2.8.1.4 Potential Problems with Prescribing High Protein Diets 50 2.8.2 Protein Supplements for the Management of Type 2 Diabetes 51

2.8.2.1 Effect of Whey Protein on Weight and Fat Mass 54

Page | II

2.8.2.2 Effect of Whey Protein on Lean Mass 55

2.8.2.3 Effect of Whey Protein on Glycaemic and Insulinaemic Outcomes

58

2.8.2.4 Effect of Whey Protein on Markers of Inflammation 61 2.8.2.5 Effect of Whey Protein on Serum Lipids and Blood Pressure 63

2.9 Vitamin D 65 2.9.1 Metabolism of Vitamin D 66 2.9.2 Recommended Serum 25(OH)D Levels 67 2.9.3 Vitamin D and Type 2 Diabetes: Proposed Mechanisms of Action 68

2.10 Vitamin D Supplementation for the Management of Type 2 Diabetes

70

2.10.1 Effect of Vitamin D on Glycaemic and Insulinaemic Outcomes 70 2.10.2 Effect of Vitamin D on Body Composition 71 2.10.3 Effect of Vitamin D on Markers of Inflammation 73 2.10.4 Effect of Vitamin D on Serum Lipids and Blood Pressure 75

2.11 Exercise, Protein and Vitamin D for the Management of Type 2 Diabetes

78

2.11.1 Effects of Exercise and Protein or Exercise and Vitamin D on Lean Mass

78

2.11.2 Effects of Exercise Combined with Protein and Vitamin D on Lean Mass

91

2.11.3 Effects of Exercise, Protein or Vitamin D on Glycaemic and Insulinaemic Outcomes

93

2.11.4 Effects of Exercise, Protein and Vitamin D on Cardiovascular Health

102

2.12 Summary 107 Chapter 3

Exercise, Weight Loss and Inflammation in Type 2 Diabetes 3.1 Declaration Statement 110 3.2 Abstract 111 3.3 Introduction 113 3.4 Methods 115

3.4.1 Participants 115 3.4.2 Study Design 115 3.4.3 Ethics 117 3.4.4 Intervention 117 3.4.5 Measurements 121

3.4.5.1 Cytokine and Endothelial Inflammatory Markers Measurements

121

Page | III

3.4.6 Statistical Analysis 122 3.5 Results 122

3.5.1 Changes in Inflammatory Cytokines 124 3.5.2 Change in Adiponectin 128 3.5.3 Changes in Endothelial Markers 131

3.6 Discussion 134 3.7 Limitations 139 3.8 Conclusion 140 3.9 Acknowledgements 140

Chapter 4 Methods for a 6-month Randomised Controlled Trial Investigating The Effects

of Progressive Resistance Training, Whey-Protein and Vitamin D

Supplementation on Glycaemic Control, Body Composition and Cardiovascular

Risk Factors in Older Adults with Type 2 Diabetes

4.1 Declaration Statement 142 4.2 Abstract 143 4.3 Methods 144

4.3.1 Study Design 144 4.3.2 Ethics 144 4.3.3 Funding 145 4.3.4 Participants 145 4.3.5 Recruitment 145 4.3.6 Screening and Eligibility 145 4.3.7 Consent 147 4.3.8 Randomisation 147 4.3.9 Intervention 147

4.3.10 Sample Size Calculations 151 4.3.11 Outcome Measures 151

4.3.11.1 Anthropometry 155 4.3.11.2 Body Composition 155

4.3.11.3 Biochemical and Hormonal Assessment and Measures of Markers of Inflammation

158

4.3.11.4 Blood Pressure 160 4.3.11.5 Muscle Strength 161 4.3.11.6 Dietary Assessment 163 4.3.11.7 Habitual Physical Activity 165 4.3.11.8 Medical History, Health Status, Medication Use 165

Page | IV

4.3.11.9 Compliance Assessment 166 4.3.11.10 Adverse Events 166

4.3.12 Statistical Analysis 167 Chapter 5

Lessons Learned Recruiting Older Adults with Type 2 Diabetes into a Community-based Exercise and Nutrition Randomised Controlled Trial

5.1 Declaration Statement 169 5.2 Abstract 170 5.3 Introduction 172 5.4 Methods 173

5.4.1 Study Overview 173 5.4.2 Ethics 174 5.4.3 Funding 175 5.4.4 Sample Size Calculations 175 5.4.5 Screening Procedure and Inclusion/Exclusion Criteria 175 5.4.6 Recruitment Strategies 176 5.4.7 Data Collection and Analysis 181

5.5 Results 182 5.5.1 Recruitment 182 5.5.2 Response Rates and Reasons for Ineligibility or Non-participation 182 5.5.3 Recruitment Return by Recruitment Strategy 184 5.5.4 Recruitment Return by Gender and Age 185 5.5.5 Recruitment Timeline 186 5.5.6 Recruitment Cost 188

5.6 Discussion 190 5.6.1 Eligibility Rate 190 5.6.2 Success of Recruitment Strategies 191 5.6.3 Recruitment Cost 193 5.6.4 Reasons for Ineligibility 194 5.6.5 Reasons for Choosing Not to Participate 194

5.7 Limitations 194 5.8 Conclusion 195

Chapter 6 The Effects of Progressive Resistance Training Combined with a Whey-Protein

Drink and Vitamin D Supplementation on Glycaemic Control, Insulin Sensitivity, Body Composition and Cardiovascular Risk Factors in Older Adults

with Type 2 Diabetes 6.1 Declaration Statement 198

Page | V

6.2 Abstract 199 6.3 Introduction 201 6.4 Methods 203

6.4.1 Study Design 203 6.4.2 Participants 203 6.4.3 Ethics 203 6.4.4 Funding 203 6.4.5 Randomisation 204 6.4.6 Intervention 204

6.5 Outcome Measures 206 6.5.1 Anthropometry 206 6.5.2 Blood Pressure 206 6.5.3 Body Composition 206 6.5.4 Muscle Strength 207 6.5.5 Biochemical, Hormonal and Inflammatory Cytokine Measurements 207 6.5.6 Dietary Assessment 208 6.5.7 Habitual Physical Activity 209 6.5.8 Medical History, Health Status and Medication Use 209 6.5.9 Compliance Assessment 209

6.5.10 Adverse Events 210 6.5.11 Statistical Analyses 210

6.6 Results 212 6.6.1 Participant Characteristics 212 6.6.2 Study Attrition 214 6.6.3 Compliance 217 6.6.4 Adverse Events 218 6.6.5 Physical Activity and Diet 220 6.6.6 Glycaemic and Insulinaemic Outcomes 228 6.6.7 Body Composition and Muscle Strength 235 6.6.8 Cardiovascular Health 242 6.6.9 Other Medication Use and Change 250

6.6.10 Inflammatory Cytokines, Hormonal and Biochemical Factors 250 6.6.11 Per Protocol Analysis 257

6.7 Discussion 260

6.7.1 Effects of PRT, Whey Protein and Vitamin D on Lean Mass, Muscle Size and Strength

261

6.7.2 Effects of PRT, Whey Protein and Vitamin D on Fat Mass and Body Weight

267

Page | VI

6.7.3 Effects of PRT, Whey Protein and Vitamin D on Glycaemic and Insulinaemic Outcomes

269

6.7.4 Effects of PRT, Whey Protein and Vitamin D on Blood Pressure and Lipids

278

6.7.5 Effects of PRT, Whey Protein and Vitamin D on Markers of Inflammation

282

6.8 Strength and Limitations 285 6.9 Conclusion 288

Chapter 7 Summary, Implications, Future Recommendations and Conclusions

7.1 Summary 291

7.2 Key Research Findings, Limitations and Directions for Future Research

293

7.2.1 Recruiting ‘at risk’ older adults with T2DM into exercise and nutrition intervention trials is challenging and expensive

294

7.2.2 Structured and supervised as well as community-based PRT results in relevant cardiometabolic health improvements important to those with T2DM

297

7.2.3 The most effective diet or nutritional approach for the management of T2DM remains unclear

299

7.3 Conclusions and Public Health Implications 302 References 305 Appendices 353

Page | VII

Abbreviations

1,25(OH)2D: 1,25-dihydroxyvitamin D

25(OH)D: 25-hydroxyvitamin D

ACSM: American College of Sports Medicine

ACE: Angiotensin converting enzyme

ADA: American Diabetes Association

AHA: American Heart Association

AIHW: Australian Institute of Health and Welfare

ALM: Appendicular lean mass

ANCOVA: Analysis of covariance

AUC: Area under the curve

AUD$: Australian Dollars

AusDiab: Australian Diabetes, Obesity and Lifestyle BCAAs: Branched chain amino acids

BDA: British Diabetic Association

BMI: Body mass index

BMRest: Estimated Basal Metabolic Rate

CCK: Cholecystokinin

CHAMPS: Community healthy activities model program for seniors

CI: Confidence interval

cm: Centimetre(s)

CSA: Cross-sectional area

CV: Co-efficient of variation

CVD: Cardiovascular disease

CYP27B1: 1-alpha- hydroxylase

DBP: Diastolic Blood Pressure

DPP: Diabetes Prevention Study

DPP-4: Dipeptidyl peptidase 4

DXA: Dual-energy X-ray absorptiometry

EAAs: Essential amino acids

eGFR: Glomerular filtration rate

EI: Energy Intake

Page | VIII

EOI: Expression of interest

FGF-23: Fibroblast growth factor 23

FPG: Fasting plasma glucose g: Gram(s)

GI: Gastrointestinal

GLUT4: Glucose transporter type 4

GP: General practitioner

HbA1c: Glycated haemoglobin

HDL: High-density lipoprotein

HOMA: Homeostasis model assessment

hs-CRP: High sensitive C-reactive protein

HRmax: Heart rate maximum

HRR: Heart rate reserve

ICAM-1: Intercellular Adhesion Molecule 1

IDF: International Diabetes Federation

IFG: Impaired fasting glucose

IGT: Impaired glucose tolerance

IGF-1: Insulin like growth factor-1

IOM: Institute of Medicine

IL-6: Interleukin 6

IL-8: Interleukin 8

IL-10: Interleukin 10

IU: International Units

kg: Kilogram(s)

kJ: Kilojoule(s)

LDL: Low-density lipoprotein

MDRD: Modification of Diet in Renal Disease

ml: Millilitre(s)

mmHg: Millimetres of mercury

mmol/L: Millimole per litre

MPB: Muscle protein breakdown

MPS: Muscle protein synthesis

mTOR: Mammalian target of rapamycin

Page | IX

NDSS: National Diabetes Support Scheme

NHANES: National Health and Nutrition Examination Survey

NHMRC: National Health and Medical Research Council

nmol/L: Nanomoles per litre

NSAIDs: Nonsteroidal anti-inflammatory drugs

OGTT: Oral glucose tolerance test

PAL: Physical activity level

Pmol/L: Picomoles per litre

pQCT: Peripheral quantitative computed tomography

PRT: Progressive resistance training

PTH: Parathyroid hormone

QA: Quality assurance

RAAS: Renin angiotensin aldosterone system

RCT(s): Randomised controlled trial(s)

REVAMP-IT: Resistance Exercise, Vitamin D and Muscle Protein Intervention Trial

RM: Repetition maximum

RPE: Ratings of perceived exertion

RRR: Relative risk reduction

SBP: Systolic blood pressure

SD: Standard deviation

SEM: Standard error of the mean

TNF-α: Tumour necrosis factor alpha

T2DM: Type 2 diabetes mellitus

US$: United States dollars

VAT: Visceral adipose tissue

VDR: Vitamin D receptor

VLCD: Very low calorie diet

VO2max: Maximal oxygen consumption

VO2R: VO2 reserve

WHO: World Health Organization

WL: Weight loss

Page | X

List of Tables

Number Title Page

Chapter 2 Table 2.1 Diagnostic criteria for pre-diabetes and type 2 diabetes. 15 Table 2.2 Major risk factors for type 2 diabetes. 17 Table 2.3 Minimum exercise recommendations for patients with type 2

diabetes. 25

Table 2.4 Summary of the main findings (between-group differences) in RCTs investigating the effects of PRT or the combination of PRT and aerobic training under supervised gymnasium-based settings in older adults with type 2 diabetes.

28

Table 2.5 Analysis of effect size for change in HbA1c stratified by characteristics of the PRT program.

38

Table 2.6 Macronutrient recommendations for the management for type 2 diabetes by the British and American Diabetes Association and the American Heart Foundation.

45

Table 2.7 Types of commercially available whey protein. 53 Table 2.8 Recommended serum vitamin D targets and classes of

deficiency as recommended by the IOM. 68

Table 2.9 Summary of RCTs which have examined the interactive effects of various protein supplements with PRT or exercise on lean mass in older and elderly adults.

85

Table 2.10 Summary of RCTs which have examined the interactive effects of increased dietary protein or protein supplements with PRT or exercise on glycaemic and/or insulinaemic outcomes in older and elderly adults.

98

Chapter 3 Table 3.1 Baseline descriptive characteristics of the PRT+WL and WL

group. 122

Table 3.2 Mean baseline values and the percentage change relative to baseline for serum IL-10, IL-6 and TNF-α for the PRT+WL and WL groups after 3-, 6-, 9- and 12-months.

126

Table 3.3

Mean baseline values and the percentage change from baseline for serum adiponectin in the PRT+WL and WL groups after 3-, 6-, 9- and 12-months.

129

Table 3.4 Mean baseline values and the percentage change from baseline for serum ICAM-1 and resistin for the PRT+WL and WL groups after 3-, 6-, 9- and 12-months.

132

Chapter 4 Table 4.1 Ineligibility criteria for the 24-week Lift for Life® RCT. 146

Page | XI

Table 4.2 Summary of the primary and secondary outcome measures collected and methods of collection.

152

Chapter 5 Table 5.1 Reasons participants were deemed ineligible for the trial. 183 Table 5.2 Number and proportion (percentage) of expressions of interest

who chose not to participate in this trial and the reasons provided for non-participation.

184

Table 5.3 Number and proportion (percentage) of expressions of interest and participants deemed eligible for the trial based on the various recruitment strategies.

185

Table 5.4 Number and proportion of men and women screened and deemed eligible or ineligible for the trial.

186

Table 5.5 The total costs, proportion of total recruitment costs, the number of eligible participants plus cost per participant for each recruitment strategy in this trial.

189

Chapter 6 Table 6.1 Baseline characteristics of participants in the PRT+ProD and

PRT groups. 213

Table 6.2 Number and proportion of musculoskeletal complaints reported by participants in the PRT+ProD and PRT groups that were deemed to be associated with the PRT program. Categorised by skeletal/muscular site.

219

Table 6.3 Physical symptom(s) and number of adverse events related to the whey protein supplement in the PRT+ProD supplement group.

220

Table 6.4 Baseline values and absolute within-group changes in the PRT+ProD and PRT group and the net between-group differences for the change at 12- and 24-weeks relative to baseline for moderate-vigorous physical activity.

223

Table 6.5 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for all macronutrients, excluding protein intake and the protein-vitamin D supplements.

224

Table 6.6: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for habitual protein intake and protein intake inclusive of supplemental protein on non-training and training days in g/day and g/kg/day.

226

Page | XII

Table 6.7 Total number and proportion of participants taking oral hypoglycaemic medications and the changes at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

229

Table 6.8 Total number and proportion of participants taking oral hypoglycaemic medications at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

230

Table 6.9 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change relative to baseline for HbA1c, fasting plasma glucose, insulin, insulin sensitivity and C-peptide.

232

Table 6.10 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups for weight, body mass index (BMI) and waist circumference and the net between-group differences for the change relative to baseline.

237

Table 6.11 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for total body and regional (arms and legs) lean mass, fat mass and appendicular lean mass.

238

Table 6.12 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for 25% femur muscle cross-sectional area (CSA), muscle density, intermuscular and subcutaneous fat CSA.

240

Table 6.13 Baseline values and within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change relative to baseline in leg press and seated row one-repetition maximum muscle strength and knee extensor isometric muscle strength.

241

Table 6.14 Total number and proportion of participants prescribed anti-hypertensive and/or lipid-lowering medications at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

243

Table 6.15 Types of anti-hypertensive medications participants were prescribed at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

244

Table 6.16 Number and proportion of participants in the PRT+ProD and PRT groups presenting with hyperlipidaemia.

245

Table 6.17 Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for systolic and diastolic blood pressure.

247

Page | XIII

Table 6.18 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum total, HDL and LDL cholesterol and triglycerides.

248

Table 6.19 Total number and type of other medications prescribed to participants at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

250

Table 6.20 Baseline values and percent changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum levels of interleukin (IL)-10, IL-6, IL-8, tumor necrosis factor-alpha (TNF-α), adiponectin and high-sensitive C-reactive protein (hs-CRP).

252

Table 6.21 Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum creatinine, estimated glomular filtration (eGFR), 25-hydroxyvitamin D (25(OH)D) and insulin-like growth factor-1 (IGF-1).

255

Table 6.22 Baseline characteristics of participants included in the per protocol analysis of the PRT+ProD and PRT groups.

258

Page | XIV

List of Figures

Number Title Page

Chapter 2 Figure 2.1 Percentage of Australian adults with or at risk of developing

T2DM as assessed by fasting plasma glucose in 2011-12. 11

Figure 2.2 Common aetiological pathways and the metabolic links shared between sarcopenia and type 2 diabetes.

20

Figure 2.3 Protein fractions and types of whey protein derived from whole milk.

52

Figure 2.4 The serum glucose and insulin responses to a high-glycaemic index breakfast meal following a whey protein (white circles) or placebo (black circles) pre-load in 15 participants with type 2 diabetes.

59

Figure 2.5 Metabolism of vitamin D from the sun and dietary sources. 67

Figure 2.6 Proposed role of vitamin D in the pathophysiology of type 2 diabetes.

69

Figure 2.7 Mean ± SD absolute changes (in kg) in total body weight, fat mass and lean mass after 16-weeks on a hypocaloric high protein (33% energy from protein) or hypocaloric control diet (19% energy from protein) with and without PRT.

80

Figure 2.8 Mean (± SD) absolute changes in fasting insulin (pmol/L), glucose (mmol/L) and HbA1c (%) following a 16-week high protein (33% energy from protein) or control diet (19% energy from protein) with or without participation in PRT (3 days/week 70-85% 1-RM).

94

Figure 2.9 Absolute percentage change in total cholesterol, HDL cholesterol, LDL cholesterol and triglycerides following a 12-week intervention of multi-modal exercise, multi-modal exercise plus 1,200 IU/day of vitamin D, 1,200 IU/day of vitamin D alone or control.

105

Chapter 3 Figure 3.1 CONSORT flow diagram of participants through the trial. 117 Figure 3.2 Mean percentage change with 95% CI from baseline for

serum A) IL-10, B) TNF-α, C) IL-6 and D) Adiponectin following the gymnasium-based (3- and 6-months) and home-based (9- and 12-months) training for the PRT+WL (●) and WL (○) groups.

130

Figure 3.3 Mean percentage change with 95% CI from baseline for serum A) ICAM-1 and B) Resistin following the gymnasium-

133

Page | XV

based (3- and 6-months) and home-based (9- and 12-months) training for the PRT+WL (●) and WL (○) group.

Chapter 4 Figure 4.1 Flow diagram of the progress through the 24-week PRT

program used in this trial modelled from the Lift for Life® program.

148

Figure 4.2 Single use sachet of protein supplement and shaker cup used for protein supplement preparation.

150

Figure 4.3 Sub-regions within the whole body DXA scan. 156 Figure 4.4 Peripheral quantitative computed tomography (pQCT) scan

at the 25% femur site. 157

Figure 4.5 Participant positioning for the knee extensor strength test. 162

Chapter 5 Figure 5.1 Example of the study advertisement in state print media

(newspaper). 177

Figure 5.2 Example of the study advertisement for local print media (newspaper).

178

Figure 5.3 An example of the study recruitment flyer. 180

Figure 5.4 The number of male and female participants eligible for this trial and the recruitment strategies they responded from.

186

Figure 5.5 Number of participants randomised to this trial each month for the duration of the recruitment period.

187

Figure 5.6 Timeline and timing of recruitment strategies implemented during 2014 and 2015.

188

Chapter 6 Figure 6.1 Flow diagram of the progress through the 24-week PRT

program used in this trial modelled off the Lift for Life® program.

205

Figure 6.2 CONSORT flow diagram of participants through the trial. 216

Figure 6.3 Histogram of the percentage exercise compliance by participants in the PRT+ProD and PRT group.

217

Figure 6.4 Histogram of the percentage compliance with the whey protein drink (panel A) and vitamin D supplements (panel B) in the progressive resistance training plus protein and vitamin D supplementation (PRT+ProD) group.

218

Figure 6.5 Total dietary protein intakes (habitual plus supplemental) in older adults with type 2 diabetes at baseline, 12- and 24-weeks.

228

Figure 6.6 Mean absolute changes from baseline (95% CI) in HbA1c (%) (A), fasting glucose (mmol/L) (B), fasting insulin (pmol/L)

234

Page | XVI

(C) and HOMA2%S (D) in the PRT+ProD (●) and PRT (○) groups.

Figure 6.7 Mean percentage change from baseline (95% CI) in log transformed serum interleukin (IL)-6 (A), IL-10 (B), IL-8 (C), TNF-α (D), adiponectin (E) and high sensitive hs-CRP (F) in the PRT+ProD (●) and PRT (○) groups.

254

Page | XXI

List of Appendices

Number Title Page

1 Mean baseline and the absolute change from baseline and the net differences for the change for HbA1c and body composition measurements in the PRT+WL and WL groups at 3, 6, 9 and 12-months

362

2 Mean values ± SD in various inflammatory markers for the PRT+WL and WL groups at 3-, 6-, 9- and 12-months

363

3 Mean values ± SD in endothelial markers for the PRT+WL and WL groups at 3-, 6-, 9- and 12-months

364

4 Deakin University Human Research Ethics Committee Approval Letter

365

5 Telephone Screening Questionnaire 366 6 GP Letter and Recommendation to Participate Form 367 7 Plain Language Statement and Consent Form 370

8 National Diabetes Support Scheme Recruitment Letter Mail-Out

379

9 Baseline values and absolute within-group changes in the PRT+ProD and PRT group and the net between-group differences for the change at 12- and 24-weeks relative to baseline for habitual protein intake plus the protein from the whey protein supplement

381

10 Per Protocol Results Tables 383

Page | 1

Chapter 1

Introduction

Chapter 1

Page | 2

1.1 Research Problem

Type 2 diabetes mellitus (T2DM) is one of the most prevalent chronic metabolic

diseases of the 21st century (1, 2). In 2011, 366 million people were diagnosed with

diabetes globally, and by the year 2040 it is predicted that 642 million adults will

have diabetes (3). The human and economic burden of illness associated with T2DM

contributes significantly to ill health, disability and premature death, and is further

exacerbated by the onset of micro- and macrovascular complications, which appear

to be driven in part by the presence of an underlying chronic low-level of systemic

inflammation in adults with this condition (4). Thus, there is a need to develop safe,

effective and sustainable population-based prevention and management strategies

that collectively improve glycaemic control, insulin sensitivity and the multiple risk

factors associated with this disease.

Lifestyle modification combining energy restriction, weight loss and physical

activity remains the cornerstone of T2DM management (5, 6). While a reduction in

body weight and improvements in glycaemic control have been observed following

energy restriction, weight loss and aerobic or endurance activity, a concomitant loss

in lean mass also tends to occur (7, 8). Lean mass is critical for people with T2DM,

as it is the largest mass of insulin-sensitive tissue and the predominant reservoir for

glucose disposal (9). Losses in muscle mass can negatively impact metabolic rate,

compound the problems of insulin resistance and lead to reduced physical function

and quality of life (10, 11). As a result, current international consensus exercise

guidelines recommend that progressive resistance training (PRT) be incorporated

into the overall physical activity plan for people with T2DM (6).

Previous research has demonstrated that high-intensity PRT conducted within a

controlled setting is safe and effective for improving glycated haemoglobin (HbA1c)

levels and lean mass in older adults with T2DM (12-14). Furthermore, exercise and

to a lesser extent PRT has also been shown to play a role in lowering chronic low-

grade inflammation, particularly in people who are overweight or obese and/or have

a diagnosed chronic disease (15-18). Chronic low-grade inflammation has been

linked to accelerated muscle loss and has emerged as the common denominator

linking T2DM, metabolic syndrome and cardiovascular disease (19-22). This chronic

Chapter 1

Page | 3

state of inflammation has also been associated with a decrease in beta-cell insulin

secretion and a subsequent deterioration in insulin resistance (19-22). However,

whether improvements in markers of inflammation are associated with improvements

in glycaemic control remain to be observed.

Whilst there has been considerable research into the effects of PRT on body

composition, HbA1c, insulin sensitivity and to a lesser degree inflammation, many of

the randomised controlled trials (RCTs) have commonly occurred under tightly

controlled and structured clinical laboratory settings. The translation of this research

into practice and whether similar benefits can be achieved from participation in

community based-programs, where there is often less supervision and more

independence in performing the training, remains uncertain. Improvements in health

outcomes following community-based exercise programs, even if modest, are still

important from a public health perspective given small improvements at an

individual level can translate to substantial changes within the population (23).

Further, community-based physical activity programs are a key avenue for assessing

the relevance and real-world applicability of research-to-practice programs. Previous

research measuring the economic value of research-to-practice programs in

community-settings has also found participation in such programs may reduce total

healthcare costs for older adults, society and the national healthcare system (24).

Since nutritional management is also an important component in the treatment of

T2DM, combining PRT with dietary modification may offer an incremental effect on

glycaemic control, insulin sensitivity as well as body composition and cardiovascular

risk factors. Traditionally, caloric restriction has been prescribed to adults with

T2DM largely due to the well-documented benefits on glycaemic control, blood

pressure and serum lipid levels as well as fat mass and overall weight loss (25-27).

However, weight reduction remains a difficult-to-reach goal for many and long-term

maintenance of caloric restricted diets and the resultant weight loss often fails to be

maintained (28-30). Aerobic or endurance training is also often combined with

caloric restriction but this approach does not appear to attenuate the muscle loss

arising from weight loss. However, a limited number of studies in overweight and

obese adults (31, 32) and those with T2DM (33-35) have reported that exercise,

Chapter 1

Page | 4

primarily aerobic training, combined with weight loss/caloric restriction is more

effective at improving glycaemic control and various inflammatory markers than

either exercise or diet alone. A study which combined calorie restriction with PRT

compared to calorie restriction alone also found that the combination was effective at

improving glycaemic control, fat mass, lean mass and upper body strength to a

greater degree than weight loss alone (12). However, the effects of PRT combined

with caloric restriction on circulating inflammatory markers has not been examined

in adults with T2DM. This is an important question given the role that systemic

inflammation plays in the pathogenesis of T2DM and related co-morbidities

including cardiovascular disease.

While the optimal macronutrient composition of the diet for the management of

T2DM remains uncertain, emerging evidence suggests that there are health benefits

associated with high-protein diets in overweight and obese adults and those with

T2DM (36, 37). For instance, a meta-analysis of nine RCTs ranging from four to 24-

weeks reported that high-protein diets had beneficial effects on weight loss and

HbA1c levels and tended to reduce blood pressure in people with T2DM, with no

adverse effects on blood lipids (38). Despite these positive findings, dietary studies

controlling for macronutrient composition are often difficult to implement in the

‘real-world’ as they require an individual to follow a prescribed meal plan.

Therefore, the addition of a protein supplement might be a more practical and

effective approach, as it does not require individuals to make marked changes in their

usual dietary habits.

Acute studies have shown that both whey protein and PRT stimulate muscle protein

synthesis (MPS) (39). A number of long-term (>10 weeks) human intervention trials

in healthy older adults have also reported that ingestion of high-quality protein can

enhance the effects of PRT on muscle mass and strength (40-42), although these

findings are not consistent (34, 43). The inconsistent findings may be due to a

number of factors, including the type of protein, the dose, timing of intake and the

distribution throughout the day (44, 45). In terms of the type of protein, there is

considerable evidence showing that whey protein is particularly effective for

stimulating an acute increase in MPS, which is likely due to the fact that it contains

Chapter 1

Page | 5

all the essential amino acids, particularly leucine, which is crucial for triggering the

initial MPS response (46-48). While there is still ongoing research into defining

whether there is an optimal dose of protein, particularly in older adults or those with

chronic disease, to elicit a synergistic anabolic muscle response with PRT, several

recent studies and reviews have recommended that 20 to 40g of high-quality, rapidly

digested, leucine-rich protein, such as whey protein, be consumed soon after each

bout of PRT to maximally stimulate MPS and promote muscle hypertrophy whilst

concomitantly reducing muscle protein breakdown (MPB) (49-51). Furthermore,

previous studies have demonstrated that whey protein and its bioactive components

may offer insulinotropic (52-56), muscle-sparing (57) and cholesterol-lowering

effects (58) in adults with T2DM. Presently, however, the long-term effects of whey

protein supplementation in combination with PRT on body composition, glycaemic

control, insulin sensitivity and inflammation along with serum lipid levels and blood

pressure in older adults with T2DM remains unknown.

There are also other lifestyle factors that might have beneficial effects on skeletal

muscle. For instance, there is mounting evidence that vitamin D may act as a

modifier of diabetes risk and that deficiency in serum 25(OH)D, the circulating

marker of vitamin D, is associated with impaired beta-cell function, glucose

intolerance and insulin resistance and reduced muscle function, strength and size (22,

59-62). Whilst an inverse association exists between serum 25(OH)D levels and

T2DM (22, 63, 64), the role that vitamin D exerts on insulin resistance and

glycaemic control remains controversial with mixed findings from a limited number

of RCTs conducted in older adults with T2DM (65-68). Nevertheless, there is some

evidence that vitamin D supplementation can improve glycaemic control and insulin

sensitivity in adults with or at high risk of this disease, including those with

prediabetes and T2DM (69-71).

In summary, there is overwhelming evidence to support a positive role for supervised

and structured PRT in older adults with T2DM, however, whether the addition of

certain nutritional factors, particularly whey protein and vitamin D, can act

synergistically to enhance the health benefits of a community-based PRT program

Chapter 1

Page | 6

remains unknown. One of the key aims of this thesis is to conduct a high quality

RCT to address this question.

1.2 Thesis Aims

The primary aim of this thesis is to investigate if lifestyle strategies such as caloric

restriction to promote weight loss or nutritional supplementation with protein and

vitamin D, in combination with PRT, can promote greater improvements in

glycaemic and insulinaemic outcomes, body composition, cardiovascular risk factors

and systemic inflammation in older overweight adults with T2DM compared to PRT

alone.

The specific aims are:

1. To compare the effect of PRT plus a moderate weight loss program versus

weight loss alone on systemic and endothelial markers of inflammation in older

overweight adults with T2DM (Chapter 3).

2. To describe the challenges related to recruiting older adults with T2DM into a 6-

month community-based exercise and nutrition research intervention, and to

assess the costs associated with the recruitment methods used (Chapter 5).

3. To investigate whether ingestion of a daily whey-protein drink in combination

with vitamin D supplementation can enhance the effects of a community-based

PRT program on glycaemic control and insulin sensitivity in older adults with

T2DM (Chapter 6).

4. To examine whether a community-based PRT program combined with a whey-

protein drink and vitamin D supplementation is more effective for enhancing

total body and regional lean mass, muscle cross-sectional area (CSA), muscle

strength and reducing inter-/intra-muscular fat infiltration, than PRT alone in

older adults with T2DM (Chapter 6).

5. To compare the effects of a community-based PRT program combined with

whey-protein and vitamin D supplementation versus PRT alone, on

cardiovascular risk factors, including blood pressure and blood lipid levels, and

pro-inflammatory and anti-inflammatory cytokines. (Chapter 6).

Chapter 1

Page | 7

1.3 Thesis Hypotheses

It is hypothesised that in older adults with T2DM:

1. Supervised high-intensity PRT combined with weight loss will lead to greater

improvements in various inflammatory and endothelial markers than weight loss

alone.

2. A community-based PRT program combined with a daily whey-protein drink

and vitamin D supplements will lead to greater improvements in glycaemic

control and insulin sensitivity compared to PRT alone.

3. A community-based PRT program combined with a whey-protein drink and

vitamin D supplementation will augment the anabolic effects of PRT alone on

total body and regional lean mass, muscle cross-sectional area, muscle strength

and reduce inter-/intra-muscular fat infiltration.

4. A community-based PRT program combined with a whey-protein drink and

vitamin D supplementation will be associated with greater improvements in

cardiovascular risk factors, including circulating total, high-density lipoprotein

(HDL) and low-density lipoprotein (LDL) cholesterol levels, triglycerides and

blood pressure and a reduction in the catabolic milieu as reflected by a decrease

in pro-inflammatory cytokines and an increase in anti-inflammatory markers

compared to PRT alone.

1.4 Significance of this Research

The International Diabetes Federation (IDF) estimates 415 million adults currently

suffer a form of diabetes (3). The most recent predictions, which are based on the

present growth of this disease, suggest that by the year 2040 642 million adults will

have diabetes (3). The rapid rise and predicted continued increase in the prevalence

of this condition is largely due to T2DM (3), which accounts for up to 91% of all

total cases of this condition in high-income countries (72, 73). The human and

economic burden of illness associated with T2DM is further exacerbated with the

onset of micro- and macro-vascular complications, highlighting the need for

sustainable population-based prevention and management approaches that can

improve multiple risk factors for T2DM and its associated micro- and macrovascular

Chapter 1

Page | 8

complications. In older adults with T2DM the most effective combined exercise and

nutrition strategy to improve glycaemic control, body composition and

cardiovascular outcomes, and concomitantly reduce the risk for micro- and

macrovascular complications, remains unknown. If successful, the findings from this

thesis will make an important contribution to the development of evidence-based and

accepted community-based exercise and nutrition treatment approaches effective for

improving multiple health outcomes implicated in the development and progression

of this disease. Of note, an increase in circulating levels of pro-inflammatory

cytokines with concomitant lower levels of anti-inflammatory markers is a common

finding in older adults with T2DM. Such an inflammatory profile can have

particularly deleterious consequences for older adults with T2DM given that it has

been associated with an increased risk of cardiovascular disease and various

diabetes-related micro- and macro-vascular complications. This thesis will provide

an insight into whether combining calorie restriction (for weight loss) with PRT may

result in an additive effect on augmenting markers of inflammation in older adults

with T2DM than either strategy alone. As an extension of this work, this thesis will

also investigate whether a community-based PRT program combined with whey

protein and vitamin D supplementation can enhance the effects of PRT alone on

body composition, glycaemic control, insulin sensitivity and cardiovascular health

outcomes including systemic inflammation, lipids and blood pressure in older adults

with T2DM. The results of the studies that make up this thesis will assist in

answering many important questions about the most appropriate lifestyle strategy for

the management of T2DM in older adults. Further, the results of the studies in this

thesis will provide critical insight into the effectiveness of community-based PRT

programs for older adults with T2DM on a range of important health outcomes. More

specifically, this thesis will identify whether nutritional factors in combination with a

community-based PRT program can enhance the recognised and established health

benefits of PRT alone in older overweight and obese adults with T2DM.

Page | 9

Chapter 2

Review of the Literature

Chapter 2

Page | 10

2.1 Type 2 Diabetes – A Global Health Problem

Globally, type 2 diabetes mellitus (T2DM) currently represents one of the largest and

most prevalent chronic, non-communicable diseases of the 21st century (3). The

International Diabetes Federation (IDF) estimates 415 million adults currently suffer

a form of diabetes (3). There has been an unrelenting increase in the global

prevalence of this chronic condition in recent decades, due largely to the rise in

prevalence of T2DM (3). It is believed that T2DM accounts for up to 91% of the

total cases of this condition in high-income countries (72, 73). In addition, the most

recent predictions, based on the current growth of this condition, project by the year

2040 approximately 642 million adults will have diabetes (3). A further 318 million

adults are currently estimated to suffer the pre-diabetic conditions of impaired

glucose tolerance (IGT) or impaired fasting glucose (IFG), both intermediary points

between normoglycaemia and T2DM (74-77).

Advancing age is associated with increased rates of diabetes prevalence across all

regions of the world (78). At present the highest observed age-specific prevalence of

T2DM is in people aged 60-79 years, however, the largest total number of

individuals with T2DM are those aged 40-59 years where 184 million people

globally have been diagnosed (78). It is expected that this prevalence pattern will

persist and by the year 2035 the largest total number of individuals will be those aged

60-79 years as people transition into old age (78).

In Australia, statistics from the 2010-11 follow-up investigation of the population-

based, prospective Australian Diabetes, Obesity and Lifestyle (AusDiab) study

revealed that the prevalence of T2DM was 12% in adults aged 25 years and over

(79). Recent figures published by the Australian Institute for Health and Welfare

(AIHW) reported the prevalence of T2DM in Australian adults aged 18 years and

over to be 4.7% (849,000 people) (80). This disagreement and underestimate in the

AIHW figures is likely due to the fact this data was self-reported data (80). Like

global figures, the prevalence of this chronic condition has been steadily increasing

for decades, and currently in Australia 280 new cases of diabetes are diagnosed every

day (79). More men compared to women are affected by T2DM (14.8% versus

9.8%), with yearly incidence rates also higher in men (0.8% compared to 0.6%) (79).

Chapter 2

Page | 11

Paralleling global figures, the incidence of T2DM in Australia also increases with

advancing age as shown in Figure 2.1 (79, 81). By 2031, it is projected that 3.3

million Australians will be diagnosed with this condition (82, 83). The 2010-11

AusDiab follow-up survey found that a further 2 million Australians suffer from a

pre-diabetic condition (79). Finally, it is also important to highlight the high rate of

missed or undiagnosed (and thus underreported) cases of T2DM; for every five-

people diagnosed with T2DM, four cases remain undiagnosed (84). Collectively,

these findings highlight that T2DM is currently a major public health problem that is

projected to increase substantially in coming decades, unless effective strategies are

identified and implemented to treat and prevent this condition.

Figure 2.1 Percentage of Australian adults with or at risk of developing T2DM as assessed by fasting plasma glucose in 2011-12. Sourced from Australian Bureau of Statistics (85).

Type 2 diabetes that is not appropriately managed can lead to numerous

complications, increased morbidity and premature mortality (86). For instance,

poorly controlled T2DM is associated with an increased risk of micro-vascular

(retinopathy, nephropathy and neuropathy) and macro-vascular complications

[cardiovascular disease (CVD) and associated conditions including hypertension,

hypertriglyceridaemia, coronary heart disease and stroke] (87, 88). In almost all

high-income countries including Australia, the most predominant diabetes-

Chapter 2

Page | 12

complications are CVD, retinopathy, kidney disease and lower limb amputations

(89). To further compound this issue, many of these conditions do not exist

exclusively; the presence of one comorbid condition is frequently associated with

one or more other co-morbidities or additional complications.

The most predominant cause of morbidity and mortality in people with T2DM is

CVD (90-92). Mortality from CVD is more than double in those with T2DM

compared with age-matched healthy adults (93). The risk of CVD is strongly

associated with and rises with increases in fasting plasma glucose (FPG) levels, even

prior to reaching levels sufficient for a diagnosis of diabetes (94). In Australia in

2011-12, over two-thirds of people with diabetes (68%) reported suffering a form of

CVD; the most common and serious types including coronary heart disease, stroke

and heart failure (95). The reasons and exact mechanisms which contribute to the

high prevalence of CVD in people with T2DM have not been fully elucidated, but

have been postulated to be due to conventional risk factors which contribute

similarly to both conditions, such as obesity, hyperglycaemia, a sedentary lifestyle

and chronic systemic inflammation (4, 96).

2.2 The Economic Burden of Type 2 Diabetes

The continual and rapid growth of T2DM prevalence and related complications and

the associated increased risk of premature mortality associated with this disease is

imposing a substantial burden on national health care budgets globally. In 2015,

healthcare expenditure associated with the treatment and management of this

condition was estimated to be $673 million or 12% of total global health expenditure

(3). By 2040, universal expenditure is estimated to exceed $US802 billion for the

prevention and treatment of diabetes and its complications (3). In Australia, the

Australian Institute of Health and Welfare (AIHW) reported that the total national

healthcare expenditure on diabetes alone in 2008-09 was approximately $1,507

million or 2.3% of total health-care expenditure, placing diabetes 14th out of 200

diseases (97). This value was an increase of 86% from the year 2001-02, with the

largest increase in diabetes health-care expenditure being for hospital admitted

patient services, where diabetes expenditure more than doubled from $300 million to

$647 million (97). By 2051, health care costs are predicted to increase 2.5-fold, due

Chapter 2

Page | 13

predominantly to our ageing population. When including both obesity and physical

inactivity, both risk factors for T2DM discussed in section 2.5, the financial burden

accompanied with treating this disease is set to quadruple over this period (98).

Consequently, there is an urgent need to both prevent and develop better strategies to

manage this condition in Australia and globally.

It is important to note these aforementioned cost estimates are based on calculations

involving direct and non-direct health care costs which are both quantifiable. A

limitation of these estimates is the inability to estimate the indirect or intangible costs

associated with T2DM. This includes pain, anxiety, inconvenience, losses in

productivity in the work force and a reduced quality of life, all of which can have a

significant impact on the lives of people with this disease and their families and

contribute further to the overall economic burden associated with this condition.

Thus, the estimates do not provide a complete picture of diabetes related health

expenditure but do capture approximately 70% of health dollars spent on diabetes as

a disease (97).

2.3 Pathophysiology of Type 2 Diabetes

The pathophysiology of T2DM is complex and typically involves three basic

metabolic defects; insulin resistance, diminished beta-cell functioning and an

increase in hepatic glucose production (99). While there is an ongoing debate

regarding the contributions of each of these factors, and which precedes the other,

there is a general consensus that insulin resistance is the primary defect in T2DM and

is responsible for the impairment in insulin-stimulated glucose metabolism (100,

101). Insulin is the key hormone for regulating plasma glucose levels and

normoglycaemia is maintained by a complex and tightly regulated interplay between

secretion and action of insulin at various target tissues, including skeletal muscle,

liver and adipose tissue (102). In individuals with T2DM, hepatic glucose production

is excessive and remains high when in a post-prandial state, even though

concentrations of plasma insulin can be two to four-fold higher than normal (103,

104). In addition, the ability of endogenously secreted insulin to enhance glucose

uptake at the site of muscle is diminished in these individuals and causes plasma

Chapter 2

Page | 14

glucose levels to remain chronically high with eventual weakened beta-cell

functioning and reduced insulin secretion (103).

Over more recent decades it has become apparent that low-grade systemic

inflammation, closely associated with obesity and insulin resistance, precedes and is

able to predict the development of T2DM (105). Adipocytes, or fat cells, particularly

in those who are overweight/obese secrete a number of pro-inflammatory cytokines

(105). Some of these cytokines are recognised to directly inhibit insulin signalling.

Such an effect has several negative consequences in the human body including an

augmentation and perpetuation of this already low-level of inflammation, a

worsening of insulin sensitivity and can also alter the cardiovascular system with

some cytokines established to result in vasoconstriction, potentially progressing the

onset and development of CVD .

2.4 Defining Pre-Diabetes and Type 2 Diabetes

Type 2 diabetes is diagnosed based on the presentation of chronic hyperglycaemia

resulting from impaired insulin secretion, insulin resistance or both (88). The

intermediate condition between normal glucose tolerance and overt T2DM is termed

pre-diabetes, which includes both IGT and IFG. Diagnosis of pre-diabetes and

diabetes is made by an oral glucose tolerance test (OGTT) and/or fasting plasma

glucose (FPG) assessment. Table 2.1 outlines the diagnostic cut-offs for T2DM and

pre-diabetes as defined by the World Health Organization (WHO) report on the

Diagnosis and Classification of Diabetes Mellitus and adopted by the National

Health and Medical Research Council (NHMRC) of Australia (75, 106). Once

diagnosis of a pre-diabetic condition is made, around 50% of those diagnosed will

progress to develop T2DM within a 10-year period (77, 107). The cut-off values

employed for the diagnosis of T2DM are based on associations with diabetes related

microvascular and macrovascular complications (108-110). For instance,

microvascular risk increases significantly with plasma glucose concentrations ≥7.0

mmol and macrovascular disease risk increases with fasting values ≥7.0 mmol (108,

109, 111).

Chapter 2

Page | 15

Table 2.1: Diagnostic criteria for pre-diabetes and type 2 diabetes. Sourced from Stumvoll et al. (102).

Diagnosis Plasma glucose (mmol/L)

Fasting glucose OGTT HbA1c%

Pre-diabetes

IGT <7.0 and 7.8-11.0

IFG 6.1-6.9 and <7.8

Type 2 diabetes ≥7.0 or ≥11.1 ≥6.5

IGT, Impaired glucose tolerance; IFG, Impaired fasting glucose; OGTT, Oral glucose tolerance test. In recent years, the measurement of glycated haemoglobin (HbA1c), reflective of the

average blood glucose concentration over the previous two to three-month period,

has been recommended as an alternative test to diagnose T2DM. The use of HbA1c as

a diagnostic test has been endorsed by WHO, the IDF and the American Diabetes

Association (ADA) (106, 112, 113). An expert committee established by the

Australian Diabetes Society has recommended that an HbA1c value ≥6.5% be used as

the cut-point for diagnosis T2DM (113). While this cut-point has been derived based

on data showing an association between HbA1c and prevalent retinopathy (114), there

is also evidence that a 1% reduction in HbA1c is associated with a 21% relative risk

reduction (RRR) for any clinical end point or death related to diabetes, 14% for

myocardial infarction and 37% for microvascular complications (109, 115).

However, a recent study that used HbA1c for the sole identification of individuals

with T2DM in population based health surveys failed to identify a substantial

proportion of previously undiagnosed individuals who would be considered as

having diabetes using a glucose-based test (116). These findings highlight the

importance of glucose-based tests for the detection of T2DM when calculating

national and global prevalence of this disease (116).

2.5 Risk Factors for the Development of Type 2 Diabetes

Common risk factors for T2DM include a range of non-modifiable (genetics, age,

gender, ethnicity) and modifiable (obesity, physical inactivity, poor diet quality)

Chapter 2

Page | 16

factors, which can form a complex interaction with one another (Table 2.2) (117). A

brief discussion of some of these risk factors is presented below.

Non-modifiable risk factors

Genetics / Family History While T2DM is often considered a lifestyle-related disease, twin and family studies

estimate that disease risk is increased up to three-fold in those with first degree

relatives with T2DM and five to six-fold in those with both maternal and paternal

disease history (102, 118). A genetic predisposition to T2DM, if present, may be

triggered in the presence of a “diabetogenic” environment such as high-calorie

consumption and a sedentary lifestyle (119, 120). Others have suggested that specific

genes may be implicated in the development of T2DM. At present, 88 genes have

been identified to potentially play a role in the genetic or inbred component of

T2DM risk (121). This genetic heritability remains poorly understood with limited

evidence available on how the identified genes specifically interrelate with

environmental factors that have been linked to T2DM. Thus, it presently remains

impossible to estimate an individual’s risk for T2DM through genetics alone (121,

122).

Chapter 2

Page | 17

Table 2.2: Major risk factors for type 2 diabetes. Adapted from Chen et al. (1).

Non-modifiable risk factors

§ Age greater than 45 years

§ Gender; males at higher risk

§ Ethnicity; Hispanic, Native American, African American, Asian American, or Pacific Islander descent

§ First degree relative or family history of T2DM (e.g. parent or sibling)

§ History of gestational diabetes or delivering a baby with a birth weight of over 9 pounds

§ Polycystic ovary syndrome

Modifiable risk factors

§ Body fat mass

§ High BMI

§ Reduction in lean mass

§ Physical inactivity

§ Poor diet

§ Smoking

§ Previously diagnosed IGT or IFG

§ Low serum 25(OH)D

§ Chronic low grade systemic inflammation

§ Hypertension (>140/90 mmHg) or dyslipidaemia (HDL <1.0 mmol/L for men and <1.3 mmol/L in women or triglyceride level >2.0 mmol/L)

BMI, Body mass index; IGT, Impaired glucose tolerance; IFG, Impaired fasting glucose; HDL, High-density lipoprotein cholesterol

Age Age per se is not a risk factor for T2DM, however, the chances of being diagnosed

increase with advancing age with incidence greatest after 45 years (79). However,

over the last decade there has been a concerning trend for an increasing incidence in

younger adults, and even adolescents, which is likely driven by rising obesity rates

(123).

Chapter 2

Page | 18

Gender The reason males have a greater risk for T2DM has been proposed to be related to

differences in the anatomical distribution of fat relative to females (124-126). Males

have a predisposition to distribute their fat centrally which is a recognised and

independent risk factor for insulin resistance, glucose intolerance and several

cardiovascular risk factors (127-129). In contrast, women tend to store fat

peripherally which has not been found to be strongly associated with such metabolic

defects (126). Other proposed reasons for the gender differences include the effects

of the sex hormones oestrogen and testosterone (126). Oestrogen has been proposed

to have beneficial effects on insulin sensitivity via several possible mechanisms,

including directly effecting insulin and glucose homeostasis, involvement in adipose

tissue metabolism and body composition and/or effects on pro-inflammatory markers

(130-132).

Ethnicity Ethnic differences in the prevalence of T2DM remain well documented (133, 134),

with a higher prevalence (and incidence) observed in Asians, Hispanics and Blacks

compared to Caucasians, even after adjusting for recognised lifestyle factors (133).

In 2001 in Australia, approximately 35% of individuals who reported a diagnosis of

diabetes were born overseas (135).

Modifiable risk factors

Overweight and Obesity There is consistent and compelling evidence demonstrating that excessive body

weight is a major risk factors for the development of T2DM, with 60-90% cases

worldwide directly related to obesity (136-138). In a meta-analysis of prospective

cohort studies which included 18 trials in adults aged 18-80 years (total sample size

of 590,251), it was established that the relative risk of diabetes diagnosis if

overweight and obese was 2.92 (95% CI, 2.57 to 3.32) and 7.28 (95% CI, 6.47 to

8.28), respectively (139), independent of age, family history of T2DM and physical

activity. Additionally, the distribution of adipose tissue has been identified as an

important risk factor for T2DM, with central visceral adipose tissue (VAT) carrying

a greater degree of risk compared to subcutaneous fat distribution (140, 141). This

Chapter 2

Page | 19

has been attributed in part to the fact that VAT releases several bioactive molecules

and hormones, such as non-esterified free fatty acids and several pro-inflammatory

factors, which possesses unique characteristics that negatively influence a range of

metabolic complications and abnormalities, including insulin resistance, glucose and

lipid metabolism, which can lead to endothelial dysfunction, all of which have been

found to directly precede the development of T2DM (142, 143).

Loss of Muscle / Sarcopenia Losses in skeletal muscle are particularly detrimental for people at risk or diagnosed

with T2DM as skeletal muscle is the predominant (~80%) site of glucose disposal

under insulin stimulated conditions and is the major reservoir for glucose storage

(144, 145). It is well established that ageing is accompanied with a natural

progressive decline in skeletal muscle mass, most adults with T2DM appear to

experience this loss in muscle mass, strength and function, termed sarcopenia, at an

accelerated rate in comparison to healthy peers (146-148). Originally, this was put

down to a greater degree of type II muscle fibre atrophy (146, 147) however, others

have shown no difference in muscular myotype between healthy older adults and

those with T2DM (148). Instead, insulin resistance and reduced glycaemic control

both of which are independently associated with muscle loss, are believed to be

responsible (Figure 2.2) (149, 150). Further, several cross-sectional studies have

demonstrated an association between low muscle mass and insulin resistance,

impaired insulin secretion leading to a deterioration in glycaemic control and thus an

increased risk for T2DM, independent of central and visceral adiposity (6, 151-154).

This was confirmed in the third National Health and Nutrition Examination Survey

(NHANES) which reported a 10% increase in skeletal muscle mass was associated

with an 11% reduction in insulin resistance and a 12% decrease in the diagnosis of

pre-diabetes (10).

Chapter 2

Page | 20

Figure 2.2: Common aetiological pathways and the metabolic links shared between

sarcopenia and type 2 diabetes. Adapted from Landi et al. (155).

Physical Inactivity and Sedentary Behaviour Physical inactivity, defined as not meeting the current recommended level of

physical activity, is a fundamental modifiable risk factor for T2DM (156). Physical

inactivity results in reduced energy expenditure, facilitates weight gain and is

associated with abnormal glucose tolerance (157). It can also lead to increased levels

of pro-inflammatory cytokines and promote the development of an atherogenic lipid

and cholesterol profile, termed dyslipidaemia (157-160). Whilst the role of exercise

for the management of T2DM will be discussed in greater detail later in this thesis, a

considerable body of evidence indicates that physically active or regularly exercising

individuals have a 30-50% reduced risk for T2DM compared to their physically

inactive counterparts (157, 161). Further, recent observational and epidemiological

studies strongly suggest that irrespective of physical activity participation, sedentary

behaviour, defined as any waking activity characterised by an energy expenditure ≤

1.5 metabolic equivalents and a sitting or reclining posture, may also be a direct and

independent risk factor for T2DM (157, 162-164).

Chapter 2

Page | 21

Poor Diet Quality A large degree of uncertainty remains concerning specific macronutrients which may

modulate T2DM risk (165, 166), yet previous research reports indicate that Western

type diets, characteristically reflective of heightened consumption of processed,

energy dense foods (i.e. large amounts of red meat, processed meat, high fat dairy

products, sugar-sweetened beverages, sweets and desserts) are associated with

increased prevalence and incidence of T2DM, independent of age, BMI or physical

activity (167-169). Chronic excess energy consumption and increased dietary

saturated and trans fatty acid intake have all been associated with increased T2DM

risk (170-172). As such, nutrition recommendations made by peak health bodies such

as the NHMRC, Diabetes Australia and the ADA, advocate those at risk of T2DM to

reduce total calorie and saturated fat intake, achieve the recommended daily intake

for dietary fibre and consume foods containing wholegrains (166). More specific

details about the role of nutrition for the management of T2DM is discussed in

section 2.8.

Low Serum 25(OH)D A review of longitudinal, prospective and small-scale intervention studies provide

evidence that low levels of serum 25-hydroyxvitamin D (25(OH)D), the main

circulating form of vitamin D, are associated with future T2DM development (173).

In a recent meta-analysis which included 76,220 participants and had 4,996 incident

T2DM, each 10 nmol/L increment in serum 25(OH)D was associated with a 4%

reduced risk of T2DM (linear trend P<0.0001) (174). However, the findings from

several randomised controlled trials (RCTs) have largely found no effect of vitamin

D supplementation on glycaemia or T2DM incidence (22, 65, 175-180). As pointed

out in a recent review, a concrete conclusion cannot be determined from these trials

as the majority were designed for other primary outcomes with T2DM examined

post-hoc (181). More detailed information about the role of vitamin D in the

management of T2DM will be presented in section 2.9.

Chronic Low-grade Systemic Inflammation There is accumulating evidence from both in vitro, in vivo and epidemiological

studies suggesting that chronic low-grade systemic inflammation, defined as a two-

Chapter 2

Page | 22

to four-fold age-related increase in circulating inflammatory cytokines and acute

phase reactants, is implicated in a number of metabolic processes that contribute to

the development and progression of insulin resistance which plays a crucial

intermediary role in the pathogenesis of T2DM (16, 182-184). The quantifiable risk

posed by the presence of inflammation has not yet been confirmed with further

research in this area presently required. The effects of chronic inflammation in those

with T2DM will be discussed in further detail below.

2.6 Prevention of Type 2 Diabetes

Since T2DM is considered to be a lifestyle related disorder, numerous RCTs have

examined whether lifestyle interventions aimed at reducing weight, increasing

physical activity and improving dietary habits can reduce the risk for this disease.

Overall the findings from these studies indicate that T2DM is largely preventable,

even in those at high risk for this condition (27, 86, 185-190). For instance, the

Diabetes Prevention Study (DPP), the largest RCT conducted to date in this area,

randomised 3,234 participants with IGT to one of three interventions: 1) standard

lifestyle and metformin; 2) standard lifestyle plus placebo, or 3) an intensive lifestyle

program for four-years, with re-assessments conducted annually (191). Those in the

standard lifestyle intervention were provided written information on what constitutes

a healthy lifestyle. The intensive lifestyle intervention was goal oriented, with

participants encouraged to achieve at least 150 min/week of moderate-intensity

physical activity and a 5-10% reduction in weight. Participants in this group were

also advised to cease smoking, limit alcohol intake and reduce total and saturated fat

intake. To enhance successful achievement of the above recommendations,

participants were enrolled in a 16-session education program covering topics such as

exercise, nutrition and behaviour modification (191). After a mean follow-up of 3.2

years, there was a 58% relative risk reduction (RRR) in the incidence of T2DM in

the intensive lifestyle compared to standard lifestyle group, which was greater than

the 31% RRR in the metformin group (27, 192). Furthermore, the intensive lifestyle

intervention induced a greater reduction in HbA1c compared to either metformin or

control (27). A number of other RCTs have also reported favourable results with

similar lifestyle interventions (186, 193, 194). Collectively, these findings suggest

Chapter 2

Page | 23

that a lifestyle approach to prevent and manage this disease may be more effective

than pharmacological strategies.

In recent years, several systematic reviews and meta-analyses have examined the

effects of the above lifestyle interventions for the prevention of T2DM. Gillies et al.

(193) aimed to quantify the effectiveness of lifestyle and pharmacological

interventions on the delay or prevention of T2DM in those with IGT. Of the 17 trials

evaluated, seven focused on a combined lifestyle intervention (exercise and diet)

with the remaining ten either focussing on the effects of diet or exercise alone or the

combined effects of these with pharmaceutical agents. The lifestyle interventions

utilised in these seven studies examined the individual and combined effects of diet

and physical activity in comparison to a control group and were all implemented for

greater than six-months. Type 2 diabetes incidence was the primary outcome

measure in all studies included (193). The pooled effect for all types of lifestyle

interventions provided a hazard ratio of 0.51 (P<0.001), indicative of a 49%

reduction in risk of T2DM (193). When considering each intervention separately

(diet, exercise and diet and exercise), there was a similar reduction in risk [hazard

ratios 0.67 (95% CI, 0.49 to 0.92), P=0.013; 0.49 (95% CI, 0.32 to 0.74), P=0.001;

and 0.49 (95% CI, 0.40 to 0.59), P<0.001, respectively] (193). Pharmacological

interventions were also found to be as effective as lifestyle in reducing T2DM

incidence [hazard ratios 0.70 (95% CI, 0.62 to 0.79), P<0.001] (193). However, there

is evidence that the lifestyle interventions may offer a long-term risk reduction in that

they may reduce the incidence of T2DM beyond the active intervention phase (189).

For instance, in a 20-year follow-up of the Da Qing study population, a 43% reduced

risk of developing T2DM was observed in those in the combined intervention

compared to control group (189). In summary, the available evidence suggests that

long-term interventions targeting lifestyle behaviours are safe, feasible, and effective

at reducing the risk for developing T2DM, with the benefits extending beyond just

the intervention period.

The following sections of this literature review will discuss the results of human

intervention studies, with a focus on RCTs, which have examined solely or in

Chapter 2

Page | 24

combination the effects of exercise and/or nutrition modification on glycaemic

control, insulin sensitivity, body composition and cardiovascular risk factors in older

adults with T2DM.

2.7 Exercise for the Management of Type 2 Diabetes

Physical activity is central to the management of T2DM. The contractile muscle

activity associated with regular exercise produces a multitude of physiological,

biochemical and molecular changes within muscle cells which play an important role

in regulating blood glucose levels (195). These metabolic responses associated with

single bouts of exercise, which generally last 24-48 hours, can be translated to long-

term beneficial metabolic adaptations, which are largely ascribed to the accumulative

effects of repeated single-bouts of exercise (196). While it is beyond the scope of this

thesis to discuss in detail all the cellular responses to exercise, in people with T2DM

acute bouts of exercise have been shown to increase glucose transport through the

increase in number of glucose transporter type 4 (GLUT4) proteins and translocation

of these proteins to the muscle cell surface, which results in enhanced regulation,

utilisation and uptake of plasma glucose from the circulation into muscle,

subsequently reducing plasma glucose levels (157). In response to regular exercise

training, the flux through these muscle glucose uptake processes, which are

controlled by several insulin-independent signals generated within working muscles

and which are heavily dependent on levels of circulating insulin, are boosted in

individuals with T2DM (157). Importantly, long-term exercise performance has been

consistently shown to result in favourable effects on FPG, fasting insulin, HbA1c and

low grade systemic inflammation as well as cholesterol, blood pressure and body

composition, all important for the management of T2DM and the prevention or delay

in development of chronic complications (6, 23, 185). Indeed, the current Australian

exercise prescription guidelines for individuals with or at risk of T2DM recommend

a combination of aerobic and resistance training (Table 2.3) (185, 197). These

recommendations are consistent with the recent position statement from the

American College of Sports Medicine (ACSM) (197) and are included in the most

recent Standards of Care for Diabetes Patients published by ADA (198). Despite

these recommendations and the well-established health benefits, there is still some

Chapter 2

Page | 25

controversy surrounding the optimal dose (intensity, frequency, duration) that is most

beneficial for people with T2DM.

Table 2.3: Minimum exercise recommendations for patients with type 2 diabetes. Adapted from Hordern et al. (185).

Type of Exercise Intensity Duration/week Frequency

Aerobic Training (E.g. walking,

running, cycling, swimming)

Moderate 40-59% VO2R or HRR

55-69% HRmax RPE 12-13

OR

210-minutes No more than two

consecutive days without

exercising Vigorous

60-84% VO2R or HRR 70-89% HRmax

RPE 14-16

125-minutes

Progressive Resistance Training

Moderate to vigorous 8-10 exercises

2-4 sets 8-10 repetitions

1—2 min rest intervals

60-minutes (included in totals above)

2 or more times/week

VO2R= VO2 reserve, HRR=Heart rate reserve, HRmax=Heart rate maximum, RPE=Ratings of perceived exertion

2.7.1 Aerobic Training and Type 2 Diabetes

Aerobic or endurance exercise (running, brisk walking, swimming and/or cycling) is

recommended for the management of T2DM due largely to its positive effects on

reducing weight and improving cardiovascular risk factors (8, 199, 200). However,

such programs alone may not be the most efficacious to prescribe to individuals with

T2DM given that as many as 80% are overweight or obese and may suffer from any

number of long-term complications including CVD, impaired mobility or visual

impairment, that may make it challenging for these individuals to reach the required

volume and/or intensity of training to achieve health benefits (201). Additionally,

such training has little effect on lean mass and strength. For instance, some studies

have reported a loss in lean mass following participation in aerobic-type training,

Chapter 2

Page | 26

particularly when combined with weight loss induced by caloric restriction (7, 8).

Since skeletal muscle plays a critical role in glycaemic control and metabolic

homeostasis and accounts for up to ~80% of glucose disposal under insulin

stimulated conditions (145), losses in lean mass can negatively impact metabolic rate

and further compound the problems of insulin resistance and glycaemic control (6,

154). As a result, PRT is included in current exercise guidelines for people with

T2DM because it is widely recognised as a safe and viable mode of training that can

significantly improve lean mass, size and strength in older adults, including those

with T2DM. The following section will provide an overview of the available

evidence regarding the efficacy of PRT for improving glycaemic control, insulin

sensitivity, body composition, inflammation and cardiovascular health in adults with

T2DM.

2.7.2 Progressive Resistance Training and Type 2 Diabetes

2.7.2.1 Effects of PRT on Body Composition

As summarised in Table 2.4, a number of RCTs conducted over a period of 12- to

52-weeks have reported positive effects of PRT on lean mass and/or size, with gains

of up to ~1-2 kg (absolute net differences) reported after some trials (202) and

reductions in fat mass in the range of ~1 kg (12, 157, 202-208). It has been suggested

that the intensity of PRT is one of the most important parameters determining clinical

outcomes including change in weight and fat mass in those with T2DM (209, 210).

Many early resistance training studies which focused on light- to moderate-intensity

circuit type resistance training (50-59% of 1-repetition maximum (RM)) reported

modest or no marked effects on measures of body composition (205, 211). In

contrast, moderate- to high-intensity (≥ 60-80% 1-RM) PRT programs have typically

observed beneficial effects on both fat mass and lean mass (203). For instance, a 16-

week RCT in 62 adults with T2DM (mean ± SD; age 66 ± 8 years) found that thrice

weekly moderate to high-intensity (60-80% 1-RM) supervised PRT resulted in a

mean gain of 1.2 kg (P=0.04) in whole-body lean mass and a reduction of 0.7 kg

(P=0.01) in trunk fat mass in comparison to standard care (no exercise) (203). A

meta-analysis in older adults with T2DM which included 626 adults involved in 12

trials of eight to 12-week duration found that PRT was associated with a mean 1.5%

Chapter 2

Page | 27

reduction in total body fat percentage when compared to baseline (212). Ten of the

12 studies in this meta-analysis prescribed training intensity above 60% of 1-RM

(212). Collectively, the available evidence indicates that PRT programs which are of

moderate to high-intensity appear to be best for improving lean mass and reducing

fat mass in older adults with T2DM. Indeed, most current exercise prescription

guidelines for adults with T2DM recommend PRT programs consisting of 2 to 3 sets

of 8 to 12 repetitions at 50-75% 1-RM and containing 8-10 exercises targeting major

muscle groups of the body with training be performed 2 to 3 times per week (213).

Page | 28

Table 2.4: Summary of the main findings (between-group differences) in RCTs investigating the effects of PRT or the combination of PRT and aerobic training under supervised gymnasium-based settings in older adults with type 2 diabetes.

Reference Subjects Intervention Period,

Intervention and Training Frequency

Training Volume and Intensity Main Results and Adverse Events

PRT Training Alone

Church et al. 2010 (7)

n=262 Age (years) PRT: 56.9 ± 8.7 COMB: 55.4 ± 8.3 AE: 53.7 ± 9.1 CON: 58.6 ± 8.2 Men and women

36-weeks PRT, AE and combination of PRT and AE compared to controls 3 sessions per week

PRT: n=73 2- sets x 10-12 reps upper and lower body; 2 sets x 10-12 reps of 2 core exercises AE: n=72 Treadmill walking 150 min per week at 50-80% VO2 max. COMB: n=76; AE and PRT: PRT 2 sessions per week with only one set of above PRT program completed. CON: n=41 Non-exercise controls.

Fat mass: PRT ↓ 1.4 kg vs CON (P<0.05) Lean mass: PRT ↑ 0.8 kg vs COMB and AE (P<0.05) 21 adverse events with prevalence similar across groups (CON, 3 events; PRT, 8 events; AE, 6 events; and COMB, 4 events).

De Lade et al. 2016 (214)

n=23 Age (years) PRT: 57 ± 12 AE: 54 ± 9 Men and women

20-weeks Comparisons of PRT to AE

PRT: n=11 2-3 sets x 12-15 reps; moderate-intensity (established as 11-13 on the Borg scale of RPE) AT: n=12

No between-group differences in any outcomes including HbA1c, FPG, lipid or cholesterol levels, body weight, height, waist circumference. Lean mass and fat mass not assessed.

Page | 29

40 minutes of cycling, walking or elliptical machine use. Intensity controlled within 60-70% predicted HRmax or by utilising the Borg scale of RPE

No adverse events reported

Plotnikoff et al. 2010 (215)

n=48 Age (years) PRT: 55 ± 12 CON: 54 ± 12 Men and women

16-weeks PRT compared to control. 3 sessions per week

PRT: n= 27; Weeks 1-9 70-85% of 1-RM 3 sets x 10-12 reps Weeks 10-16 70-85% of 1-RM 3 sets x 8-10 reps CON: n=21 Non-exercise controls

HDL cholesterol: PRT ↑ 0.1 mmol/L vs CON (P=0.049) 1-RM muscle strength: PRT ↑ 9.3 kg bench press, ↑ 41.0 leg press, ↑ 12.4 kg upright row vs CON (all P<0.01). Fasting insulin in PRT reduced significantly compared to baseline only. No adverse effects reported.

Honkola et al. 1997 (216)

n=38 Age (years) PRT: 62 ± 2 CON: 67 ± 2 Men and women

20-weeks PRT compared to control. 2 sessions per week

PRT: n=18 Moderate-intensity circuit style PRT (intensity NS) CON: n=20 Non-exercise controls

HbA1c: PRT ↓ 0.5% vs CON (P<0.05) No reported adverse events.

Castaneda et al. 2002 (203)

n=62 Age (years) PRT: 66 ± 2 CONT: 66 ± 1 Men and women

20-weeks PRT performed 3 sessions per week

PRT: n=31 Weeks 1–8; 60–80% of 1-RM Weeks 10–14; 70–80% 1-RM CON: n=31

Lean mass: PRT ↑ 1.2 kg vs CON (P=0.04) HbA1c: PRT ↓ 1% (absolute reduction) vs CON (P=0.01)

Page | 30

Non-exercise controls SBP: ↓ 17.4 mmHg PRT vs CON (P=0.05) No complications or injuries reported.

Cauza et al. 2005 (202)

n=39 Age (years) PRT: 56.2 ± 1.1 AE: 57.9 ± 1.4 Men and women

16-weeks PRT performed 3 sessions per week

PRT: n=22 Moderate-intensity (No % of 1-RM supplied), training targeted towards muscle hypertrophy 3 sets x 10-15 reps AE: n=17 Cycle ergometer at 60% VO2max

HbA1c: PRT ↓ 0.9% vs AE (P=0.04) Blood glucose: PRT ↓ 56 mg/dL vs AE (P=0.002), HOMA-IR: PRT ↓ 3.5 vs AE (P=0.009) TC: PRT ↓ of 78 mg/dL vs AE (P=0.002) Body composition was not assessed. No adverse effects reported.

Dunstan et al. 2002 (12)

n=29 Age (years) PRT: 66.9 ± 5 PRT+WL: 67.6 ± 5 Men and women

24-weeks PRT combined with a weight loss (WL) program compared to sham exercise and WL 3 times per week

PRT+WL: n=16 75-85% 1-RM 3 sets x 8-10 reps plus moderate WL diet WL: n=13 Sham exercise (stretching) plus moderate WL

HbA1c: PRT+WL ↓ 0.8% (absolute reduction) vs WL (P<0.05) Lean mass: PRT+WL ↑ 0.9 kg vs WL No adverse events

Sigal et al. 2007 (8)

n=251 Age (years)

26-weeks PRT: n=64 HbA1c: PRT ↓ 0.38% vs CON (P=0.038)

Page | 31

PRT: 54.7 ± 7.5 AE: 53.9 ± 6.6 COMB: 53.5 ± 7.3 CON: 54.8 ± 7.2 Men and women

PRT, AE and the combination were compared to controls 3 times per week

2-3 sets x 7-9 reps maximal weight that could be lifted (no % of 1-RM training rate supplied) AE: n=60 60-75% HRmax on treadmills and bicycles COMB: n=64 Both the PRT and AE programs completed CON: n=63 Non-exercise controls

Thigh muscle CSA: PRT ↑ 8.0 cm2 vs CON (P<0.001) Four individuals, all in the AE group, withdrew because of adverse events; 38% of exercise group participants and 14% of control reported an adverse event.

Mavros et al. (217)

n=103 Age (years) PRT: 67.1 ± 4.8 CON: 68.9 ± 6.0 Men and women

48-weeks PRT program compared to sham exercise 3 sessions per week

PRT: n=47 80% of 1-RM with concentric explosive force. 3 sets x 8 reps CON: n=53 Sham exercises (no load and no progression)

Mid-thigh muscle CSA: PRT ↑ 5.6 cm2 vs CON (P<0.01) No adverse effects reported

Kwon et al. 2010 (208)

n=28 Age (years) PRT: 55.7 ± 6.2 CONT: 57.0 ± 8.0 Women only

12-weeks PRT compared to controls 3 sessions per week

PRT: n=13 Light resistance building to 40-50% 1-RM (Thera-bands) by week 12 CON: n=15 Non-exercise control group

Lean mass: PRT ↑ ~2 kg vs CON (P=0.007) Fat mass: PRT ↓ ~1 kg vs CON mass (P=0.039) No adverse effects reported.

Jorge et al. 2011 (218)

n=48 Age (years) PRT: 54.1 ± 8.9

12-weeks Comparisons of PRT, AE and combination to controls

PRT: n=12 Whole body program (no intensity or rep information provided)

No differences between the groups for insulinaemic or glycaemic outcomes, blood

Page | 32

AE: 52.1 ± 8.7 COMB: 57.9 ± 9.8 CON:53.4 ± 9.8 Men and women

3 sessions per week AE: n=12 Cycling at a heart rate corresponding to lactate threshold COMB: n=12 PRT interchanged with AE performed at same intensity and half the volume of the AE and PRT groups. CON: n=12 Sham (Light stretching)

pressure or lipid profile. Body composition not assessed. No adverse events reported.

Combination Training

Balducci et al. 2012 (219)

n=606 Age (years) COMB: 59.0 ± 8.9 CON: 61.9 ± 8.0 Men and women

52-weeks Combination of PRT and AE compared to a usual care program. 2 sessions per week

COMB: n=303 AE: 55–70 % of VO2max using a treadmill, step, elliptical, arm, or cycle-ergometer. PRT: 60–80% of 1-RM (no sets or reps information was provided) CON: n=303 Non-exercise (received usual care)

HbA1c: COMB ↓ 0.3% vs CON (P<0.001) Fasting insulin: COMB ↓ 1.18 pmol/L vs CON (P<0.001) HOMA-IR: COMB ↓ 0.36 vs CON (P=0.047) SBP and DBP: COMB ↓ 4.2 and 1.7 mmHg vs CON (both P<0.01) LDL: COMB ↓ 9.6 mg/dL vs CON (P<0.003) HDL: COMB ↑ 3.7 mg/dL vs CON (P<0.001) BMI: COMB ↓ 0.78 kg/m2 vs CON (P<0.001)

Page | 33

Adverse effects related to training were more frequent (not significant) in COMB than in CON subjects.

Cuff et al. 2003 (220)

n=28 Age (years) COMB: 59.4 ± 1.9 AE: 63.4 ± 2.2 CON: 60.0 ± 2.9 Women only

16-weeks Combination of PRT and AE compared to AE and controls 3 sessions per week

COMB: n=10 PRT: Light – moderate 2 sets x 10-12 reps AE: 60-75% heart rate reserve using mixed aerobic equipment (treadmills, bicycles etc.) AE: n=9 60-75% heart rate reserve using mixed aerobic equipment (treadmills, bicycles etc.) CON: n=9 Non-exercise control group

Body weight: COMB ↓ 4.9 kg vs CON (P<0.05) No complications or adverse events reported

Tan et al. 2012 (221)

n=25 Age (years) COMB: 65.9 ± 4.2 CON: 64.8 ± 6.8 Men and women

24-weeks Combination training versus control 3 sessions per week

COMB: n=15 AE: 30 minutes of walking/running intensity controlled within the individualised 55-70% predicted HRmax PRT: 2 sets x 10-12 reps 50-70% of 1RM CON: n=10 Maintenance of daily activities without commencing exercise

HbA1c: COMB ↓ of 0.61% vs CON (P<0.05) % Body Fat: COMB ↓ 2.3% vs CON (P<0.05) Total cholesterol: COMB ↓ 1.35 mmol/L in TC (P<0.001) TG: COMB ↓ 0.83 mmol/L vs CON (P<0.05)

Page | 34

No reported injuries or adverse effects of training

Liu et al. 2015 (222)

n=48 Age (years) COMB: 52.6 ± 11.4 CON: 51.2 ± 11.3 Men and women

12-weeks Combination of AE and PRT compared to controls 3 sessions per week

COMB: n=21 AE: The exercise intensity for each patient set at 40–60% of VO2max. PRT: 50–60% 1-RM CON: n=17 Conventional therapy

HbA1c: COMB ↓ 0.52% vs CON (P<0.001) Postprandial blood glucose: COMB ↓ 1.9 mmol/L vs CON (P<0.01) Postprandial insulin: COMB ↓ 22.6 mmol/L vs CON (P<0.05) TG: COMB ↓ 0.79 mmol/L vs CON (P<0.05) No adverse events reported.

Note-Only significant changes relative to controls (between-group differences) are reported. Data reported as net differences. Age is mean ± SD. Abbreviations: PRT, Progressive resistance training; AE, Aerobic exercise; COMB, Combination of PRT and AE; CON, control; WL, weight loss; CSA, Cross-sectional area; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, total triglycerides; ↓ decrease; ↑ increase; HRmax, heart rate maximum; 1-RM, 1 repetition maximum; VO2max, maximal oxygen uptake, RPE, ratings of perceived exertion; NS, not stated

Chapter 2

Page | 35

2.7.2.2 Effects of PRT on Glycaemic and Insulinaemic Outcomes

In those with T2DM there is consistent evidence from RCTs and meta-analyses of

these trials demonstrating that structured and supervised PRT is effective at

improving FPG, insulin sensitivity (HOMA-IR) and HbA1c as shown in Table 2.4

(12, 203, 205, 212, 223-228). Similarly, there is evidence that PRT can improve

glucose disposal rates, increase glycogen storage capacity and increase the number of

GLUT4 receptors on muscle, which is important because glucose uptake by

contracting skeletal muscle occurs by facilitated diffusion, dependent on the presence

of GLUT4 in the surface membrane and an inward diffusion gradient for glucose

(229). Despite these favourable findings, what remains less clear is the specific

characteristics of a PRT program (intensity, frequency and duration) that are most

effective. While it is beyond the scope of this thesis to review all the studies

conducted in this area, the following section will focus on training intensity and its

effects on glycaemic control and insulin sensitivity as as mentioned previously,

training intensity is proposed to be a key influencing factor determining the success

or failure of exercise programs to affect a range of clinically relevant health

outcomes in those with T2DM.

One of the first studies to examine the glycaemic and insulinaemic changes in adults

with T2DM following participation in PRT utilised a supervised low to moderate-

intensity (~50-55% of 1-RM) circuit resistance training program (205). Fifteen

previously sedentary adults (mean age, 51 years) performed supervised circuit

resistance training three times per week for eight-weeks (205). Significant reductions

were observed in both glucose and insulin area under the curve (AUC) in the training

group compared to controls as assessed from OGTT (205). There was no change in

HbA1c, which may be related to the relatively short intervention period of only 8-

weeks and/or the low-moderate training intensity (205). Assessment of HbA1c is best

made at three-monthly intervals due to the long lifespan of red blood cells. In

contrast to these findings, a five-month trial which included supervised modest

intensity PRT (2 sets, 12-15 reps, intensity monitored with the Borg scale) performed

twice per week in 18 adults with T2DM reported a significant net 0.5% absolute

benefits to HbA1c in the training compared to control group (216). However, it is

important to note that there was no change in HbA1c in the PRT group (7.5 ± 0.3% to

Chapter 2

Page | 36

7.4 ± 0.2%), and so the net difference was largely driven by a deterioration in HbA1c

levels in the control group (7.7 ± 0.3 to 8.1 ± 0.3%, P<0.01) (216). The lack of an

improvement in the PRT group in this study may be related to the modest training

dose (twice per week, 2 sets of 12-15 reps) and/or intensity (modest as assessed by

the Borg scale). Based upon the findings presented here and the results of others

(214), low- to moderate-intensity PRT programs appear to have little or no marked

effects on improving HbA1c levels. In a meta-analysis of 23 studies comprising 954

patients with T2DM which aimed to define the characteristics of PRT that might be

most effective for improving glycaemic control, it was reported that there was no

relationship between training intensity and HbA1c reduction (Table 2.5) (228).

However, it should be noted that most of the included trials in this meta-analysis

prescribed similar training programs and intensities (50-80% of 1-RM) and thus there

was potentially not enough heterogeneity between the studies to detect differences.

Several studies have found that high-intensity PRT in which the training load is 75-

85% of 1-RM is safe, well-tolerated and effective for improving HbA1c and insulin

sensitivity in older adults with T2DM (12, 203, 230). For instance, a 16-week RCTs

in 62 older adults with T2DM (mean age ± SE, 66 ± 2 years) compared the effects of

supervised moderate- to high-intensity (60-80% 1-RM) PRT versus standard care on

glycaemic control, FPG and insulin sensitivity (203). Participants allocated to the

PRT program who completed three supervised 45-minute training sessions per week

demonstrated a significant improvement in HbA1c (8.7 ± 0.3% to 7.6 ± 0.2%) when

compared to control (8.4 ± 0.3% to 8.3 ± 0.5%, P = 0.01) (203). Additionally, in

subsequent analysis of this same study insulin resistance (HOMA-IR) was found to

improve in the PRT group (median reduction 0.7%, P=0.05) and deteriorate in the

controls (mean increase 0.8%, P=0.05) (230). No significant change was observed in

FPG or insulin for either group (203, 230). Importantly, of the 62 individuals who

participated in this trial, all but two completed the PRT program with exercise

compliance reported above 90% in the PRT group. This demonstrates that high-

intensity PRT was safe and well-tolerated by older adults with T2DM (203).

In recent years several meta-analyses have investigated the effects of training dose

on measures of glycaemic control and insulinaemic outcomes following PRT in

Chapter 2

Page | 37

people with T2DM (212, 227, 228). While these meta-analyses have consistently

reported beneficial effects of PRT on HbA1c (effects size -0.32 to -0.64), they have

been unable to find any association between training intensity, frequency or number

of exercises performed and an improvement in HbA1c. However, in the meta-analysis

by Ishiguro et al. (228) they reported that completing ≥21 sets of PRT per session

was associated with a greater improvement in HbA1c compared to <21 sets (Table

2.5). While this suggests that the total dose of training may be more important than

the intensity, it is important to note that many of the RCTs included in this meta-

analysis used a similar training frequency (3 sessions per week) and intensity (60-

80% 1-RM), which is what is commonly recommended for adults with T2DM. Thus,

the effects of PRT programs greater than this volume on HbA1c remain inconclusive

(228).

In summary, the literature reviewed above and presented in Table 2.4 suggests that

moderate to high-intensity supervised and structured PRT performed three times per

week is safe, manageable and results in clinically meaningful improvements in

glycaemic control in older adults with T2DM (12, 202, 203, 212, 227, 228). This

aligns with the current physical activity guidelines for individuals with T2DM by

bodies such as the ADA and Exercise Sports Science Australia (ESSA) who

recommend PRT at a moderate- to high-intensity be incorporated into a physical

activity plan and performed at least twice a week, including all major muscle groups

(185, 231).

Chapter 2

Page | 38

Table 2.5: Analysis of effect size for change in HbA1c stratified by characteristics of the PRT program. Adapted from Ishiguro et al. (228).

Program Characteristic

Number of RCTs

Effect size (%) (95% CI)

I2 P-valuea

P-valueb

Intervention Period ≥12-weeks 12 -0.33 (-0.60 to -0.06) 84.9 <0.001

<12-weeks 11 -0.39 (-0.62 to -0.17) 46.5 0.04 0.72

Frequency ≥3-weeks 17 -0.25 (-0.44 to -0.06) 77.8 <0.001

<3-weeks 6 -0.66 (-0.88 to -0.44) 11.7 0.34 0.09

Number of Exercises ≥9 items 10 -0.54 (-0.90 to -0.19) 49.7 0.04

<9 items 13 -0.25 (-0.47 to -0.04) 84.1 <0.001 0.24

Intensity ≥75% 1-RM 10 -0.41 (-0.72 to -0.09) 86.8 <0.001 <75% 1-RM 10 -0.30 (-0.51 to -0.09) 53.3 0.02 0.60

Interval (time between exercises) ≥1.5 min 8 -0.47 (-0.88 to -0.06) 91.3 <0.001

<1.5 min 5 -0.38 (-0.97 to -0.21) 0.0 0.95 0.85

Total sets per session ≥21 sets 10 -0.65 (-0.97 to -0.32) 62.7 0.004

<21 sets 13 -0.16 (-0.38 to 0.05) 79.8 <0.001 0.03

Total sets per week ≥60 sets 14 -0.32 (-0.58 to -0.06) 80.9 <0.001

<60 sets 9 -0.40 (-0.70 to -0.09) 72.6 <0.001 0.09 a P-value for heterogeneity b P-value for difference between strata. 1-RM, 1 repetition maximum; CI, confidence interval; RCTs, Randomised controlled trials.

2.7.2.3 Effects of PRT on Markers of Inflammation

Some, but not all, cross-sectional and longitudinal studies have demonstrated that

regular physical activity, with or without weight loss, can reduce circulating levels of

inflammatory markers (232-235). While the vast majority of interventional research

in this area has focused on the effects of aerobic training or general physical activity,

there is some, albeit limited, evidence that participation in PRT can improve

Chapter 2

Page | 39

circulating inflammatory markers in older healthy adults, with only limited

favourable evidence in adults with T2DM (218, 222, 230, 236-240). For example, 26

overweight/obese older adults (mean aged 61 years) with T2DM who performed

moderate-to-high intensity (60-80% 1-RM) PRT three times per week (236) for 12-

weeks experienced a non-significant 0.52 mg/L reduction in hs-CRP in comparison

to a control program (P=0.189) (236). The lack of significance observed was

proposed to be due to either the lack of fat mass reduction or that the volume of

training required to reduce inflammation is greater than what was prescribed in this

trial. In another trial, the change in IL-6 and hs-CRP was assessed in 102 sedentary

middle-aged and older adults (40-65 years of age) performing either; PRT (n=35, 70-

75% 1-RM) or aerobic training (n=41, 70-75% HRmax) or no exercise (controls,

n=25) for 10-weeks (240). A 3.7% reduction in total body fat mass and a 32.7%

reduction in hs-CRP in the PRT group compared to baseline (P<0.05) was observed

in the PRT group (240). Post-hoc analyses demonstrated there was a trend towards a

difference in hs-CRP in the PRT group compared to the post-intervention aerobic

and control group (P=0.11 and P=0.08, respectively) which authors suggested to be

due to the significant pre-post reduction in percentage fat mass, although a

significant pre-post reduction in percentage fat mass was observed in the aerobic

group without the same trend towards a significant reduction in hs-CRP (240). As

this trial, and the previous study by Kadoglou et al. (236) prescribed similar training

interventions the contrasting results suggest that improvements in inflammation are

likely related to changes in fat mass.

Mechanistically, it has been suggested that reductions in fat mass are required to

reduce inflammatory gene expression in visceral adipose tissue (241, 242). Others

have suggested that the improvements in inflammation following weight loss are due

to a shift in the activity of lipolysis; adipocyte lipolysis is known to increase adipose

tissue inflammation (243). Whilst the mechanism(s) remain undefined, evidence

from some RCTs demonstrate an association between reductions in fat mass and/or

increases in lean mass and improvements in inflammation. In a recent trial in which

older (mean age 68 years) diabetic adults were randomised to 12-months of high-

intensity PRT (80% 1-RM) or a sham exercise program (low-intensity, non-

progressive exercise), performed three days per week (238), it was found that hs-

Chapter 2

Page | 40

CRP levels tended to decrease more in the PRT group when compared to sham

(P=0.087) (238). Further analysis of these results revealed that reductions in hs-CRP

were associated with both increases in muscle mass (r=-0.48, P=0.01) and reductions

in total fat mass (r=0.45, P=0.02) in the PRT group, but not in the sham group (238).

This suggests that the greatest benefits on inflammation may be achieved with

exercise-induced fat loss combined with muscle gain. Despite these positive results, a

limitation of this trial was that they only assessed one inflammatory marker and as

such further studies are needed to not only confirm these results but to also examine

the effects of PRT on other inflammatory markers. Recently, findings from a meta-

analysis of exercise interventions on inflammatory markers that included 14 RCTs in

people with T2DM, three of which included PRT, found that mostly aerobic but

some PRT programs of longer duration or which had a larger number of total training

sessions were associated with the greatest benefits for circulating IL-6 levels (244).

This suggests that the duration and dose of training may play an important role in

improving systemic inflammation (244).

In summary, epidemiologic studies demonstrate that exercise plays a role in reducing

inflammation, and whilst the body of evidence is small from intervention studies in

adults with T2DM, there are some studies which have observed an improvement

which may be explained by the duration or dose of the training program or

concomitant changes in body composition.

2.7.2.4 Effects of PRT on Blood Pressure and Blood Lipids

There is some evidence that PRT can also lower blood pressure in adults with T2DM

(245, 246), although others have also observed no marked benefits (8). For example,

6-months of high-intensity PRT (75-85% 1-RM, 3 sessions per week, 3 sets of 8-10

repetitions) in 29 older (mean age, 67 years) obese (mean BMI, 31.5 kg/m2) adults

with T2DM lowered systolic blood pressure (SBP) and diastolic blood pressure

(DBP) by 6.7 and 4.4 mmHg, respectively (P<0.01) (12). However, since this 6-

month program also involved a moderate weight-loss diet the improvements in blood

pressure may not have been the result of PRT alone. However, 12-weeks of PRT (3

times per week, 60 minutes per session) in 48 older overweight adults (age ± SD 54.1

± 8.9 years, BMI ± SD 30.9 ± 4.1 kg/m2) with T2DM significantly lowered both SBP

Chapter 2

Page | 41

and DBP (10 and 2.5 mmHg, respectively P<0.05) compared to baseline but not

when compared to controls or aerobic or combined aerobic and PRT (218). A recent

meta-analysis of ten RCTs in 403 participants which aimed to determine the effects

of structured PRT on blood pressure changes in adults with T2DM, Figueria et al.

(247) reported that PRT performed on average three times per week ranging from

eight to 26-weeks was associated with significant 4.44 mmHg (95% CI, -6.76, -2.11)

and 2.84 mmHg (95% CI, -3.88, -1.81) (both P<0.05) reductions in SBP and DBP

respectively, compared to controls (247). Sensitivity analysis also demonstrated that

the greatest reductions in blood pressure occurred in those with hypertension at

baseline (247). Analyses of data according to the weekly amount of exercise found

the improvements in blood pressure were greatest when PRT was performed for

more than a total of 150 minutes per week (247).

Dyslipidaemia, like hypertension, is common among those diagnosed with T2DM

and is significantly associated with CVD (93). While there is some evidence that

PRT can have a positive effect on lowering lipids levels in adults with T2DM (218,

248-251), some studies have observed no effect (12, 252, 253). Studies as short as 8-

weeks have demonstrated improvements in triglyceride and/or cholesterol levels

(248) while others have observed long-standing improvements in serum lipids with

training interventions up to 12-months (249). For instance, a study conducted in 236

older men and women (mean age 74 years) who performed 12-weeks of PRT (3

times per week; 3 sets, 6-8 repetitions at 75-80 % of the 1-RM) demonstrated

significant reductions in LDL cholesterol (mean change 0.47 mmol/L), total

cholesterol (mean change 0.67 mmol/L) and triglycerides (mean change 0.14

mmol/L) (all P<0.05). The positive effects of PRT on cholesterol and lipid levels has

been suggested to be due to reductions in cholesterol formation and/or increases in

lipid oxidation via an increase in lipoprotein lipase, although this remains to be

confirmed (249, 254). As stated above, not all studies have observed a favourable

response of PRT on blood lipids. A 6-month trial of high-intensity PRT (3 days per

week, 80% 1-RM) was found not to alter levels of triglycerides, total, LDL or HDL

cholesterol in 16 older adults (mean age ± SD, 67.6 ± 5.2 years) with T2DM who

were also on a moderate weight loss diet (-500 calories/day) in comparison to sham

exercise and weight loss alone (n=13, mean age ± SD, 66.9 ± 5.3 years) or even

Chapter 2

Page | 42

baseline (12). The lack of an effect may have been due to participants presenting

with relative normal lipid levels at baseline and/or the fact that both groups in this

study lost a similar amount of weight and fat mass (12). A recent meta-analysis

which included 12 intervention trials ranging from 8- to 12-months and which

compared aerobic and resistance exercise in adults with T2DM, provided important

clinical insights into cardiovascular health outcomes following such training

programs (212). A total of 422 participants from ten of the 12 trials examined

provided within-group pre-post change data on serum triglycerides and HDL levels

(212). Improvements in serum triglycerides were pooled from aerobic and PRT

interventions and found to be significant [triglycerides −0.33 mmol/L (95% CI

−0.47, −0.18), all P<0.05] (212). Within this meta-analysis pooled data from nine

PRT trials found that this mode of training resulted in significant reductions in both

LDL [mean change: -0.05 mmol/L (95% CI −0.09 to −0.01)] and total cholesterol

[mean change -0.22 mmol/L (95% CI −0.30 to −0.14)] (212).

In summary, there is a growing body of evidence from a number of RCTs and even a

few meta-analyses in older adults with T2DM which report significant beneficial

effects of structured and clinically controlled PRT programs PRT on serum lipids

and blood pressure levels. While the findings from some studies may be confounded

by the addition of weight loss via caloric restriction, these effects appear to be

magnified in those with hypertension and dyslipidaemia at baseline.

2.7.3 Efficacy of Community-Based Resistance Training Programs

Most research examining the health benefits of PRT in people with T2DM have been

conducted in tightly-regulated, structured and supervised clinical exercise

laboratories where both participants and research conditions are highly controlled.

The effectiveness of less controlled community-based training programs on body

composition changes in older adults with T2DM is less clear, but from a public

health perspective it is important to understand just how effective PRT programs are

when undertaken in the community (255). Community settings provide an optimal

avenue for assessing the relevance and applicability of research-to-practice

programs. Intervention studies in older adult’s show that group-based community

exercise programs can increase time spent exercising and frequency of exercise (256,

Chapter 2

Page | 43

257). Furthermore, previous research measuring the economic value of research-to-

practice programs in community settings has found participation in such programs

may reduce total healthcare costs for older adults (24).

In a retrospective analysis of a 24-week community based research-to-practice PRT

program called Lift for Life® (75-85% 1-RM, 3 sets of 8-10 reps performed 3 times

per week), in which training was supervised but performed in small groups (not one-

on-one supervision) in a community setting, 86 adults with or at risk for T2DM

demonstrated significantly lower central obesity following 8-weeks of training [mean

reduction in waist circumference: -1.9cm (95% CI, -2.8 to -1.0)]. By 24-weeks, the

mean reduction in waist circumference -4.9 cm (95% CI, -6.7 to -3.0; P<0.001 for a

time effect) in those individuals (n=36) who completed the full training program

(255). Although this study did not include assessment of other common clinically

relevant outcomes (e.g. HbA1c, lean mass, blood pressure, lipids etc.) these results

highlight that community-based PRT programs, with less supervision than a clinical

exercise laboratory-based trial, may be effective in improving health and body

composition measures in older adults with T2DM.

A recent meta-analysis further supports community-based exercise programs as

effective methods for managing T2DM (23). Pooling 11 studies examining

community-based physical activity interventions, largely performed using exercise

machines or group physical activity education programs, yoga classes, telephone

counselling or motivational techniques with some interventions also based in social-

cognitive theories or interventions that were tailored based on such theories,

demonstrated that such interventions were effective in reducing HbA1c levels (0.32%

absolute reduction) which only approached statistical significance (P=0.06) possibly

because four of the studies included in this meta-analysis reported no change in

HbA1c (23). This meta-analysis further demonstrated that community-based physical

activity programs were also effective in reducing weight and waist circumference

and increasing habitual physical activity levels (23). Collectively, these findings

indicate that community-based physical activity programs can provide important

health improvements in adults with T2DM (23). Additionally, such programs have

been found to be cost-effective for individuals with T2DM and there is also evidence

Chapter 2

Page | 44

of lower health care utilisation in individuals with T2DM who attain minimum

physical activity guidelines (258, 259). Despite this evidence, a number of

unanswered questions still remain in relation to other outcomes of relevance to older

adults with T2DM such as effects on insulin sensitivity, lipids and cholesterol,

inflammation and the longer-term maintenance of such programs over periods of

time greater than 2-months. Further, little is known about the enhanced effect

nutrition may provide in addition community-based PRT interventions on these

aforementioned outcomes.

2.8 Nutrition for the Management of Type 2 Diabetes

Traditionally, nutrition recommendations made by peak medical and/or nutrition

authorities around the world for people with T2DM have recommended a percentage

energy contribution from carbohydrate, fat and protein of 50-60%, ≤30% and 10-

20%, respectively (Table 2.6). In addition, these recommendations suggest

consuming moderate amounts of polyunsaturated fat whilst restricting saturated fat

intake due to the apparent adverse effects on CVD and related outcomes (260-262).

The rationale for such a macronutrient distribution was based on preventing

excessive spikes in chronic and post-prandial glycaemia and improving plasma lipid

profiles to reduce CVD risk (263). While less attention has been given to dietary

protein, there is emerging evidence to support an important physiological role of

dietary proteins and constituent amino acids as part of an overall diet in the

management of T2DM (264-267). However, questions remain as to what proportion

of energy intake should be derived from dietary protein for adults with T2DM. The

following sections will provide an overview that the role dietary protein may play in

modulating important metabolic and physiological health outcomes in adults with

T2DM.

Chapter 2

Page | 45

Table 2.6: Macronutrient recommendations for the management for type 2 diabetes by the British and American Diabetes Association and the American Heart Foundation. Sourced from Ajala et al. (268).

Variable Diabetes UK (262) ADA (260) AHA (261)

Carbohydrate (%) 50-55 50-60 45-55

Fat (%) 30-35 35-35 <30

Protein (%) 10-15 15-20 12-20

ADA, American Diabetes Association; AHA, American Heart Association

2.8.1 High Protein Diets for the Management of Type 2 Diabetes

The following section provides a brief overview of the effects of diets high in protein

(i.e. 30% energy from protein) on glycaemic and insulinaemic outcomes, change in

body composition, triglycerides, cholesterol, blood pressure and markers of

inflammation in older overweight adults and those with T2DM. Subsequent to this

section is a more in-depth discussion about the role and potential health benefits of

protein supplementation (i.e. whey protein) for adults with T2DM.

2.8.1.1 Effects of a High Protein Diet on Glycaemic and Insulinaemic Outcomes

Previous research has shown that short-term diets higher in protein can have

favourable influence on glycaemic measures in overweight adults (265, 269) as well

as those with T2DM (263, 267, 270-272). For instance, in eight men with T2DM

who were randomly assigned to consume a high (30% total energy) or low (15%

total energy) protein diet for 5-weeks there was a 29% (P<0.003) reduction in FPG in

the high protein group by week 5; HbA1c was significantly reduced by week 3 and

22% lower than the low protein group by week 5 (P<0.05) (272). However, longer-

term (at least 12-months) dietary intervention trials examining the effects of

increased dietary protein provide mixed evidence regarding the effects on glycaemic

control in adults with T2DM (273, 274). For instance, a study of 419 adults with

T2DM aged 30–75 years with a BMI >27 kg/m2 who were randomised to

hypocaloric diets of either high protein (30% of energy) or lower protein (15% of

energy) for 12-months found no significant differences in FPG or HbA1c (274).

However, in this study only 6% of the high protein diet group attained the target

protein intake (25% energy from protein) with the remainder consuming < 21%

Chapter 2

Page | 46

energy from protein (274). The authors of this study suggested that the null findings

were likely attributed to the difficulty participants had in achieving the prescribed

protein intake over an extended period. Nevertheless, the findings from a meta-

analysis of nine RCTs ranging in duration from 4- to 24-weeks and including 418

adults with T2DM (mean age 46–63 years and BMI 31–39 kg/m2) revealed that high

protein (25-32% of total energy) compared to normal or low protein (15-20% of total

energy) diets led to significant reductions in HbA1c [mean difference, 0.52% (95%

CI, -0.90, -0.14)] (38). Based on these findings, increasing dietary protein intake may

play a valuable role in optimising glycaemic control in adults with T2DM. Questions

remain as to whether such an approach is feasible and sustainable in the long-term

and, what the optimal dietary protein intake is to achieve clinically meaningful

benefits in glycaemic control.

Dietary protein and specific amino acids, particularly arginine, leucine and

phenylalanine, have also been reported to offer acute insulinotropic effects, a

phenomenon observed in several acute postprandial trials and which has been

observed to occur in older adults with long-standing T2DM (275-277). Whilst the

exact mechanism(s) behind this process have not yet been fully identified, it appears

amino acids promote the secretion of insulin from the pancreatic beta-cell (278-280).

For instance, one study in 60 older adult males with T2DM found that protein (0.3

g/kg) or protein hydrolysate (0.3 g/kg) with co-ingestion of carbohydrate was

associated with a 99 and 110% postprandial increase in insulin in comparison to

carbohydrate ingestion alone, whilst attenuating the postprandial rise in glucose by

22% (281) with other researchers reporting similar observations in acute settings

observing similar in an acute setting (275-277). Despite these positive acute effects

on insulin, the effects of longer-term (≥12-weeks) high protein diets on fasting

insulin and insulin sensitivity in older overweight adults (282-285) and in older

adults with T2DM (286-288) remain mixed. Indeed, several of the studies conducted

to date in those with T2DM are confounded by the incorporation of caloric restriction

which has led to weight loss. For example, in the study by Brinkworth et al. (288) 66

obese adults with T2DM were randomised to a high protein (30% energy) or low

protein (15% energy) diet plus energy restriction for 8-weeks followed by 4-weeks of

energy balance. At the end of the 12-week period the high protein diet resulted in a

Chapter 2

Page | 47

22% reduction in HOMA-IR and a 14% reduction in fasting insulin levels (both

P<0.01) when compared to baseline (288). This reduction was no different to the low

protein group likely explained by the fact both groups lost a similar amount of

bodyweight (288). As there was no high protein diet group without energy restriction

in this trial, the effects of a higher protein diet in the absence of weight loss remains

uncertain in older adults with T2DM. However, recently an improvement in HOMA-

IR independent of weight loss in overweight and obese women without T2DM (mean

age ± SD, 44.0 ± 9.1 years and BMI 37.7 ± 3.4 kg/m2) was observed when

consuming a diet providing 27 and 35% energy as protein. The same improvement in

HOMA-IR relative to baseline was not seen in those consuming only 20% energy

from protein in the same trial (289). In summary, the effects of high protein diets on

fasting insulin and insulin sensitivity/resistance appear to be favourable in older

adults with T2DM yet the studies conducted to date are confounded by the

prescription of caloric restriction to induce weight loss. Further trials are required

which prescribe a high protein diet in the absence of caloric restriction to investigate

whether a high protein diet without weight loss can improve insulinaemic outcomes

in older adults with T2DM.

2.8.1.2 Effects of a High Protein Diet on Body Composition

Dietary protein and its constituent branched chain amino acids have been found to

play an important role in stimulating muscle protein synthesis (MPS) and reducing

muscle protein breakdown (MPB) in both young and older adults (290-292). In

healthy or overweight/obese adults, long-term exposure to such stimuli (protein) has

been shown to preserve and in some instances, increase muscle mass whilst

concomitantly reducing weight and fat mass (293-296). Maintenance of skeletal mass

is of relevance for older adults and those with T2DM because of the important role

muscle plays in insulin-stimulated glucose uptake and storage, as discussed

previously in this review.

There are a number of mechanisms which have been proposed to explain how greater

reductions in fat mass can be achieved on a high protein diet. Explaining at length

many of these proposed mechanisms is beyond the scope of this review. Briefly

however, proposed mechanisms include the thermic effect of feeding which is

Chapter 2

Page | 48

greater in those with T2DM consuming high protein diets compared to low protein

diets (297-299). Additionally, high protein diets have been found to blunt the

reduction in resting energy expenditure commonly observed following weight loss

from an energy restrictive diet in obese non-diabetic and lean populations (300, 301),

but this remains unconfirmed in adults with T2DM and. Furthermore, protein

increases secretion of satiety hormones gastric inhibitory polypeptide (GIP) and

glucagon-like peptide-1 (GLP-1) and reduces secretion of the orexigenic hormone

ghrelin (302-304).

The effects of increased protein on fat mass and total weight reductions in the short

and longer-term appear favourable with reductions from 2 to 9 kg observed

depending on the length of the intervention (38, 264, 267, 305-307). However, the

number of trials of longer duration are limited in older adults with T2DM. A meta-

analysis conducted by Dong et al. (38) comprising nine studies ranging in duration

from 4- to 24-weeks, including 418 T2DM patients (mean age 46–63 years and mean

BMI 31–39 kg/m2) revealed high protein diets (25-32% of total energy) compared to

normal or lower protein (15-20% of total energy) diets lead to greater reductions in

weight [mean difference -2.08 kg (95% CI, -3.25, -0.90)] (38). However, the authors

highlighted the lack of evidence for longer term trials with most of the interventions

examined being ≤ 6-months and thus the long-term efficacy of such diets is not yet

known (38).

Ingestion of protein has been shown in the young, elderly and those with T2DM to

successfully stimulate a MPS response, which in the long-term may translate to

maintenance or enhancement of muscle mass (308-312). However, it has been

suggested that older adults with T2DM may be less responsive to such anabolic

stimuli (313, 314), although recent data indicates that the MPS response to protein is

not impaired in adults with T2DM (308). Ageing muscle also appears to be less

sensitive to lower doses of protein/amino acids, with reductions in lean mass

occurring rapidly with low protein intake, subsequently suggesting older adults with

T2DM may require higher quantities of protein to acutely stimulate an equivalent

MPS response above basal (310, 312). For instance, 17 obese men and women with

T2DM (mean age ± SD, 46 ± 3 years) who followed a low protein diet (15% energy)

Chapter 2

Page | 49

for 4-weeks were found to lose ~1 kg of lean mass (P=0.004) when measured with

bioimpedance, whereas when these same adults (after a 3-week washout) consumed

a high-protein (30% energy) diet there was no loss in lean mass (315). Trials of

longer duration in older adults with T2DM generally corroborate the short-term

findings although the maintenance of such diets appears to falter after a few months.

For example, in a parallel clinical intervention conducted by Brinkworth et al. (306)

58 older (mean age 50.2 years) adults who were hyperinsulinaemic but not diagnosed

with T2DM followed a 12-week energy-restricted weight loss diet either high in

protein (30% energy as protein) or low in protein (15% energy) following this the

high and low protein diet was continued but energy intake was balanced without

restriction (306). Protein intake was significantly greater in the high protein group

during the initial 16 weeks (P<0.001), but decreased in the high protein and increased

in low protein groups during 52-weeks of follow-up (306). Subsequently, there was

no difference between the groups in protein intake at week 68, indicating poor long-

term dietary adherence behaviour to both dietary patterns.

In summary, high protein diets appear to translate to relevant reductions in total body

weight and fat mass in older adults with T2DM. Such diets show promise for

maintaining or enhancing muscle mass, but long term maintenance of these diets

appears to be difficult with marked deviations from prescribed diets evident in some

studies. Long-term maintenance of such diets may be enhanced with the use of a

protein supplement which will be discussed in section 2.8.2.

2.8.1.3 Effects of High Protein Diets on Lipids, Blood Pressure and Markers of Inflammation

Higher protein diets, with a low intake of fat, have been associated with

improvements in blood lipids, blood pressure and to a smaller degree inflammation

in overweight/obese adults with limited evidence in adults with T2DM (267, 306,

316). Proposed mechanisms for improvements in serum lipids include increased

hepatic bile acid synthesis (317, 318), enhanced faecal sterol excretion (319, 320),

decreased hepatic de novo cholesterol biosynthesis (319, 321) or reduced uptake of

cholesterol through reductions in LDL receptor activity (321-323). The interactions

between protein-digested products (bioactive peptides) and gut hormones including

Chapter 2

Page | 50

GLP-1 are thought to drive blood pressure improvements (324) with an attenuation

in adipose tissue oxidation and inflammatory responses or suppression of

inflammatory synthesis pathways to drive improvements in inflammatory factors

(325).

Studies in older adults with T2DM examining the effects of high protein diets on

lipids, blood pressure and inflammatory cytokines remain limited. In the 64-week

trial in obese older adults with T2DM conducted by Brinkworth et al. (306)

discussed above, the high protein weight reduction diet led to a significant reduction

in plasma level of hs-CRP (baseline vs 64-weeks; 5.0 ± 1.0 vs 3.8 ± 0.8 mg/L,

P<0.05). Those in the higher protein group also had greater improvements in blood

pressure plus total and LDL cholesterol however, like inflammation these

improvements were not different to those on the low protein diet, possibly explained

by the similar amount of weight lost in both groups (306). In the meta-analysis by

Dong et al. (38) discussed in section 2.7.2.3 of this review, the pooled treatment

effects found high protein diets did not alter triglycerides, total, HDL or LDL

cholesterol, but there was a trend for an improvement in SBP (-3.13 mmHg (95 % CI

-6.58, 0.32) P-value not reported) and DBP (-1.86 mmHg (95 % CI -4.26, 0.56) P-

value not reported) (38). Further, in another more recent systematic review and meta-

analysis of nine RCTs ranging from six to 36-weeks in duration with participant

numbers from 20 to 190 obese, hypertensive adults largely with metabolic syndrome,

no significant effect of higher protein diets on circulating levels of hs-CRP were

observed. However, the authors noted that their results were limited by considerable

heterogeneity across all included trials (326). Differences in trial duration and the

level of professional (i.e. dietetic) support made available to participants as well as

differences in the macronutrient composition of the diets make any conclusions about

the effects of high protein diets on blood lipids, blood pressure and/or inflammation

difficult with further research required.

2.8.1.4 Potential Problems with Prescribing High Protein Diets

Whilst many of the trials presented above provide support for a beneficial role of a

high protein diet for the management of T2DM and improvement of cardiovascular

Chapter 2

Page | 51

risk factors, there remains insufficient data to conclusively recommend such a diet.

Conducting large scale RCTs which control for macronutrient content are habitually

difficult to implement and adherence to dietary recommendations is rarely sustained

(327). Such interventions typically require participants to follow prescribed meal

plans which over an extended period of time can become tedious and burdensome,

often leading to high dropout rates and poor adherence to the prescribed diet (286,

307). In addition, adherence often relies on self-reported dietary intake, which in

obese and T2DM populations may not be appropriate as under-reporting of food

intake is widely acknowledged to occur in these groups (328). To account for these

issues, the use of a protein supplement may be a more appropriate strategy to

increase dietary protein intake and to encourage greater compliance, particularly over

a longer period of time.

2.8.2 Protein Supplements for the Management of Type 2 Diabetes

Protein supplements can be broadly categorised according to their nutrient profile as

providing protein as a single source protein or as a multi-ingredient supplement i.e.

protein and carbohydrate. For example, whey protein derived from milk is one such

example of a single source protein; others include casein, soy, pea or egg protein. Of

all single source protein supplements available, whey protein has received the

greatest amount of attention due to its high nutritional value as it contains all

essential amino acids, it is rapidly absorbed compared to other sources of protein like

casein, and has been shown to have positive effects on insulin secretion, lowering the

postprandial glycaemic response and stimulating MPS (329, 330). The evidence

available for these effects is discussed in greater detail below (329, 330).

Chapter 2

Page | 52

Figure 2.3: Protein fractions and types of whey protein derived from whole milk.

Whey proteins are derived from whole milk and are a by-product of cheese and curd

manufacturing (Figure 2.3) (331). Several advancements in processing technology

such as ultrafiltration, microfiltration, reverse osmosis and ion-exchange have

resulted in development of several different whey products (331). These condensed

products include whey concentrate, isolate and hydrolysate (332, 333). These

condensed forms of whey protein preserve the favourable components such as the

protein and amino acid content whilst reducing other components such as fat and

lactose, Table 2.7 describes these various whey protein products (333, 334). Whey

protein concentrate contains approximately 35-80% protein, with the remainder

consisting of fat, lactose and minerals (331). Whey protein isolate contains

approximately 85-90% protein and minimal fat or lactose (331). Both whey protein

concentrate and isolate are manufactured from whey using ultrafiltration, spray

drying and evaporation techniques (335). Whey protein hydrolysates are peptides

derived from hydrolysing the proteins in whey in a process that includes their

fermentation with proteolytic enzymes (336). Both whey protein isolate and

hydrolysate are more expensive in comparison to whey protein concentrate, which is

an important consideration should whey protein supplements be made commercially

available as a nutritional approach for the management of T2DM.

Chapter 2

Page | 53

Mortensen et al. (337) observed the first phase insulin response (assessed from AUC)

to be greater after whey protein hydrolysate consumption in comparison to other

types of whey protein including whey isolate and mixed whey products (whey

protein plus alpha-lactalbumin and whey protein plus casein), when consumed with a

high fat/carbohydrate meal. However, whey protein hydrolysates, have been found to

be less palatable than whey concentrate or isolate, detracting from their potential

therapeutic use (332). Further, the available data to date indicates that over the long-

term there is no convincing evidence that one form of whey protein can stimulate

insulin secretion or has better glycaemia lowering effects than another (332).

Therefore, whey protein concentrate which is more cost-effective for a consumer,

combined with its enhanced palatability and beneficial health properties, is most

commonly used.

Table 2.7: Types of commercially available whey protein. Adapted from Marshall et al. (331).

Product Description Protein Concentration Fat, Lactose and

Mineral Content

Whey Protein Concentrate

Most commonly available as 80%. Can range from 25-89%

Some fat, lactose, and minerals. As the protein concentration increases, fat, lactose, and mineral content decreases.

Whey Protein Isolate

90-95% Little if any

Whey Protein Hydrolysate

Variable hydrolysis used to cleave peptide bonds. Larger proteins become smaller peptide fractions. Reduces allergy potential of whey protein.

Varies with protein concentration

As mentioned above, whey protein supplements have received considerable attention

largely because of their role in stimulating MPS which may help to preserve or

increase muscle mass (338-340). Their use as a functional food in the management of

chronic diseases including T2DM has also begun to receive considerable attention. A

growing number of studies in adults with T2DM highlight that whey protein

Chapter 2

Page | 54

supplementation can have insulinotropic and glycaemia lowering effects (341-343).

Studies in healthy and/or overweight and obese adults have also demonstrated that

whey protein can enhance thermogenesis, aid in satiety and reduce subsequent

energy intake, which may be of value in supporting an energy deficit to facilitate

weight loss (344-348). Whey protein is also a more robust stimulator of MPS and has

been found to be more effective than other protein sources such as casein and soy

(340, 349). Others have shown that whey protein can have beneficial effects on blood

pressure, vascular function, inflammation, lipids and lipoproteins levels (333, 346,

350). Collectively these findings indicate that whey protein may have an important

role in managing weight, muscle mass and cardiovascular health in older adults and

those with T2D, but the longer-term effects of whey protein in older adults with

T2DM on these aforementioned outcomes has received less attention. The following

section will provide an overview of the effects of whey protein on weight

management, glycaemic control and insulin sensitivity, markers of inflammation,

serum lipids and cholesterol and blood pressure in individuals with T2DM. Where

possible this review only included studies or interventions that were conducted in

older adults diagnosed with prediabetes or T2DM.

2.8.2.1 Effect of Whey Protein on Weight and Fat Mass

Long-term whey-protein supplementation in older overweight/obese adults has been

associated with reductions in fat mass and total body weight (351-356). However, the

findings from some of these studies are confounded as some included caloric

restriction or included a low-fat dietary component (352). Nevertheless, in one 23-

week intervention trial in which 73 older overweight (mean BMI 31 kg/m2) adults

followed an ad-libitum diet and were randomised to one of three supplements (whey

protein or soy protein both containing 26 g/serve of protein or an isoenergetic

carbohydrate supplement consumed twice daily – breakfast and lunch), Baer et al.

(353) reported that those who consumed the whey protein supplement had a mean

1.8 kg and 2.3 kg significantly lower total body weight and fat mass than the

carbohydrate group at the completion of the study, respectively (both P<0.006)

(353). Lean mass did not differ between groups (353). In contrast, a 12-week

intervention in 45 middle-aged overweight (mean ± SD, BMI 32.1 ± 3.0 kg/m2) men

who consumed either 65 g of whey protein (80% WPC) or 60 g of soy protein isolate

Chapter 2

Page | 55

30-minutes prior to their largest meal of the day (midday-meal) found that there was

also a greater reduction in total body weight (6.4 ± 1.1 kg versus 3.5 ± 0.3 kg,

P=0.008) and percentage body fat (9.2 versus 3.1%, P<0.001) in the whey protein

compared to soy group after 12-weeks (355). The differences in magnitude of

reductions in weight and fat mass when comparing these two trials may have been

due to the greater single bolus of protein consumed in the second study compared to

the first or as will be discussed below the effects on satiety of the two different doses

of protein.

The mechanism(s) proposed for the greater reductions in body weight and fat mass

from whey protein compared to soy protein (and other sources of protein) might be

due to differential effects among protein sources on energy intake or body weight

regulation (353). For instance, and drawing upon the two previous studies discussed

above, the first study, unexpectedly observed a greater increase in serum grehlin

levels, a hormone which serves as a hunger signal and has been found to strongly

increase food intake (353, 357). This could explain the smaller reduction in body

weight and fat mass compared to the second study where a significantly greater

reduction in total calorie intake in the whey compared to soy protein groups was

observed (355). Suggesting that the whey protein had a more profound effect on

appetite suppression (355). Reductions in energy intake following whey protein

supplementation have previously been observed (348, 358) and are believed to be

associated with the ability of protein or amino acids to elevate peripheral

concentrations of the anorexogenic hormones glucagon-like polypeptide-1 (GLP-1),

and cholecystolinin (CCK), the satiety related gastrointestinal hormones (348, 354,

359, 360). No studies have specifically examined the independent effects of whey

protein on body composition in adults with T2DM.

2.8.2.2 Effect of Whey Protein on Lean Mass

With advancing age, rates of MPS in response to an anabolic stimulus such as

physical activity and food consumption decline, which contribute to age-related

losses in skeletal muscle mass (275, 361). It is well established that the balance

between MPS and MPB largely determines any loss or gain in muscle mass.

Maintenance or gains in muscle mass occur as a result of a net positive protein

Chapter 2

Page | 56

balance, which is largely determined by consumption of an adequate dose of protein

and/or exercise (361-363). There has been extensive research into determining the

optimal type, dose, timing and distribution of protein intake for muscle health, and it

appears that doses of whey protein <15 g are largely ineffective at stimulating MPS

in older adults. In contrast, a number of acute studies have shown that doses of 20-40

g of whey protein increases MPS compared to basal (51, 312, 339, 364). For

instance, in a study of 33 healthy older men (mean age ± SD, 73 ± 2 years) who were

randomised to receive either a 10, 20 or 35 g single bolus of whey protein, Pennings

et al. (364) reported that consumption of a 20 and 35 g dose of whey protein resulted

in the greatest increase in whole body MPS compared to the 10 g dose (P<0.01);

there was no differences between the 20 and 35 g doses (364). Since a similar dose of

whey protein has been found to provide an additive effect on the acute MPS response

when older adults perform PRT, a dose of 20-40 g of high quality protein (e.g. whey)

is likely to provide the greatest MPS benefits to older adults (51). The additive effect

protein has on an acute MPS and over the longer-term on lean mass will be discussed

in section 2.11.

In addition to the dose of protein, the amino acid content of a protein bolus or

supplement is integral to whether it is effective at eliciting an anabolic response (47,

363). The MPS effects of whey protein are largely believed to be due to the high

leucine (~10%) and other branched chain amino acid content along with its fast-

digestion rate (275, 365, 366). Leucine is reported to be the key regulator of muscle

protein metabolism as it possesses the power to activate the mammalian target of

rapamycin (mTOR) pathway which is necessary for cellular protein synthesis

regulation (367, 368). Older adults appear to require a leucine dose of ~2-3 g to

initiate MPS (361). This has been termed the ‘leucine threshold’ or ‘trigger’ point

(39, 369). Importantly, leucine provided alone appears to be ineffective in promoting

an anabolic muscle response whereas leucine co-ingested with other amino acids, as

is the case in whey protein, enhances the postprandial MPS response (370).

Randomised controlled trials which have investigated the long-term (>12-weeks)

effects of whey protein supplementation alone on muscle outcomes in older adults

have produced conflicting results (41, 371, 372). This may be explained by

Chapter 2

Page | 57

differences in population groups (e.g. older adults, older obese middle-aged adults,

elderly, sarcopenic) examined or differences in the methodological prescription of

the whey supplement (as a pre-meal, pre-load or once or multiple times/day). For

example, in a multi-centre 18-month RCT, 106 older adults (~70 years) were

supplemented with 45 g/day of whey protein with another 102 older adults provided

with a maltodextrin control supplement (41). Baseline protein intakes were self-

reported to be between 0.6 to 1.0 g/kg/day (41). Following the 18-month intervention

a significant between-group difference was observed for the change in total body

lean mass in favour of the whey protein supplemented group (0.33 kg, P<0.05) as

assessed via DXA (41). However, two other studies investigating the effects of whey

protein supplementation alone on muscle mass have failed to observe any beneficial

effects (371, 372). In a two-year randomised, double-blind, placebo controlled trial,

elderly post-menopausal women aged 70-80 years (mean 74.3 ± 2.7 years) were

randomly assigned to either a daily high protein drink containing 30 g of whey

protein (n=109) or a placebo drink containing only 2.1 g of whey protein (n=110)

daily (371). At both 1- and 2-years follow-up there were no differences between the

groups and no within-groups changes for total body or appendicular lean mass

(ALM) (371). The authors proposed that the null effect was due to participants

baseline protein intakes being quite high at 1.2 g/kg/day. This theory is supported by

the results of another RCT where protein replete well-nourished older individuals

(mean baseline protein intake >0.8 g/kg/day) experienced no gain in total body lean

mass following whey protein supplementation (28 g) twice/day for 23-weeks (353).

Based on this limited evidence, it appears that the effectiveness of a daily whey

protein supplement to improve muscle mass or prevent loss in healthy older adults is

limited and may depend on the existing habitual protein intake (371).

The timing or spread of whey supplementation throughout the day combined with the

habitual protein intake are also important considerations for maximising gains in lean

mass in older adults. Indeed, there is emerging research that a more uniform pattern

of protein consumption throughout the day (i.e. doses of ~20-30 g protein consumed

at breakfast, lunch and dinner) may allow for greater optimisation of the postprandial

MPS response translating to positive effects on lean mass (373-376). While the

current evidence from long-term human intervention trials is limited, a study in 80

Chapter 2

Page | 58

mobility-limited older adults (aged 70 to 85 years) randomised to consume two

serves of 20 g of whey protein/day or an isocaloric control supplement whilst

performing high-intensity PRT three times per week for 6-months found whey plus

PRT increased lean mass by 1.3% and muscle cross-sectional area (CSA) by 4.6%

compared to baseline (377). Whilst the magnitude of change in these muscle

measures was greater than that observed in the control group (0.6% and 2.9%,

respectively) there was no significant difference observed between the groups (377).

Which was suggested to be due to changes in dietary protein intake from ad-libitum

foods during the 6-months, as when taking into consideration the compliance with

the supplement the increase in protein intake averaged only 18 g/day (377).

In summary, there is consistent evidence showing that acute ingestion of whey

protein and the essential amino acid leucine, particularly at a dose of 20-40 g (2-3 g

leucine) are key factors in stimulating MPS in older adults. However, the findings

from trials investigating the long-term effects of daily whey protein supplementation

on lean mass remains mixed. Furthermore, there is little or no research into the long-

term effects of whey protein on body composition in older adults with T2DM.

2.8.2.3 Effect of Whey Protein on Glycaemic and Insulinaemic Outcomes

Nutritional strategies which effectively stimulate early phase and long-term insulin

secretion in those with T2DM may serve to improve daily and long-term glycaemic

control. Several acute studies and to a lesser extent longer-term intervention trials

have shown that consumption of whey protein has a positive effect on improving

insulin secretion, insulin sensitivity and postprandial glucose levels (52, 337, 341-

343, 351, 378, 379), but questions remain with regard to the optimal type and dose

required. Further, the degree of improvement in these outcomes from the available

literature is inconsistent, largely explained by methodological differences between

the studies. For instance, of the studies conducted some have used different delivery

methods (as a pre-load to a meal or as a stand-alone supplement), a wide range of

whey protein doses (4.5 to 50g) and different forms of whey protein (concentrate,

isolate, hydrolysate).

Chapter 2

Page | 59

Whey protein consumed as a pre-load to a meal or consumed in conjunction with a

meal is established to have an insulinotropic effect (52, 337, 343, 379). Whey protein

has also been found to confer glucose-lowering effects in those with T2DM (379).

For example, 15 individuals with well-controlled T2DM, consumed on two separate

days either a whey protein drink (50 g mixed with 250mls of water) or placebo

(250ml of water), followed by a standardised high glycaemic-index breakfast (379).

The AUC in serum glucose immediately following breakfast (0-30 minutes) was

significantly lower in the whey than placebo group (Figure 2.4) (379). Similarly

spikes in plasma glucose levels were significantly lower during the 60- to 120-

minute period and for the overall measured period (154 ± 8.5 vs 213.6 ± 13.8

mmol/L x min P=0.001) (379). Conversely, insulin levels were significantly higher

during the postprandial early insulin release phase (0-30 minutes), remained higher

and increased more rapidly in the whey group compared to the placebo pre-load for

the entire post meal intervention as shown in Figure 2.4 (379). This study

successfully demonstrated that a whey protein pre-load reduces both the peak and

AUC for post meal glucose which was associated with a rapid and significantly

enhanced early and late postprandial insulin response in adults with T2DM (379).

Doses of whey protein ranging from 17 g to as high as 55 g have also been found to

offer similar effects on glucose and insulin levels (52, 337, 343). Collectively these

studies highlight that a pre-meal dose of protein may be optimal for those with

T2DM to improve daily insulin and glucose parameters.

Figure 2.4: The serum glucose and insulin responses to a high-glycaemic index breakfast meal following a whey protein (white circles) or placebo (black circles) pre-load in 15 participants with type 2 diabetes. Sourced from Jakubowicz et al. (379). Values are means ± SEM. *p<0.05 vs placebo for the same time point.

Chapter 2

Page | 60

The acute insulinotropic properties of whey protein are believed to be due to the

branched chain amino acids present in whey which exert direct effects on stimulating

pancreatic beta-cells to produce insulin (53, 275). In addition, the amino acids and

bioactive peptides present in whey may facilitate the rise of the incretin hormones

gastric inhibitory peptide (GIP) and GLP-1, which both exert strong insulinotropic

effects (380). In fact, following a bolus of oral glucose, approximately two thirds of

the plasma insulin response can be attributed to the effects of GIP and GLP-1 (332).

The incretin hormone GLP-1 is also recognised to play a role in the management of

postprandial glycaemia in adults with T2DM largely through its effects on slowing

gastric emptying (380, 381). Delayed gastric emptying reduces postprandial

glycaemic increases whereas rapid gastric emptying has the opposite effect (381).

The results of acute studies demonstrating beneficial effects on both insulinaemic

and glycaemic outcomes has led some researchers to propose that whey protein

supplements should be considered as a long-term management strategy in adults with

T2DM.

At present, there is limited data from intervention trials with regard to the long-term

effects of whey protein on insulin sensitivity and HbA1c in adults with T2DM (341).

Seven older overweight/obese adults (mean age and BMI ± SEM, 60 ± 2 years and

31 ± 2 kg/m2) were randomly assigned to consume a chocolate-flavoured whey

protein pre-load (100 ml water with 25 g whey protein) or placebo (25 g chocolate-

flavoured ‘diet’ sauce), 30-minutes before each main meal for 4-weeks, followed by

a 2-week washout, and then the alternative pre-load for 4-weeks (341). At the start

and end of each treatment period participants were provided the meal pre-load

following by a high glycaemic index breakfast meal with the glucose response

measured for next 240 minutes (341). Following the 4-weeks of whey protein pre-

load, postprandial blood glucose was lower after whey compared to placebo (P<0.05)

(341). However, HbA1c was not changed from baseline or different between the

groups likely explained by the short intervention period. In overweight and obese

adults, the effects of longer-term whey protein supplementation on insulin outcomes

show some promise. For example, Pal et al. (351) investigated the effects of a twice

daily whey protein supplement (27g of protein per drink) on insulin and glucose

parameters in 89 overweight and obese women (BMI ± SEM, 31.3 ± 0.8 kg/m2) in

Chapter 2

Page | 61

comparison to a supplement containing either casein (27g of protein per drink) or

glucose control (27g of glucose per drink) over a period of 12-weeks (351).

Participants were asked to consume these drinks 30-minutes prior to a breakfast and

an evening meal (351). At the end of the 12-week period fasting plasma insulin

levels and HOMA-IR were decreased by 11% and 10%, respectively, in the whey

protein group compared with baseline (P=0.012 and P=0.046, respectively) which

was significantly different from the change in the controls (between-group difference

P=0.049 and P=0.034, respectively) (351). Fasting plasma glucose and HbA1c were

not assessed. Importantly, the benefits were independent of changes in body

composition (including visceral fat). However, further studies are required to

determine why acute consumption of whey protein, as a pre-meal supplement, can

have insulinotropic effects but in the long term can decrease plasma insulin levels yet

improve insulin sensitivity (351).

Despite the overwhelming evidence for the positive effects of whey protein on

insulin and glucose levels in adults with T2DM in an acute setting, and some

evidence for beneficial effects in the longer-term in overweight/obese adults, there

remains no long-term intervention trials which have examined if these same benefits

can be observed in adults with T2DM, with a clear need for these interventions to be

performed.

2.8.2.4 Effect of Whey Protein on Markers of Inflammation

According to Hayes et al. (382) bioactive peptides from milk and present in whey

protein which have an impact on the human body can be categorised into anti-

hypertensive, anti-thrombotic, anti-microbial and even immunomodulatory Further,

whey has been identified to have anti-oxidant and potentially anti-inflammatory

properties (383). Whilst limited evidence exists, a mechanism by which whey protein

may positively alter anti-oxidant or anti-inflammatory levels includes inhibiting

angiotensin-converting-enzyme activity (329, 384, 385). It has also been suggested

that the peptides in whey along with specific proteins including α-lactalbumin may

inhibit the production of several inflammatory cytokines including TNF-α and IL-6

(386, 387).

Chapter 2

Page | 62

To the best of my knowledge there are no studies which have examined whether

whey protein is able to modify levels of circulating inflammatory markers in adults

with T2DM. Of the studies conducted in healthy adults, only a few small studies

have demonstrated an improvement in levels of inflammation (as assessed from hs-

CRP) following whey supplementation in an acute (388, 389) or chronic (one month)

setting (390). For example, in a randomised, crossover trial, 11 obese non-diabetic

subjects (aged: 40-68 years, BMI: 30.3-42.0 kg/m2) were provided a fat-rich mixed

meal supplemented with 45 g of one of four proteins (cod, whey isolate, gluten or

casein) with blood samples collected for 4-hours during the postprandial phase (388).

Notably, a significant reduction in AUC of the inflammatory marker chemokine

ligand 5 was observed following the whey protein supplemented meal when

compared to the casein and the cod supplemented meal, but not the gluten meal

(P<0.05 for both) (388). The inflammatory marker chemokine ligand 5 has been

observed to be positively related to the development of T2DM, and has also been

implicated in the onset and progression of atherosclerotic heart disease (388, 391).

No significant differences between meals were observed for other inflammatory

cytokines including adiponectin, macrophage inflammatory protein-1β, platelet-

derived growth factor and IL-1ra (388). Whilst providing some positive evidence for

an anti-inflammatory effect of whey protein, this study was acute and only small in

design and whilst participants were obese they were otherwise healthy.

Studies which have used older adult populations or population groups with metabolic

conditions also provide mixed evidence for the effects of whey protein on

inflammation. Only four small RCTs have examined the effects of whey protein on

inflammation in older adults, with considerable variation among the populations

studied making conclusions difficult (one in healthy active older adults, two with

stable chronic obstructive disorder and one recruited hospitalised stroke patients)

(386, 392-394). Of these four studies, two demonstrated a favourable effect of whey

protein on various markers of inflammation (e.g. hs-CRP, IL-6, IL-8, and TNF-α)

(386, 392), whereas the other two observed no benefit (393, 394). Studies among

adults with obesity or other metabolic conditions have mostly reached the same

conclusion, that is, whey protein intake was not associated with a decrease in serum

hs-CRP levels in individuals with obesity (285, 384), hypertension (395) and even

metabolic syndrome (396). The reasons for this lack of effect may have related to a

Chapter 2

Page | 63

range of factors, including limited follow-up periods, small sample sizes or even the

composition of the whey supplements provided to the intervention groups (397).

A recent meta-analysis including nine RCTs in adults aged 48 to 77 years ranging

from four to 36-weeks and sample sizes of 20 to 190 investigated the inflammatory

mediating effects of whey protein (326). Of these nine trials, six were conducted in

adults with prehypertension, mild hypertension, chronic obstructive pulmonary

disease or metabolic syndrome (326). Whilst there was considerable heterogeneity in

the design of these trials and the dose of whey protein prescribed (doses ranged from

0.7 to 60 g/day), the meta-analysis concluded that there was not enough evidence to

support the hypothesis of an active modulation of inflammation by whey protein in

adults (326). However, sub-group analysis in those who presented at baseline with

serum levels of hs-CRP ≥ 3 mg/L, which is often reported in adults with T2DM

(398), found that whey protein had a small yet non-significant effect in reducing hs-

CRP (326). Whether long-term whey protein supplementation can reduce markers of

inflammation in older adults with T2DM, particularly in the presence of increased

inflammation, remains to be determined.

2.8.2.5 Effect of Whey Protein on Serum Lipids and Blood Pressure

Human and animal models suggest that whey protein may favourably alter serum

lipids and cholesterol and improve blood pressure (319, 384, 399-402). Biologically

plausible mechanisms by which whey protein may improve these measures include

the promotion of hepatic lipid metabolism, inhibiting the absorption of fatty acids

and cholesterol in the intestine and increasing the excretion of faecal sterol (403).

Evidence from in vitro studies demonstrates the bioactive peptides found in whey

protein are effectively able to inhibit enzymatic angiotensin converting enzyme

(ACE) activity (404), which is a rate limiting step in the conversion of angiotensin I

to angiotensin II and is responsible for vasoconstriction therefore playing a role in

hypertension (405).

There is limited evidence for the independent effects of acute or chronic whey

protein supplementation on blood pressure with no studies conducted in adults with

T2DM. However, studies in young normotensive and hypertensive overweight adults

Chapter 2

Page | 64

have investigated such effects over acute (385) and chronic settings (351, 406) with

conflicting results. For example, 12-weeks of whey protein supplementation (27 g

twice/day) in 70 overweight (BMI ± SEM, 31.3 ± 0.8 kg/m2, mean age ± SEM 48 ±

1.9 years), normal and hypertensive men and women improved blood pressure when

compared to a baseline (SBP; 119.3 ± 3.2 mmHg vs 114.5 ± 3.1 mmHg; P=0.020 and

DBP; 64.1 ± 1.9 mmHg vs 62.0 ± 1.7 mm Hg; P = 0.038) (384). Compared to

controls there was a greater reduction in DBP at 12-weeks (384). In contrast, in

young (~20 years of age) men and women 28 g/day of either hydrolysed or non-

hydrolysed whey protein over 6-weeks had no effect on SBP or DBP (406).

However, when subgroup analyses were performed in those with elevated SBP (≥120

mmHg) and DBP (≥ 80 mmHg) it was found that whey protein supplementation

significantly reduced SBP and DBP by 8.0 and 8.6 mmHg respectively in

comparison to baseline (P<0.001) (406). In summary, the current body of evidence,

although limited, suggests that whey protein supplementation may have a positive

effect on blood pressure in non-diabetic adults, but further trials are needed in adults

with T2DM and there is a need to determine if there is an optimal type and dose of

whey protein that is most effective.

The health benefits of acute and longer-term whey protein ingestion may also extend

to lowering blood lipids levels yet few studies in overweight/obese older adults or

those with T2DM have investigated this with inconsistent results (351, 378). To my

knowledge, only one acute study has been conducted in adults with T2DM (378). In

this study, 12 men and women with T2DM (mean ± SD, age 64.6 ± 3.3 years and

BMI 28.9 ± 3.7 kg/m2) were randomised to receive a high-fat meal supplemented

with either 45g of whey, casein, cod or gluten protein (378). For 6-hours following

the ingestion of the meals it was observed that the AUC of plasma triglycerides were

significantly lower in the whey supplemented meal when compared to the three other

meals (mean ± SD, whey, 205 ± 86 mmol/L vs casein, 282 ± 132 mmol/L; cod, 296

± 11 mmol/L; gluten, 299 ± 75 mmol/L all P<0.05) (378). There are several factors

which control the circulating concentrations of triglycerides including intestinal

chylomicron secretion, hepatic very low density cholesterol secretion, conversion of

triglyceride-rich lipoproteins to triglyceride-depleted lipoproteins, and tissue uptake

of triglyceride-depleted lipoproteins, all of which may have influenced the

Chapter 2

Page | 65

postprandial triglyceride response (407). Whilst this study was only conducted in a

very small number of adults (n=12) with T2DM, importantly, the findings align with

the results observed in a study of 89 overweight and obese individuals (385). In this

other study, 89 overweight and obese adults (mean BMI 31.3 kg/m2) to 12-weeks of

whey, casein or glucose supplementation (351). Following the 12-week intervention

fasting triacylglycerol levels were significantly lower in those receiving the whey

compared with the control supplement (P=0.035) (351). There was also a

significantly greater reduction in total cholesterol in the whey group when compared

to both the casein and control groups (P<0.05 for both) (351). Whilst chronic effects

of whey protein supplementation in adults with T2DM remain unexamined, the

authors of this study highlighted that most participants displayed at least one or two

metabolic syndrome risk factors at baseline (351).

In summary, the effects of whey protein supplementation on blood pressure in

normotensive and overweight/obese adults appears favourable, however, no studies

have been conducted in adults with T2DM. Acute studies also support improved

triglyceride levels in adults with T2DM following whey supplementation, although

no chronic studies have been conducted. Given these findings and the proposed

mechanisms by which whey protein may improve blood pressure, serum lipids and

cholesterol, further long-term trials with different types and doses of whey protein

supplementation in adults with T2DM are warranted to determine the efficacy of

such a nutritional approach.

2.9 Vitamin D

While vitamin D is widely recognised for its importance in bone and mineral

metabolism, over the past two decades there has been considerable interest in the role

that vitamin D may play in several extra-skeletal health outcomes, including T2DM

(408). The renewed interest stems from the discovery that most body tissues and

cells possess vitamin D receptors (VDR) and the required enzymes to convert the

primary circulating form of vitamin D [25-hydroxyvitamin D (25(OH)D)], to the

active form 1,25-dihydroxy vitamin D (408). Vitamin D is a fat-soluble vitamin that

exists in two major forms. Vitamin D2 or ergocalciferol, which is available from

plant based foods such as mushrooms, and vitamin D3, or cholecalciferol, which is

Chapter 2

Page | 66

produced endogenously following exposure of the skin to ultraviolet light (sun

exposure) and is present in small amounts in certain foods (salmon, tuna, mackerel

and fish liver oils) and in some fortified products and supplements (409). Previously

it was thought there was an age-related decline in some of steps of vitamin D

metabolism (410, 411). However, it has been subsequently shown that intestinal

absorption of vitamin D does not decrease with advancing age (412, 413).

Nevertheless, vitamin D obtained from the sun or consumed through food must

undergo two hydroxylation reactions to become active as discussed below and shown

in Figure 2.5. Below is a discussion of the most recent evidence investigating the

potential health benefits of vitamin D supplementation on glycaemic control, insulin

sensitivity, muscle health, serum lipids and blood pressure in adults with T2DM.

Prior to that a brief overview of the metabolism of vitamin D and the current

recommended serum targets is provided.

2.9.1 Metabolism of Vitamin D

Vitamin D3 (cholecalciferol) is synthesised in the skin from 7-dehydrocholesterol by

ultraviolet irradiation, the subsequent production of vitamin D is dependent on the

intensity of UV irradiation which varies with season and latitude (414).

Cholecalciferol obtained from the sun or directly from food is then metabolised in

the liver to 25(OH)D by the enzyme vitamin D-25-hydroxylase to produce 25-

hydroxyvitamin D, the major circulating concentrations of vitamin D that serve as

the primary biomarker of vitamin D status (408). This metabolising step is not

enough to produce the biologically active vitamin D, and thus in the kidneys

25(OH)D undergoes further metabolism by the enzyme 1,25-dihydroxyvitamin D-

1α-hydroxylase also called 1-OHase (CYP27B1) producing 1,25-dihydroxyvitamin

D (1,25(OH)2D), which is the biologically active hormone (also called calcitriol)

(408). Even though the kidney is the primary site of CYP27B1 expression, several

other tissues also express this enzyme including the epithelial cells in the skin, lungs,

breast, intestine, prostate and endocrine glands including the parathyroid gland,

pancreatic islet cells, thyroid, ovary, placenta and some cells of the immune system

including macrophages. However, the contribution of these tissues to calcitriol

formation is yet unknown (415). The renal production of 1,25(OH)2D is tightly

controlled primarily by two hormones, one which up-regulates calcitriol production

Chapter 2

Page | 67

(parathyroid hormone (PTH)), and another which down regulates production via

fibroblast-like growth factor (FGF23). Calcitriol, following synthesis in the kidneys,

binds to vitamin D binding protein where it is transported to target organs and exerts

its actions (408). Calcitriol increases the expression of the enzyme 25-

hydroxyvitamin D-24- hydroxylase (24-OHase) to catabolise 1,25(OH)2D to

calcitroic acid, a biologically inactive water soluble compound which is excreted in

bile (408). A summary of this process is provided below in Figure 2.5.

Figure 2.5: Metabolism of vitamin D from the sun and dietary sources. Adapted from Holick. (408). Enzymes for the relevant metabolic conversions are written in italic text. The dotted arrow line reflects the two hormones which are responsible for controlling the renal production of 1,25(OH)2D.

2.9.2 Recommended Serum 25(OH)D Levels

Currently there is ongoing debate globally as to the optimal serum 25(OH)D

concentrations for health benefits, particularly for older adults. Position statements

Chapter 2

Page | 68

released by the Endocrine Society of Australia, Osteoporosis Australia and the

Working Group of the Australian and New Zealand Bone and Mineral Society and

the Institute of Medicine (IOM) proposed that serum 25(OH)D concentrations >50 to

60 nmol/L year-round should be considered adequate/sufficient (Table 2.8) (416,

417). In contrast, the International Osteoporosis Foundation (IOF) and the

Endocrine Society Guidelines suggest a proposed a cut-off of >75 nmol/L be used to

define vitamin D sufficiency (418, 419). The main difference between these

guidelines relates to the population groups of reference; the IOM guidelines relate to

the general population whereas the Endocrine Society guidelines are targeted

towards a clinical population (420). While it is beyond the scope of this thesis to

debate the relative merits of whether 50 or 75 nmol/L should be considered

sufficient, for this thesis the Australian/IOM criteria will be adopted. It is important

to note however, that such reference guidelines are recommended based on

effectiveness of calcium absorption and bone metabolism and that such levels may or

may not also translate to beneficial effects on non-skeletal outcomes.

Table 2.8: Recommended serum vitamin D targets and classes of deficiency as recommended by the IOM (416).

Serum Vitamin D Classification Serum Vitamin D Target Range Adequate/Sufficient ≥ 50-60 nmol/L at the end of winter Mild Deficiency 30–49 nmol/L

Moderate Deficiency 12.5–29 nmol/L Severe Deficiency < 12.5 nmol/L

1 nmol/L = 0.4 ng/mL

2.9.3 Vitamin D and Type 2 Diabetes: Proposed Mechanisms of Action

Whilst poorly understood, low serum 25(OH)D status is thought to play a role in the

diminishment of normal glucose metabolism due to the presence of the vitamin D

receptor (VDR) in all tissues receptive to insulin, including skeletal muscle, adipose

tissue and pancreatic beta-cells (Figure 2.6) (421). Mechanistically, the active form

of vitamin D (1,25(OH)2D) can bind directly to VDR in beta-cells, and stimulates the

expression of insulin receptors and promotes insulin-mediated glucose transport via

the translocation of GLUT4 proteins to the cell surface of insulin receptive tissues

Chapter 2

Page | 69

(Figure 2.6) (422). It has also been shown that 1a-hydroxylase, the key enzyme

regulating the conversion of 25(OH)D to 1,25(OH)2D, is expressed in pancreatic

beta-cells which further supports a role for vitamin D in regulating blood glucose

levels (423). Several other potential mechanisms may also explain the link between

vitamin D and T2DM, including regulation of calcium homeostasis and inflammation

(22). Vitamin D deficiency can alter circulating calcium levels and affect calcium

influx to beta-cells (22). Calcium is a crucial ion in insulin secretion and action, with

large deviations in calcium concentration (hypo- or hypercalcemia) known to impair

the proper function of pancreatic beta-cells and alter insulin sensitivity of target

tissues (22, 421). Further, vitamin D may regulate inflammation as 1,25(OH)2D

decreases the production of inflammatory cytokines, which is important as increased

inflammation can impair both beta-cell function and insulin sensitivity (22, 421, 422,

424). However, the role of vitamin D and its ability to modulate inflammation related

to T2DM or other chronic diseases remains to be confirmed with some studies

observing effects to the contrary (425).

Figure 2.6: Proposed role of vitamin D in the pathophysiology of type 2 diabetes

Type 2 diabetes is characterised by increased insulin resistance followed by beta-cell dysfunction. Consequential to this, insulin is no longer able to block lipolysis in fat tissue, glucose production in the liver or able to stimulate glucose absorption in the muscle. Biologically active vitamin D, 1,25(OH)2D (shown as Vitamin D) may reduce beta-cell dysfunction by restoring insulin production/secretion, thereby reducing insulin resistance and improve glucose uptake in the muscle. Additionally, vitamin D may also lessen inflammation in the pancreas by reducing inflammatory cytokine production. The negative effects of vitamin D deficiency are depicted with the red arrows.

Chapter 2

Page | 70

2.10 Vitamin D Supplementation for the Management of Type 2 Diabetes

2.10.1 Effect of Vitamin D on Glycaemic and Insulinaemic Outcomes

Several prospective epidemiological studies have demonstrated an association

between serum 25(OH)D concentrations and the incidence of T2DM (22, 61, 174,

426, 427). For example, data from the 5-year prospective AusDiab study involving

>5,000 adults aged ~51 years (199 incident cases of diabetes were diagnosed)

showed that a median 25(OH)D level of 70 nmol/L at baseline was associated with a

57% reduced risk of developing T2DM (61). Low serum 25(OH)D levels have also

been associated with impaired insulin sensitivity and reduced beta-cell function

(428). Direct evidence from RCTs examining the effects of vitamin D

supplementation on insulin sensitivity and glycaemic control in those with T2DM is

continuing to expand yet the studies completed to date remain inconclusive (71, 429-

433). Much of this heterogeneity is likely due to the methodological differences in

terms of the dose of vitamin D prescribed, the baseline serum 25(OH)D level and the

population group examined (e.g. normoglycaemic, IGT or diagnosed with T2DM).

While it is beyond the scope of this review to examine all the intervention studies

conducted on this topic, data from the most recent systematic review and meta-

analysis is provided. This systematic review and meta-analysis included 23 RCTs

representing 1,797 adults with T2DM with interventions ranging from 4-weeks to

12-months and doses of vitamin D from 400 IU/day to 300,000 IU as a single dose

over 3-months (434). The overall finding from this systematic review was that

supplemental vitamin D had no significant effect on any parameters of glycaemic

control or insulin outcomes (HbA1c, fasting glucose or HOMA-IR) in patients with

T2DM (434). Furthermore, they found that the results remained unchanged when

separating the studies into those sufficient or deficient in vitamin D at baseline (434).

A number of reasons may explain the findings, including the short duration of some

of the interventions, the lack of an appropriate vitamin D dosage or change in serum

25(OH)D levels, the lack of a control comparison group and baseline 25(OH)D

levels (434, 435). Interestingly, one 12-week RCT in adults with T2DM reported

small but significant beneficial effects of high dose (50,000 IU weekly) vitamin D

supplementation on glycaemic parameters, even in those with sufficient (>50

Chapter 2

Page | 71

nmol/L) baseline serum 25(OH)D levels (436). Similarly, another 6-month trial in 54

adults with T2DM found that treatment with 300,000 IU vitamin D3 intramuscularly

improved insulin sensitivity and HbA1c (437). Despite these positive finding, others

have reported no benefits of high dose supplementation on glycaemic control (438).

It is evident from the available data that further work in this area is required to

elucidate whether supplementation with vitamin D in adults with T2DM serves as an

appropriate strategy to improve glycaemic and/or insulinaemic outcomes.

2.10.2 Effect of Vitamin D on Body Composition

There is some evidence that low serum vitamin D concentrations (<50 nmol/L) are

associated with increased adiposity (439, 440) and reduced lean mass in older adults

and those with T2DM (441, 442). Numerous hypotheses have been proposed to

explain how inadequate vitamin D status may influence fat mass or vice versa, and

include sequestration of vitamin D to adipose tissue, and/or that overweight/obese

adults are inactive and thus less likely to perform outdoor activities (443). Another

proposed mechanism is that higher intakes of vitamin D can repress fatty acid

synthase enzyme activity by decreasing intracellular Ca2+ in adipocytes (444, 445).

Proposed mechanisms which explain the relationship of vitamin D supplementation

with improvements in skeletal muscle mass, strength and function may be through

calcium handling and signalling and accumulation in the sarcoplasmic reticulum

(influencing the involvement of calcium in muscle contraction) or through the

activation of vitamin D receptors found in the cell nuclei of muscle cells (446-450).

At present, the available evidence from RCTs investigating the effects of vitamin D

supplementation on change in fat mass in middle-aged to older adults have largely

been equivocal (177, 451-453). For example, Salehpour et al. (452) successfully

demonstrated that 42 middle-aged overweight/obese women (mean ± SD, age 38 ±

8.1 years, BMI 29.8 ± 4.1 kg/m2) with low serum 25(OH)D levels (<40 nmol/L)

supplemented with 1,000 IU/day of vitamin D for 12-weeks experienced a greater

reduction in fat mass compared a placebo control group (mean change -2.7±2.1 vs -

0.5 ± 2.1 kg; P<0.001). In contrast, a study in overweight men and women (mean age

49 years) with 25(OH)D levels <30 nmol/L who were randomised to receive 3,320

IU/day of vitamin D3 (n=82) or a placebo (n=83) and participated in a healthy

Chapter 2

Page | 72

weight-reduction program for 12-months showed that there was no difference for the

change in weight between the groups (mean ± SD change: vitamin D -5.7 ± 5.8 kg vs

placebo -6.4 ± 5.6 kg)] (177). The authors suggested that the lack of an effect of

vitamin D treatment in this study may have been confounded by a greater reduction

and subsequent lower intake in total energy, carbohydrate, protein and fat intake in

the placebo group as opposed to the vitamin D group (177). Nevertheless, these

findings are in accordance with a recent systematic review and meta-analysis which

found that supplementation with vitamin D had no effect on adiposity measures,

including fat mass and BMI, in adults aged 60 years from 26 RCTs including 42,430

participants with vitamin D doses ranging from 400 IU to 12,695 IU/day and with a

mean follow-up of 12-months (454).

In older adults with T2DM, there are also mixed findings from intervention trials

with regard to the effect of vitamin D supplementation (or vitamin D plus calcium)

on fat mass (455, 456). In one 12-week RCT, 118 older adults with serum 25(OH)D

levels <75 nmol/L and diagnosed with T2DM were randomly assigned to one of four

groups (1) 50,000 IU per week of vitamin D plus a calcium placebo; (2) 1000 mg per

day calcium plus vitamin D placebo; (3) 50,000 IU per week vitamin D plus 1,000

mg of calcium/day; or (4) vitamin D placebo plus calcium placebo (456). Participants

in the vitamin D plus calcium group had a greater reduction in BMI (mean ± SD -

0.17 ± 0.12 kg/m2) when compared to all other groups (P=0.03), which was

attributed to reductions in waist circumference (mean ± SD, -0.83 ± 0.44 cm) (456).

These same improvements were not observed in the vitamin D and placebo group,

suggesting improvements in these outcomes may have been related to the additional

calcium (456). Few other studies have examined if vitamin D can alter measures of

fat mass in older adults with T2DM, and largely these studies fail to corroborate the

positive findings reported above (457, 458). In summary, given the limited studies

available, the marked heterogeneity in populations studied (ethnicity, age,

geographical location), differences in the duration of interventions and the dose of

supplemental vitamin D prescribed, it remains uncertain as to whether vitamin D

supplementation can improve fat mass in older adults with T2DM.

Several recent trials have investigated the effects of vitamin D supplementation on

lean mass with doses of vitamin D ranging from 800 IU/day to a mega-dose of

Chapter 2

Page | 73

50,000 IU in healthy older adults or those with T2DM (453, 459-461). These recent

trials found there was no effect found of vitamin D supplementation on lean mass

outcomes (453, 459-461). Consistent with these trials a systematic review and meta-

analysis of 30 RCTs with 5,615 participants (mean aged 61 years) and

supplementation periods ranging from 1-month to 5.5 years with vitamin D doses

ranging from 400 IU/day up to ~3,500 IU/day, found no evidence for a beneficial

effect on lean mass (462).

In summary, intervention trials which have examined the effects of vitamin D

supplementation on measures of fat and lean mass in older adults with T2DM or

overweight/obese adults show very little support for any improvement on such

outcomes. It is possible that the results of these trials are confounded by aspects of

trial designs including the dose of vitamin D provided, the baseline serum 25(OH)D

level of participants plus differences in the length of interventions and other

micronutrients provided at the same time (i.e. calcium). It is also possible that the

paucity of trials in this area, the great degree of heterogeneity in studies conducted to

date and participants changes in energy intake during these interventions explains the

lack of effect observed. It is evident that further research in this area is required.

2.10.3 Effect of Vitamin D on Markers of Inflammation

There is some evidence that supplementation with vitamin D may mediate and

attenuate inflammation as seen in in vivo, in vitro and in animal studies (463-465).

Indeed, the findings from predominantly in vitro studies, has expanded our

understanding of the mechanisms by which vitamin D may alter cytokine production

and although not conclusive, there is some suggestion that the coupling of

1,25(OH)2D to vitamin D receptors located in several immune cells including

monocytes, macrophages, T-cells and beta-cells, reduces the production of

inflammatory cytokines including TNF-α, IL-6, IL-12 and IL-23 while increasing the

production of various anti-inflammatory cytokine such as IL-1 and IL-4 (466). As a

result, considerable interest exists in investigating if treatment with vitamin D exerts

anti-inflammatory effects in humans.

Chapter 2

Page | 74

In adults without T2DM, a recent systematic review and meta-analysis found no

association between vitamin D supplementation and improved inflammatory

biomarkers (467), however, evidence from prospective studies suggests there may be

a role for vitamin D in ameliorating systemic inflammation in high risk groups with

various chronic diseases, including T2DM (468). However, intervention studies

which have investigated the effects of vitamin D supplementation on various

circulating inflammatory markers in those with T2DM remain largely negative (463,

464, 469, 470). One 16-week trial which randomised 64 older adults (mean age

53.5 ± 9.5 years) with T2DM who had 25(OH)D levels <50 nmol/L to 4,000 or 2,000

IU of vitamin D (depending on baseline serum 25(OH)D status) or placebo found

that there were no changes in hs-CRP (463). Similarly, the findings from another 12-

week RCT in 100 adults with T2DM observed no change in hs-CRP following 12-

weeks of 5,000 IU of vitamin D compared to placebo (471). A limitation of both

studies was the measurement of only a single inflammatory marker (463, 471). In

another 12-week trial in older adults (mean age >55 years) with T2DM who were

supplemented with vitamin D (11,200 IU daily for 2-weeks followed by 5,600 IU

daily for 10-weeks), Kampmann et al. (469) failed to observe any significant within

group changes or between group differences in hs-CRP, IL-6, IL-10 or TNF-α in

comparison to placebo (469). Collectively, these findings indicate that vitamin D

supplementation has little effect on various inflammatory biomarkers, but it is

important to note that from the available studies there is considerable heterogeneity

in the dose of vitamin D provided, the starting level and change in serum 25(OH)D

concentrations.

There is some evidence that the combination of vitamin D and calcium

supplementation may be associated with improvements in inflammation (472). In an

8-week RCT in 118 adults (mean age 51.2 years) with T2DM who were randomised

to receive placebo, calcium (1,000 mg calcium carbonate), vitamin D (50,000

IU/week) or calcium plus vitamin D supplements (50,000 IU vitamin D per week

plus 1,000 mg calcium carbonate/day) for 8-weeks, Tabesh et al. (472) found that

those who received both vitamin D and calcium plus vitamin D supplements

experienced significant reductions in serum IL-6, TNF-α and leptin, compared to

placebo (472). Whilst significant reductions in markers of inflammation were also

Chapter 2

Page | 75

seen with calcium supplementation alone, all observed reductions in the vitamin D

alone group were of greater magnitude, except for leptin, where no difference

between-groups was observed (472). The reason for the positive finding in this study

compared to previous trials is difficult to explain, but the authors noted that this

study was conducted during summer where endogenous production of vitamin D

may have increased the total amount of vitamin D received during this period.

Furthermore, compliance with the supplements was excellent (almost 100%) (472).

Studies in adults with T2DM which have used vitamin D fortified food products such

as milk and yogurt have also observed improvements in various inflammatory

markers, including hs-CRP, IL-6, IL-1 and adiponectin (473, 474). Despite these

positive findings, it remains unknown whether it is the vitamin D alone or the

combination of vitamin D with other ingredients in the food which is responsible for

the beneficial effect.

In summary, there are mixed findings regarding the sole effects of vitamin D

treatment on markers of inflammation in adults with T2DM. To date, most studies

have typically been of short duration with considerable heterogeneity in the

population groups examined as well as the dose of vitamin D used. Of the studies

which have found a favourable effect most have co-supplemented with calcium or

used fortified-food products making it difficult to determine the independent benefits

of vitamin D. As such, high-quality RCTs with large numbers of participants over an

extended period are still required to investigate if vitamin D supplementation confers

a positive effect on markers of systemic inflammation in this population group.

2.10.4 Effect of Vitamin D on Serum Lipids and Blood Pressure

Several cross-sectional and prospective studies propose an association between

serum 25(OH)D, hypertension and dyslipidaemia (408, 475-477). For example, in a

meta-analysis of 18 studies (4 prospective and 14 cross-sectional), every 40 nmol/L

increase in serum 25(OH)D levels was associated with a 16% reduced risk of

hypertension, However, most studies included in this meta-analysis had a cross-

sectional design, which cannot exclude the possibility of reverse causality (477).

Nevertheless, these observations are supported by the potential biological

mechanisms by which vitamin D may affect blood pressure and the suppressive

Chapter 2

Page | 76

effects it can exert on the renin-angiotensin-aldosterone system (RAAS) (478). The

RAAS is a key regulator of blood pressure via its regulation of renin activity (478).

Renin cleaves angiotensin I to angiotensin II and once bound to the receptor it exerts

regulatory effects on blood pressure (478). Activation or stimulation of RAAS is

established to proceed the development of hypertension, therefore the suppression of

RAAS by vitamin D may lower blood pressure (478). Others suggest the presence of

vitamin D receptors on the endothelium may be play a role in the anti-hypertensive

effects of vitamin D (479). Improvements in serum lipid profiles with vitamin D may

be due to increases in calcium absorption which reduces triglyceride formation or

secretion (480-482). Other potential mechanisms include mediation of parathyroid

hormone levels which are known to suppress lipolysis (482). Despite these proposed

yet unconfirmed mechanisms, results of intervention trials examining the effects of

vitamin D supplementation on lipid profiles and blood pressure are contradicting in

those with T2DM which will be discussed below.

At present, there are mixed findings with regard to the effects of vitamin D

supplementation on blood lipids in adults with T2DM. A recent meta-analysis which

included 17 RCTs ranging from eight to 48-weeks and a total 1,365 participants

aimed to assess the effects of supplemental vitamin D on serum triglyceride and

cholesterol levels in adults with T2DM (483). While there was trend towards vitamin

D treatment reducing triglyceride levels in those with serum 25(OH)D levels <50

nmol/L at baseline (P=0.089), there was no effect in those with basal serum

25(OH)D levels between 50 and 75 nmol/L (P=0.631) (483). Other factors which

may influence the effects of vitamin D supplementation on lipid outcomes is the dose

prescribed and the duration of the intervention. In the meta-analysis above, it was

found that doses less than 2,000 IU/day for a minimum of 12-weeks were

significantly associated with improvements in triglycerides and total cholesterol, but

not HDL or LDL cholesterol (483). Interestingly, doses greater than 2,000 IU/day of

vitamin D were not associated with any such improvements (483). The reason for

these contrasting results remains uncertain, but could relate to differences in

dyslipidaemia management and the delivery of vitamin D in such studies i.e. fortified

food products or tablet forms (483). In terms of the duration of the intervention, the

same meta-analysis reported that only interventions less than 12-weeks were

Chapter 2

Page | 77

associated with significant improvements in LDL cholesterol; there were no

significant effects of duration on triglycerides or total cholesterol (483). In contrast,

it was found that interventions less than 12-weeks had a negative effect on HDL

cholesterol, although interventions longer than 12-weeks were not significantly

associated with improvements in HDL cholesterol either (483). While the findings

from this meta-analysis suggest that vitamin D treatment may help to improve the

lipid profile of adults with T2DM, it is clear that further long-term trials are needed

to confirm such an effect.

A recent systematic review and meta-analysis which evaluated the effects of

micronutrients, specifically vitamin D supplementation, on blood pressure in adults

with T2DM found vitamin D to be effective at reducing both SBP and DBP (484).

Pooling data from seven interventions in 542 older adults with T2DM aged 50 to 66

years led to a significant reduction of 4.6 mmHg in SBP (95% CI, −7.65, −1.47,

P=0.004) and a reduction in DBP of 2.44 mmHg (95% CI, −3.49, −1.39, P < 0.001)

(484). The authors of this systematic review and meta-analysis however, pointed out

that these findings should be interpreted with caution given the small number of trials

included and that another recent systematic review found no effect of vitamin D

supplementation on SBP in older adults with T2DM when including 15 studies and

1,134 participants with T2DM. As such, the evidence of vitamin D supplementation

on blood pressure in older adults with T2DM appears to be mixed depending on the

trials examined and the differences in population groups and study design (e.g.

baseline serum 25(OH)D level variation, varying sun exposure and different dosing

regimens) with further trials required.

In summary, there are biologically plausible mechanisms by which vitamin D

supplementation may improve plasma lipids and blood pressure, and along with an

expanding body of evidence from RCTs and meta-analyses vitamin D

supplementation may be important for improving SBP and DBP, triglycerides, total

and LDL cholesterol in older adults with T2DM. Whether there is an optimal dose

and/or achieved serum 25(OH)D level to improve these measures remains unknown.

Chapter 2

Page | 78

2.11 Exercise, Protein and Vitamin D for the Management of Type 2 Diabetes

As discussed above, there is evidence that PRT, whey protein and vitamin D each

may have a beneficial effect on glycaemic control, body composition and

cardiovascular risk factors in older adults with T2DM. In recent years, there has been

interest in whether combining PRT with various nutritional factors may provide

additive or synergistic health benefits in older adults and those with T2DM. The

following section will provide an overview of the evidence regarding the combined

effects of exercise and nutritional supplementation, with a focus on protein and/or

vitamin D supplementation, on body composition, glycaemic control, insulin

sensitivity/resistance, and cardiovascular risk factors including serum lipids,

inflammation and blood pressure, in older adults and/or those with chronic diseases,

including T2DM.

2.11.1 Effects of Exercise and Protein or Exercise and Vitamin D on Lean Mass

Over the past two decades, there has been a growing number of RCTs which have

investigated whether PRT or multi-modal exercise programs combined with

additional protein can produce added benefits on muscle compared to PRT alone in

healthy older adults. As a result, there have been at least three meta-analyses and

systematic reviews on this topic (485-487). These three meta-analyses and systematic

reviews demonstrate the literature in this area is currently inconclusive with

inconsistent findings, which could be due to different trial inclusion criteria used in

these meta-analyses. For example, Cermak et al. (486) classified older adults as >50

years and included 22 RCTs and 680 participants, whereas Finger et al. (485)

selected a cut point of >60 years and included six RCTs with 334 adults. In the most

recent meta-analysis, Thomas et al. (487) chose >70 years to reflect an elderly

population and included 15 RCTs and 917 participants. The first two listed

systematic reviews reported that increased dietary protein or protein supplementation

enhanced the effects of PRT on fat-free mass [(0.69 kg (95% CI, 0.47, 0.91),

P=0.00001) and (0.23 kg (95% CI, 0.05, 0.42)], respectively; there was no significant

effect on muscle CSA or muscle mass (485, 486). In contrast, the most recent meta-

analysis by Thomas et al. (487) failed to detect any added benefits of protein or

essential amino acid supplementation combined with PRT on muscle mass in the

Chapter 2

Page | 79

elderly (487). These contrasting results may have been due to the fact, as touched

upon above, there was considerable variability in the characteristics of the trials

included in each of these meta-analyses, including differences in the source/quality

of protein, the quantity of protein provided, the baseline dietary protein intake, the

inclusion of other ingredients such as vitamin D, leucine and other essential amino

acids plus the timing of supplementation relative to the PRT programs. Nevertheless,

in healthy older adults aged 50 to 80 years, long-term participation in PRT (> 6-

weeks) combined with increased dietary protein, predominantly dairy derived such as

whey protein, appears to provide a small (~0.5 kg) but significant additive effect on

fat-free mass (485, 486).

To date, little consideration has been given to whether increased dietary protein

concomitant to PRT in older adults with T2DM can offer an additive effect on

muscle mass. In the only study to date, Wycherley et al. (286) conducted a 2x2

factorial design RCT that compared isocaloric energy-restricted diets of either

standard control (19% energy from protein) or high protein (33% energy as protein)

with or without supervised PRT (3 days/week, 70-85% 1-RM) for a period of 16-

weeks in 83 overweight/obese men and women (mean age ± SD, 56.1 ± 7.5 years,

BMI ± SD, 35.4 ± 4.6 kg/m2). To facilitate good dietary compliance, a combination

of dietary advice and some food products and recipes were provided by a qualified

dietitian (286). Protein intake averaged 1.12 g/kg/day in the high protein groups and

participants demonstrated good compliance with their intervention diets (mean

percent energy from protein: control and control plus PRT ~18% vs high protein and

high protein plus PRT ~32%, P<0.001 diet and treatment effect) (286). There were

no improvements in total body lean mass in any of the groups and in fact an overall

non-significant reduction in total body lean mass was observed across groups, which

is likely explained by the calorie restricted diet (Figure 2.7) (286). Total body weight

loss was greater in the high protein plus PRT groups compared to the control and

high protein diet (P<0.05) but statistical significance was not reached when

compared to the control diet plus PRT (286). Similarly, fat mass reduced in all

groups yet was greatest in the high protein plus PRT compared to both the control

and high protein diet groups (P<0.05) yet again was not different to the control plus

PRT group (Figure 2.7) (286). The lack of an effect of the high protein diet

Chapter 2

Page | 80

concomitant to PRT on total body lean mass could be related to a number of factors,

including the level of protein intake achieved (dose in g/kg/day), the quality of the

protein used, the timing of consumption relative to participation in the PRT program,

the change in protein intake from baseline and/or the PRT load prescribed. The

following section will review the available evidence with regard to the influence of

the dose, distribution and timing of protein intake regarding PRT or multi-modal

exercise programs in older adults or those with T2DM.

Figure 2.7: Mean ± SD absolute changes (in kg) in total body weight, fat mass and lean mass after 16-weeks on a hypocaloric high protein (33% energy from protein) or hypocaloric control diet (19% energy from protein) with and without PRT. Taken from Wycherley et al. (286). * P<0.05, # P<0.01 vs high protein plus PRT

While there is considerable evidence from acute studies indicating that the dose of

whey protein and leucine are important factors that can influence the MPS response

to exercise, there are mixed findings from long-term human intervention trials.

Several longer-term human intervention trials have shown that there is little or no

added benefits when PRT is combined with doses of whey protein < 20 g (and < 2 g

of leucine) (284, 488-493), but there also mixed findings from a number of trials that

used higher doses of protein (285, 377, 494). In one study, it was observed that when

Chapter 2

Page | 81

327 middle to older aged overweight participants (age ± SD 48.0 ± 7.9 years)

consumed whey protein supplements at a dose of either 0, 10, 20 or 30 g per serve

twice per day and participated in a 9-month resistance and aerobic exercise program

(3 days/week) there was no additive effect of whey protein on exercise induced gains

in DXA-measured lean muscle (285). In a secondary analysis of this same study,

when participants were stratified by total protein intake (<1.0, ≥1.0-<1.2 and ≥1.2

g/kg/day) rather than dose of supplement there was still no difference between the

groups for the change in total body lean mass (494). While another 6-month trial in

80 70- to 85-year-old adults found that 40 g/day of whey protein (20 g at breakfast

and dinner) increased total body lean mass by 1.3%, this change was not significantly

different to the 0.6% increase observed in the isocaloric placebo group (377). The

lack of enhanced effect of whey protein on PRT induced improvements in lean mass

in these two studies was likely due to the baseline protein intakes of the participants,

which exceeded 1.0 g/kg/day.

As summarised in Table 2.10, there are few long-term human intervention trials in

older adults which have shown that the combination of PRT with additional dietary

or supplemental protein enhance the effects of PRT on muscle mass or size. As

already indicated, many of the studies where protein intake at baseline has been ~1.0

g/kg/day or higher did not observed an enhanced effect of additional protein in

conjunction with PRT or exercise on lean mass or size (284, 377, 492). This is

perhaps not unexpected given that most current international guidelines recommend

that older adults (65+ years) have a daily protein intake of at least 1.0 to 1.2 g/kg/day

of protein for the maintenance of physical function and optimal health. However, it is

also recommended that higher levels (>1.2 g/kg/day) are needed for those that

regularly participate in exercise (495). In part support of the above recommendation,

there is some evidence for an additive effect of protein with PRT on lean mass in

those with initial protein intakes <1.0 g/kg/day and those who have poor health for

example are sarcopenic (284).

The terms ‘protein spread’ and ‘protein change’ were proposed several years ago and

have subsequently been suggested other potential factors that may explain the

discrepant findings amongst some studies investigating effects of PRT with protein

Chapter 2

Page | 82

on muscle (373). Protein spread refers to the magnitude of difference in protein

intake between the groups during an intervention, whereas protein change refers to

whether there is a sufficient change in total protein intake from baseline during the

intervention (373). Signifying the importance of these factors was a review of 17

intervention trials which examined the effects of additional protein intakes combined

with PRT in both young and older adults (373). Interestingly it was found that in the

studies which did observe an added benefit of protein with PRT on lean mass the

average percent increase (change) in habitual protein intake (g/kg/day) was 59.5% as

opposed to only 6.5% in the studies which saw no added benefit (373). Additionally,

in those studies which concluded that higher protein interventions were effective

there was an average 66% g/kg/day between group difference (spread) compared to

only a 10% g/kg/day spread in the studies which were unsuccessful in observing an

additive effect (373).

The timing of protein intake relative to participation in a PRT program and the

distribution of protein intake, that is, dispersing protein more evenly throughout the

day, may be important factors influencing the effects of additional protein in

combination with exercise on lean mass (49). For instance, a 12-week study in 13

men (mean age ± SEM, 74 ± 1 years, mean baseline protein intake 1.1g/kg/day)

found 10 g of protein consumed immediately (within 5-minutes) of PRT completion

amounted to greater gains in total body lean mass compared to the men consuming

the protein supplement 2-hours following PRT (496). However, others have failed to

detect any added benefits of protein consumed either before or after PRT on muscle

hypertrophy (282, 497), and thus questions remain as to whether there is an optimal

time for protein intake relative to exercise. More recently however, there is some

evidence indicating that studies which have dispersed protein intake more evenly

throughout the day alongside a PRT program may provide some added benefits to

lean mass (0.5 to 1 kg) (refer to Table 2.9) (42, 283). It has been suggested that PRT

(exercise) may sensitise skeletal muscle to the anabolic effects of amino acids for up

to 24-hours, and thus this even protein distribution (at a sufficient dose) throughout

the day could enhance gains in skeletal muscle mass (498-501). However, others

following a similar protocol have not observed a favourable effect (377), which may

be related to the fact that repeated intake of supplements could act as a partial meal

Chapter 2

Page | 83

replacement as the study by Chalé and colleagues found that habitual dietary protein

intake reduced throughout the intervention (377). In summary, there is some

evidence that dispersing protein intake throughout the day may enhance the effects of

PRT on muscle, but further studies are still needed to address this question.

Few studies have examined whether combining PRT or exercise with vitamin D

supplementation can have an additive effect on muscle mass in older adults or those

with T2DM. Previously, 52 older women (mean age >68 years) with T2DM who had

insufficient serum 25(OH)D levels (<40 nmol/L) were randomised to either circuit

training (3-4 times per week comprising PRT and aerobic exercise), circuit training

plus 1,200 IU of vitamin D/day, vitamin D alone (1,200 IU/day) or control (502).

Significant improvements were observed in total body weight (-2.1%), fat mass (-

4.9%), percent body fat (-2.1%), total abdominal fat area (-9.1%) and subcutaneous

fat area (-9.2%) in those who completed the circuit training program with vitamin D

supplementation compared to vitamin D and control yet these results were not

different to those who performed circuit training alone (502). Additionally, there was

a 1.5% improvement in lean mass resulting from the vitamin D plus circuit training

program however, this improvement was no different to any of the other arms of the

study (502). In another 16-week RCT, 20 older men (aged 60-75 years) with serum

25(OH)D levels >50 nmol/L consumed ~2,000 IU/day of vitamin D with PRT

performed three days per week (70-75% 1-RM) in the final 12-weeks of the

intervention (503). Again, no significant additive effect of vitamin D with PRT on

changes in DXA-derived total body lean mass and magnetic resonance imaging-

derived muscle size was observed in comparison to control (503). It is unclear to

what extent baseline and target vitamin D concentrations, vitamin D dose and

treatment duration may influence the outcomes of such intervention trials, however,

any one or a combination of these factors could explain the lack of an enhanced

effect. For instance, the precise serum 25(OH)D level which may be associated with

improved muscle health or body composition outcomes remain unknown, but we do

know that vitamin D deficiency [serum 25(OH)D <25-30 nmol/L] is associated with

muscle weakness (504, 505). Thus, in older adults with serum levels >25-30 nmol/L

there may be little impact on muscle mass Additional, well-designed RCTs

supplementing vitamin D to older adults with a range of baseline serum 25(OH)D

Chapter 2

Page | 84

levels are required to fully elucidate if there is any additive effect on total body lean

mass or other body composition benefits when combined with exercise/PRT.

Page | 85

Table 2.9: Summary of randomised controlled trials which have examined the interactive effects of various protein supplements with PRT/ exercise and those which have examined the additive effects of protein and vitamin D supplements with PRT/exercise on lean mass in older and elderly adults. Adapted from (370).

Reference Study Characteristics Baseline Protein

(g/kg/day)

Supplement Details (Dose, ∆ Protein

Intake and Timing of Intake)

Comparison Group

Outcome and Method of Assessment

Milk and Dairy-based protein supplements

Campbell et al. 1995 (506)

n=12 healthy sedentary adults aged ~64 years. 2 days/week, 3 sets, 8-12 reps, 80% 1-RM for 12-weeks.

0.6

Dose: 1.6 g/kg ∆ Protein: 1.0 g/kg/day Timing: NS

Low-protein (0.8 g/kg)

Lean mass: Significant increase (~1 kg) compared to baseline but no difference between groups as assessed by total body weighing using the three compartment model of Siri.

Rosendahl et al. 2006 (507) plus Carlsson et al. 2011 (508).

n=191 living in residential care adults aged 85 years. Multi-modal program 5 times per fortnight for 12- weeks.

NS Dose: 7.4 g/day ∆ Protein 6.1 g/day Timing: After exercise

Ex + placebo, milk or control plus placebo

No difference between groups as measured using a bioelectrical impedance spectrometer.

Iglay et al. 2009 (492)

n=36 healthy untrained adults aged 61 years. 3 days/week, 3 sets, 8 reps, 80 % 1-RM for 12-weeks.

1.1

Dose: 1.6 g/kg ∆ Protein 0.1 g/kg/day Timing: At meal times

Low protein (0.9 g/kg)

Lean mass: Significant increase of ~1kg compared to baseline. No difference between groups as measured by DXA.

Page | 86

Kukuljan et al. 2009 (493)

n=180 healthy untrained males aged ~60 years 3 days/week, 2–3 sets, 8–20 reps, 60–85 % 1-RM 72-weeks.

~1.3

Dose: 13 g/day ∆ Protein: 11.9 g/day Timing: Morning and afternoon/evening

Ex, fortified milk or usual

care

Lean mass: Significant within-group increase of ~1 kg as assessed by DXA. No difference between-groups.

Tieland et al. 2012 (283)

n=62 frail elderly adults aged 78 years. 2 days/week, 3–4 sets, 8–15 reps, 75 % 1-RM for 24-weeks.

1.0

Dose: 30 g/day ∆ Protein: 0.3 g/kg/day Timing: After breakfast and lunch

Flavoured CHO drink

Lean mass: 1.3kg significant within group increase in the intervention group. Significant net difference of 1.6 kg as measured by DXA.

Leenders et al. 2013 (284)

n=60 healthy untrained adults age=d 70 years. 3 days/week, 3–4 sets, 8–15 reps, 75–80 % 1-RM for 24-weeks.

~1.1

Dose: 15 g/day ∆ Protein: 0.18-0.24 g/kg/day Timing: After breakfast

Lactose and calcium drink

Lean mass: Similar significant ~1 kg increase but no differences between the groups as assessed by DXA.

Buhl et al. 2016 (509)

n=29 acutely ill adults aged 72-73years. 3 days/week, 3 sets, 8–12 reps (intensity NS) for 12-weeks.

0.74 Dose: 18.8 g/day ∆ Protein 14.1 g/day Timing: After exercise

Standard care

Lean mass: Significant ~0.5 kg reduction compared to baseline. No difference between the groups in as measured by DXA.

Page | 87

Whey Protein

Candow et al. 2006 (497)

n=29 mobility limited adults aged 63-66 years. 3 days/week, 3 sets, 10 reps, 70 % 1-RM for 12-weeks.

NS

Dose: 0.3 g/kg ∆ Protein: 0.3 g/kg/day Timing: Before or after exercise

Chocolate CHO drink

Lean mass: Similar significant increase in lean mass in all groups compared to baseline with no differences between-groups as measured by air-displacement plethysmography.

Chale et al. 2013 (377)

n=80 healthy untrained adults aged 77-78, M/F 3 days/week, 2–3 sets, 10–12 reps, 80 % 1-RM for 24-weeks.

~0.9

Dose: 40 g/day ∆ Protein: 18 g/day Timing: After breakfast and evening meal

Maltodextrin Lean mass: No between-group differences in lean mass as assessed by DXA.

Arnarson et al. 2013 (510)

n=161 obese untrained adults aged 73-74 years. 3 days/week, 3 sets, 6–8 reps, 75–80 % 1-RM for 12-weeks.

1.1

Dose: 20 g/day (7 g EAA) ∆ Protein: 0.06 g/kg/day Timing: Immediately after exercise

Carbohydrate control

beverage

Lean mass: No change in lean mass as assessed by DXA. No between-group differences.

Soy-based protein

Fiatarone et al. 1994 (511)

n=100 frail elderly adults aged 87 years. 3 days/week, 3 sets, 8 reps, 80 % 1-RM for 10-weeks.

NS Dose: 15 g/day, ∆ Protein: 15 g/day Timing: Evening

Ex, low energy beverage or

control

No within-group changes in lean mass and no between-group differences measured by whole body potassium as an index of body cell mass.

Page | 88

Casein

Verdijk et al. 2009 (282)

n= 26 healthy untrained males aged 72 years. 3 days/week, 4 sets, 8-15 reps, 75-80% 1-RM for 12-weeks.

1.1

Dose: 20 g/day ∆ Protein: 20 g/day Timing: Prior to and following exercise

Flavoured water

Significant similar (~0.6 kg) increases in lean mass in both groups, no group by time interactions as measured by DXA.

Leucine

Trabal et al. 2015 (490)

n= 30 adults living in residential care, aged 84-85. Three days/week, 2 sets, 15 reps, 65% 1-RM for 12-weeks.

1.2

Dose: 5 g/day (twice) ∆ Protein: 0.03 g/kg/day Timing: After lunch and dinner

Maltodextrin

No differences within or between-groups for calf circumference and triceps skin-folds (assessment of lean mass).

Essential amino acids

Godard et al. 2002 (488)

n= 17 healthy untrained males aged 71-72 years. 3 days/week, 3 sets, 10 reps 80% 1-RM or fatigue for 12-weeks.

1.1

Dose: 12 g/day ∆ Protein: 2% increase in energy from protein Timing: After exercise or at same time each day

Usual care

Similar (7 and 6%) increases in muscle CSA in intervention and control groups. No differences between the groups from CT measured thigh cross-sectional area.

Kim et al. 2012 (489)

n= 155 sarcopenic women aged 79 years. 2 days/week, 1 set, up to 8

NS Dose: 3 g/day (twice) ∆ Protein: 6 g/day

Exercise, EAA only or health

education

No within-group changes or between-group differences in ALM. Protein plus PRT was significantly better than health education for improving leg

Page | 89

reps, 14-16 RPE for 12-weeks.

Timing: Twice a day (no statement on time)

lean mass (P<0.010). 2 and 3% increases in leg lean mass in protein plus PRT and PRT alone vs baseline (P<0.05). Measurements conducted with BIA.

Multi-nutrient supplements (Protein plus Vitamin D)

Verreijen et al. 2015 (512)

n= 80 obese older adults aged 63 years. PRT 3 times/week, 3 sets, 10 reps (intensity NS) for 13-weeks. All followed a hypocaloric diet (-600 calories/day).

NS

Dose: 21 g whey, 3 g leucine, 800 IU vitamin D per supplement ∆ Protein: 1.11 g/kg/day of protein was consumed during the intervention by the intervention group Timing: Every morning and immediately following training on training days

Isocaloric control plus

exercise

Significant interaction (P=0.03) between the groups. Driven by a 0.4 kg gain in the PRT plus protein group with a 0.5 kg reduction in the control group.

Rondanelli et al. 2016 (513)

n= 130 sarcopenic elderly adults aged 80 years. Multi-modal exercise program of moderate-intensity 5 times/week for 12-weeks.

0.9

Dose: 1 x 32 g (22 g whey, 4 g leucine, 100 IU vitamin D) ∆ Protein: 1 g/day Timing: NS

Maltodextrin plus exercise

1.4 kg increase in lean mass in the intervention group, (P<0.001) compared to baseline as measured by DXA. This change led to a significant between-group difference (P<0.001).

Page | 90

Holm et al. 2008 (514)

n= 38 healthy untrained women aged 55 years. PRT 2-3 times/week, 3 x 15 reps at 20-RM weeks 1-2, 3 x 10 reps at 10-RM 3-12 and 5 x 8 reps at 8-RM weeks 13-24.

1.0

Dose: 10 g of whey protein 200 IU of vitamin D ∆ Protein: Timing: One/day immediately after training on training days

Placebo plus PRT

No between-group difference for change in lean mass. A 0.8 kg increase in lean mass was observed in the intervention group compared to baseline. Body composition measured with DXA.

NS, Not stated; DXA, Dual energy X-ray absorptiometry; CT, computed tomography; IU, International units; EAA, essential amino acids; BIA, Bioelectrical impedance analysis; RPE, ratings of perceived exertion

Chapter 2

Page | 91

2.11.2 Effects of Exercise Combined with Protein and Vitamin D on Lean Mass

Several recent interventions have investigated whether multi-nutrient supplements

including protein and vitamin D, when combined with exercise can enhance the

effects of exercise on muscle mass and strength in older adults (Table 2.9) (512-515).

In one trial, 80 obese older adults (mean age ± SD, 63.0 ± 5.6 years) performed PRT

(3 times per week), followed a hypocaloric diet (-600 calories) and were randomised

to either a high whey protein, leucine and vitamin D rich supplement (150 calories,

21 g of protein, 2.8 g leucine, 800 IU of vitamin D) or an isocaloric control for 13-

weeks (512). All supplements were consumed prior to breakfast and after training

sessions on training days (512). During the intervention period and inclusive of the

supplement, protein intake was 1.1 g/kg/day in the intervention group. Baseline

protein intake was not reported. Baseline serum 25(OH)D status was not reported nor

was the change in serum 25(OH)D level. After 13-weeks, similar reductions in total

body weight and fat mass in the intervention and control groups were observed (total

body weight; 3.4 ± 3.6 kg vs 2.8 ± 2.8 kg; fat mass 3.2 ± 3.1 kg vs 2.5 ± 2.4 kg, all

P<0.001, respectively) which was likely due to the hypocaloric diets followed by all

participants (512). Following the 13-week weight loss intervention, the change in

ALM and leg muscle mass was significantly different between the intervention and

control group [mean change in ALM ± SD; intervention, +0.4 ± 1.2 kg and control, -

0.5 ± 2.1 kg, P=0.03 and mean change in leg muscle mass ± SD; intervention, +0.3 ±

1.2 kg and control -0.6 ± 1.8 kg, P=0.01] (512). This suggests that a multi-nutrient

supplement containing whey protein, leucine and vitamin D concurrent with PRT can

enhance the effects of PRT on muscle mass in older adults (512). In another study,

Rondanelli et al. (513) examined the effects of a 12-week multi-nutrient supplement

(22 g of whey protein, 4 g of leucine and 100 IU of vitamin D) or placebo combined

with a moderate-intensity physical activity program (aerobic and strength based

training) performed 5 days per week on muscle mass in 130 sarcopenic elderly men

and women (513). The combination of the multi-nutrient supplement and exercise

program increased total body lean mass compared to placebo plus exercise [mean net

difference 1.7 kg (95% CI, 0.9, 2.5), P<0.001 for the between-group interaction]

(513). The greater magnitude improvement in this trial may be due to the differences

in population groups examined (e.g. sarcopenic elderly adults compared to obese

Chapter 2

Page | 92

older adults). Nevertheless, the findings from these two trials demonstrate an

integrated intervention combining a multi-nutrient supplement containing protein and

vitamin D in addition to a PRT or a multi-modal exercise program can lead to greater

improvements in muscle mass in older adults when compared exercise alone (512,

513).

Despite the positive findings from two trials, not all interventions have observed an

enhanced effect of PRT combined with a multi-nutrient supplement containing

vitamin D and protein on muscle mass in older adults. For instance, the findings from

a 24-week RCT in which early postmenopausal women (mean age 55 years) were

provided a multi-nutrient supplement (n=16) containing 10 g of protein (no report of

leucine content), 31 g of carbohydrate, 250 mg of calcium and 200 IU of vitamin D

or a placebo product (n=13) consumed immediately following PRT (five 20 minute

sessions per week of moderate-intensity) showed there were no additive benefits on

DXA assessed lean or fat mass (514). The only significant result was a small increase

in lean mass compared to baseline in the multi-nutrient intervention group (514). As

baseline protein intake were on average >1.0 g/kg/day, it is likely that the additional

10g of protein was not sufficient to enhance the anabolic effects of the exercise

program. Another possible reason for the lack of an additive effect is that the

participants in this trial were middle aged women, a time around which reductions in

muscle mass due to ageing are just beginning to commence (516, 517), greater

improvements may have been observed had participants been sarcopenic as seen

previously (513). The authors of this study also posited that the lack of an interactive

effect on gains in muscle may have been related to the moderate-intensity and

moderate volume of the PRT program (514).

Drawing conclusions from the studies conducted to date is difficult as the design of

the trials, prescription of exercise/PRT programs, the doses of protein and vitmain D

prescribed, the starting levels of vitamin D, protein status (deficient or replete),

intervention protein prescribed (large dose or modest dose) and the age/gender

characteristics of these trials were all different. Despite these factors, there is some

positive evidence that PRT/exercise combined with increased protein intake and

vitamin D supplementation may enhance the improvement in lean mass offered from

Chapter 2

Page | 93

PRT/exercise alone. Whether the same benefits would also be observed in older

adults with T2DM is not known.

2.11.3 Effects of Exercise, Protein or Vitamin D on Glycaemic and Insulinaemic Outcomes

Whether the combination of PRT and increased protein enhances the glycaemic and

insulinaemic improvements typically associated with PRT in older adults and those

with T2DM remains unknown. Studies which prescribe weight loss/energy

restriction alongside increased dietary protein and PRT have been associated with

improvements in glycaemic control and insulin sensitivity as summarised in Table

2.10 yet the inclusion of energy restriction/weight loss may confound the findings as

weight loss/energy restriction is commonly associated with improvements in these

outcomes. For instance, the only study to examine the effects of increased dietary

protein in conjunction with PRT on glycaemic and insulinaemic outcomes in older

adults with T2DM also prescribed a hypocaloric diet to induce weight loss, as

described previously (Table 2.10) (286). Briefly, in this 16-week RCT, 83

overweight/obese men and women (mean age 56.1 ± 7.5 years) with T2DM were

randomly assigned to a hypocaloric high (33% energy from protein) or low protein

(19% energy from protein) diet with or without PRT (3 days/week, 70-85% 1-RM)

(286). After 16-weeks all groups experienced a similar significant reduction in

plasma glucose (reductions ranged from 1.9 to 2.5 mmol/L) and HbA1c (reductions

ranged from 1.1 to 1.8%) (286). Interestingly, there was a significant reduction in

insulin in the high protein plus PRT group compared to baseline (P<0.001), which

was two-fold greater than the other groups, but again no interaction was observed

(P=0.11) (Figure 2.8) (286). Secondary analysis and pooling of the groups in this

study found the change in insulin was significantly correlated with changes in both

total body weight (r=0.35, P<0.01) and fat mass (r=0.36, P=0.005), which is perhaps

not surprising as body fat has been found to predict insulin sensitivity in older people

(518). This may explain the greater reduction in insulin in the PRT plus high protein

group as this group experienced the greatest reduction in fat mass (mean reduction -

11.4 kg, P>0.01) (286). Other studies have also failed to demonstrate the

combination of increased dietary protein with PRT is more effective than PRT alone

Chapter 2

Page | 94

on improving glycaemic and insulinaemic outcomes (285, 519), this is believed to be

attributed to the fact that all participants experienced similar reductions in weight.

Figure 2.8: Mean (± SD) absolute changes in fasting insulin (pmol/L), glucose (mmol/L) and HbA1c (%) following a 16-week high protein (33% energy from protein) or control diet (19% energy from protein) with or without participation in PRT (3 days/week 70-85% 1-RM). Taken from Wycherley et al. (286).

Several studies examining the effectiveness of increased dietary protein alongside

PRT, independent of a hypocaloric or weight loss diet, have failed to clearly

demonstrate the value of such an approach on improving glycaemic control, insulin

sensitivity and insulin levels (283-285, 519-521). For instance, 16-weeks of whey

protein supplementation (21 g, three times per day) combined with high-intensity

PRT performed four times per week in 27 healthy middle-aged adults (mean age 47

years) resulted in significant reductions in glucose (21%), insulin (14%) and HOMA-

IR (31%) when compared to baseline (all P<0.05), but these improvements were no

different to the protein only intervention without exercise (520). Potentially this was

because both groups experienced similar significant mean reductions in body weight

(1.4 kg), percent body fat (0.7%) and abdominal fat (0.3 kg) respectively, compared

to baseline. Only the protein plus PRT group experienced a significant increase in

percent total body lean mass (mean ± SD, 0.9 ± 0.3%, P<0.05) yet this increase was

no different to those in the protein only group (520). Several possible reasons for the

Chapter 2

Page | 95

lack of effect were proposed and include participants at baseline were consuming

upwards of 1.1 g/kg/day of protein, the supplements were prescribed to provide an

extra 60 g of protein per day on top of habitual protein intake yet the mean increase

was only 34 g, suggesting displacement of habitual protein intake (520). The

proposed displacement of protein intake following the addition of the protein

supplements may have been both a consequence and a limitation of the study design

where supplements were prescribed to be consumed in-line with the three daily main

meals. Had the protein supplements successfully been consumed in addition to the

habitual diet of participants (rather than replacing) this would have raised daily

protein intakes to ~1.8 g/kg and percentage energy to well above 30%. Indeed, the

findings from another study in middle-aged (mean age 48.4 years) overweight and

obese adults showed that increasing total protein intake from ~20% to 35%, with the

use of whey protein supplements, significantly improved insulinaemic outcomes,

independent of PRT, weight loss or gains in total body lean mass (351). While a few

other intervention trials in older adults have also used a protein supplement to

investigate glycaemic outcomes, again these findings remain inconclusive which

may be related to a number of factors, including the type and dose of protein. Table

2.10 provides an overview of these interventions (283-285, 519, 521).

Whether there is an optimal dose of protein to enhance the effects of PRT on

glycaemic and insulinaemic outcomes remains uncertain. The closest study to

investigate a dose response relationship was conducted in 220 healthy adults (mean

age 48 years) who all performed 36-weeks of high-intensity combined resistance and

aerobic training and were randomly assigned to one of four twice daily doses of

whey protein (0g (placebo), 10g, 20g or 30 g of whey protein) (285). Whilst the

primary outcome of this study was to examine change in body composition, changes

in glucose, HOMA-IR and insulin sensitivity were also assessed. At the end of the

intervention no differences were observed between the groups in terms of the gains

in total body lean mass or any glycaemic or insulinaemic measures (285). However,

pooling of the data found an overall reduction in insulin AUC of 2.6 ± 32% (-7.5 ±

29 nmol/L × 3 h, P = 0.01), which coincided with an overall 1.9 ± 2.8% (P<0.001)

increase in total body lean mass (285). The lack of a greater magnitude gain in lean

mass was likely due to participants in this trial being relatively healthy (albeit

Chapter 2

Page | 96

overweight) with sufficient intakes of protein at baseline (~1.0-1.1 g/kg/day).

Another study also observed no beneficial effect of PRT combined with a twice daily

milk protein concentrate supplement on glycaemic or insulinaemic outcomes in 62

older frail but metabolically healthy adults (mean age ~78 years) who had intakes of

protein at baseline of ~1.0 g/kg/day. Participants in this study also presented with

FPG and insulin levels in the healthy normal range (mean glucose 5.3 ± 0.5 mmol/L

and mean insulin 130.6 ± 47 pmol/L) which did not change following twice daily

(breakfast and lunch, 15 g per serve) milk protein concentrate supplementation with

PRT (twice per week) (283). Other possible reasons for the lack of an additive effect

may have been due to the type of protein used (e.g. milk protein) or the level of total

protein intake not being significantly different from the control group (supplement

83.5 g/day vs control 77.7 g/day, P=0.61), combined with the lack of a marked

change in protein intake from baseline (mean increase of only 6 g/day) (283).

In summary, studies investigating the combined effects of PRT with increased

protein on insulinaemic and glycaemic outcomes remain inconclusive, largely

confounded by the incorporation of energy restriction/weight loss in these trials

which is well established to be a potent method to improve glycaemic control and

insulin sensitivity. Nevertheless, several studies have demonstrated the importance of

independent participation in PRT for improving glycaemic control and to a lesser

extent levels of insulin as discussed in section 2.7.2.2 of this literature review.

It is possible that other nutrients such as vitamin D in addition to PRT and increased

protein consumption may interact to improve glycaemic control and insulin

sensitivity in older adults with T2DM. However, no studies appear to have

specifically addressed this question. The closest study to do so randomised 52 elderly

(mean age 70 years) women deficient in vitamin D with T2DM to vitamin D

treatment (1,200 IU/day) or placebo with and without circuit training (moderate-

intensity PRT and aerobic training) for 12-weeks (502). Following the intervention,

no significant differences were observed between the groups for the change in FPG,

insulin or HOMA-IR, but greater non-significant improvements in the combined

group relative to controls was observed (-10.7% vs 4.1% fasting insulin; -35.8% vs

29.2% and HOMA-IR; -42.8% vs 28.9%) (502). The lack of a significant interaction

Chapter 2

Page | 97

may have been due to the intervention period not being long enough, the lack of

change in lean mass, the insufficient training intensity and/or the dose of vitamin D

being low. Whilst the dose of vitamin D and serum 25(OH)D level which may offer

glycaemic and insulinaemic improvement remains unknown, a study which did find

a significant positive effect of vitamin D supplementation on insulin outcomes in

middle-aged women with T2DM, yet without exercise or PRT, provided a dose four

times as high (4,000 IU/day) (65). Clearly further research is need to determine if

there is in fact an optimal serum level of 25(OH)D and/or dose of vitamin D that may

produce an additive effect with PRT on glycaemic and insulinaemic outcomes.

Page | 98

Table 2.10: Summary of RCTs which have examined the interactive effects of increased dietary protein or protein supplements with PRT or exercise on glycaemic and/or insulinaemic outcomes in older and elderly adults.

Reference Study Characteristics

Baseline Protein Intake

(g/kg/day)

Supplement/Diet Details

(Dose/Intake, ∆ Protein

Intake, Type)

Comparison Group

Change in insulin or glycaemic parameters

Adults with Type 2 Diabetes

Wycherley et al. 2010 (286)

n= 83 adults aged 56 ± 7.5 years. PRT 3 days per week, 3 sets 8-12 reps 70-85% 1-RM

NS

Dose: 1.12 g/kg ∆ Protein Intake:

Unknown Type: High protein food sources (not specified)

Control diet, high protein

diet and control diet plus PRT

Glucose and HbA1c similarly and significantly reduced in all groups no difference between groups. Insulin reduced to a greater degree in the high protein plus PRT group (two-fold) but was not significant compared to other groups.

Healthy Older or Elderly Adults

Tieland et al. 2012 (283)

n= 62 adults aged 78 ± 7 years PRT completed 2 days/week for 24-weeks 3-4 sets, 8-10 reps 75% 1-RM for 24-weeks

~1.0

Dose: 15 g twice/day (breakfast and lunch) ∆ Protein Intake: 0.3

g/kg/day Type: Milk protein

concentrate 80

Placebo plus PRT

Plasma glucose and insulin did not change in either group.

Page | 99

Layman et al. 2005 (305)

n= 48 women aged ~47 years 2 d/week 30 min of stretching and PRT. PRT program, 7 exercises, minimum one 12-rep set on each machine with weight set to fatigue by final rep. Plus 5 days/week 30 min walking for 16-weeks.

~0.8-0.9

Dose: 1.6 g/kg/day (30% energy)

∆ Protein Intake: ~30 g/day in both higher

protein groups Type: Greater intake of

high protein food sources (meat, eggs, dairy and

nuts)

Lower protein diet of 0.8

g/kg/day with exercise or

lower protein only or higher protein with no

PRT.

Insulin fell by ~50 pmol/L in both exercising groups (higher and lower protein) compared to baseline with no differences between the groups.

Meckling et al. 2007 (519)

n= 60 women aged 43 years performed 3 days/week of PRT (within a circuit training program), 80% max heart rate for 12-weeks.

~0.8

Protein intake: 1g:1g of protein:carbohydrate.

∆ Protein Intake: 15g in higher protein only and

50g/day in higher protein plus PRT

Type: Greater intake of high protein food sources

(meat, eggs, dairy and nuts)

Higher protein alone or control diet plus PRT or control diet only. Control diet protein: carbohydrate ratio 1g:3g.

* All participants

randomised to

No within group changes or between group differences observed in fasting plasma glucose or insulin.

Page | 100

hypocaloric (-500 calories)

Iglay et al. 2007 (521 )

n=36 adults aged ~61 years performed PRT 3 days/week 3 sets 8 reps 80% 1-RM for 12-weeks.

~1.0

Dose: 1.2 g/kg/day higher protein diet.

∆ Protein Intake: ~6 g or 0.1 g/kg/day

Type: Higher intake of egg and dairy proteins

0.9 g/kg/day lower protein diet plus PRT.

Insulin AUC reduced in the control group but did not change in the higher protein group (group by time interaction P<0.05). No changes or between group differences observed for FPG, glucose AUC, HOMA or HbA1c.

Leenders et al. 2013 (284)

n= 60 adults mean age ~70 years. PRT 3 days/week, 3–4 sets, 8–15 reps, 75–80 % 1-RM for 24-weeks.

~1.1

Dose: 15 g/day ∆ Protein Intake: 0.18-

0.24 g/kg/day Type: Milk protein

concentrate 80

Lactose and calcium drink

No change in fasting glucose or insulin, HbA1c, HOMA-IR.

Arciero et al. 2014 (520)

n= 51 adults mean age ~50 years. PRT performed 4 days/week, 2-3 sets 7-9 reps 80% 1-RM for 16-weeks. Multi-modal exercise: 4 days/week PRT+aerobic and functional training,

~1.0-1.1

Dose: All whey protein was consumed 20 g 3

times/day (upon waking, mid-afternoon/following

exercise and within 2 hours of bed)

∆ Protein Intake: 25-35 g/day for all groups

Whey protein alone or whey protein plus multi-modal

exercise.

No change from baseline in fasting glucose or insulin or HOMA-IR and no difference between the groups.

Page | 101

yoga/pilates and stretching exercises.

Type: Whey protein (no further details provided)

Weinheimer et al. 2012 (285)

n=220 adults aged 48 ± 7.9 years performed PRT 2 days/week, 3 sets of 8-10 reps ~80% 1-RM plus 1 day per week a 60-minute aerobic training, ~70% maximum heart rate for 36-weeks.

Range 0.97-1.12

Dose: 10, 20 or 30 g whey protein

∆ Protein Intake: 0.16-0.72 g/kg/day

Timing: Breakfast and lunch

Type: Whey protein concentrate 80

Placebo beverage

Insulin AUC fell by 2.6 ± 32%, P =0.01 when all participants were pooled. No between group interactions observed. Fasting glucose, glucose AUC and HOMA-IR no change.

Data is presented as mean ± SD. NS, Not stated; PRT, Progressive resistance training; 1-RM, one repetition maximum; AUC, area under the curve.

Chapter 2

Page | 102

2.11.4 Effects of Exercise, Protein and Vitamin D on Cardiovascular Health

The interactive effect of PRT with high protein diets or protein supplementation on

cardiovascular health outcomes in older adults with T2DM has not been thoroughly

examined. In the only intervention trial conducted to date in older adults with T2DM

by Wycherley and colleagues which has been discussed extensively above in section

2.11.1 page 78, they found increased dietary protein alone and in combination with

PRT was associated with significant improvements in blood pressure, lipids and hs-

CRP, but there were no between group differences for any of these outcomes (286).

This may be explained by the fact that participants in this intervention did not present

with elevated levels of lipids, cholesterol or blood pressure (286). Indeed, more

favourable changes in serum lipid and cholesterol levels in response to greater

protein intake or increased protein intake plus PRT in those with adverse levels at

baseline have been found in other studies (522, 523). Secondly, although participants

in the high protein diet groups (with or without PRT) were reported to be consuming

approximately 118 g/day or 1.3 g/kg of protein during the intervention the baseline

protein intake was not reported and thus the change in protein intake may not have

not been sufficiently large enough (286). As previously discussed, the change in

protein intake from baseline is an important factor which could explain why no effect

was observed as another study found raising protein intake (via the prescription of a

high protein diet) by 50 g/day for 10-weeks from 0.9 g/kg to 1.6 g/kg resulted in

significant improvements in total cholesterol (5.80 ± 0.16 to 5.38 ± 0.21 mmol/L,

P<0.05), LDL (3.81 ± 0.17 to 3.45 ± 0.19 mmol/L, P<0.05) and triacylglycerol levels

(1.31 ± 0.21 to 0.98 ± 0.16 mmol/L, P<0.05) compared to baseline (305). These

improvements were likely due to the significant reductions in total fat and saturated

fat that were observed to occur in those receiving protein supplements with or

without PRT, suggesting that the increased intake of protein was associated with

displacement of fat intake in the habitual diet of these participants (305).

Studies using a protein supplement (as opposed to a high protein diet) in combination

with PRT in middle-aged and older adults have observed mixed effects on

cardiovascular risk factors. In a 24-week RCT, 60 healthy elderly men and women

(mean age ± SEM, 70 ± 1 year) were randomly assigned to a PRT program combined

Chapter 2

Page | 103

with 15 g/day of milk protein concentrate or placebo (284). Triglyceride levels were

within normal ranges at baseline (<1.7 mmol/L) and did not change during the

intervention in any group (284). In contrast, total and LDL cholesterol levels were

elevated (<5.2 and <2.6 mmol/L, respectively) at baseline in all participants and by

12-weeks both placebo plus PRT and protein plus PRT groups experienced similar

significant reductions in total cholesterol [(range 0.13 to 0.26 mmol/L, P<0.001)] and

reductions in LDL cholesterol by 12-weeks (range, 0.16 to 0.32 mmol/L, P<0.001)

and 24-weeks (range 0.7 to 0.16 mmol/L P<0.05)] (284). Significant (~6 mmHg)

reductions in SBP and DBP were also observed with no differences between the

groups (284). The findings from this study indicate that PRT was effective at

lowering cholesterol, lipid and blood pressure levels, but the additional milk based

protein did not provide any enhanced benefits (284). Several other studies using PRT

or exercise in combination with protein supplementation have observed mostly a null

effect on blood pressure, lipids or cholesterol and markers of inflammation in

comparison to placebo (285, 393, 524). For example, the findings from a study in 26

older (mean age ± SD, 65 ± 5 years) overweight, sarcopenic men who were

randomised to 4-months of PRT (three times per week, 80% 1-RM) with post

exercise consumption of a either a dairy based protein supplement (13.5 g protein

and 3.5 g of leucine), soy based protein supplement (12 g of protein and 3.5 g of

leucine) or a placebo product (0.6 g of protein) found no within group changes (in

any groups) or between-groups differences in triglycerides, LDL and HDL

cholesterol or inflammatory markers (TNF-α, IL-6 or hs-CRP) (524). This was

despite above 90% compliance with the supplements in each of the groups. There

were no marked changes in weight or fat mass which has been associated with

improvements in triglycerides and cholesterol levels along with blood pressure and

likely explains the null findings.

Further research is still required to ascertain if increased dietary protein/protein

supplements can enhance the cardiovascular benefits of PRT in older adults and/or

those with T2DM. Given the studies conducted to date have prescribed relatively low

doses of protein that have resulted in only modest increases in dietary protein along

with the discrepancies in trial designs and population groups studied, there is a clear

Chapter 2

Page | 104

need for further large scale RCTs investigating the cardiovascular health benefits of

PRT combined increased protein/protein supplements in older adults with T2DM.

The effects of combining PRT (and aerobic exercise) with vitamin D (and protein

supplements) on cardiovascular risk factors may provide a greater beneficial effect

than either alone. However, the available evidence in this area is limited with only

one study conducted in older women with T2DM assessing cardiovascular risk

factors as discussed extensively in section 2.11.1 (502). In comparison to controls,

women allocated to the PRT and vitamin D supplemented group experienced

significantly greater reductions in serum triglyceride (-17.2 vs 20.3%, P<0.05), total

cholesterol (-12.5 vs 3.5%, P<0.001) and LDL cholesterol levels (-9.7 vs 6.4%,

P<0.001) whilst improving HDL cholesterol levels (8.5 vs -16.5%, P<0.001) (502).

Significant improvements in these same parameters were not observed in those

receiving only the vitamin D supplements (502). Whilst only small in sample size

and failing to report important information, including baseline and follow-up serum

25(OH)D levels, this study demonstrated the combination of PRT plus vitamin D

supplementation may have a positive effect on cardiovascular health outcomes not

seen with vitamin D treatment alone. It is possible these benefits were due largely to

the PRT program as opposed to the additive effect of vitamin D supplements. PRT

alone only significantly improved total cholesterol (-7.4%), LDL (-8.7%) and HDL

(6.7%) cholesterol levels, but not triglycerides (502). These improvements were also

of a lower magnitude than the PRT and vitamin D group (Figure 2.9).

Chapter 2

Page | 105

Figure 2.9: Absolute percentage change in total cholesterol, HDL cholesterol, LDL cholesterol and triglycerides following a 12-week intervention of multi-modal exercise, multi-modal exercise plus 1,200 IU/day of vitamin D, 1,200 IU/day of vitamin D alone or control. Taken from Kim et al. (502). *P<0.05 †P<0.01 significantly different from baseline. Values without a common letter are significantly different.

Excess adiposity has a negative effect on blood pressure, inflammation and other

cardiovascular health risk factors, including serum lipid and cholesterol levels (525).

Conversely, reductions in fat mass resulting from participation in exercise can

improve these outcomes (526). All participants in the previous study by Kim et al.

(502) performing the PRT and aerobic training, irrespective of receiving vitamin D

or a placebo, experienced similar significant reductions in total abdominal fat area

compared to baseline. It is thus possible that the improvements in serum lipids and

cholesterol levels observed in this study were influenced by the reductions in fat

mass resulting from the exercise program as opposed to the combined effect of

exercise and vitamin D. The limited evidence in this area makes conclusions about

the effects of exercise/PRT and vitamin D on serum lipid and cholesterol levels

difficult and thus it is evident that further studies prescribing a range of vitamin D

doses to participants with varying baseline serum 25(OH)D status with or without

PRT remain warranted due to the limited evidence available, some confounding in

Chapter 2

Page | 106

the available evidence and limited reporting in the studies conducted (i.e. baseline

serum 25(OH)D status and final serum level) to decisively establish if greater

improvements in lipid, cholesterol, blood pressure and/or inflammation can occur

from the combined effects of PRT and vitamin D.

In recent years, there has been some interest into whether multi-nutrient supplements

such as protein and vitamin D combined with PRT can improve various health

outcomes of older adults. However, few studies have included cardiovascular health

measures in their trial design (42, 513, 527). In one of the only studies to include

such measures, Abizanda et al. (527) examined the effects of a multi-nutrient

supplement (2x200 ml bottles containing 500 IU of vitamin D, 20 g of protein and

480 mg of calcium/day) plus resistance, function and balance training (performed 5

days per week) on inflammation and cholesterol in 91 elderly adults (>70 years). No

changes were detected following the 12-week intervention on total cholesterol or hs-

CRP, which may have been due to factors such as participants presenting with

normal total cholesterol levels at baseline, the relatively low dose of vitamin D used

(possibly not altering serum 25(OH)D status), the short duration of the intervention

or that the training program/intensity was insufficient to illicit a change in

cardiovascular health outcomes in these frail older adults. A limitation of this trial

and the reporting of the results was that the source/type of protein used in the

supplement was not identified thus its quality is unknown, the baseline and change in

habitual protein intake was also not reported. Further, baseline serum 25(OH)D

status (or the magnitude of the change in 25(OH)D levels) was not reported

numerically although we were informed most of the participants were deficient in

vitamin D. One or a combination of these factors could have influenced the findings

of this trial. Additionally, this study was not a RCT so the results were not compared

to a control or exercise alone group. Another trial, provided a once daily nutritional

supplement containing 22 g of whey protein and 100 IU of vitamin D to frail older

(mean age 80.3 years) adults whilst participating in a supervised multi-modal

exercise program (20 minutes per session, 5 times per week, moderate-intensity of 12

to 14 on the Borg scale) for 12-weeks and reported a non-significant reduction in hs-

CRP [−0.19 mg/dL (95% CI, −0.57, 0.19) P=0.329] and a non-significant increase

[0.44 mg/dL (95% CI, −0.02, 0.90) P=0.06] in the control group (placebo plus

Chapter 2

Page | 107

exercise) such that there was a significant between-group difference (P=0.038) (513).

Unfortunately, other parameters such as triglyceride, cholesterol and blood pressure

levels were not assessed in this study.

Whilst only scarce, and far from compelling, there is some promising evidence of an

additive effect of PRT or multi-modal exercise, protein and vitamin D supplements

on improving some cardiovascular risk factors in older adults. Yet given the paucity

of this data, there is a pronounced need for trials to examine the additive effects of

protein and vitamin D supplements in addition to PRT to ascertain if this novel

combination provides a more pronounced effect on a combination of these risk

factors in older adults with T2DM. Should the combination of these strategies prove

to be beneficial for a range of cardiovascular outcomes, such a strategy could play a

significant role in reducing risk for CVD morbidity and mortality experienced by

many older adults with T2DM.

2.12 Summary

Skeletal muscle mass is of critical importance to those with T2DM as it is the largest

mass of insulin sensitive tissue and the primary site for glucose disposal. Losses in

muscle mass can negatively impact metabolic rate further compounding the problems

of insulin resistance and glycaemic control as well as exacerbate cardiovascular risk

factors. PRT is one of the few approaches that can simultaneously have beneficial

effects on almost all the above factors, but most trials to date have been conducted in

a tightly-controlled clinical exercise laboratory environments with little examination

of the ‘real-world’ effectiveness of such an exercise program. Nutritional

modification and/or caloric restriction are also recognised as primary elements in the

ongoing management of T2DM. Combining PRT with dietary modification may

offer an additive effect on glycaemic and insulinaemic outcomes, body composition

and cardiovascular risk factors compared to either strategy alone. Historically,

caloric restriction has been recommended to adults with T2DM with the goal to

reduce weight and fat mass, but such an approach has been associated with a loss in

skeletal muscle mass. However, few long-term trials have examined the effects of

PRT combined with calorie restriction on glycaemic control, muscle mass and

markers of systemic inflammatory in adults with T2DM.

Chapter 2

Page | 108

Over the past two decades, there has been a growing body of evidence indicating that

an increase in dietary protein, particularly rapidly digested proteins rich in leucine,

such as whey protein, can enhance the anabolic effects of PRT on muscle.

Favourable acute effects of whey protein alone on insulin and glucose have also been

observed in those with T2DM. However, no studies have examined the long-term

benefits of PRT combined with daily whey protein supplementation on lean mass,

size and strength, glycaemic control, insulin resistance or cardiovascular risk factors

in older adults with T2DM. Additionally, there is mounting evidence that vitamin D

supplementation may offer several skeletal and non-skeletal health benefits of

relevance to those with T2DM, including improvements in glucose tolerance and

insulin resistance. However, the findings from intervention trials to date have been

mixed with little consistency in the dose of vitamin D provided or the population

groups examined.

Given that the prevalence of T2DM is projected to reach ~ 584 million by the year

2040, there is an urgent need to develop evidence-based management programs for

older adults with T2DM that can simultaneously improve skeletal muscle mass,

glycaemic control and cardiovascular risk factors whilst being safe, practical and

widely accessible for people with this disease. Evaluating the efficacy of a lifestyle

approach that incorporates PRT in combination with a protein enriched supplement

and vitamin D has the potential to underpin more precise exercise and nutrition

guidelines for the management of glycaemic control, insulin sensitivity, body

composition and cardiovascular risk factors along with the ongoing refinement of

community-based initiatives for the management of this condition.

Page | 109

Chapter 3

Effects of Progressive Resistance Training and Weight Loss versus

Weight Loss alone on Inflammatory and Endothelial Biomarkers in

Older Adults with Type 2 Diabetes:

A 12-month Randomised Controlled Trial

Chapter 3

Page | 110

3.1 Declaration Statement

The findings from this chapter represent secondary analysis of a previous 12-month

RCT in which the primary aim was to investigate the effects of high-intensity

progressive resistance training with moderate weight loss compared to weight loss

alone on glycaemic control, body composition and blood lipids in older overweight

and obese adults with type 2 diabetes (T2DM). As a result, some findings presented

within this chapter have previously been published, however, these have been

appropriately cited. The aim of this study (and the analysis retrospectively performed

as part of my thesis)) is to investigate the effects of the 6-month supervised PRT plus

weight loss intervention compared to weight loss alone and the subsequent 6-month

home-based training on systemic and endothelial markers of inflammation, including

serum IL-6, TNF-α, ICAM-1, resistin, IL-10 and adiponectin in older overweight

adults with T2DM.

Chapter 3

Page | 111

3.2 Abstract

Circulating markers of inflammation and endothelial function are often increased in

people with type 2 diabetes mellitus (T2DM), and have been associated with

increased risk of cardiovascular disease and diabetes-related complications. Aerobic

exercise has been shown to improve these biomarkers in adults with T2DM, but

whether high-intensity progressive resistance training (PRT) with weight loss (WL)

is effective remains uncertain. In this 12-month randomised controlled trial (RCT)

we investigated the effects of PRT+WL versus WL alone on systemic and

endothelial markers of inflammation, including serum interleukin-10 (IL-10), IL-6,

tumour necrosis factor (TNF)-α, adiponectin, intercellular adhesion molecule-1

(ICAM-1) and resistin, in older overweight adults with T2DM. Sedentary,

overweight adults aged 60-80 years with poorly controlled T2DM were randomised

to 6-months of supervised PRT+WL (n=19) or a supervised stretching (sham)

program plus WL (n=17) followed by 6-months of home-training without dietary

modification. DXA was used to assess total body fat mass and lean mass. Fasted

blood samples were collected at baseline and subsequent 3-month intervals. Markers

of inflammation were measured using a Milliplex immunoassay assay kit. Exercise

compliance was similar between groups (phase 1, 86%; phase 2, 75%). Both groups

lost similar amounts of weight and fat mass (P<0.01) during the supervised training,

but PRT+WL had a net 0.9 kg gain in lean mass compared to WL (P<0.05) over the

initial 6-months. These results were not maintained during the home-based training

with similar significant increases in both groups for weight and fat mass (P range

<0.05-0.01) compared to the 6-month mark. There were no significant within-group

changes or between-group differences detected for any inflammatory or endothelial

biomarker following the 6-month supervised exercise and WL phase. There was a

greater reduction in IL-10 at 9-months in the PRT+WL relative to WL group

(P=0.033). There was also a greater reduction in TNF-α at 9- and 12-months in the

PRT+WL relative to WL group (P=0.026 and P=0.024, respectively). Serum

adiponectin increased in the PRT+WL relative to WL group after 12-months

(P=0.036). All results were adjusted for baseline values, age, weight, sex, diabetes

duration, medication use and any change in medication. In conclusion, the main

finding from this 12-month trial was that a 6-month moderate weight loss program

with and without high-intensity gymnasium-based PRT did not change any markers

Chapter 3

Page | 112

of systemic inflammation or endothelial function in older overweight adults with

T2DM during weight loss. However, a further 6-months of continued home-based

PRT independent of change in weight can result in some improvements in certain

inflammatory markers in older overweight adults with type 2 diabetes compared to

sham-exercise.

Chapter 3

Page | 113

3.3 Introduction

Type 2 diabetes is a common chronic disease that is currently estimated to affect 373

million people globally (528). Although type 2 diabetes is considered a multifactorial

disease caused by a combination of genetic and lifestyle-related factors, it has also

been associated with an increase in circulating levels of pro-inflammatory cytokines

including tumour necrosis factor-α (TNF-α), interleukin-6 (IL-6) and high sensitive

C-reactive protein (hs-CRP) with concomitant lower levels of anti-inflammatory

markers such as interleukin-10 (IL-10) and adiponectin (529, 530). Clinically these

changes in inflammatory cytokines are important as they have been associated with a

decrease in beta-cell insulin secretion and an increase in insulin resistance (19, 20),

along with the development and progression of various micro- and macro-vascular

complications (16, 531). Thus, there has been considerable interest in identifying

strategies that can improve the inflammatory profile of adults with type 2 diabetes.

It is widely recognised that adipose tissue is an endocrine organ that can secrete a

variety of inflammatory proteins (adipokines). As such, obesity has been associated

with subclinical systemic inflammation, which may explain in part its link to insulin

resistance and the development of T2DM (532, 533). To counter this increase in

chronic systemic inflammation, weight loss or dietary modification are often

recommended. In obese adults without diabetes and to a lesser extent people with

T2DM, there is some evidence that diet induced weight loss can positively affect

circulating pro-inflammatory cytokines and increase anti-inflammatory markers such

as adiponectin (17, 33, 534, 535), but the findings remain mixed likely related to the

magnitude of the weight loss (536, 537). Indeed, two studies have suggested the most

consistent improvements in inflammatory markers are observed with at least a 10%

reduction in weight (538, 539).

Exercise training has also been shown to have a role in lowering chronic low-grade

inflammation, particularly in people who are overweight or obese and/or have been

diagnosed with a chronic disease (15). In a meta-analysis that included 14 RCTs in

people with T2DM, Hayashino et al. (244) reported that exercise was associated with

a significant decrease in circulating levels of hs-CRP and IL-6, but not adiponectin or

resistin. It was also observed the greatest benefits were apparent following aerobic

training, but only three resistance training trials were included and all were short-

Chapter 3

Page | 114

term (12- to 16-weeks). A recent 12-month intervention in older adults with T2DM

found that progressive resistance training (PRT) alone was associated with a

significant reduction in hs-CRP levels compared to sham exercise (238).

Interestingly, the exercise-induced improvements in hs-CRP in this study were found

to be mediated by both a reduction in fat mass and an improvement muscle mass

(238). This suggests that the greatest benefits on inflammation may be achieved with

fat loss combined with muscle gain. Recently, a limited number of studies in

overweight and obese adults and those with T2DM have reported that exercise,

primarily aerobic training, combined with weight loss arising from caloric restriction,

is more effective at improving various inflammatory markers than either exercise or

caloric restriction alone (31, 33, 34, 523, 540). However, the effects of PRT

combined with weight loss on circulating inflammatory markers has not been

examined in adults with type 2 diabetes.

This study is a secondary analysis using archived blood samples and existing data

from a 12-month RCT that was originally designed to examine the effects of PRT

plus weight loss on glycaemic control and body composition compared to weight

loss alone in older adults diagnosed with T2DM (12, 14). As previously reported, 6-

months of high-intensity PRT performed within a controlled and supervised research

setting (gymnasium) in combination with weight loss was found to be effective for

improving glycated haemoglobin (HbA1c), total body lean mass and muscle strength

compared to weight loss alone in older adults with poorly controlled T2DM; both

groups lost a similar amount of weight and fat mass. In addition, following a further

6-months of home-based training with no further recommendations for weight loss,

PRT performed at home was effective for maintaining the benefits on muscle mass

and strength, but both groups experienced similar significant increases in weight, fat

mass and HbA1c although overall body weight remained significantly lower than

baseline levels in both groups (14). Building on these findings, the aim of this study

is to investigate the effects of the 6-month supervised PRT plus weight loss

intervention compared to weight loss alone and the subsequent 6-month home-based

training on systemic and endothelial markers of inflammation, including serum IL-6,

TNF-α, ICAM-1, resistin, IL-10 and adiponectin in older overweight adults with

T2DM. It was hypothesised that PRT combined with weight loss would lead to

Chapter 3

Page | 115

greater improvements in various inflammatory and endothelial markers than weight

loss alone in older adults with T2DM.

3.4 Methods

3.4.1 Participants

As previously described (12, 14), men and women aged between 60-80 years, with

treated (diet and/or oral hypoglycaemic medications) T2DM, were recruited from the

International Diabetes Institute clinics and a local media campaign. Detailed

information on the recruitment methods and screening procedures have been

previously published (12, 14). Participants were eligible for the study if they were:

(1) overweight or obese (BMI>27 kg/m2 and ≤40 kg/m2); (2) not engaged in regular

PRT and undertaking less than 150-minutes of brisk walking or moderate exercise

per week or undertaking > 60-minutes of vigorous exercise per week in the preceding

6-months; (3) had established but not optimally controlled T2DM (HbA1c range 7-

10%); (4) were not prescribed insulin and were non-smokers. Any prescribed anti-

diabetic and anti-hypertensive medications were continued during the study period.

3.4.2 Study Design

This study was a two arm, 12-month RCT that was separated into two distinct phases

as previously reported and discussed in greater detail below (12, 14). Phase 1

consisted of 6-months of supervised and structured gymnasium-based training (PRT

or sham exercise) with moderate weight loss (WL). Phase 2 consisted of a further 6-

months of home-based PRT or sham-exercise training without specific dietary

advice. Participants were randomised to one of the two groups by an independent

staff member not involved in the study using a computer generated random numbers

table (Microsoft Excel, Office 97). As shown in Figure 3.1, of the 36 participants

initially randomised to either PRT+WL (n=19) or WL (n=17), 20 had a history of

hypertension, three had a history of neuropathy, one had a history of retinopathy, and

seven reported a history of arthritis. During phase 1, two participants from the

PRT+WL group and four participants from the WL group withdrew from the study

during the first 8-weeks. The reasons for withdrawal included health problems not

related to the intervention (n=2) or other commitments that precluded ongoing

Chapter 3

Page | 116

participation (n=4). One participant from the PRT+WL group was placed on insulin

treatment within the first 6-weeks of the trial and was not included in any analysis.

Thus, 29 participants [16 PRT+ WL (84%) and 13 WL (76%)] successfully

completed phase 1 of the intervention (12, 14). During the home-based training, a

further three participants withdrew from the study (PRT+WL, n=2; WL, n=1). All

withdrawals occurred within the first 2-weeks of the home-based training. Reasons

for withdrawals included overseas travel, continued pain associated with

osteoarthritis of the knee and personal problems unrelated to the study. Thus, 72% of

the participants [PRT+WL, n=14 (74%); WL, n=12 (71%)] completed the 12-month

intervention. Outcome assessments for all participants were performed by the same

research staff, but not all staff were blinded to the group allocation.

Chapter 3

Page | 117

Figure 3.1: CONSORT flow diagram of participants through the trial.

Progressive resistance training plus weight loss (PRT+WL); weight loss (WL).

3.4.3 Ethics

The study was approved by the International Diabetes Institute and Deakin

University Human Research Ethics Committees. Written informed consent was

obtained from all participants prior to their participation in the research program.

3.4.4 Intervention

This study was a 12-month RCT with measurements performed at baseline and

subsequent 3-month intervals. As reported above, the intervention was divided into

two distinct phases (supervised gymnasium based and home-based) which are

described in detail below.

Chapter 3

Page | 118

Phase 1: Supervised gymnasium-based training plus weight loss program

Participants were randomly assigned to either PRT+WL (n=19) or a moderate weight

loss group plus ‘sham’ exercise program (flexibility exercise) (WL, n=17). All

training was conducted within a controlled exercise laboratory and participants were

asked to train on three non-consecutive days per week. Those in the PRT+WL group

performed a 5-minute warm up and 5-minute cool-down period of low-intensity

stationary cycling and approximately 45-minutes of high-intensity PRT (dynamic

exercise involving concentric and eccentric contractions). During the first and second

weeks of training, the resistance was set at 50-60% of an individual’s 1-repetition

maximum (RM). The 1-RM was defined as the maximum amount of resistance that

could be moved through the full range of motion of an exercise for no more than one

repetition. Thereafter, the goal for each training session was to lift a weight

consistently between 75 and 85% of 1-RM. Participants followed an individually

supervised PRT program using free weights and a multiple station weight machine.

Nine exercises were used for training which included bench press, leg extension,

upright row, lateral pull-down, standing leg curl (ankle weights), dumbbell seated

shoulder press, dumbbell seated bicep curl, dumbbell triceps kickback and abdominal

curls. All participants were instructed to perform each repetition in a slow, controlled

manner, with a rest of 90- to 120-seconds between sets. Three sets of 8 to 10

repetitions were performed for all exercises with the exception of abdominal curls at

each training session. All sessions were supervised to ensure correct technique and to

monitor the appropriate amount of exercise and rest intervals. The training work load

was increased regularly as tolerated for each muscle group after participants had

successfully achieved three sets of 10 repetitions with appropriate technique. Every

12-weeks the 1-RM testing was repeated to establish a new baseline to maintain

training intensity between 75-85% of 1-RM. Exercise compliance was computed

from the exercise cards completed by the participants at each gym visit and checked

by the research staff after each session. During the supervised gymnasium-based

training phase compliance with the exercise program was 88% and 85% for the PRT

+ WL and WL groups respectively.

The ‘sham’ exercise program with WL was designed to only provide participative

involvement but not elicit change in muscle strength, mass or cardiovascular fitness.

Chapter 3

Page | 119

Each session involved stationary cycling with no workload for 5-minutes, followed

by a series of static stretching exercises for approximately 30-minutes. Participants

were not blinded to the treatments and were informed that improved flexibility was

an expected outcome of the study.

Weight loss/Healthy eating plan

A healthy eating program was implemented under the supervision of a qualified

dietitian four weeks prior to the commencement of phase 1. All participants were

placed on a healthy eating plan supplying 30% or less of the total energy intake from

fat (<10% from saturated fat), with the remainder distributed between carbohydrates

and protein (12, 14). The healthy eating component of the study was designed to

elicit a moderate weight loss of approximately 0.25 to 0.50 kg per week over the

course of phase 1. All eating plans were individually prescribed by a dietitian

calculated by utilising two separate 3-day food records performed during the initial

4-week baseline period. The macronutrient breakdown of the diets was as follows:

carbohydrate 55-60%, protein at least 0.8 g/kg, fat < 30%, cholesterol < 300 mg/day

and fibre 40 g/day. Compliance with the healthy eating program was assessed via

dietitian lead interviews every 2-weeks thereafter and by completion of a weekly

food checklist. A 3-day food record was obtained at all subsequent assessments in

order to evaluate changes in nutrient intake. Nutritional information obtained from

food records was analysed by a dietitian using nutrient analysis software (Foodworks

V2.10, Xyris Software, Queensland, Australia).

Phase 2: Home-based Training

At the completion of the gymnasium-based training, all participants were provided

with individualised instructions and equipment (dumbbells/ankle weights or a

flexibility wall chart) to continue the training at home or a commercial/community

facility 3-days per week. No participants in the PRT+WL group continued their

training programs within commercial or community facilities during this phase. To

accommodate the transition from supervised gymnasium-based to home-based

training, participants in the PRT+WL group completed their home-based exercise

programs within the supervised gymnasium-based training phase for the final 4-

weeks of phase 1. The home-based exercises were similar to those used in the

Chapter 3

Page | 120

gymnasium-based program, with the exception that dumbbells and ankle weights

replaced the exercises performed on the multi-station weight machines. As reported

previously in (14), the dumbbells provided for the home-based training provided

capacity for workloads between 2.5 and 30 kg, and the ankle weights provided

workloads between 0.5 and 20 kg. Additional weights were provided periodically to

facilitate progression. The nine-home-based exercises included lying dumbbell flies,

seated single leg-extension (ankle weighted), dumbbell shoulder press, dumbbell

bent-over row, standing leg curl (ankle weights), dumbbell upright row, dumbbell

triceps kickback and abdominal curls. Participants were also provided with detailed

instruction booklets containing detailed descriptions on each resistance training

exercise and how to safely perform these exercises, and were asked to follow an

individually prescribed training program (3 sets of 8-10 repetitions) with the goal to

exercise at an intensity corresponding to approximately 60-80% of the current 1-RM.

However, it was estimated previously (14) that the volume of training reduced by

~52% from the gymnasium-based program to the home-based program largely

explained by the reduction in the amount of weight lifted. During the home-based

training program, it was impossible to retain the absolute workload of the gym-based

program as various exercises performed using machine weights had a total workload

capacity much larger than that provided or available from hand or leg weights.

During the first week of the home-based training, home visits were conducted to

ensure the training environment was appropriate and safe. Participants were

telephoned weekly for the first 4-weeks and every fortnight thereafter to monitor

compliance, answer any questions and provide program feedback. In addition,

participants recorded their training in training diaries each week and were asked to

attend the gymnasium monthly to perform the home-based training program so that

technique and progression could be monitored. During phase 2, participants were not

required to follow a healthy eating plan, the monitoring and compliance with

dietitians was ceased and participants were free to consume food ad-libitum.

The sham exercise group was provided with a stretching wall chart and was asked to

continue with the stretching program at home. Participants were telephoned weekly

for the first 4-weeks and every 2-weeks thereafter to monitor compliance, answer

questions and provide individualised feedback. All participants also completed

Chapter 3

Page | 121

weekly training diaries and were required to attend Deakin University monthly to

perform the home-based training so that technique and progression could be

monitored. During the home-based training phase, exercise compliance was similarly

reported at 73% and 78% in the PRT + WL and WL groups respectively.

3.4.5 Measurements

Detailed information about the methodology related to the key outcomes, including

glycated haemoglobin, fasting plasma glucose (FPG), fasting insulin, insulin

sensitivity, body composition and muscle strength, as well as height, weight, habitual

physical activity and medication use, have previously been reported (12, 14).

3.4.5.1 Cytokine and Endothelial Inflammatory Markers Measurements

In order to measure cytokine and endothelial markers of inflammation morning blood

samples were obtained from each participant following an overnight fast at baseline,

3-, 6-, 9- and 12-months. All samples were collected at least 48-hours post-exercise.

Of the 29 participants at baseline, two participants had insufficient serum available

for analysis at baseline and 3-months with a further seven at 6-months. During the

home-based training, five participants at 9-months and six participants at 12-months

had insufficient serum available for analysis. The following parameters were

measured by Cardinal Bio-research Pty Ltd (Australia) approximately 10-years after

the trial was completed with the serum samples stored at -80º C during this time.

Serum concentrations of IL-6, IL-10 and TNF-ɑ were measured in duplicate using a

Millipore high sensitive cytokine immunoassay assay kit (Millipore Corp, Billerica,

Massachusetts, USA) as per the manufacturer’s instructions. The mean intra and

inter-assay CVs for IL-6, IL-10 and TNF-ɑ were <12%. The mean intra and inter-

assay CVs for adiponectin, ICAM-1 and resistin were <8%. Adiponectin, ICAM-1

and resistin were assayed using an in-house multiplex immunoassay. Reagents were

prepared as per previously described (541). Capture and detection antibodies were

obtained from R&D Systems (Minneapolis, MN USA). The mean intra- and inter-

assay CV was <8%. Samples with results below the lowest detectable limits of the

assay were allocated the minimum detectable concentration: IL-6 = 0.1 pg/mL; IL-10

Chapter 3

Page | 122

= 0.1 pg/mL; TNF-ɑ = 0.8 pg/mL; adiponectin = 0.01 µg/mL; ICAM-1 = 0.3 ng/mL

and resistin = 0.05 ng/mL.

3.4.6 Statistical Analysis

Statistical analysis was conducted using Stata statistical software release 14 (College

Station, TX: StataCorp LP.). All data was checked for normality and the cytokines

IL-10, IL-6 and TNF-α, and the endothelial marker ICAM-1 were log-transformed

prior to analysis to improve normality. The data was analysed on a modified

intention-to-treat basis, including all randomly assigned participants with at least one

follow-up observation. Linear mixed models with random intercepts were fitted for

each outcome including fixed effects for time, group, and an interaction between

group and time. The models were adjusted for baseline values (model 1) and

baseline, age, weight, sex, diabetes duration, medication use and any change in

medication during the intervention (model 2). Between-group differences were

calculated by subtracting within-group changes from baseline for the PRT+WL

group from within-group changes for the WL group after 3-, 6-, 9- and 12-months.

Results from all models are reported as marginal means with 95% confidence

intervals, back-transformed for any log transformed variables. No data imputation

was used for missing data as one of the strengths of the linear mixed model is that it

can handle missing data points without excluding participants. The percentage of

change in results Figures 3.1 and 3.2 represents the absolute difference from baseline

in the log transformed data multiplied by 100. P<0.05 was used to determine

statistical significance. Data presented as mean ± SD unless otherwise specified.

3.5 Results

Baseline characteristics for the 29 participants included in the 12-month intervention

have previously been reported and are shown in Table 3.1 (12, 14). There were no

group differences in age, weight, BMI, diabetes duration, use of oral hypoglycaemic

medication, energy intake or physical activity. Similarly, the groups were well

matched for total body fat and lean mass (Table 3.1).

Chapter 3

Page | 123

Table 3.1 Baseline descriptive characteristics of the PRT+WL and WL group. Reported previously in (12).

PRT + WL WL

n 16 13

Age (years) 67.6 ± 5.2 66.9 ± 5.3

Sex (M/F) 10/6 6/7

Duration of diabetes (years) 7.6 ± 5.4 8.8 ± 7.9

Oral hypoglycaemic medication use (n) 15 10

Weight (kg) 88.7 ± 10.9 89.5 ± 12.1

Total body lean mass (kg) 33.1 ± 7.4 35.6 ± 6.8

Total body fat mass (kg) 51.8 ± 8.1 49.7 ± 9.5

BMI (kg/m2) 31.5 ± 3.4 32.5 ± 3.8

HbA1c (%) 8.1 ± 1.0 7.5 ± 1.1

Total energy intake (kcal/day) 1,783 ± 349 1,815 ± 431

Estimated energy expenditure (kcal/day)1 3,022 ± 413 3,109 ± 428

Values represent mean ± SD or number. 1 Calculated from 7-day recall.

As already stated, the primary outcomes of the original trial have previously been

published (12, 14). A brief summary of these published results is provided below for

the reviewer’s benefit. Following the 6-month supervised training program, both the

PRT+WL and WL groups experienced a similar significant reduction in weight

(mean change ± SD; PRT+WL -2.5 ± 2.9 kg; WL -3.1 ± 2.1 kg) and total body fat

mass (PRT+WL -2.4 ± 2.7 kg; WL -2.7 ± 2.5 kg) (12). In contrast, there was a net

benefit of 0.9 kg (95% CI, 0.05–1.8) in total body lean mass to the PRT+WL group

(group-by-time interaction, P<0.05). This was due to an increase in lean mass in the

PRT+WL group (mean change, 0.5 kg (0.3, 0.7)) and decreased in the WL group

(mean change, -0.4.kg (-0.7, -0.1)) (12). The PRT+WL program was also associated

with a significant reduction in HbA1c [mean absolute change; -1.2% (95% CI, -1.7, -

0.7)] following supervised training relative to the WL group [-0.4% (95% CI, -0.9,

0.1)] (group-by-time interaction, P<0.05) (12). As expected, the PRT+WL group

experienced a significantly greater increase in both upper and lower body strength

throughout the supervised training intervention compared to the WL group

(interaction terms P<0.01) (12). Following home-based training, both groups

Chapter 3

Page | 124

experienced similar significant increases in body weight compared to the end of the

supervised-training [mean change (kg): PRT+WL, 1.4 kg (95% CI, 0.5, 2.3), WL,

1.5 kg (95% CI, 0.4, 2.6)] and fat mass [PRT+WL, 1.8 kg (95% CI, 0.7, 2.7); WL,

2.0 kg (95% CI, 0.8, 3.0)]. However, weight remained significantly lower than

baseline in both groups (14). Lean mass did not change significantly in either group

during the home-based training (6- to 12-months), but a significant 0.6 kg (95% CI, -

0.9, -0.4) reduction was observed in the WL group from baseline to 12-months

(P<0.05). HbA1c levels increased significantly in both groups during the home-based

training (both P<0.05), and the net benefit observed in the PRT+WL after the

supervised training was not maintained following the 6-month home-based training.

However, the improvements in upper and lower-body strength observed following

supervised training in the PRT+WL group were maintained at the completion of the

home-based training (14).

3.5.1 Changes in Inflammatory Cytokines

The baseline values and the percentage change from baseline in serum IL-10, IL-6

and TNF-α for both groups across the supervised and home-based training are

presented Table 3.2 and Figure 3.2. At baseline, serum IL-6 was higher in the

PRT+WL compared WL group at baseline (P=0.05).

Overall, there were no within-group changes or between-group differences for the

change over time in serum IL-6, TNF-α or IL-10 after 3-, 6-, 9- or 12-months, with

the exception of the following: 1) there was a significant decrease relative to baseline

in TNF-α in the PRT+WL group at both 9-months [mean change, -1.26 pg/ml (95%

CI, -2.37, -0.15); P=0.026] and 12-months [2.09 pg/ml (95% CI, -3.13, -1.06);

P=0.001], which resulted in a significant difference for the change over time relative

to the WL group [mean difference: 9-months, 2.37 pg/ml (95% CI, -4.37, -0.37);

P=0.020; 12-months, 2.22 pg/ml (95% CI, -4.06, -0.38); P=0.018)] which remained

unchanged after adjustment for age, sex, weight, duration of diabetes, use of oral

hypoglycaemic medication and any change in medication 2) there was a meaningful

between-group difference for the change in IL-10 after 9-months [mean difference, -

2.20 pg/ml (95% CI, -5.12, -0.71); P=0.138], which became significant after

adjusting for confounders (P=0.033) including age, sex, weight, duration of diabetes,

Chapter 3

Page | 125

use of oral hypoglycaemic medication and any change in medication. This was

driven by a non-significant reduction in the PRT+WL group [mean change, 0.94

pg/ml (95% CI, -2.23, 0.34); P=0.150] and non-significant increase in the WL group

[1.26 pg/ml (95% CI, -1.32, 3.84); P=0.337].

Page | 126

Table 3.2 Mean baseline values and the percentage change relative to baseline for serum IL-10, IL-6 and TNF-α for the PRT+WL and WL groups after 3-, 6-, 9- and 12-months.

Baseline Values and Within Group Changes

PRT+WL WL Intervention Effects

Mean ± SD or (95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference (95% CI)

P- values Model 1 | Model 2

IL-10

Baseline (pg/ml) 14.12 ± 19.17 ‡ 4.20 ± 5.67

∆ 3-month -0.80 (-2.10, 0.50) 0.227 -0.60 (-2.06, 0.87) 0.424 -0.20 (-2.20, 1.79) 0.840 | 0.524

∆ 6-month -0.89 (-2.18, 0.40) 0.172 0.54 (-1.63, 2.70) 0.628 -1.43(-3.98, 1.12) 0.272 | 0.081

∆ 9-month -0.94 (-2.23, 0.34) 0.150 1.26 (-1.32, 3.84) 0.337 -2.20 (-5.12, 0.71) 0.138 | 0.033

∆ 12-month 0.13 (-1.82, 2.09) 0.894 -0.12 (-1.98, 1.74) 0.896 0.25 (-2.47, 2.99) 0.854 | 0.651

IL-6

Baseline (pg/ml) 3.65 ± 3.06 ‡ 1.61 ± 1.78

∆ 3-month -0.41 (-0.94, 0.12) 0.126 0.24 (-0.58, 1.05) 0.571 -0.65 (-1.67, 0.37) 0.213 | 0.750

∆ 6-month -0.17 (-0.80, 0.47) 0.605 0.33 (-0.57, 1.22) 0.472 -0.50 (-1.64, 0.65) 0.395 | 0.885

∆ 9-month -0.48 (-1.02, 0.06) 0.084 0.99 (-0.19, 2.18) 0.101 -1.47 (-2.83, -0.12) 0.033 | 0.127

∆ 12-month -0.07 (-0.80, 0.66) 0.853 0.79 (-0.33, 1.91) 0.168 -0.86 (-2.25, 0.53) 0.227 | 0.624

Page | 127

TNF-α

Baseline (pg/ml) 8.23 ± 3.64 7.10 ± 5.02

∆ 3-month -0.30 (-1.50, 0.91) 0.629 -0.04 (-1.37, 1.28) 0.947 -0.26 (-2.05, 1.55) 0.784 | 0.820

∆ 6-month 0.14 (-1.19, 1.47) 0.834 0.84 (-0.75, 2.43) 0.299 -0.70 (-2.78, 1.38) 0.508 | 0.552

∆ 9-month -1.26 (-2.37, -0.15) 0.026 1.11 (-0.54, 2.77) 0.188 -2.37 (-4.37, -0.37) 0.020 | 0.026

∆ 12-month -2.09 (-3.13, -1.06) 0.001 0.13 (-1.39, 1.64) 0.871 -2.22 (-4.06, -0.38) 0.018 | 0.024

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from model 1 – adjusting for baseline values. Significant differences are highlighted in bold. a P<0.05 vs WL at baseline. Model 1 represents the P-values after adjusting for baseline values. Model 2 represents the P-value after adjusting for baseline values, age, weight, sex, diabetes duration, medication use and any change in medication.

Chapter 3

Page | 128

3.5.2 Change in Adiponectin

At baseline adiponectin was lower in the PRT+WL compared WL group (P=0.004).

Adiponectin levels remained unchanged in the both the PRT+WL and WL group

across the supervised-gymnasium-based training program (Table 3.3 and Figure 3.2).

During the home-based phase, levels of adiponectin in the PRT+WL group increased

by an average of 0.49 µg/ml [(95% CI, 0.03, 0.96); P=0.036] relative to baseline after

12-months, such that there was a significant group-by-time interaction when

adjusting for potential confounders (Model 2, P=0.036).

Page | 129

Table 3.3 Mean baseline values and the percentage change from baseline for serum adiponectin in the PRT+WL and WL groups after 3, 6, 9 and 12-months.

Baseline Values and Within Group Changes

PRT+WL WL Intervention Effects

Mean ± SD or

(95% CI) P-value

Mean ± SD or

(95% CI) P-value

Net Difference

(95% CI)

P- values

Model 1 | Model 2

Adiponectin

Baseline (µg/ml) 1.68 ± 0.66 ‡ 2.67 ± 0.95

∆ 3-month 0.08 (-0.32, 0.48) 0.700 0.27 (-0.15, 0.70) 0.206 -0.19 (-0.80, 0.42) 0.534 | 0.722

∆ 6-month 0.23 (-0.19, 0.64) 0.278 0.25 (-0.21, 0.70) 0.287 -0.02 (-0.66, 0.62) 0.958 | 0.813

∆ 9-month 0.47 (0.03, 0.90) 0.034 0.49 (0.05, 0.94) 0.030 -0.02 (-0.67, 0.61) 0.933 | 0.789

∆ 12-month 0.49 (0.03, 0.96) 0.036 -0.10 (-0.57, 0.36) 0.661 0.59 (-0.07, 1.27) 0.081 | 0.036

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from model 1 – adjusting for baseline values. Significant differences are highlighted in bold. a P<0.05 vs WL at baseline. Model 1 represents the P-values after adjusting for baseline values. Model 2 represents the P-value after adjusting for baseline values, age, weight, sex, diabetes duration, medication use and any change in medication.

Page | 130

Figure 3.2: Mean percentage change with 95% CI from baseline for serum A) IL-10, B) TNF-α, C) IL-6 and D) Adiponectin following the gymnasium-based (3 and 6-months) and home-based (9 and 12-months) training for the PRT+WL (●) and WL (○) groups. The percentage changes in log transformed IL-6, IL-10 and TNF-ɑ represent the absolute differences from baseline multiplied by 100. * P<0.05, † P<0.01 for within-group change from baseline; # P<0.05 for between-group difference for the change from baseline. All P-values are based upon results adjusted for covariates.

Chapter 3

Page | 131

3.5.3 Changes in Endothelial Markers

In both the PRT+WL and WL group, there were no significant within or between-

group differences (group-by-time interactions) in either resistin or ICAM-1 at any

time during the study (Table 3.4 and Figure 3.3), with the exception that resistin

decreased significantly in the WL group relative to baseline at 12-months [mean

change -20% (95% CI, -40, 1), P= 0.01]. All results remained unchanged following

adjustment for age, sex, duration of diabetes, use of oral hypoglycaemic medication

and any change in medication.

Page | 132

Table 3.4 Mean baseline values and the percentage change from baseline for serum ICAM-1 and resistin for the PRT+WL and WL groups after 3, 6, 9 and 12-months.

Baseline Values and Within Group Changes PRT+WL WL Intervention Effects

Mean ± SD or

(95% CI) P-value

Mean ± SD or (95% CI)

P-value Net Difference

(95% CI) P- values

Model 1 | Model 2 ICAM-1 Baseline (ng/ml) 134.86 ± 59.58 142.38 ± 69.44 ∆ 3-month 2.37 (-9.36, 14.10) 0.692 1.78 (-10.34,13.90) 0.773 0.59 (-16.25, 17.44) 0.945 | 0.970 ∆ 6-month 0.18 (-11.71, 12.06) 0.977 -8.76 (-20.72, 3.19) 0.151 8.94 (-7.90, 25.79) 0.298 | 0.355 ∆ 9-month -7.81 (-19.29, 3.66) 0.182 -0.80 (-13.61, 12.02) 0.903 -7.02 (-24.22, 10.18) 0.424 | 0.462 ∆ 12-month -12.64 (-24.58, -0.70) 0.038 -10.03 (-22.37, 2.31) 0.111 -2.61 (-19.79, 14.56) 0.766 | 0.797 Resistin Baseline (ng/ml) 10.54 ± 5.64 10.99 ± 3.86 ∆ 3-month 1.16 (-0.14, 2.46) 0.080 0.59 (-0.71, 1.89) 0.373 0.57 (-1.27, 2.41) 0.542 | 0.417 ∆ 6-month 0.53 (-0.82, 1.87) 0.441 -0.02 (-1.42, 1.38) 0.979 0.55 (-1.40, 2.49) 0.581 | 0.267 ∆ 9-month -0.23 (-1.57, 1.11) 0.736 0.39 (-1.01, 1.80) 0.584 -0.62 (-2.57, 1.32) 0.530 | 0.921 ∆ 12-month -1.97 (-3.44, -0.50) 0.008 -0.84 (-2.31, 0.63) 0.263 -1.13 (-3.21, 0.95) 0.286 | 0.618

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from model 1 – adjusting for baseline values. Significant differences are highlighted in bold. Model 1 represents the P-values after adjusting for baseline values. Model 2 represents the P-value after adjusting for baseline values, age, weight, sex, diabetes duration, medication use and any change in medication.

Chapter 3

Page | 133

Figure 3.3: Mean percentage change with 95% CI from baseline for serum A) ICAM-1 and B) Resistin following the gymnasium-based (3- and 6-months) and home-based (9- and 12-months) training for the PRT+WL (●) and WL (○) group. The percentage changes in log transformed ICAM-1 represent the absolute differences from baseline multiplied by 100. All P-values are based upon results adjusted for covariates.

Chapter 3

Page | 134

3.6 Discussion

It is well established that obesity is associated with subclinical systemic

inflammation (542) and that dietary-induced weight loss can lower circulating

inflammatory cytokines (543, 544) including in people with T2DM (545). There is

also evidence that regular exercise training including aerobic training, PRT and the

combination, can lower pro-inflammatory cytokines and increase anti-inflammatory

markers in overweight and obese adults (15) and those with T2DM (33, 34, 244). On

this basis, we hypothesised that combining PRT with weight loss would lead to more

favourable changes in circulating markers of inflammation compared to weight loss

alone. However, we found no evidence that moderate diet-induced weight loss alone

or in combination with supervised high-intensity PRT influenced any marker of

inflammation in older overweight and obese adults with T2DM, despite significant

reductions in weight and fat mass (12). Whilst there is some evidence to suggest

inflammatory cytokines undergo some degradation when stored for longer than three

years (546), all inflammatory markers in this study were analysed at the same time

and thus were all under storage for a similar length of time.

Previous studies examining the combined effects of weight loss and exercise training

on inflammatory markers in older obese adults with T2DM are scarce. Nevertheless,

the findings from a 16-week intervention in 34 obese women aged 40-60 years

revealed neither diet alone nor diet plus PRT performed twice per week led to any

changes in circulating levels of IL-6 or CRP and the soluble receptors of TNF-α,

despite a 6 to 8% reduction in total body weight (523). It is difficult to explain our

results and these findings given that a number of interventions in overweight and

obese adults (31, 534, 547, 548) and a larger intervention in adults with T2DM (34)

reported that diet-induced weight loss, alone or in combination with exercise, was

associated with a significant reduction in various inflammatory cytokines. For

instance, the findings from a 12-month multi-centre RCT in 593 individuals with

newly diagnosed T2DM revealed that diet-induced weight loss alone or in

combination with regular physical activity (30 minutes of brisk walking) was

associated with a significant 21-22% reduction in hs-CRP levels (and an

improvement in adiponectin) after 6-months compared to usual care (34). However,

Chapter 3

Page | 135

there was no differences in the magnitude of the change in hs-CRP between the

weight loss alone and weight loss plus exercise group. Subsequent analysis found

that the change in weight mediated around 40% of the total effect on hs-CRP (34).

Although there is evidence that regular exercise can lower systemic inflammation,

independent of changes in body composition (534), this finding is consistent with a

number of previous trials which found that changes in circulating inflammatory

cytokines in response to lifestyle interventions were largely related to weight loss

and not exercise (31, 549).

In our study, the moderate weight loss diet resulted in similar significant reductions

in body weight of 2.8% and 3.5% in the PRT+WL and WL alone groups

respectively. While it has been previously suggested that at least a 10% reduction in

body weight is required to induce a reduction in various inflammatory markers (538),

others have demonstrated that a 5% decrease in body weight can improve the

inflammatory profile in obese adults or those with T2DM (17, 544). The healthy

eating plan was expected to reduce body weight by almost double the amount

observed in our trial, as such it is plausible the lack of significant change in any of

the inflammatory markers in either group in our study during the initial 6-month

period is explained, at least in part, by the smaller reduction in body weight .

Secondary to this, another possible explanation may be the absence of change in

visceral fat. Visceral fat is widely recognised to be a key secretory source for various

systemic inflammatory markers or adipokines, and thus is it possible that the

magnitude of the change in visceral fat in our participants was not enough to improve

inflammation. This is only speculative given that visceral fat was not directly

quantified in our study, however, both groups experienced a similar and significant

6.7 to 7.0 cm reduction in waist circumference after 6-months, which is often used as

surrogate estimate of visceral adiposity (550, 551). A more likely explanation for the

lack of any changes in any of the inflammatory markers in our study is the relatively

modest (mean 2.5 to 3.0 kg) reductions in overall weight (and fat mass).

Interestingly, another study in obese adults with T2DM reported no improvements in

inflammation (hs-CRP) following a 5-6 kg diet-induced weight loss over an 8-week

period, but improvements were observed after 12-months (288). Similarly, a 4-month

Chapter 3

Page | 136

trial in 27 obese adults with T2DM failed to detect any changes in any markers of

inflammation (CRP, IL-1, IL-2, IL-6, IL-8, IL-10, TNF-a) following a very low

caloric diet (VLCD) or VLCD plus exercise, with the exception of a reduction in hs-

CRP in the combination group (35). However, in this study the mean reduction in

weight was 25 kg, and at subsequent follow-ups (6- and 18-months) whereby

participants were in a eucaloric state, significant beneficial effects were observed for

nearly all inflammatory markers. These findings suggest that the duration of the

study or follow-up period may be an important factor in determining the

inflammatory response to lifestyle-related interventions.

Following the 6-month supervised gymnasium-based training plus weight loss

program, we found that 6-months of continued home-based resistance training

resulted in modest improvements in the inflammatory markers TNF-α and

adiponectin, yet a reduction in the anti-inflammatory marker IL-10. This was

somewhat unexpected given that this phase was eucaloric and associated with a 1.3

to 1.5 kg weight regain in both groups. Nevertheless, the improvements in various

inflammatory markers following the home-based maintenance phase supports the

notion that there may be a delay in the inflammatory response to exercise and/or

weight loss. Although there is evidence of acute or short-term changes

(improvements) in markers of inflammation following exercise and/or weight loss, as

discussed above the findings from our 12-month intervention are consistent with the

results from several trials which observed a delayed improvement in inflammatory

markers in both overweight and obese adults and those with T2DM (35, 539). While

the underlying mechanism(s) explaining these findings remain unknown, several

other studies observing a delay in inflammatory marker improvements following

exercise and/or weight loss have proposed this to be due to the effects of such

lifestyle interventions on adipose tissue lipolysis (35, 552). The components of total

lipolysis are the sum of “basal lipolysis”, which appears elevated in the presence of

adiposity and is greater in visceral adipose tissue compared to subcutaneous adipose

tissue, plus “demand lipolysis”, which is a consequence of nutritional demand (35).

It has been suggested that in the early stages of weight loss, adipocyte size does not

change and therefore basal lipolysis remains high, yet following continued weight

Chapter 3

Page | 137

loss (and during a eucaloric phase), demand lipolysis is reduced with lower local free

fatty acid levels (35). This lower level of local free fatty acids is proposed to be

associated with a reduced number of adipose tissue macrophages and a decrease in

the free fatty acid-driven cytokine production, and consequentially a reduction in

circulating cytokines (35). A study in mice found that this does occur (553), yet this

hypothesis requires further investigation in humans but does provide a plausible

explanation for the observations made during the second phase of our intervention.

While there is some evidence that long-term exercise training, including PRT, can

improve circulating levels of inflammatory markers (554-556), we found no

evidence that our program of high-intensity PRT combined with weight loss

improved any marker of inflammation in overweight and obese adults with T2DM.

However, as reported above we found that during the less intense home-based

training there were modest improvements in circulating levels of TNF-α and

adiponectin, compared to sham-exercise. This is consistent with the findings from

previous studies which have also reported mixed findings with regards to the effects

of PRT on inflammatory cytokines in adults with T2DM (523, 540). Although

factors such as age, fitness level, degree of adiposity, as well as the presence of other

comorbid conditions are likely to have contributed to the mixed findings in various

interventions, there is also evidence that differences in exercise duration, intensity

and frequency can influence the inflammatory response to exercise. Indeed, the

findings from a meta-analysis of exercise interventions on inflammatory markers in

adults with T2DM found that mostly aerobic, but some PRT programs of longer

duration or which had a larger number of total training sessions, were associated with

the greatest benefits for circulating IL-6 levels (244). Similarly, it has been reported

that interventions of 16-weeks or longer and/or with training intensities of at least

80% of 1-RM may influence the inflammatory responses to PRT (557, 558). In light

of these findings, it is somewhat surprising that our 6-month high-intensity PRT

program, where training was prescribed three times per week at an intensity of 75-

85% 1-RM and compliance was high averaging 2.8 out of three sessions per week,

did not have an effect on markers of inflammation assessed, particularly given the

significant beneficial effects on HbA1c and the improvements in fat mass and lean

Chapter 3

Page | 138

mass in the PRT+WL group. In part support of these findings, another meta-analysis

of eight RCTs found that there were no differences between the PRT and control

group for the change in serum concentrations of adiponectin, leptin, IL-6 and TNF-ɑ,

but PRT was associated with a significant reduction in circulating CRP relative to

controls (559). In addition, meta-regression revealed no dose-response relationship

between PRT intensity and changes in inflammatory response. It is evident from the

above findings that there is considerable heterogeneity across studies concerning the

effects of PRT on inflammatory biomarkers, and thus further studies remains

warranted.

Like systemic inflammatory markers, endothelial markers such as ICAM-1 and

resistin are also significantly elevated in adults with T2DM (560). In our study, we

observed no changes in either ICAM-1 or resistin following the supervised

gymnasium- or home-based resistance training. This is consistent with the findings

from several previous trials which also examined the effects of resistance training on

endothelial functioning in older adults with T2DM yet observed no effect (561, 562).

For example, Kwon et al. (562), investigated the effects of aerobic or resistance

training on endothelial function as assessed by flow-mediated dilation, in 40 older

overweight women with T2DM compared to a control program (562). Participants

randomised to aerobic or resistance training completed 60 minutes of training, 5 days

per week for 12-weeks, whilst the control program did not exercise (562). At the

completion of the intervention, endothelial function was improved in the resistance

and aerobic training group, however, the improvement was only significant for the

aerobic training group (2.2 ± 1.9%, P=0.002 compared to control) (562). Whilst the

exact mechanisms by which exercise training can improve endothelial function

remain unknown, it has been suggested that the mode of training is an important

factor. For instance, there is evidence for a positive effect on various endothelial

markers following aerobic training in adults with chronic disease such as chronic

heart failure, which has been related to the more consistent increase in blood flow

and laminar shear stress associated with this mode of training (563, 564).

Furthermore, aerobic training also results in greater improvements in

cardiorespiratory fitness which may translate into improved vascular endothelial

Chapter 3

Page | 139

functioning and in turn reduce the endothelial expression of cellular adhesion

molecules (561, 562, 565, 566). Therefore, the lack of any changes in any endothelial

marker in either group in our study may be due to the absence of an aerobic

component in the exercise program. As the precise mechanism(s) responsible for any

improvements in endothelial function in older adults with T2DM remain unidentified

and there is only limited evidence that PRT either with or without weight loss

confers improvements in endothelial markers in older adults with T2DM (567),

further research in this area is required.

3.7 Limitations

There are a number of limitations associated with this study which must be

considered when interpreting the findings. First, although multiple cytokines

reflective of systemic inflammation were assessed, hs-CRP, a more global and

universal inflammatory marker for which there is clinical reference values, was not

measured. Second, our study was limited to an assessment of circulating

concentrations of various cytokines which have a short half-life, and a measure

cytokine soluble receptors may be more representative of the inflammatory response

(568). Third, a key goal of the healthy eating program was to reduce body weight by

0.25-0.5 kg per week totalling approximately 6 kg over the duration of phase 1. The

total amount of weight lost was only approximately half this which may in part

explain the lack of significant improvement in levels of inflammatory markers

assessed in this study. Further, our study was a secondary analysis and limited by a

relatively small sample size, and given the known variability in inflammatory

cytokines, it is likely that our study was underpowered to detect any potential

between group differences. Finally, when interpreting our findings, it is important to

acknowledge the long-time period (10-years) that the serum samples were stored

prior to analysis. Thus, it is possible that there was degradation in the various

cytokines during this time as there is some evidence that inflammatory markers

degraded by up to 50% over a period of 2-3 years. Few studies have examined the

stability of serum samples and the inflammatory markers measured in this trial,

however, de Jager et al. (568) measured the effects of long time storage (up to 4

years) on IL-6 and IL-10 and observed these inflammatory markers degraded by 50%

Chapter 3

Page | 140

or less of the baseline value within 2-3 years of storage. A strength of our analysis

though was that all samples were stored for the same amount of time and thawed and

analysed simultaneously. It is also worth noting that a comparison of the mean

baseline values of the participants in our study was similar to that previously

published in our laboratory in healthy older men where samples were stored for only

12- to 24-months using the same methodology (42, 569).

3.8 Conclusion

The main finding from this 12-month trial was that a 6-month moderate weight loss

program with and without high-intensity gymnasium-based PRT did not change any

markers of systemic inflammation or endothelial function in older overweight adults

with T2DM. However, a further 6-months of continued home-based PRT

independent of weight loss did result in modest improvements in the inflammatory

markers TNF-α, IL-10 and adiponectin, compared to sham-exercise. These

improvements may be beneficial to overweight older adults with T2DM given the

close association of adverse CV health and systemic inflammation. Future trials

remain necessary to optimise PRT prescription for the improvement of markers of

inflammation in overweight older adults with T2DM. In addition, future trials with

larger sample sizes are required to investigate if an improvement in inflammation as

a result of participation in a PRT program is related to improvements in glycaemic

control, insulin sensitivity and/or changes in body composition.

3.9 Acknowledgements

This study was financially supported by a grant from the Victorian Health Promotion

Foundation (VicHealth). Funds for the purchase of exercise equipment were kindly

provided by the Rotary Club of Kew, Victoria, Australia and by Soroptimist

International, Brighton Division. With great thanks to Elena Lekhtman and Lucy

Robinson for their kind assistance in the clinical management of the volunteers. Most

importantly, all authors are indebted to the volunteers whose cooperation and

dedication made this study possible.

Page | 141

Chapter 4

Methods for a 6-month Randomised Controlled Trial Investigating

the Effects of Progressive Resistance Training, Whey-Protein and

Vitamin D Supplementation on Glycaemic Control, Body

Composition and Cardiovascular Risk Factors in Older Adults with

Type 2 Diabetes

Chapter 4

Page | 142

4.1 Declaration Statement

The PhD student was responsible for developing the intervention testing and protocol

booklet which outlined the specific methodology to be used for each of the outcome

measures assessed. The student was also responsible for developing questionnaires,

screening forms, trainer guide books/exercise cards, compliance calendars, monthly

phone call forms and co-ordinating the 21-month recruitment campaign for the RCT

outlined in this Chapter. The student was also responsible for co-ordinating several

training sessions of qualified personal trainers/exercise physiologists who were not

Lift for Life® accredited under Fitness Australia. The student commenced her PhD

studies on a grant which had already been awarded funding and thus was not

involved in the conceptualisation of this project thus was not first author on the

methodology publication.

Chapter 4

Page | 143

4.2 Abstract

While physical activity, energy restriction and weight loss are the cornerstone of type

2 diabetes mellitus (T2DM) management, less emphasis is placed on optimising lean

mass. As muscle is the largest mass of insulin-sensitive tissue and the predominant

reservoir for glucose disposal, there is a need to develop safe and effective evidence-

based lifestyle management strategies that optimise lean mass as well as improve

glycaemic control and cardiovascular risk factors in people with this disease,

particularly older adults who experience accelerated muscle loss. Using a two-arm

randomised controlled trial (RCT), this 6-month study builds upon the community-

based progressive resistance training (PRT) programme Lift for Life® to evaluate

whether ingestion of a whey-protein drink combined with vitamin D supplementation

can enhance the effects of PRT on glycaemic control, body composition and

cardiovascular health in older adults with T2DM. Approximately 200 adults aged 50

to 75 years with T2DM, treated with either diet alone or oral hypoglycaemic agents

(not insulin), were recruited. All participants were asked to participate in a

structured, supervised PRT programme based on the Lift for Life® programme

structure, and randomly allocated to receive a whey-protein drink (20 g daily of

whey-protein plus 20 g after each PRT session) plus vitamin D supplements (2,000

IU/day), or no additional powder and supplements. The primary outcome measures

collected at baseline, 3- and 6-months were glycated haemoglobin (HbA1c) and

insulin sensitivity (homeostatic model assessment). Secondary outcomes included

changes in: muscle mass, size and intramuscular fat; fat mass; muscle strength; blood

pressure; levels of lipids, adipokines and inflammatory markers, serum insulin-like

growth factor-1 and 25-hydroxyvitamin D; renal function and change in diabetes

medication. The findings from this study will provide new evidence as to whether

increased dietary protein, achieved through the ingestion of a whey-protein drink,

combined with vitamin D supplementation, can enhance the effects of PRT on

glycaemic control, muscle mass and size, and cardiovascular risk factors in older

adults with T2DM.

Chapter 4

Page | 144

4.3 Methods

4.3.1 Study Design

The Resistance Exercise, Vitamin D and Muscle Protein Intervention Trial

(REVAMP-IT) was a 24-week two-arm parallel, RCT. Participants with established

T2DM who were suitable for the current community-based Lift for Life® resistance

training program and met trial inclusion criteria (refer to section 4.2.6 Screening and

Eligibility) were randomised to one of two groups: 1) the Lift for Life® program

combined with a whey-protein drink and vitamin D supplementation or 2) the Lift for

Life® program alone. The participants randomised to Lift for Life® alone did not

receive placebo supplements. A placebo product was not used in this trial as it

became evident through consultation with the manufacturer of the whey-protein

drink that ingredients used to develop a placebo for use in this trial (e.g. using

maltodextrin as a food additive) had the potential to alter blood glucose levels or

influence muscle mass, which are two key outcomes for this trial. Thus, to avoid any

potential adverse (or positive) effects on blood glucose levels of the participants

assigned to this group, no placebo products were prescribed. We believed this would

not compromise trial outcomes and that there was a strong justification for not

including a matched placebo in this trial. It should also be noted that the selection of

a two-arm design (e.g. lack of a true ‘non-exercise’ control arm) was consistent with

our primary research objectives which sought to examine the effectiveness of the

addition of whey-protein and vitamin D to an existing community-based PRT

program (Lift for Life®). All research staff, except the project manager, were blinded

to the intervention groups. The project manager was solely responsible for the

distribution of whey-protein and vitamin D supplements to those in the Lift for Life®

program plus protein and vitamin D arms. The study was coordinated from the

Melbourne metropolitan campus of Deakin University (Melbourne, Victoria,

Australia).

4.3.2 Ethics

Ethics was approved by the Deakin University Human Research Ethics Committee:

Project number EC2013-050, Does a whey-protein enriched drink and vitamin D

enhance the health benefits of the Lift for Life® resistance training program in older

Chapter 4

Page | 145

adults with type 2 diabetes? (Appendix 4). This study was also registered with the

Australian New Zealand Clinical Trials Registry, registration number

ACTRN12613000592741.

4.3.3 Funding

This project was funded by a grant from the National Health and Medical

Research Council Project (APP1046269). The whey-protein powder was provided by

OmniBlend (Campbellfield, Victoria, Australia) and the vitamin D supplements

(Ostelin) by Sanofi-Aventis Australia Pty Ltd (Macquarie Park, New South Wales,

Australia).

4.3.4 Participants

Men and women aged 50 to 75-years with established T2DM, treated with diet alone

or any oral hypoglycaemic agents (except insulin), were invited to participate in this

study.

4.3.5 Recruitment

Recruitment methods used for this RCT are extensively discussed in Chapter 5 of

this thesis. Briefly, recruitment occurred via targeted mail-outs to registrants of The

National Diabetes Support Scheme (NDSS) database. Recruitment for this trial was

further supplemented by a number of State and local media campaigns including

newspaper advertisements, web-based media and notices at current Lift for Life®

facilities, recruitment was also further supplemented by referrals from general

practitioner (GP) and other allied health professionals including dieticians,

endocrinologists, diabetes educators and local support groups.

4.3.6 Screening and Eligibility

A two-step screening process was employed in this study. Firstly, a telephone

screening questionnaire (Appendix 5) was used to assess an individual’s eligibility.

Participants were eligible if aged 50-75 years, had been diagnosed with established

T2DM and were treating their condition with diet or oral hypoglycaemic medication

only. Participants were excluded from the trial based on the criteria outlined in Table

Chapter 4

Page | 146

4.1. Those who passed the telephone screening were then required to gain GP

approval prior to randomisation and participation in the Lift for Life® program

(second screening step). Medical clearance was deemed to have been approved by

the participants GP upon completion of a Lift for Life® Recommendation to

Participate Form based on guidelines published by the Australian College of Sports

Medicine (ACSM) (refer to Appendix 6). All enrolled participants were encouraged

and monitored to keep constant the use of lipid-lowering or anti-hypertensive

medication throughout the trial and were additionally instructed to not modify their

lifestyle habits other than necessary for the trial. In order to increase the external

validity of this study and due to the lack of consensus regarding optimal serum

vitamin D concentration, vitamin D status was not used as exclusion or inclusion

criteria but was measured as part of the biochemical analysis post-randomisation.

Table 4.1: Ineligibility criteria for the 24-week Lift for Life® RCT.

Health-related

Not diagnosed with T2DM

Any medical condition contraindicated to PRT

BMI >40kg/m2

HbA1c >10%

Presence or indication of kidney disease

Current smoker

Physical Activity Status

Meeting or exceeding National Physical Activity Guidelines

Medication or Supplement Use

Prescribed insulin for management of T2DM

Taking vitamin D supplements >500IU/day

Taking dietary protein supplements

Travel

Travel plans which impeded participation in the trial

Other

Aged <50 or >75 years of age

Chapter 4

Page | 147

4.3.7 Consent

Following completion of the telephone screening questionnaire, eligible participants

were provided with a Plain Language Statement (PLS) and Consent Form (refer to

Appendix 7). Participants who wished to proceed with their involvement in this RCT

were invited to complete baseline testing at Deakin University. Following baseline

testing, participants were randomised to the Lift for Life® PRT program plus whey-

protein and vitamin D group or the Lift for Life® PRT program only group.

4.3.8 Randomisation

Randomisation occurred at the level of the individual participant, stratified by gender

and diabetes treatment (diet or oral hypoglycaemic medication), in blocks of 4-8

using a computer-generated random number sequence (Microsoft Excel 97) by an

independent researcher. As mentioned previously, all research staff except the

project manager were blinded to the intervention groups. The project manager was

solely responsible for the distribution of protein and vitamin D supplements to those

in the Lift for Life® program plus whey-protein and vitamin D arms.

4.3.9 Intervention

Lift for Life®: A community-based progressive resistance training program

All participants involved in this trial were required to follow a training program

modelled off the structure of the Lift for Life® PRT program. The Lift for Life®

program is an evidence-based PRT program designed for people with diabetes or

those at risk of developing T2DM. The program was developed based upon a series

of previous laboratory and community-based exercise intervention trials (12, 204,

205). Lift for Life® is a commercial program with a limited number of accredited

training sites in Melbourne licensed and currently running the program which is

overseen by Fitness Australia in collaboration with Baker IDI Heart and Diabetes

Institute. The Lift for Life® program comprises moderate-intensity PRT (2-3 sets of

8-12 repetitions at 60-75% of maximum strength of 8-10 exercises) involving

dynamic concentric and eccentric contractions, focusing on the major muscle groups

of the body. Some examples of the exercises used throughout the program include

bench press, leg extension, upright row, lateral pull down, standing leg curl,

Chapter 4

Page | 148

dumbbell seated shoulder press, dumbbell seated biceps curl, dumbbell triceps

kickbacks and abdominal curls. Training was made incrementally more challenging

at a rate of 2-10% per week to meet the principles of progressive overload with the

Borg Rating of Perceived Exertion (RPE) scale used to validate training intensity. An

appropriate training intensity level for this trial was established as 12 to 15 (moderate

to high-intensity) on the RPE scale. The RPE scale has previously been validated for

use in older adults with T2DM and found to appropriately measure exercise intensity

(570).

Due to the limited number of accredited Lift for Life® program providers in

Melbourne Australia, the trial was expanded to include training locations such as

commercial gymnasiums that were not accredited as a Lift for Life® program

provider but which did allow participants to safely perform a PRT program under the

guidance of qualified Certificate IV personal trainers. In such instances, the structure

of the training programs for these participants replicated that of the Lift for Life®

program. The same progressive overload and training principles were applied,

consequently, all trial participants followed the same training program as discussed

below.

Figure 4.1: Flow diagram of the progress through the 24-week PRT program used in this trial modelled from the Lift for Life® program.

Chapter 4

Page | 149

The 24-week Lift for Life® program is divided into three distinct phases (Bronze,

Silver and Gold), each running for a period of eight weeks as shown above in Figure

4.1. During the initial phase (Bronze), participants were asked to attend two PRT

sessions per week. After eight weeks, participants commenced the second eight-week

phase (Silver), but with the aim to participate in one additional PRT session to

achieve the goal of three PRT sessions per week. The final phase (Gold) was a

replication of the Silver phase. Throughout the program all completed exercises, sets

and reps for each session were documented on Lift for Life® training cards. All

training cards were collected and reviewed at the completion of the first four weeks

of training with programs modified as required by the trainers. Subsequently, every

eight weeks training programs, reported intensity and progressive overload were

reviewed by Lift for Life® trainers or Certificate IV personal trainers and if required

a new program was developed to maintain the training intensity at 12-15.

To enhance participation in and retention of participants in this 24-week program

participants received monthly follow-up phone calls from the research staff to

enquire about their experiences at their respective training locations and discuss any

issues or concerns they had experienced with the training program or with their

trainers. Finally, to further promote adherence to the Lift for Life® PRT program all

participants were eligible to receive up to AUD$240 by way of vouchers to cover the

costs associated with their participation in the Lift for Life® program. The full

reimbursement was provided to all participants who achieved 80% or above

compliance with the exercise program, calculated from the Lift for Life® self-

completed exercise cards (see below section 4.2.11.9 Compliance Assessment for

further information). Costs of the PRT program ranged from $3-$12 per session and

were set by the training location.

Whey-Protein and Vitamin D Supplementation

Participants randomised to the Lift for Life® plus whey-protein and vitamin D

supplementation group received a 12-week supply of a whey-protein enriched

powder and vitamin D supplements at baseline testing and again after 12-weeks of

training. Supplements were provided in single use sachet form with a number code

Chapter 4

Page | 150

(OmniBlend, Campbellfield, Victoria, Australia) (Figure 4.2). Participants were

instructed to mix one sachet containing 20 g of whey-protein concentrate 80%

(WPC80), containing 2.4 g of leucine, with 150ml of water every morning of the trial

and consume an additional supplement within two hours of each Lift for Life® PRT

session on training days. This dosage raised the total supplemental protein dose on

training days to ~40 g, providing ~32 g of whey-protein. Participants received a

marked shaker cup with instructions on how to reconstitute the whey-protein powder

in water (1 sachet per ~150 ml of cold water) along with appropriate storage

instructions for the supplements. Participants were offered two flavours to select

from either vanilla or mocha coffee. Each protein drink will provide approximately

335 kJ of energy, 2 g of lactose, 1 g of fat and 5 g of fibre.

Figure 4.2: Single use sachet of protein supplement and shaker cup used for protein supplement preparation.

In addition to the whey-protein supplements, participants randomised to this

treatment group were also asked to take two 1,000 IU capsules of vitamin D3

(Ostelin, Melbourne, Victoria, Australia) each day for the duration of the study. The

goal of vitamin D3 treatment was to raise serum 25(OH)D concentrations to at least

75 nmol/L. Previously, in a 6-month RCT in 95 overweight and obese adults it has

been shown that daily supplementation with 2,000IU was effective in raising serum

25(OH)D levels to greater than 75nmol/L within 2-months of treatment and greater

than 95nmol/L after 6-months in 91% of the trial population (571). Consistent with

the double-masked design, the target goal of ≥75 nmol/L was not checked prior to

randomisation.

Chapter 4

Page | 151

4.3.10 Sample Size Calculations

The calculated sample size for this trial was based on the following power

calculations from previously published studies of PRT in older adults (including

those with T2DM) (12-14, 204), and work of others that have assessed the

independent or combined effects of protein, vitamin D and PRT on the outcome

measures (351, 425, 572). It was estimated that 168 participants would provide 90%

power (P<0.05 two-tailed) to detect a 0.5% difference for the change in HbA1c levels

between the groups, assuming a conservative SD of 1.1%. For insulin sensitivity, a

sample size of 140 would be required to detect an 0.7 difference for the change in

HOMA-2 insulin resistance between the groups at a power of 90%, assuming a

conservative SD of 1.2. To compensate for a projected 20% drop-out, a recruitment

target of 202 participants for this trial was established. Participants were randomised

1:1 to the two groups (101 per group). This recruitment target allowed for sufficient

power (80-90%, P<0.05, two-tailed) to detect the following intervention effects on

our secondary outcome measures: 0.6 kg for lean mass; 4 mmHg in SBP; 15% in

serum IL-6 and IGF-1, and 12% in homocysteine levels.

4.3.11 Outcome Measures

Participants attended Deakin University a minimum of twice throughout the duration

of the study for assessment (baseline and 24-weeks). All outcome measures were

assessed within the School of Exercise and Nutrition Sciences at Deakin University,

Burwood campus with the exception of fasted blood sample collections which

occurred at local pathology clinics at baseline, 12- and 24-weeks. Research staff

conducted on-site testing at each health and fitness centre after 12-weeks for a subset

of the measures (weight, waist circumference, blood pressure, knee-extensor strength

assessment and questionnaire collection).

The primary outcome measures for this study were glycaemic control as measured by

HbA1c and insulin sensitivity (estimated from the HOMA-2) which was assessed

using FPG and insulin measured at ≥48-hours after the last Lift for Life® PRT

session. Secondary outcome measures included: changes in body composition (total

body and regional lean mass, 25% femur muscle cross-sectional area (CSA) and

Chapter 4

Page | 152

intramuscular fat), blood pressure, blood lipids, adipokines, inflammatory markers,

IGF-1, muscle strength, renal function and diabetes medication (purpose, variety and

dosage). Other covariates and variables of interest assessed included: anthropometry,

physical activity, diet, use of lipid-lowering and blood pressure medication and

serum 25(OH)D. A summary of all the outcome measures and their assessment

methods is shown below in Table 4.2.

Page | 153

Table 4.2: Summary of the primary and secondary outcome measures collected and methods of collection.

Variables Data Collection Method Data Collection Points

Primary Outcome Measures Baseline 12-weeks 24-weeks

HbA1c Overnight fasted serum sample x x x

HOMA-2 Insulin Sensitivity Overnight fasted serum sample, HOMA-2 calculator x x x

Secondary Outcome Measures

Anthropometry Height, weight and waist circumference x x x

Body Composition DXA total and regional lean and fat mass x x

pQCT scan at 25% femur site x x

Biochemistry Measures Routine biochemistry x x x

HOMA-2 beta-cell function Overnight fasted serum sample, HOMA-2 calculator x x x

Serum 25(OH)D Levels Overnight fasted plasma collection x x x

Markers of Inflammation Overnight fasted plasma collection x x x

Blood Lipids Overnight fasted plasma collection x x x

Blood Pressure Automated measurement x x x

Muscle Strength 3-Repetition Maximum leg press and seated row x x

Isometric knee extensor strength x x x

Page | 154

Table 4.2 continued

Physical Activity CHAMPS questionnaire x x x

Dietary Assessment 24-hour Food Recalls x x x

Diabetes and Other Medication Monthly Phone Calls

Adverse Events Monthly Phone Calls

Lift for Life® Program Adherence Calculated from exercise cards collected every 4-weeks

Supplement Compliance Calculated from supplement sachets and vitamin D capsules returned at 12 and 24-weeks

Chapter 4

Page | 155

4.3.11.1 Anthropometry

All participants’ height was measured to the nearest 0.1 cm with a wall-mounted

stadiometer (Holton Limited. Crymmych, Pembs, U.K.). Body weight was measured

to the nearest 0.1 kg using calibrated electronic digital scales (AND Personal

Precision Scale UC-321). Waist circumference was measured on a horizontal plane,

halfway between the lowest lateral portion of the ribcage and the iliac crest.

4.3.11.2 Body Composition

Dual Energy X-Ray Absorptiometry

Total body and regional (arms and legs) lean mass, fat mass and percentage body fat

was measured from total body scans performed using Dual X-ray Absorptiometry

(DXA) (Lunar Prodigy, GE Lunar Corp., Madison WI), using software version

12.30.008. To obtain total body scans all participants were instructed to wear loose

fitting clothing free of any metal and to remove all metal objects (e.g. jewellery, bras

and belts) for the scanning process. Patient positioning followed standardised

procedures for whole body scanning (573). Briefly, participants were instructed to lie

supine within the delineated boundaries of the scanning table, with their arms placed

beside them and palms facing down, ensuring minimal contact was made between

the upper limb and trunk soft tissue. The participant’s legs were positioned slightly

apart and internally rotated. Participants were informed of the approximate length of

the scan and were alerted of the mid-way point of the scan to assist with comfort.

Participants were instructed to remain still for the duration of the scan with the image

monitored for evidence of movement. If the image showed evidence of excessive

movement the scan was aborted and repeated. For analysis, the total body scans were

divided into sub-regions of interest to isolate the different body regions. The

following standardised criteria, as provided in the manufacturer’s manual were used

to define each body region (Figure 4.3).

All scans and follow-up scans were performed by a sole researcher blinded to the

randomisation. All follow-up measurements were analysed using the ‘comparison’

feature of the Lunar Prodigy program. Quality assurance (QA) using phantom

scanning procedures were performed prior to each measurement as part of regular

Chapter 4

Page | 156

clinical practice. The short-term co-efficient of variation (CV) for repeated

measurements of total body lean mass and fat mass within the laboratory ranges from

1.0% to 1.7%.

Head: The cut line was placed just below the chin;

Left and right ribs: The cut lines around the ribs were positioned lateral to the spine

and superior to the pelvis;

Left and right arm: The cut lines were placed on the most medial border of the

humeral head and care was taken to make sure that no trunk or leg soft tissue was

placed within the arm region;

Left and right leg: The cut lines were angled mid-way through each femoral neck,

and care was taken to include all leg soft tissue within the leg region border;

Pelvic: The cut lines were just above the most superior point of the pelvis and

through the mid-point of each femoral neck, creating a triangular pelvic region.

Figure 4.3: Sub-regions within the whole body DXA scan.

Chapter 4

Page | 157

Peripheral Quantitative Tomography

A peripheral quantitative computed tomography (pQCT) scanner (XCT 3000, Stratec

Medizintechnik GmbH, Pforzheim, Germany) was used to measure muscle CSA,

subcutaneous fat CSA and muscle density, as a surrogate measure of intermuscular

adiposity at the 25% femur site (Figure 4.4). The protocol used followed what has

been previously reported (574). After performing a scout view of the distal end of the

femur, the scanner reference line was placed midway over the most proximal aspect

of the distal femur epicondyle. Images were acquired at 4% and 25% of the femur

site proximal to the reference line. Slice thickness was set at 2.3 mm, and voxel size

set at 0.3 mm with a scanning speed of 10 mm/s. Image quality was visually assessed

following scan acquisition. Scans were rejected and repeated if the cortical shell was

irregular due to movement artifacts. Subcutaneous fat CSA was determined by

selecting the area with thresholds -40 to +40 mg/cm3 HA density (contour mode 3,

peel mode 1), and muscle CSA was determined by subtracting the total bone CSA

(threshold, 280 mg/cm3; contour mode 1, peel mode 2) and subcutaneous fat CSA

from the total area of the distal femur (threshold, -40 mg/cm3, contour mode 3, peel

mode 1) (574). Stratec XCT scanners are factory calibrated against the European

Forearm Phantom for single energy which was performed prior to each scan. For

consistency, all pQCT scans were performed and analysed by a single investigator

blinded to the randomisation. The CV for femur muscle CSA within the laboratory is

1.3%.

Figure 4.4: Peripheral quantitative computed tomography (pQCT) scan at the 25% femur site.

Chapter 4

Page | 158

4.3.11.3 Biochemical, Hormonal and Inflammatory Markers

Following an overnight fast, a rested morning (8-10am) venous blood sample was

collected from each participant’s antecubital vein at a National Association of

Testing Authorities Royal College of Pathologists Australasia accredited pathology

laboratory in each participant’s local area. The following series of parameters were

all assessed by the pathology lab using standardised techniques: glycated

haemoglobin (HbA1c), fasting plasma glucose (FPG), blood lipids (total cholesterol,

high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL)

cholesterol and triglycerides), high-sensitive C-reactive protein (hs-CRP), estimated

glomerular filtration rate (eGFR), creatinine, calcium. LDL cholesterol was

calculated by using the Friedewald formula. eGFR, as a measure of kidney function,

was calculated using the participants’ serum creatinine, age and gender according to

the abbreviated Modification of Diet in Renal Disease (MDRD) formula, which is

now used by most laboratories in Australia:

eGFR (mL/min/1.73m2)=175 x [Serum Creatinine (umol/L) x 0.0113]-1.154 x

Age(years)-0.203(x 0.742 if female)

A series of serum aliquots (5 x 1.5 ml) were collected and stored at -80°C so that the

following hormonal and inflammatory parameters could be assessed in a single batch

at the completion of the study including serum 25(OH)D and insulin-like growth-

factor 1 (IGF-1), tumour necrosis factor α (TNF-α) and interleukins 6, 8 and 10 (IL-

6, IL-8 and IL-10).

Measurement of Fasting Insulin and HOMA-IR

Fasting insulin was assessed from stored serum using the ARCHITECT® insulin

assay (Abbott Laboratories, Abbott Park, IL 60064 USA). This assay is a 1-step

chemiluminescent microparticle immunoassay. Samples were prepared as instructed

in the immunoassay kit. The 1-step immunoassay uses paramagnetic microparticles

coated with an anti-insulin monoclonal antibody and acridinium-labelled insulin

monoclonal antibody conjugate. Addition of the pre-trigger reagent leads to

acridinium-produced chemiluminescence. This Acridinium-produced

Chapter 4

Page | 159

chemiluminescence was measured as relative light units on the ARCHITECT

immunoassay optical system. The relative light units are directly proportional to the

insulin concentration in the serum sample. In our lab, the imprecision in CV% was

3.65, 3.22 and 3.41% for low (107.6 pmol/L), medium (434.8 pmol/L) and high

(1080.6 pmol/L) insulin levels respectively. All samples were tested in duplicate and

the mean values have been reported.

Insulin sensitivity (%S) and steady state beta-cell function (%B) were measured

using the updated HOMA Calculator© as available for download from The

University of Oxford Diabetes Trials Unit (https://www.dtu.ox.ac.uk/

homacalculator/). This updated model considers variations in hepatic and peripheral

glucose resistance, increases in the insulin secretion curve for plasma glucose

concentrations above 10 mmol/L (180 mg/dL) and the contribution of circulating

proinsulin (575).

Measurement of serum IGF-1

Serum IGF-1 was measured using a 1-step sandwich chemiluminescense

immunoassay kit. The kit was a LIAISON® IGF-1 kit (DiaSorin, Saluggia (VC),

Italy) with the protocol published in the kit instructions and adhered to directly. A

monoclonal antibody is used for coating magnetic particles (solid-phase) and another

monoclonal antibody is liked to an isoluminol derivative (isoluminol-antibody

conjugate). During the incubation period, any IGF-1 present in samples, calibrators

or controls binds to the solid phase and to the conjugate. After the incubation, the

unbound material is removed with a wash cycle. Following this, started reagents are

added to induce a chemiluminescence reaction. The light signal, and the amount of

isoluminol conjugate is measured as relative light units on a LIAISON® Analyser.

The relative light units measured indicate the concentration of IGF-1 present in

calibrators, samples and controls. In our lab, the imprecision in CV% was 4.60, 4.00

and 3.50% for low (8.26 nmol/L), medium (26.05 nmol/L) and high (33.54 nmol/L)

IGF-1 levels respectively. All samples were tested in duplicate and the mean values

have been reported.

Chapter 4

Page | 160

Measurement of Serum 25(OH)D

Serum 25(OH)D was analysed at Monash Health, Melbourne, Australia. This

laboratory is National Association of Testing Authorities, Australia (NATA) certified

and subscribes to the Vitamin D External Quality Assessment Scheme. Samples were

measured on the AbSciex Q Trap 5500 MS by liquid chromatography-tandem mass

spectrometry (LC-MS/MS). This system used a Phenomenex Kinetex

Pentafluorophenyl (PFP) column that achieves baseline separation of 25(OH)D. The

assay was calibrated with the Chromsystems, 3 Plus1 Multilevel Calibrator for 25-

OH-Vitamin D3 (part number: 62029). The inter-assay CVs for the quality control

analysed in each assay was 6.5-9.0% for 25(OH)D.

Measurement of Serum Inflammatory Markers

The measurement of the inflammatory parameters, IL-6, IL-8, IL-10, TNF- ɑ and

Adiponectin was conducted by Cardinal Bio-research Pty Ltd (Australia). Serum

concentrations of IL-6, IL-10, IL-8 and TNF-ɑ were measured in duplicate using a

Millipore high sensitive cytokine immunoassay assay kit (Millipore Corp, Billerica,

Massachusetts, USA) as per the manufacturer’s instructions. Plates were read on the

Bioplex (V.5.0, Bio-Rad Laboratories, Hercules, CA). Adiponectin was assayed

using an in-house multiplex immunoassay with capture and detection antibodies

obtained from R&D Systems (Minneapolis, MN USA). Antibodies were coupled to

Luminex xMAP beads using standard Luminex protocols and as previously

described (541). The mean intra and inter-assay CVs for IL-6, IL-10, IL-8, TNF-ɑ

and Adiponectin was <12%. Samples with results below the detectable limits of the

assay were allocated the minimum detectable concentration for each assay: IL-6=

0.19 pg/mL; IL-10= 0.03 pg/mL; IL-8= 0.08 pg/mL; TNF-ɑ = 0.03 pg/m;

Adiponectin = 0.01 µg/mL.

4.3.11.4 Blood Pressure

Following a 5-minute rest period where all participants were seated in a quiet room,

SBP and DBP was measured using an automated blood pressure monitor (AND Vital

Sensor, Model number TM-2551P, Abingdon, Oxford). Four measurements were

Chapter 4

Page | 161

taken on the left arm with a 2-minute interval between readings; the mean of the final

three readings were used in the analysis.

4.3.11.5 Muscle Strength

Knee Extensor Strength

Isometric knee extensor strength (force in kg) was measured on the participant’s

dominant leg using Lord's strap assembly incorporating a strain gauge (Neuroscience

Research Australia, Sydney, Australia). Participants were stabilised in a seated

position with one Velcro strap wrapped around the dominant leg and connected to

the spring-loaded strain gauge ensuring the hip and knee joint were both supported at

90°. The Velcro strap was positioned approximately 5cm above the ankle joint

allowing dorsiflexion of the ankle (Figure 4.5). Participants were instructed to leave

the contralateral leg free of pressing against a chair leg or supporting arm on the

chair, however, participants could hold on to the chair with their hands for support.

Participants executed 3-4 submaximal concentric contractions with a 10 second rest

between each sub-maximal contraction. Following a 60 second rest participants then

performed one maximal concentric effort, holding this maximal force for 3-seconds

followed by another 60 second rest. Following a second rest another maximal

contraction was repeated. The two readings from the two maximal contractions were

recorded with the peak force used in the analysis. This test has been shown to have

excellent test-retest reliability ICC=0.97 (576).

Chapter 4

Page | 162

Figure 4.5: Participant positioning for the knee extensor strength test.

3-Repetition Maximum Assessment

Maximal muscle strength of the lower limbs and back was estimated by employing

three-repetition maximum strength (3-RM) tests for the bilateral leg press (Synergy

Omni Leg Press S-31 OPD, QLD, AUS) and the seated row (Nautilus F3 Adjustable

Tower Pulley System F3ATFS, Nautilus, Vancouver, WA). A 3-RM is the greatest

weight that can be lifted for three complete repetitions of an exercise whilst

maintaining correct form and technique. A 3-RM test corresponds to ~85% of an

individual’s 1-RM (577). The 3-RM rather than the 1-RM test was chosen for use in

this trial as previously it has been found that 1-RM testing can lead to injuries (578).

The protocol employed is presented below but follows what has previously been

published (578). Prior to 3-RM testing beginning participants completed a 5-minute

warm-up on an exercise bike. To determine 3-RM, each participant initially

performed a warm-up set of 8-10 repetitions with a light load. After the successful

completion of a further 6-8 repetitions at an incrementally heavier weight selected by

the instructing researcher and following a brief rest (~2 to 3 minutes), the workload

was increased incrementally until only three repetitions with correct technique could

Chapter 4

Page | 163

be completed. For each participant, the below formula, as employed by Wathen et al.

(579) and used previously in older adults (580), was used to calculate participants leg

and back strength 1-RM:

1-RM = 100 x (3-RM load) / (48.8 + 53.8 x e (0:075x3))

The short-term CV for repeated measurements of strength testing in our laboratory

was 2.04% for leg and 1.1% for back strength.

4.3.11.6 Dietary Assessment

Dietary data was collected through 24-hour dietary recalls at all time-points.

Participants were provided two blank food diaries a minimum of one week prior to

their testing appointment. Participants were asked to record all food and drink

consumed on a regular weekday and one weekend day. At the 12- and 24-week

assessments participants were instructed to complete the two dietary recalls on non-

training days. At the respective testing appointments completed food diaries were

reviewed using the ‘triple pass’ method to maximise the respondents recall of all

food and drink consumed. This procedure was based on that used by the Australian

Bureau of Statistics in the 1995 National Nutrition Survey, and is designed to

maximise the ability of respondents to recall everything consumed, ensuring an

adequate food diary was completed. Staff conducting these recalls had all completed

appropriate training in dietary assessment methods. Household measures (measuring

cups, plates, bowls and glasses) were used to help estimate food portion sizes. The

data collected from the 24-hour recalls was entered into FoodWorks Professional

(Version 8, Xyris Software, Queensland, Australia) to calculate total dietary energy

intake and dietary macronutrient composition using the AUSNUT 2011-13 database

including AusBrands and AusFoods.

Total energy intake (EI) was examined for under/over-reporting following collection.

Several equations exist in order to calculate an estimated basal metabolic rate

(BMRest), however, validation studies in overweight/obese populations have

previously found the Mifflin-St Jeor equation to give the most precise calculation of

Chapter 4

Page | 164

BMR in population groups with a BMI over 30 as opposed to other equations such as

the Schofield, Owen or Harris-Benedict equation (581). A physical activity level

(PAL) of 1.4 reflecting low activity and appropriately age-matched was selected

based on that published (582). This PAL was held constant over the intervention

period and used in the equations at all subsequent time points. To identify over- and

under-reporters at the group level, the modified Goldberg equation (583) was used to

calculate the specific lower and upper cut-offs for all participants as used by others

(584-586). Individuals greater or less than two standard deviations outside of these

upper and lower cut offs were classified as under and over-reporters respectively.

Participants within this range were classified as plausible reporters. Participants were

coded as over, plausible or under reporters at each assessment. A total of 91 and 95

participants from the PRT+ProD and PRT groups respectively returned the 24-hour

food recalls at baseline. Underreporting of energy intake at baseline was similar in

the PRT+ProD and PRT groups (PRT+ProD, 12.0%, n=11 vs PRT, 9.5%, n=9). Over

reporting of energy intake at baseline was also similar among both the PRT+ProD

(1%, n=1) and PRT (2%, n=2) groups with no differences between the groups. The

prevalence of under and over reporting remained consistent in both groups at 12- and

24-weeks (data not shown). Removing individuals who were classified as over- and

under-reporters did not change the results of the analysis and therefore all

participants were included in subsequent analysis.

Mean daily alcohol consumption was estimated from self-reported intakes over the

previous seven days. Previous research has shown that the seven-day alcohol recall

method is an accurate method to assess alcohol intake as it reduces the random

variability found in methods which estimate typical consumption over a longer

period of time (587). Participants were asked about their alcohol intake during the

previous seven days and were required to recall both the amount (using the

household measure they were familiar with e.g. wine glass, stubby, shot glass) and

the type of alcohol consumed (e.g. beer, wine, spirits). Average daily alcohol

consumption (g/day) was calculated using the summed volume of all alcoholic

beverages consumed over the preceding week divided by seven.

Chapter 4

Page | 165

Habitual Protein plus Protein from Whey Protein Supplements

The additional protein consumed from the whey protein supplements was calculated

for both training days and non-training days given the differing number of

supplements prescribed (one on non-training days and two on PRT days). Individual

compliance as a percentage at both 12-weeks and 24-weeks with the whey protein

supplements was multiplied by the dose of protein (either 20 or 40 g) with this

amount subsequently added to the habitual protein intake reported from the 24-hour

food diaries to calculate the g/day of protein consumed. The same method was used

to calculate g/kg/day at both 12- and 24-weeks with weight at both these respective

time points used in these calculations to determine the g/kg/day of protein intake

inclusive of the whey protein supplement at both 12- and 24-weeks.

4.3.11.7 Habitual Physical Activity

The Community Healthy Activities Model Program for Seniors (CHAMPS) physical

activity questionnaire was specifically designed to evaluate total leisure and

recreational physical activity time (hours per week) in older adults and found to be

reliable, valid and sensitive to change (588). Participants documented the frequency

and duration of their participation in a ‘typical week’ of a range of low, moderate,

and vigorous physical activities at baseline, 12- and 24-weeks of the study. These

results are reported as estimated kilojoules per week spent in aforementioned

activities.

4.3.11.8 Medical History, Health Status, Medication Use

All participants completed a lifestyle questionnaire to obtain information on

education background, current and previous employment details, history of diseases

or illnesses, family history of diabetes, smoking history, current medication and

dietary supplement use. Information on any alterations to or new medication

prescribed by the participants’ doctors was collected by research staff via the

monthly phone calls. Information recorded included medication name, dose

prescribed and daily quantity taken. Medications were categorised into diabetic,

hypolipidemic, anti-hypertensives, other cardiac agents such as anti-arrhythmic

drugs, osteoporotic, thyroid, anti-depressant/psychiatric, diuretics, thiazide diuretics,

Chapter 4

Page | 166

hormone replacement therapy, steroids, tamoxifen, and other (e.g. anti-inflammatory)

medications.

4.3.11.9 Compliance Assessment

Lift for Life® Exercise Training Cards

Compliance with the Lift for Life® PRT program was evaluated via self-completed

exercise cards. These cards were returned to researchers at the completion of the first

four weeks of training allowing the PRT programs to be reviewed. Training cards were

reviewed to confirm training programs were of adequate intensity, volume and that

appropriate progression could be applied. Following the collection of the first exercise

card, participants were asked to post subsequent exercise cards back at the completion

of one full card or every eight weeks.

Supplement Calendars

Compliance in taking the prescribed protein and vitamin D supplements was

evaluated via self-completed compliance calendars. These calendars were cross-

referenced by counting the remaining sachets of protein and vitamin D capsules

returned at the final testing appointment. The date supplements were commenced and

ceased along with the date returned were all recorded. The exact number of

supplements that should have been taken was able to be precisely calculated.

Compliance was calculated on a percentage basis as what was consumed divided by

what should have been consumed over the duration of the trial period for each

participant.

4.3.11.10 Adverse Events

Any adverse events associated with the exercise program or supplements were

recorded by research staff during the monthly phone calls to participants.

For this trial, an adverse event was defined as any health-related untoward or

unfavourable medical occurrence (sign, symptom, syndrome or illness) that

developed or worsened during the 24-week trial. All adverse events were assessed

for seriousness, causality and expectedness by the research staff and reported adverse

Chapter 4

Page | 167

events were categorised into adverse event, serious adverse event or unanticipated

problem based upon the National Institute of Ageing guidelines (589). Information

on any alterations to or new medication prescribed for any event by a treating

physician was collected by research staff with information including medication

name, dose prescribed, and daily quantity taken recorded.

4.3.12 Statistical Analysis

Detailed information related to the statistical analysis for this study will be provided

in Chapter 6.

Page | 168

Chapter 5

Lessons Learned Recruiting Older Adults with Type 2 Diabetes

to a Community-based Exercise and Nutrition

Randomised Controlled Trial

Chapter 5

Page | 169

5.1 Student Declaration

The PhD student was responsible for the 21-month recruitment campaign outlined in

the forthcoming Chapter. The student oversaw the implementation of each

recruitment strategy used and assessed its success or determined when a strategy

should be altered. The student was largely responsible for screening all expressions

of interest received and subsequent baseline appointment scheduling. The student

was responsible for the development, analysis and reporting contained within this

Chapter and for the development and subsequent publication of this Chapter as a

peer-reviewed journal article.

Chapter 5

Page | 170

5.2 Abstract

Recruiting participants into long-term community-based lifestyle intervention trials,

particularly adults with a chronic disease, is often slow and challenging. There is

limited data on successful recruitment strategies suitable for older adults with type 2

diabetes mellitus (T2DM) into community-based lifestyle programs, and no

information on cost estimates associated with recruitment. Herein we describe the

recruitment strategies used, the success of each approach and the costs associated

with the recruitment methods used in recruiting older adults with T2DM into a 6-

month community-based exercise and nutritional supplementation randomised

controlled trial (RCT). The Resistance Exercise, Vitamin D and Muscle Protein

Intervention Trial (REVAMP-IT) is a 24-week RCT targeting 200 adults with T2DM

designed to evaluate whether ingestion of a whey-protein drink plus vitamin D can

enhance the effects of progressive resistance training (PRT) on glycaemic control,

insulin sensitivity, body composition and cardiovascular health. Participants in this

RCT were randomly allocated to either: 1) a community-based PRT program

combined with whey protein and vitamin D supplements, or 2) solely the PRT

program. Recruitment strategies included state and local newspaper and radio

advertisements, targeted mail-outs, doctor and allied health referrals, community

presentations, web-based media and word of mouth. The number of expressions of

interest (EOI) received, participants screened and randomised in the trial, and how

they first heard of the study were recorded during the screening process. Reasons for

ineligibility or non-participation were also recorded plus the cost of each recruitment

method used. A total of 1,157 EOI were received over a 21-month period. Overall

959 (83%) individuals were screened and found to be ineligible for the trial or chose

not to participate. As a result, 198 participants were randomised to the 24-week

intervention. The most effective recruitment strategies were targeted mass mail-outs

(39% of the total participant sample), state (27%) and local (15%) print media.

Recruitment expenditure totalled AUD$40,421, AUD$35 per enquiry and AUD$204

per eligible participant. Targeted mail-outs and state print media were the most

expensive strategies, accounting for 38% of total expenditure. To recruit around 200

older adults with T2DM into a community-based lifestyle trial in a timely manner,

Chapter 5

Page | 171

ensuring an adequate budget is allocated to recruitment is paramount as targeted

mail-outs and state/local print media were the costliest yet most effective strategies.

Chapter 5

Page | 172

5.3 Introduction

The success of RCTs is dependent on effective recruitment of the target population.

One of the key challenges associated with conducting intervention trials that target

populations with specific medical conditions such as people with T2DM, is the

successful recruitment of an adequate number of participants within budget and

established timelines. Failing to recruit the required number of participants impacts

the statistical power and adversely impacts on the internal and external validity of the

trial. Delays in recruitment can also extend the trial duration and result in an increase

in trial and recruitment costs.

Recruitment of people with T2DM into a lifestyle modification trial involving an

exercise and/or a nutritional intervention can be particularly challenging because it

often involves identifying participants that must first meet certain inclusion criteria

(e.g. currently inactive) and who are also motivated to change their behaviour (e.g.

engage in regular exercise). Despite the clear evidence that physical activity (PA)

and diet are key elements in the management (and prevention) of T2DM, individuals

with this condition are typically inactive and have poor dietary habits (590, 591).

Therefore, it is difficult for the target population to make a commitment to make the

behavioural changes required in these types of studies. Exercise and dietary

intervention trials can be long and demanding, requiring significant change to an

individual’s daily routine. Common barriers and reasons for not participating in

exercise trials reported by individuals include inconvenience, a lack of time to

dedicate when managing work/family commitments and a lack of understanding of

the potential health benefits of participating in such trials (592, 593). A review of

recruitment strategies for participants into RCTs revealed that methods which do not

directly target the population of interest (e.g. T2DM patients), advertisements which

are not effective in conveying the key objectives of the research or which fail to

accurately inform of the potential personal health benefits to participation, can all

negatively impact on recruitment (594). Therefore, identifying the most effective

recruitment strategies which overcome the aforementioned barriers to participation

and which appeal to potential participants as well as convey an appropriate level of

information is crucial to successfully achieving recruitment goals.

Chapter 5

Page | 173

At present, there is limited literature on successful recruitment strategies suitable for

older adults with T2DM into community-based exercise and nutrition programs with

no information on cost estimates. There has only been one paper recently published

describing the experiences and strategies used to recruit type 2 diabetic patients into

an RCT to assess the efficacy of an automated, interactive voice-response telephone

intervention to promote physical activity behaviour (593). Therefore, the aim of this

chapter is to describe recruitment strategies used to recruit older adults with T2DM

into a 6-month community-based exercise and nutrition research intervention.

Strategies were defined as successful if they were effective in generating a greater

number of enquiries to the trial and a higher proportion of eligible participants

compared to other strategies. A secondary aim is to assess the costs associated with

the recruitment methods used. By providing a detailed report of this trials recruitment

experiences it is hoped this information will help to inform future intervention

studies wishing to recruit older adults with T2DM to community-based exercise

and/or nutrition programs.

5.4 Methods

5.4.1 Study Overview

A detailed description of the protocol for this trial is provided in Chapter 4 and has

previously been published (595). Briefly, this study was a 24-week RCT in which

participants were randomly allocated to either: 1) the Lift for Life® community-based

progressive resistance training (PRT) program combined with additional whey

protein and vitamin D, or 2) the Lift for Life® PRT program alone. The primary

outcomes were glycated haemoglobin (HbA1c) and homeostasis model assessment 2

(HOMA-2) of insulin sensitivity and beta-cell function. Secondary outcome

measures included changes in body composition, muscle strength, blood pressure,

blood lipids, adipokines and inflammatory markers, growth factors, health related

quality of life and cognitive function.

All participants enrolled in the trial were asked to complete the Lift for Life® PRT

program in local community health and fitness centres which involved training twice

a week for the first eight weeks and three times a week thereafter. Training sessions

Chapter 5

Page | 174

were supervised by qualified trainers, lasting approximately 45 to 60-minutes and

consisted of moderate- to high-intensity resistance training (3 sets of 8-10

repetitions) targeting all major muscle groups and with an emphasis on progressive

overload (increments in weight of 2 to 10%). All participants were charged a fee by

their local health and fitness provider to undertake the program, but were eligible for

reimbursement up to the value of AUD$240 at the completion of the study based on

their level of compliance (595).

In addition to the above training commitment, those randomised to the Lift for Life®

plus supplement group were provided with a supply of a whey-protein enriched

powder and vitamin D supplements with the instruction to consume two vitamin D

capsules (1,000 IU of vitamin D per capsule) each day, plus prepare and consume a

whey protein drink (20 grams of protein once per day on non-training days plus 20

grams after each Lift for Life® training session). The PRT alone group received no

additional powder or supplements.

Throughout the trial, participants were required to attend Deakin University for

approximately 2 hours on two occasions (baseline and 24-weeks). Research staff

conducted on-site testing at each health and fitness centre after 12-weeks. A rested

morning (8-10am) venous blood sample was additionally collected from each

participant’s antecubital vein at an accredited pathology laboratory following an

overnight fast on three occasions over the 24-week period (baseline, 12- and 24-

weeks).

5.4.2 Ethics

This trial was managed by staff within the Institute for Physical Activity and

Nutrition (IPAN) Research at Deakin University Burwood, Melbourne, Victoria,

Australia. The study was approved by the Deakin University Human Research Ethics

Committee (HREC 2013-050) (Appendix 4), and is registered with the Australian

and New Zealand Clinical Trials Registry (ACTRN12613000592741). All

participants provided written informed consent prior to their commencement in the

study.

Chapter 5

Page | 175

5.4.3 Funding

This project was funded by a grant from the National Health and Medical Research

Council Project (APP1046269). The whey-protein powder was provided by

OmniBlend (Campbellfield, Victoria, Australia) and the vitamin D supplements

(Ostelin) by Sanofi-Aventis Australia Pty Ltd (Macquarie Park, New South Wales,

Australia).

5.4.4 Sample Size Calculations

As reported in Chapter 4, it was estimated that a sample size of 168 participants

would provide the study with 90% power (P<0.05 two-tailed test) to detect a 0.5%

absolute difference for the change in HbA1c levels between the groups, assuming a

conservative standard deviation of 1.1%. For insulin sensitivity, a sample size of 140

would be required to detect a 0.7 difference for the change in HOMA-2 insulin

resistance between the groups at a power of 90%, assuming a conservative standard

deviation of 1.2. To compensate for an estimated 20% drop-out rate, it was

calculated that 202 participants would be recruited to the study and randomised 1:1

to either of the two groups (101 participants per group).

5.4.5 Screening Procedure and Inclusion/Exclusion Criteria

As reported previously (595) and detailed extensively in Chapter 4, eligibility for this

study was assessed using a two-step screening process. Briefly, participants were

screened via a telephone questionnaire and ineligibility was based on the following

criteria: 1) aged <50 or >75 years of age; 2) HbA1c >10%; 3) current or prior

participation in a structured resistance training programme >once per week or

moderate-intensity physical activity ≥150 min/week in the previous 3-months; 4)

vitamin D or calcium supplement use >500 IU/day and >600 mg/day, respectively, in

the previous 3-months; 5) severe orthopaedic, cardiovascular or respiratory

conditions that would preclude participation in an exercise programme, or those with

absolute contraindications to exercise, according to American College of Sports

Medicine guidelines (596); 6) renal impairment (estimated glomerular filtration rate

(eGFR) <45 ml/(min 1.73 m2)) or disease; 7) regular use of protein supplements; 8)

conditions that may affect vitamin D or calcium metabolism; 9) current smoker, or

Chapter 5

Page | 176

10) body mass index (BMI) >40 kg/m2. Participants who passed the initial telephone

screening were then required to obtain approval from their doctor to clear them of

any medical conditions contraindicated to exercise, based on ACSM guidelines

(Appendix 6). Participants were also required to provide a fasted, morning blood

sample to confirm that their HbA1c level was <10%.

5.4.6 Recruitment Strategies

During the trial establishment period and prior to beginning the recruitment

campaign, chief investigators and lead trial staff met repeatedly to discuss which

strategies should be used to recruit participants into this trial. These meetings were

used to brainstorm and plan the various recruitment strategies to be used. Those

adopted first were ones which had been used previously by trial staff. These

included local newspaper advertisements, flyers/posters and GP presentations.

Within the first 2 to 3-months, recruitment of participants was modest with very few

expressions of interest received from these strategies alone and necessitated a change

in the recruitment plan. At this point, lead trial staff consulted with the Deakin

University public relations and communications team to discuss the re-development

of trial advertisements and trial communications to a clear, informative and

appealing style. Following these meetings, lead trial staff again devised additional

recruitment strategies and a range of approaches, in addition to those already in use,

were implemented to recruit participants from both metropolitan Melbourne and

surrounding regions in Victoria, Australia such as the Werribee, Geelong and

Mornington areas. Such strategies included state and local newspaper and radio

advertisements, targeted mail-outs through the National Diabetes Support Scheme

(NDSS) member database, GP and allied health referrals, community presentations,

web-based media and word of mouth. A brief overview of each of the recruitment

approaches used is below. Specific information relating to the method of recruitment

for each participant was obtained during the participant’s first enquiry to the study.

State Print Media

A total of six paid advertisements were placed in key state-wide newspapers with the

advertisements ranging in size, colour and placement within each paper. The content

Chapter 5

Page | 177

of these advertisements included an eye-catching headline, a brief and simple

description of the trial, including the potential health benefits to participants

associated with participation, and relevant contact details as shown below in Figure

5.1. The cost for each of the advertisements ranged from AUD$1,700 to AUD$3,000.

Figure 5.1: Example of the study advertisement in state print media (newspaper).

Local Print Media

Twelve paid advertisements, similar in format to the state-based advertisements as

shown below in Figure 5.2, were also placed in a range of local municipality

newspapers throughout the recruitment period. These newspapers are delivered

weekly to each household within a given area (municipality). In general, these

advertisements were placed in the same paper fortnightly over a 6-week period,

however, occasionally single advertisements were used to trial and target one locality

to gauge the level of interest. Local paper advertisements cost AUD$400 to

AUD$500 each, depending on the size and placement of the advert within the paper.

Several free advertisements were also placed in local newspapers in the community

‘What’s On’ section (limited to 40 words). These free advertisements were used as a

Chapter 5

Page | 178

buffer to continue the recruitment campaign between paid state and local media

advertisements.

Figure 5.2: Example of the study advertisement for local print media (newspaper).

Radio Advertising

The study was also advertised on a state-wide radio station. Forty-five 15-second

advertisements, which were drafted by study researchers and developed by the radio

station, were played over a five-day period (Monday to Friday). The radio station

was selected based upon the demographics of the majority of their audience (e.g.

middle aged and older adults). The advertisements were initially played during the

‘Seniors Spotlight on Trials and Studies’ segment and following this were spread

sporadically over the course of the day ranging from 6am through to 10pm.

Advertising this trial on Magic radio costs AUD$990 for the forty-five 15 second

advertisements.

Targeted Mail-outs

The research team gained approval from Diabetes Australia, a non-government

organisation, to access the NDSS database, which is a federally-funded register of

Australians with diabetes that was initiated in 1987. Briefly, the aim of NDSS is to

Chapter 5

Page | 179

enhance the capacity of people with diabetes to understand and self-manage their

condition, and to provide relevant information, support and access to essential

products at subsidised prices. In Victoria, the NDSS register contains the contact

detail of more than 85% of all clinically confirmed cases of diabetes, which includes

type 1, type 2 and gestational diabetes (597). Since 2001, individuals joining the

NDSS have been asked whether they would be willing to be informed of any

opportunities to participate in research. Only those who consented to be contacted

were eligible to be invited to participate in this study. Because of the extensive nature

of the database, the research staff first used the online Australian Diabetes Map

(http://www.diabetesmap.com.au/), which is an interactive national diabetes

prevalence map established and regularly updated by NDSS and the Australian

Bureau of Statistics (ABS), to identify local government areas and the postcodes

within these areas with a reported high prevalence of individuals with T2DM.

Thereafter, the research team contacted NDSS who were responsible for identifying

the number of individuals within each of the identified postcodes that had T2DM,

who were aged 50-75 years and reported that they were not currently taking insulin

to manage their condition. A letter of invitation to participate in the study, that was

prepared by the research staff but sent by NDSS, was then forwarded to all

individuals that fulfilled the necessary inclusion criteria (Appendix 8). Nine mail-

outs were conducted in total and the number of letters sent per mail-out ranged from

80 to 5,000 depending upon the number of registrants within a target area. The cost

of a direct mail-out was approximately AUD$1.80 per letter. This cost increased or

decreased marginally depending on the number of individuals contacted (the greater

the number of letters sent the cheaper the cost).

Referrals from GPs and Allied Health Professionals

General practitioners, endocrinologists and other relevant health professionals (e.g.

diabetes educators, dietitians and pharmacists) identified from relevant directories

(e.g. Yellow Pages), hospitals and profession specific association websites who were

based in a 45km radius of Melbourne were sent information packs via the mail that

provided details about the trial. Included in these packs was a one page study

summary, which outlined the aims, commitment required and the potential benefits

Chapter 5

Page | 180

to participants, and the key eligibility criteria. They also received trial flyers and

posters (discussed below) and were asked to place these on notice boards and/or

distribute them directly to relevant patients. Connections with several Medicare

Local groups (regional organisations who co-ordinate improvements in healthcare for

designated populations groups and oversee front line primary healthcare services)

were also made during the establishment of this trial. Specifically, the Diabetes

Australia map, mentioned previously, was used to identify areas with high

prevalence of T2DM. The respective Medicare Local groups were subsequently

contacted to inform them of the trial and were provided trial information and

advertisements and requested to include these in any communications with GPs or

allied health providers.

Flyers and Presentations

Flyers and posters (Figure 5.3) were placed in prominent public and relevant

locations such as fitness clubs, libraries, senior citizen centres, pharmacies,

community houses and retirement villages. In addition, three presentations were

made to a range of audiences; one to a diabetes support group where the attendees

were a mix of accredited Diabetes Educators, patients and carers, one to GPs at a

Medicare Local meeting and another at the Northern Accredited Diabetes Educators

annual general meeting.

Figure 5.3: An example of the study recruitment flyer.

Chapter 5

Page | 181

Website Advertisement

Information about the study was posted on the Lift for Life®, Diabetes Victoria,

Diabetes Australia, Fitness Australia, Deakin University’s Centre for Physical

Activity and Nutrition and the Australian Centre for Behavioural Research in

Diabetes websites. These listings were placed on respective websites at the beginning

of the recruitment campaign and requested to be removed from the website at the

completion of recruitment. There was no cost associated with posting information on

these websites.

Social Media

A pay-per-click advertisement (AUD$0.03 per click at a capped limit of AUD$500)

was placed on the social media domain Facebook five months into the recruitment

campaign. This advertisement was 20 words long and used key words to capture

potential participant’s attention. The adverts appeared on an individual’s Facebook

page whose age fell into the eligible age range for the trial and a postcode pre-

identified to be within a 15km radius of Deakin University. An individual who

clicked on an advertisement was directed to the Lift for Life® website for further

information about the trial. The cap of AUD$500 was not reached during the

recruitment period but did allow for ~16,600 clicks to the advert.

Word of Mouth

Participants enrolled in the trial were actively encouraged to refer family, friends or

colleagues with T2DM into the study. In addition, participants with T2DM who

enquired but were ineligible for other research studies being conducted within IPAN

and who had consented to be contacted for any other research studies, were contacted

by research staff via telephone to determine their interest and eligibility in regards to

participating in this trial.

5.4.7 Data Collection and Analysis

The number of expressions of interest (EOIs), participants screened and included in

the trial, and how they heard about the study was recorded by the research staff

throughout the recruitment process. Reasons for ineligibility or non-participation in

Chapter 5

Page | 182

the trial were also recorded. These were categorised into one of five categories;

health-related, physical activity status, medication/supplement use, travel or age.

Response rates were reported as the number and percentage of participants both

interested in and recruited into the trial. Recruitment yield was calculated as the total

number of participants recruited divided by the number of EOIs. The success of each

recruitment strategy was determined from the number of participants recruited

divided by the number of EOIs from each strategy expressed as a percentage.

Recruitment rates were also calculated as the average number of participants

recruited and randomised per month throughout the recruitment phase. Results were

also split by gender. The cost of each recruitment method used was calculated by

dividing the total amount spent on a given strategy by: 1) the number of EOIs

generated for each strategy, and 2) the total number of eligible participants the

strategy was responsible for recruiting (e.g. cost per participant recruited).

5.5 Results

5.5.1 Recruitment

Recruitment for this trial was intended to be completed within 12-months. This was

extended to a period of 21-months (February 2014 to October 2015) due to a lower

than expected recruitment rate. In total, 1,157 EOI were received from which 198

older adults with T2DM were deemed eligible for the trial and subsequently

randomised. This represents 98% of the original specified target sample size of 202

participants. The results of the recruitment campaign are presented below and

include the number of EOIs whom were determined ineligible or chose not to

participate in the trial, the recruitment yield for each strategy used, the recruitment

timeline and a cost analysis of each of the strategies employed.

5.5.2 Response Rates and Reasons for Ineligibility or Non-participation

In total, 516 of 1,157 (45%) EOIs were found to be ineligible for this trial following

the initial screening. As shown in Table 5.1 the most common reasons for

ineligibility included being too physically active (26%), taking vitamin D

supplements at a dose of >500 IU/day (25%) and management of T2DM by way of

insulin therapy (11%).

Chapter 5

Page | 183

Table 5.1: Reasons participants were deemed ineligible for the trial.

Reason for Ineligibility Total Ineligible, n (%)

Health-related 115 (22%)

Not diagnosed with T2DM 28 (5%)

Any medical condition contraindicated to PRT 18 (3%)

BMI >40kg/m2 30 (6%)

HbA1c >10% 14 (3%)

Presence or indication of kidney disease 8 (2%)

Current smoker 17 (3%)

Physical Activity Status 135 (26%)

Meeting/exceeding Physical Activity Guidelines 135 (26%)

Medication or Supplement Use 192 (37%)

Prescribed insulin for management of T2DM 59 (11%)

Taking Vitamin D supplements >500 IU/day 128 (25%)

Taking dietary protein supplements 5 (1%)

Travel 53 (10%)

Travel plans 53 (10%)

Age 21 (4%)

Aged <50 or >75 years of age 21 (4%)

Total 516 (100%)

Presence or indication of kidney disease was considered if eGFR <45 mL/min. Potential participants were excluded if meeting or exceeding National Physical Activity Guidelines of 150 minutes of moderate to vigorous physical activity or participating in greater than one strength training session per week. Participants were excluded if responded yes to taking dietary protein supplements at a protein content of <10g per serve, as specified on the products nutrition information panel.

A total of 443 participants chose not to participate in the trial. As shown in Table 5.2,

189 (43%) were unable to meet the requirements of the trial based on the

inclusion/exclusion criteria and a further 127 (29%) were lost to follow-up following

their initial enquiries into the program. In total 62 (14%) participant could not meet

the financial obligations of committing to the PRT program and 61 (14%) did not

live within travel distance to Deakin University or a have a training facility within

Chapter 5

Page | 184

their immediate area. Only 4 (1%) participants chose not to participate as they did

not wish to take supplements of any form.

Table 5.2: Number and proportion (percentage) of expressions of interest who chose not to participate in this trial and the reasons provided for non-participation.

Reason for non-participation Total, n (%)

Unable to meet requirements of the trial 189 (42.7%)

Unable to afford the Lift for Life® PRT program 62 (14%)

Not willing to consume supplements 4 (0.9%)

Lost to follow-up following initial enquiry 127 (28.7%)

Not living within a reasonable travel distance to trial sites 61 (13.8%)

Total 443 (100%)

5.5.3 Recruitment Return by Recruitment Strategy

As presented in Table 5.3, targeted mail-outs were the most successful approach for

recruitment, generating 479 (42%) of the 1,157 EOIs, from which 78 participants

were eligible for the trial (39% of those randomised). State-wide free and paid

advertisements generated the second greatest number of enquiries (n=326, 28% of

total), from which 54 participants were eligible and subsequently randomised.

Advertising in local newspapers (both paid and unpaid) generated 173 enquires

(15%), with 27 of these enquiries deemed eligible, whilst website advertisements

produced 96 enquires (8%) that led to 19 participants randomised. All other forms of

recruitment generated a low number of enquires and resulted in only 20 eligible

participants in total: word of mouth (n=6, 3%); referral from health professionals

(n=10, 5%); flyers/presentations (n=4, 2%), with zero eligible participants from radio

advertising and social media.

Chapter 5

Page | 185

Table 5.3: Number and proportion (percentage) of expressions of interest and participants deemed eligible for the trial based on the various recruitment strategies.

Eligibility Status

Eligible Expressions of Interest

Recruitment Strategy n % n %

State Print Media 54 27 326 28

Local Print Media 27 14 173 15

Radio Advertising 0 - 6 0.5

Targeted Mail-outs 78 39 479 41

Allied Health Referrals 10 5 19 2

Website Advertising 19 10 96 8

Social Media 0 - 5 0.4

Flyers/Community Presentations 4 2 11 1

Word of Mouth 6 3 37 3

No Record 0 - 5 0.4

Total 198 100 1157 100

5.5.4 Recruitment Return by Gender and Age

The total number of male participants recruited for the trial exceeded female (n=128

and n=70, respectively) resulting in a gender distribution among the trial population

of 65% male and 35% female, respectively. This male versus female distribution was

similar overall when examining expressions of interest received and those deemed

ineligible and eligible (Table 5.4). Interestingly, the only recruitment strategy that

resulted in a higher number of females (n=9) than males (n=1) was allied health

referrals, but the total number of referrals from this method was very low (Figure

5.4). In terms of the age distribution, 39% of all eligible participants were aged 50-59

years, 53% were aged 60-69 years with the remaining 11% aged over 70 years.

Chapter 5

Page | 186

Table 5.4: Number and proportion of men and women screened and deemed eligible or ineligible for the trial.

Eligibility Status

Eligible n=198

Ineligible n=959

Total Screened n=1157

n % n % n %

Male 128 65 541 56 669 58

Female 70 35 418 44 488 42

Males and females who chose not to participate were included in the ineligible figures for this analysis only.

Figure 5.4: The number of male and female participants eligible for this trial and the recruitment strategies they responded from.

5.5.5 Recruitment Timeline

As previously mentioned, recruitment for this trial spanned a 21-month period.

Figure 5.5 illustrates the number of participants randomised per month over this

period. On average, nine participants were randomised per month. The peaks on the

Chapter 5

Page | 187

graph correspond with the implementation of State based newspaper advertisements

(April, May, August, June, November 2014 and February 2015) and targeted mail-

outs through the NDSS (September, October and December 2014 and May, July,

September and October 2015). Figure 5.6 clarifies the timing of each recruitment

strategy. As shown, not all strategies were implemented continuously throughout the

campaign, however, several methods of recruitment were often in place at the same

time. This may have meant a participant was exposed to more than one recruitment

strategy such as an advertisement, recruitment flyer or mail-out however, only the

first recruitment strategy reported was recorded on the screening form.

Figure 5.5: Number of participants randomised to this trial each month for the duration of the recruitment period.

Chapter 5

Page | 188

Figure 5.6: Timeline and timing of recruitment strategies implemented during A) 2014 and B) 2015. Black square represents active recruitment strategies. P, presentation; WOM, word of mouth.

5.5.6 Recruitment Cost

Table 5.5 provides recruitment yield by cost for each recruitment method used in this

trial. Table 5.5 is presented from most to least expensive per eligible participant

recruited. Expenses included in the cost analysis do not include staff costs. Staff

costs were not included in the analysis as they were not tracked by each method and

were not able to be differentiable from other tasks performed in the administration of

the trial. The costliest recruitment methods were both state print media and NDSS

mass mailing which both accounted for 38% of the total recruitment budget. Overall,

the total costs attached to these two recruitment strategies were AUD$15,360 and

AUD$15,327 respectively. Cost per eligible participant was greatest for state print

media at AUD$284 with 54 participants recruited. By comparison the higher yield of

eligible participants from the NDSS mass mailing meant the cost per eligible

participant was lower at AUD$196. Costs per eligible participant for local print

Chapter 5

Page | 189

media were similarly high to state print media at $AUD239 however, due to the

small number of adverts placed the overall cost of AUD$6,445 was only 16% of the

recruitment budget. Printed (paid) trial flyers and posters which were used at

community presentations and provided to allied health professionals was the

cheapest form of paid recruitment, however, of paid methods it also generated the

least number of eligible participants. Radio advertising and social media, whilst

generating enquires into the study, were found not to be effective methods of

recruitment for this trial as no eligible participants were recruited from these

approaches. Free methods of recruitment including focused website advertising and

word of mouth were responsible for generating 25 eligible participants for the trial,

and as such formed an important part of trial advertising and recruitment in their own

right as there was no expense to the trial other than staff costs. The overall

recruitment costs for this trial were AUD$40,421, which equated to AUD$35 per

enquiry and AUD$204 per eligible participant.

Table 5.5: The total costs, proportion of total recruitment costs, the number of eligible participants plus cost per participant for each recruitment strategy in this trial.

Eligible

Participants (n)

Cost per Eligible

Participanta

Total Costa

% of Total Recruitment

Costs

State Print Media 54 $284 $15,360 38

Local Print Media 27 $239 $6,445 16

Radio Advertising 0 - $990 2.5

Targeted Mail-outs 78 $196 $15,327 38

Allied Health & Flyers/ Presentations

14 $128 $1,799 4.5

Website Advertisement 19 $0 $0 0

Social Media 0 - $500 1

Word of Mouth 6 $0 $0 0

Total 198 $40,421 100 aStaff costs are not included in this analysis. All costs of recruitment are in Australian Dollars. Costs per eligible participant was calculated by dividing the total cost by the number of eligible participants.

Chapter 5

Page | 190

5.6 Discussion

In this 6-month community-based exercise and dietary supplementation trial in older

adults with T2DM, a total of 1,157 EOI were received over a 21-month recruitment

period from which 198 participants (17%) were deemed eligible and subsequently

randomised. These figures reflect an average randomisation rate of nine participants

per month. The most effective recruitment strategies for this trial were targeted mail-

outs to registered members of the NDSS database (39% of the total sample) and State

print media (27%). Overall, recruitment expenditure totalled AUD$40,421, with the

aforementioned two most effective recruitment strategies each costing approximately

AUD$15,000, the combination of which corresponded to 76% of all expenditure. In

total, recruitment costs equated to AUD$35 per enquiry and AUD$204 per eligible

participant. Collectively, these findings highlight the significant challenges

accompanying recruitment of T2DM patients into a community-based lifestyle

modification trial involving exercise and a nutritional supplement.

5.6.1 Eligibility Rate

Of all the 1,157 EOIs for this trial, only 198 participants were found to be eligible,

equating to a 17.1% success rate. This rate of recruitment is similar to a 17.9%

recruitment rate that was reported in the Look AHEAD (Action for Health in

Diabetes) trial. The aim of this large multi-centre RCT was to investigate the effects

of a lifestyle intervention aimed at reducing bodyweight by 7% through increased

physical activity (PA) and a reduction in calorie intake on a range of health

outcomes, including incidence of heart attacks, stroke and cardiovascular-related

death in overweight or obese adults with T2DM (598). Comparing the recruitment

success rates of different trials can be problematic, as factors such as differences in

the inclusion/exclusion criteria will influence recruitment rates. Nevertheless, other

exercise intervention trials recruiting sedentary overweight and obese post-

menopausal females have reported recruitment rates ranging from 2% to 20% (599-

602). Thus, the recruitment rate in this trial appears to be consistent with previous

intervention trials in older adults and provides a realistic target for future exercise

based RCTs designed to target older adults with T2DM, particularly where the

Chapter 5

Page | 191

design of the trial has similar eligibility criteria and involves a comparable level of

commitment.

5.6.2 Success of Recruitment Strategies

The recruitment strategies used in this study were diverse and varied depending on

their success as the recruitment phase evolved. Mass mail-outs through the NDSS

was the most successful strategy for recruiting participants with T2DM into this trial.

These letters were responsible for recruiting 39% of all eligible participants. While it

is difficult to compare the success rate of our mass mail-out campaign to other trials

given the varying eligibility criteria, our rate is slightly above that reported by the

Diabetes Prevention Program (DPP) conducted in the United States. In the DPP 29%

of its randomised participants were recruited via direct mass mail-outs into their

multi-centre RCT aimed at discovering whether modest weight loss through dietary

changes and increased physical activity or treatment with the oral diabetes

medication could prevent or delay the onset of T2DM in those at high risk for the

condition (603). The ability of mass mail-outs to target a large number of participants

at relatively low cost, combined with the reported success of this strategy to yield a

high number of eligible participants in both healthy and clinical populations, has in

recent years led to mass mail-out becoming an integral part of many RCTs

recruitment plans (593, 604-606). From our experience, when implementing mass

mail-outs as a recruitment strategy it is the choice of the mail-out lists which is likely

to contribute to its effectiveness. For instance, in our trial we were able to selectively

request the NDSS target members of the registry who met three of our inclusion

criteria (T2DM diagnosis, current management of condition (prescribed only oral

hypoglycaemic medication if any) and age). The NDSS database also allowed letters

to be sent only to local government areas and postcodes which trial staff had

identified as areas with a high prevalence of T2DM. We believe that this selective

communication to a tailored list of potential participants in specific areas greatly

assisted in the efficient identification of eligible participants.

State and local print media were the second and third most prolific methods of

recruitment, yielding 27% and 14% of participants, respectively. Other RCTs using

Chapter 5

Page | 192

state and local print media have reported similar recruitment rates from such

advertisements (603, 607, 608). It has previously been reported that the most

efficient and comprehensive recruitment campaigns employ several overlapping

strategies simultaneously, with constant assessment of the strategies employed to

ensure appropriate allocation of resources to the most successful strategies (609).

Trial staff remained diligent tracking and assessing the effectiveness of each

recruitment strategy with only those with the greatest yield of eligible participants

persisted with. This may have resulted in the success rate of the mass mail-outs and

state media being over reported as these strategies were employed repeatedly

compared to those that resulted in a smaller and slower yield of eligible participants

(e.g. web advertising, allied health, word of mouth, flyers and community

presentations). Previously, it had been reported that print media including direct

mail-outs plus newspaper advertisements are two strategies which are more effective

at capturing the attention of an older adult demographic (603). A finding which was

also experienced in this trial with each of the alternate strategies employed; web

advertising, allied health, word of mouth, flyers and community presentations, radio

and social media, each recruiting less than 10% of participants.

Interestingly, medical and allied health referrals were not successful in recruiting

older adults with T2DM into the trial, a result which has also been noted previously

as a less effective recruitment strategy in a previous large community-based

Australian trial in older adults and the elderly (604). In our trial, it cannot be

determined whether this was due to medical/allied health professional’s lack of

communication about the trial, poor distribution of trial advertising material and/or if

there was a general lack of interest in participating in an exercise program from

individuals attending these appointments. Based on our experiences, it is a

recommendation for future trials to consider practice-wide presentations which

eliminates the burden on health professionals to convey trial information and may

result in a greater percentage of trial participants recruited from this approach.

Chapter 5

Page | 193

5.6.3 Recruitment Cost

In total, AUD$40,421 was spent on all recruitment strategies combined, which

equates to an average of AUD$204 per eligible participant. Very few detailed cost

analyses of other large-scale RCTs recruitment campaigns exist making it difficult to

comparatively assess the methods and associated costs of recruiting eligible

participants. However, a trial investigating weight gain prevention in young adults

reported the average cost of recruiting one participant was US$233 in 2014 (605).

Similarly, a study investigating the recruitment of minority women into the Women’s

Health Trial which also utilised targeted mass mail-outs reported per participant

recruitment costs ranging from US$100 to $144 in 1998 (610). In contrast, the DPP

trial which randomised 3,819 participants spent on average US$1,075 per

randomised participant (191). The recruitment strategies employed by the DPP trial

make comparing costs to our trial difficult as the DPP employed a public relations

agency to help direct recruitment who worked alongside a recruitment committee

with their recruitment phasing spanning a total of 3-years and costing $US4,105,000

(611).

Despite State print media acquiring the second highest number of eligible

participants for our trial, it was the most expensive method, costing a total of

AUD$15,360 or AUD$204 per eligible participant. Local print media advertising

costs were considerably lower than State media however, the small yield in eligible

participants (14%) resulted in this method being the second most expensive

recruitment strategy. Mass mail-outs through the NDSS, a strategy employed within

the first eight months of our recruitment campaign, produced a high eligibility to

response ratio resulting in this approach being implemented multiple times over the

recruitment period. Whilst this approach was the second most expensive strategy

used (AUD$15,326) and accounted for 38% of the total dollars spent on recruitment,

as indicated the large yield of eligible participants resulted in this approach costing

AUD$196 per participant. A greater comparison of recruitment methods and

associated costs will be able to be made when other investigators publish such data.

Chapter 5

Page | 194

5.6.4 Reasons for Ineligibility

Of all the EOIs received for our trial, 45% (n=516 participants) were deemed

ineligible. Of these, 26% was due to the participants being classified as too

physically active (e.g. meeting or exceeding the Australian National Physical

Activity Guidelines). This result is not unexpected as there is recent evidence that

approximately 30% of adults with T2DM were found to meet physical activity

guidelines (590). Further, our findings are comparative to the 26% exclusion for

physical activity reported by another recent RCT recruiting T2DM patients to an

automated, interactive voice-response telephone intervention to promote physical

activity behaviours in adults with T2DM (593).

5.6.5 Reasons for Choosing Not to Participate

Reasons for non-participation in RCTs for people that initially enquire are frequently

missing from recruitment publications, but are important to consider as these factors

may offer valuable insight into areas of trial design that may be improved upon to

enhance recruitment to future trials. In our trial, 443 potential participants chose not

to participate following a description of the trial and requirements of participating

from trial staff over the telephone, or after reading the plain language statement; 43%

felt the requirements of the 24-week PRT program was too much of a commitment.

A further 14% cited not being able to bear the financial costs (approximately

AUD$300-700 depending on training site) associated with joining the Lift for Life®

resistance training program, despite the incentive of a monetary reimbursement at the

completion of the trial based upon each participant’s level of compliance to the

exercise program (AUD$240 if exercise compliance was 80% or above).

Unfortunately, no information was collected on the potential effects of the monetary

reimbursement acting as an incentive to participate in the trial. Similarly, the effect

that having to pay for the Lift for Life® training program had on people’s reluctance

to participate in the trial was also not assessed.

5.7 Limitations

There are a number of limitations that should be considered when interpreting the

findings from this chapter. Our study specifically targeted older adults with T2DM

Chapter 5

Page | 195

for an exercise and dietary supplementation trial and so the results and experiences

reported should be tempered when applying to other trials recruiting alternate clinical

populations. The effects of the monetary reimbursement on incentive to participate in

the trial were not assessed and future studies need to ask these types of questions to

assess the effects of such incentives on willingness to participate in research. The

recruitment strategies found to be most successful in sourcing eligible participants

for this trial were also the ones which were extensively repeated multiple times,

potentially biasing the findings. Similar messages were used for all of the

advertisements and as such no data is available for what type of message may be

most salient to older adults with T2DM. Additionally, only one recruitment strategy

was recorded per expression of interest leaving open the potential for cross-

contamination from different recruitment methods. For example, some participants

who received a mail-out may also have been exposed to a trial advertisement in web

or print media format, however, with only one form of recruitment noted for each

expression of interest the effects of exposure to two recruitment strategies remains

unknown. In the future, it would be useful for other trials to include such a question

in order to determine the benefits of multiple exposures to recruitment methods.

5.8 Conclusion

This chapter aimed to address the practical considerations surrounding recruitment of

older adults with T2DM into a RCT involving lifestyle modification. Recruitment

required continual sustained efforts and necessitated flexibility within the recruitment

strategies used to ensure the recruitment targets were being achieved. Of the vast

array of recruitment approaches employed, strategies which were found to be

ineffective at recruiting participants to this trial were radio advertising and social

media. Successful recruitment approaches were found to be those which directly

targeted the patient population of interest. The most successful strategy was targeted

mail-outs to members of the NDSS database, with state print media the second most

effective strategy. Overall, AUD$40,421 in total was spent on recruiting participants

to this trial, costs per randomised participant were AUD$204. The reporting of this

trials recruitment experiences offers several lessons about strategies and costs for

Chapter 5

Page | 196

future trials looking to recruit T2DM patients for trials involving lifestyle

modification.

Future Recommendations

An understanding of the specific population being recruited is key to identifying the

optimal strategies to reach trial demographics. It is important to design an

appropriately budgeted recruitment plan that is effective in sourcing eligible

participants and engaging interest from the target group to ensure subsequent

enrolment into the research trial. Such planning is paramount to successfully

remaining on target for the timely completion of RCTs within the allocated budget.

Page | 197

Chapter 6

The Effects of Progressive Resistance Training Combined with a

Whey-Protein Drink and Vitamin D Supplementation on Glycaemic

Control, Insulin Sensitivity and Body Composition and

Cardiovascular Risk Factors in Older Adults with Type 2 Diabetes

Chapter 6

Page | 198

6.1 Declaration Statement

This Chapter presents the analysis, results and discussion of the 6-month community

based PRT program titled REVAMP-IT. Under the guidance of my primary

supervisor my role was to analyse the data arising from this trial as presented in this

Chapter, draft and write the results, prepare all tables and figures along with

preparing the discussion with assistance from my supervisory team.

Chapter 6

Page | 199

6.2 Abstract

Supervised and structured high-intensity progressive resistance training (PRT) has

been shown to improve glycaemic control and lean mass in older adults with type 2

diabetes mellitus (T2DM), but whether similar benefits are achieved with

community-based moderate to high-intensity PRT remains uncertain. Emerging

evidence suggests that high protein diets, whey protein and/or vitamin D

supplementation may have beneficial effects on glycaemic control, body

composition, and cardiovascular health in those with T2DM, but whether combining

protein and vitamin D with PRT can provide additive or synergistic health benefits

remains unknown. The aim of this 24-week RCT was to investigate whether

combining PRT with whey protein and vitamin D supplements could enhance the

effects of PRT alone on glycaemic control, body composition and cardiovascular

health outcomes in older adults with T2DM. A total of 198 older adults (mean ± SD

age 61.5 ± 6.2 years) with T2DM participated in a community-based PRT program

(2-3 times per week) for 24-weeks with participants randomised to whey protein

supplementation (20 g per day plus 20g following PRT) with vitamin D treatment

(2,000 IU/day) (PRT+ProD, n=98) or PRT alone (PRT, n=100). Body composition

(total body, regional lean and fat mass plus thigh muscle cross-sectional area (25%

femur)) was measured at 0 and 24-weeks by DXA and pQCT. Glycaemic and

insulinaemic parameters along with lipids and inflammatory markers were assessed

at 0, 12- and 24-weeks using standard techniques. A total of 168 participants (85%)

completed the 24-week intervention (PRT+ProD=88 and PRT=80). Mean exercise

compliance was significantly higher in PRT+ProD compared to PRT (67% vs 58%,

P<0.05) and compliance with the whey protein and vitamin D supplements was 79%

and 92%, respectively. Overall serum 25(OH)D levels were ~72nmol/L at baseline

and 24-weeks of supplementation led to a mean increase of 28 nmol/L in the

PRT+ProD group (P=0.001); there was no change in PRT. Intention-to-treat analysis

showed PRT led to significant improvements in glycaemic control, total body and

regional (arm and leg) lean mass, thigh muscle size, upper and lower body muscle

strength, waist circumference, fat mass and DBP, but there was no added benefits of

the whey protein drink and vitamin D supplements, with the exception that there was

a significantly greater reduction in serum insulin concentrations after 12- and 24-

weeks in the PRT+ProD compared to PRT group. Similarly, there was significant

Chapter 6

Page | 200

beneficial effect of PRT combined with whey protein and vitamin D relative to PRT

alone on the anti-inflammatory marker IL-10, yet no between-group differences for

the change in any other inflammatory cytokines. Secondary pre-planned analysis

examining those who achieved ³66% exercise and ³80% whey protein and vitamin

D supplement adherence revealed a greater improvement in upper body muscle

strength and serum IL-6 in the PRT+ProD group plus a greater reduction in total and

low density lipoprotein (LDL) cholesterol. In summary, a community-based PRT

program was found to be safe and effective for improving glycaemic control and

body composition, but the addition of whey protein and vitamin D supplementation

did not enhance these health benefits in older overweight and obese adults with

T2DM.

Chapter 6

Page | 201

6.3 Introduction

Type 2 diabetes is largely considered a lifestyle-related disorder, and thus regular

exercise and adequate nutrition are widely considered the key pillars for the

management of glycaemic control and reducing body weight and fat mass in those

who are overweight/obese (5, 6). Traditionally, aerobic exercise training and caloric

restriction have been advocated for the management of weight and fat mass, but such

an approach has typically been associated with a loss in lean mass (7, 8). This is

important because lean mass is the primary site of glucose disposal under insulin

stimulated conditions (9). Indeed, reductions in lean mass have been shown to

negatively affect glycaemic control and metabolic rate, and further compound the

problems of insulin resistance (10, 11).

Progressive resistance training (PRT) is one mode of exercise that has been shown to

be safe and effective for improving or maintaining lean mass, size and strength in

older adults with T2DM (8, 12, 14, 204, 212, 225, 250, 612). Indeed, current national

and international physical activity guidelines for the management of this condition

recommended that moderate to high-intensity PRT be performed at least twice a

week due to it beneficial effects on lean mass, glycaemic control and insulin

sensitivity (6, 185, 211, 231). There is also some evidence supporting a beneficial

effect of PRT on markers of systemic inflammation in older adults with T2DM (217,

230, 238), which is important as increased inflammation has been implicated in the

pathophysiology of insulin resistance, endothelial dysfunction and cardiovascular

disease (22). To date however, the majority of randomised controlled trials (RCTs)

examining the effects of PRT in older adults with T2DM have been conducted under

tightly controlled and structured clinical laboratory settings. While there is some

evidence that community-based programs can improve glycaemic control and body

composition in adults with T2DM (204, 255), the benefits appear to be less

impressive which may relate to a number of factors including training intensity,

exercise compliance and/or inter-individual differences in dietary habits.

Nutrition or nutritional modification, like exercise, is an integral component to the

management of T2DM and influences many metabolic pathways that affect the

progression of this disease. Enhancing the health benefits of PRT through nutritional

Chapter 6

Page | 202

management may offer a synergistic effect on glycaemic control, body composition

and cardiovascular risk factors. In recent years, there has been considerable interest

into the role of dietary protein, including whey protein supplements, due to its

positive effects on stimulating insulin secretion and improving glycaemic control

(52, 329, 330, 379). Furthermore, in non-diabetic adults, post-exercise ingestion of a

protein-rich supplement such as whey protein has also been found to maximise the

anabolic effects of PRT on lean mass (305, 519, 572, 613, 614). Long-term

consumption of whey protein supplements has been reported to reduce weight and fat

mass through its effects on increasing satiety and subsequently reducing total energy

intake (353, 403). There is also mounting evidence that vitamin D deficiency is

associated with impaired beta-cell function, glucose intolerance, insulin resistance

and increased systemic inflammation, all of which may be improved with

supplementation, although the findings from RCTs are mixed (22, 59, 615). Whether

there are additive health and metabolic benefits of combining vitamin D and whey

protein with a community-based PRT program in older adults with T2DM is not

known. However, in a recent 13-week double-blinded, randomised placebo

controlled trial in 130 sarcopenic elderly adults without T2DM (mean age 80.3 years)

it was reported that the combination of 22g of whey protein and 100 IU vitamin D

twice/day with exercise improved total body lean mass, reduced android fat mass,

and improved strength and reduced inflammation in comparison to the placebo plus

exercise group (513).

The primary aim of this community-based Resistance Exercise, Vitamin D and

Muscle Protein Intervention Trial (REVAMP-IT) was to investigate if a community-

based PRT program combined with a whey protein and vitamin D enriched

supplement could synergistically interact to concomitantly enhance the effects of

PRT alone on glycaemic control and insulin sensitivity in older adults with T2DM.

Secondary aims were to examine the effects of the intervention on body composition

(total body and regional lean and fat mass and percent body fat), cardiovascular risk

factors (lipid and lipoprotein levels, blood pressure) and various markers of systemic

inflammation.

Chapter 6

Page | 203

6.4 Methods

As a detailed description of the methods for this study has been provided in Chapter

4, a brief summary of the methods for REVAMP-IT is provided below.

6.4.1 Study Design

This study was a 24-week two-arm parallel, RCT. Participants with established

(diagnosed by a GP or endocrinologist) T2DM who were suitable for the current

community-based Lift for Life® PRT program and met the trial inclusion criteria

(refer to Chapter 4 section 4.2.6 Screening and Eligibility) were randomised to one of

two groups: 1) the Lift for Life® program combined with a whey-protein drink and

vitamin D supplements or 2) the Lift for Life® program alone.

6.4.2 Participants

Men and women aged 50 to 75 years with established T2DM, treated with diet alone

or any oral hypoglycaemic agents (except insulin), were invited to participate in this

study. A two-step screening process was employed in this study. In the first instance,

a telephone screening questionnaire (Appendix 5) was used to assess an individual’s

eligibility. Participants were eligible if aged 50-75 years, had been diagnosed with

T2DM and were treating/managing their condition through dietary change or oral

hypoglycaemic medication only. Those who passed the telephone screening were

then required to gain GP approval prior to randomisation and participation in the Lift

for Life® program (second screening step) (Appendix 6).

6.4.3 Ethics

Ethics was approved by the Deakin University Human Research Ethics Committee:

Project number EC2013-050 (Appendix 4). This study is also registered with the

Australian New Zealand Clinical Trials Registry, registration number

ACTRN12613000592741.

6.4.4 Funding

This project was funded by a grant from the National Health and Medical Research

Council Project (APP1046269). The whey-protein powder was provided by

Chapter 6

Page | 204

OmniBlend (Campbellfield, Victoria, Australia) and the vitamin D supplements

(Ostelin) by Sanofi-Aventis Australia Pty Ltd (Macquarie Park, New South Wales,

Australia).

6.4.5 Randomisation

Randomisation occurred at the level of the individual participant, stratified by gender

and diabetes treatment (diet or oral hypoglycaemic medication), in blocks of 4-8

using a computer-generated random number sequence (Microsoft Excel) by an

independent researcher. All research staff responsible for the collection of

anthropometric, blood pressure, and body composition data were blinded to the

intervention groups. The project manager was solely responsible for the distribution

of supplements to participants randomised to the Lift for Life® program plus whey-

protein and vitamin D supplements. A limitation of our study was that the project

manager was involved in some of the strength assessments which may have

introduced some observational bias.

6.4.6 Intervention

Lift for Life® PRT Program

All participants were required to follow a training program modelled off the structure

of the Lift for Life® PRT program (www.liftforlife.com.au). The Lift for Life®

program comprises moderate-intensity PRT (2-3 sets of 8-12 repetitions at 60-75%

of maximum strength of 8-10 exercises) involving dynamic concentric and eccentric

contractions, focusing on the major muscle groups of the body. Training was made

incrementally more challenging at a rate of 2-10% per week to meet the principles of

progressive overload with the Borg RPE scale also used to validate training intensity.

An appropriate training intensity level for this trial was established as 12-15

(moderate- to high-intensity).

Due to the limited number of accredited Lift for Life® program providers in

Melbourne Australia, the trial was expanded to include training locations such as

commercial gymnasiums that were not accredited as a Lift for Life® program

provider but which did allow participants to safely perform a PRT program under the

Chapter 6

Page | 205

guidance of qualified Certificate IV personal trainers (minimum qualification). In

such instances, the structure of the training programs for these participants imitated

that of the Lift for Life® program as depicted below in Figure 6.1.

Figure 6.1: Flow diagram of the progress through the 24-week PRT program used in

this trial modelled off the Lift for Life® program.

Whey-Protein and Vitamin D Supplementation

Participants randomised to the Lift for Life® plus whey-protein and vitamin D

supplementation group received a 12-week supply of a whey-protein enriched

powder and vitamin D supplements at the completion of baseline testing and again

after 12-weeks of training. Whey-protein supplements were provided in single use

sachet form (OmniBlend, Campbellfield, Victoria, Australia). Participants were

instructed to mix one sachet containing 20g of WPC (80%) with 150ml of water

every morning of the trial and consume an additional supplement within two hours of

each Lift for Life® PRT session on the respective training days. Participants received

a marked shaker cup with instructions on how to reconstitute the whey-protein

powder in water (1 sachet per ~150ml of cold water) along with appropriate storage

instructions for the supplements. Participants were offered two flavours to select

Chapter 6

Page | 206

from (vanilla or mocha coffee). A detailed description of the preparation of these

supplements is provided in Chapter 4.

In addition to the whey-protein supplements, participants randomised to this

treatment group were also asked to take two 1,000 IU capsules of vitamin D3

(Ostelin, Melbourne, Victoria, Australia) each day for the duration of the study. The

goal of vitamin D3 treatment was to raise serum 25(OH)D concentrations to at least

75 nmol/L.

6.5 Outcome Measures

Participants attended Deakin University on three occasions throughout the duration

of the study for assessment (baseline, 12- and 24-weeks). All outcome measures

were assessed within the School of Exercise and Nutrition Sciences at Deakin

University, Burwood campus with the exception of fasted blood sample collections

which occurred at local pathology clinics at baseline, 12- and 24-weeks.

6.5.1 Anthropometry

All participants’ height, weight and waist circumference were measured using

standard techniques.

6.5.2 Blood Pressure

Following a 5-minute rest period where all participants were seated in a quiet room,

systolic blood pressure (SBP) and diastolic blood pressure (DBP) was measured

using an automated blood pressure monitor (AND Vital Sensor, Model number TM-

2551P, Abingdon, Oxford). Four measurements were taken on the left arm with a 2-

minute interval between readings; the mean of the final three readings were used in

the analysis.

6.5.3 Body Composition

Total body and regional (arm and leg) lean mass, fat mass and percentage body fat

was measured from total body scans performed using Dual X-ray Absorptiometry

(DXA) (Lunar Prodigy, GE Lunar Corp., Madison WI), using software version

Chapter 6

Page | 207

12.30.008. The short-term co-efficient of variation (CV) for repeated measurements

of total body lean mass and fat mass within the laboratory ranges from 1.0% to 1.7%.

A peripheral quantitative computed tomography (pQCT) scanner (XCT 3000, Stratec

Medizintechnik GmbH, Pforzheim, Germany) was used to measure muscle cross-

sectional area (CSA), subcutaneous and intermuscular fat CSA and muscle density,

as a surrogate measure of intermuscular adiposity, at the 25% femur site. The CV for

femur muscle CSA within the laboratory is 1.3%.

6.5.4 Muscle Strength

Isometric knee extensor strength (force in kg) was measured on the participant’s

dominant leg using Lord's strap assembly incorporating a strain gauge (Neuroscience

Research Australia, Sydney, Australia). Maximal muscle strength of the lower limbs

and back was estimated by employing three-repetition maximum strength (3-RM)

tests for the bilateral leg press (Synergy Omni Leg Press S-31 OPD, QLD, AUS) and

the seated row (Nautilus F3 Adjustable Tower Pulley System F3ATFS, Nautilus,

Vancouver, WA). One-repetition maximum (1-RM) muscle strength was determined

using the formula by Wathen et al. (579): 1-RM = 100 x (3-RM load)/(48.8 + 53.8 x

e (0:075x3)). The short-term CV for repeated measurements of 1-RM testing in our

laboratory was 2.0% for leg and 1.1% for back strength.

6.5.5 Biochemical, Hormonal and Inflammatory Cytokine Measurements

Extensive methodology for the measurement of biochemical, hormonal and

inflammatory markers is provided in Chapter 4. Following an overnight fast, a rested

morning (8-10am) venous blood sample was collected from each participant’s

antecubital vein at a local pathology laboratory. The following series of parameters

were all assessed by the pathology clinic using standardised techniques: HbA1c,

plasma glucose, creatinine, calcium, C-peptide, estimated glomular filtration rate

(eGFR), high-sensitive C-reactive protein (hs-CRP) and blood lipids (total

cholesterol, high density lipoprotein (HDL) cholesterol, low density lipoprotein

(LDL) cholesterol and triglycerides).

Chapter 6

Page | 208

A range of hormonal and inflammatory markers were assessed in a single batch at

the completion of the study from serum aliquot samples collected and stored

throughout the study. Serum 25(OH)D were analysed at Monash Health, Melbourne,

Australia. Samples were measured on the AbSciex Q Trap 5500 MS by liquid

chromatography-tandem mass spectrometry (LC-MS/MS). Serum IGF-1 was

measured using a 1-step sandwich chemiluminescense immunoassay LIAISON®

IGF-1 kit (DiaSorin, Saluggia (VC), Italy) with samples read on a LIAISON®

Analyser. Insulin sensitivity was assessed from fasting plasma insulin and fasting

plasma glucose (FPG) concentrations using the HOMA-2 calculator available from

the Diabetes Trials Unit www.OCDEM.ox.ac.uk (616).

A detailed description of the methods for inflammatory marker measurement is

provided in Chapter 4. The mean intra and inter-assay CVs for IL-6, IL-10, IL-8,

TNF-ɑ and Adiponectin was <12%. Samples with results below the detectable limits

of the assay were allocated the minimum detectable concentration for each assay: IL-

6= 0.16 pg/mL; IL-10= 0.40 pg/mL; IL-8= 0.06 pg/mL; TNF-ɑ = 0.07 pg/m;

Adiponectin = 0.20 µg/mL.

6.5.6 Dietary Assessment

Briefly, dietary data was collected with two 24-hour dietary recalls at baseline of

which the second one was used in the analysis and one 24-hour dietary recall at 12-

and 24-weeks. The data collected from the 24-hour recalls was entered into

FoodWorks Professional (Version 8, Xyris Software, Queensland, Australia) to

calculate total dietary energy intake and dietary macronutrient composition using the

AUSNUT 2011-13 database including AusBrands and AusFoods. Mean daily

alcohol consumption was estimated from self-reported intakes over the previous

seven days.

Habitual Protein plus Protein from Whey Protein Supplements

The additional protein consumed from the whey protein supplements was calculated

for both training days and non-training days given the differing number of

supplements prescribed (one on non-training days and two on PRT days). Individual

compliance as a percentage with the whey protein supplements was multiplied by the

Chapter 6

Page | 209

dose of protein (either 20 or 40 g) with this amount subsequently added to the

habitual protein intake reported from the 24-hour food diaries to calculate the grams

per day of protein consumed. The same method was used to calculate g/kg/day at

both 12- and 24-weeks with weight at both these respective time points used in the

calculations to determine the g/kg/day of protein intake inclusive of the whey protein

supplement.

6.5.7 Habitual Physical Activity

Total leisure and recreational physical activity time (hours per week) was assessed

using the Community Healthy Activities Model Program for Seniors (CHAMPS)

physical activity questionnaire. These results are reported as estimated kilojoules per

week spent in moderate- to high-intensity activities.

6.5.8 Medical History, Health Status and Medication Use

All participants completed a lifestyle questionnaire to obtain information on

education background, history of diseases or illnesses, current medial conditions,

family history of diabetes, smoking history, current medication and dietary

supplement use, average weekly alcohol consumption. Information on any alterations

to or new medication prescribed by the participants’ doctors was collected by

research staff via the monthly telephone calls.

6.5.9 Compliance Assessment

Lift for Life® Exercise Training Cards

Compliance with the Lift for Life® PRT program was evaluated via self-completed

exercise cards. These cards were returned to researchers at the completion of the first

four weeks of training either by post or trial staff collection from respective training

locations. This allowed the PRT programs to be reviewed and additional exercises

prescribed or modified if not challenging enough.

Supplement Calendars

Compliance with the prescribed protein and vitamin D supplements were evaluated

via self-completed compliance calendars and a capsule count of remaining vitamin D

Chapter 6

Page | 210

supplements, respectively. The compliance calendars for the protein supplements

were cross-referenced by counting the remaining sachets of protein returned at the

final testing appointment.

6.5.10 Adverse Events

Any adverse events associated with the exercise program or supplements were

recorded by research staff during the monthly phone calls to participants. For this

trial, an adverse event was defined as any health-related untoward or unfavourable

medical occurrence that developed or worsened during the 24-week trial as a direct

result of either the exercise program or supplements. All adverse events were

assessed for seriousness, causality and expectedness by the research staff and

reported adverse events were categorised into adverse event, serious adverse event or

unanticipated problem based upon the National Institute of Ageing guidelines (589).

6.5.11 Statistical Analysis

For the statistical analysis of this 24-week intervention we used the Statistical

Package for the Social Sciences (SPSS, version 24) and Stata statistical software

release 14.0 (College Station, TX: StataCorp LP.). Prior to all analyses, the data was

checked for normality with natural log transformations used to achieve normality

when required. This included: serum IL-10, IL-6, IL-8, TNF-a, adiponectin, hs-CRP,

insulin sensitivity (HOMA2%S) and all strength measures (knee-extensor strength,

1-RM leg press and 1-RM seated row). Independent t-tests were used for between-

group comparisons at baseline for continuous variables and Chi-square tests for

categorical variables. The McNemar test was used to check for any differences

between the groups for the change in the proportion of participants taking diabetes

medication, anti-hypertensive, lipid-lowering, diuretic and nonsteroidal anti-

inflammatory drug (NSAIDs) therapies.

All the data was analysed on a modified intention-to-treat basis, including all

randomly assigned participants, regardless of exercise or supplement compliance,

with at least one follow-up observation. To assess whether the whey protein drink

and vitamin D supplements enhanced the effects of PRT after 12- and 24-weeks,

Chapter 6

Page | 211

generalised linear mixed models were used with random intercepts fitted for each

outcome, including fixed effects for time (baseline, 12- and 24-weeks), group

(PRT+ProD, PRT), and an interaction between group and time. Several models were

run: 1) unadjusted, 2) adjusted for the baseline value of the outcome variable, and 3)

adjusted for various covariates (see below). Adjusting for baseline for each outcome

variable made no difference to the results, with the exception of fasting insulin where

a significant between-group interaction was seen at both 12- and 24-weeks (P=0.028

and P=0.038) and for serum TNF-a where there were no longer any between-group

differences after 12-weeks (P=0.620) and 24-weeks (P=0.241). For all outcome

measures where there were only two time points, specifically body composition as

assessed from DXA and pQCT along with 1-RM strength outcomes, analysis of

covariance (ANCOVA) was performed with baseline values included as a covariate

and the change as the outcome measure. Model 3 included the following covariates:

age, gender, ethnicity, BMI, moderate-vigorous physical activity and diabetes

management. Anti-hypertensive or lipid-lowering medication were also included as

covariates for blood pressure and lipid measures, respectively. The P-values are

presented from unadjusted analysis and model 3.

To calculate the net between group differences for the changes over time, we first

calculated the within-group changes from baseline in each group at each time point

and then subtracted the within-group changes in the PRT+ProD group from those in

the PRT group at 12- and 24-weeks. Percentage changes in the previously listed

variables which were log-transformed prior to analysis represent the absolute

differences from baseline multiplied by 100. All data is presented as means ± SD or

95% CI, unless stated otherwise and P<0.05 was considered statistically significant.

Whilst we acknowledge reporting of within-group changes at multiple time points

increases the risk of type I error and could have performed Bonferroni corrections we

set our significance level at P<0.05, as stated above, along with our hypotheses being

established a priori and like others (617) considered such a method to be overly

conservative in this instance as previously reported (618).

In addition to the above, tests of interactions by gender, BMI (< 30 vs ≥ 30 kg/m2),

diabetes management (use of oral hypoglycaemic medication or lifestyle

Chapter 6

Page | 212

management) and anti-hypertensive or lipid-lowering medication use (yes or no)

were also tested for all relevant measured outcomes variables. For glycaemic

outcomes, we also conducted tests of interactions for baseline HbA1c (< 7 vs ≥ 7%)

and FPG (< 7 vs ≥ 7 mmol/L). Of all these interactions tested for each outcome

variable none were found to be significant and thus the results are not presented.

All these same statistical tests and tests of interactions as stated above were run in the

same manner for the per protocol analysis using only those participants who met the

per protocol requirements. For the per protocol analysis, the cut point was set at 66%

compliance or approximately two PRT sessions per week along with 80% of the

whey protein and vitamin D supplements.

6.6 Results

6.6.1 Participant Characteristics

A total of 198 adults (126 men and 72 women) with established T2DM aged 50-75

years (mean ± SD: 61.5 ± 6.2 years) were randomised to participate in this 24-week

intervention trial. The mean ± SD age at diagnosis for T2DM was 54.9 ± 7.7 years

and the mean disease duration was 7.0 ± 5.2 years (range 21 days to 21.7 years). An

equal proportion of participants in each group at baseline were classified as

overweight (PRT+ProD, 41.8%; PRT, 36.0%, Chi-square P=0.40) or obese

(PRT+ProD, 44.9%; PRT, 58.0%, Chi-square P=0.065). An equal proportion of men

and women were allocated to each group and of similar ethnic backgrounds (Table

6.1). Approximately 70% of participants managed their diabetes with medication but

there were no differences in the proportion of participants in each group with regard

to how they managed their diabetes (e.g. lifestyle alone or medication) (Table 6.1).

There were also no differences at baseline between the two groups for any of the

additional characteristics listed in Table 6.1, including the number and proportion of

participants who reported previous diagnosis with hypertension,

hypercholesterolaemia or CVD as diagnosed by a doctor. The only exception to this

was the PRT+ProD group were found to have a significantly larger number and

proportion (n=65, 66%) of participants who had a family history of T2DM compared

to those in the PRT group (n=46, 46%, P<0.01).

Chapter 6

Page | 213

Table 6.1: Baseline characteristics of participants in the PRT+ProD and PRT groups. PRT+ProD PRT

n 98 100 Male / Female, n 62 / 36 64 / 36

Age (years) 61.1 ± 6.2 62.0 ± 6.2

Height (cm) 170.2 ± 10.3 170.5 ± 9.2 Ethnicity

Caucasian, n (%) 84 (86) 89 (89)

Asian, n (%) 11 (11) 8 (8)

Other, n (%) 3 (3) 3 (3) Age at diagnosis (years) 54.1 ± 7.2 55.1 ± 7.9

Duration of diabetes (years) 6.9 ± 5.4 6.9 ± 5.3

Family history of diabetes, n (%) 65 (66)** 46 (46) Diabetes management (lifestyle / medication), n 27 / 71 32 / 68

Overweight/Obese

Normal weight, n (%) 13 (13) 6 (6) Overweight, n (%) 41 (42) 36 (36)

Obese, n (%) 44 (45) 58 (58)

Ex-smoker, n (%) 36 (37) 41 (41)

Self-reported co-morbid condition Hypertension, n (%) 56 (60) 62 (62)

Hypercholesterolaemia, n (%) 27 (29) 25 (25)

CVD1, n (%) 7 (7) 12 (12) Employment status

Working full-time, n (%) 42 (43) 35 (35)

Working part-time/Semi-retired, n (%) 16 (16) 26 (26)

Not-working/Retired, n (%) 40 (41) 39 (39) Values presented are mean ± SD unless stated. The classification of overweight and obese was completed using the following BMI cut-offs, overweight BMI ≥ 25.0- ≤ 29.9 and obese BMI ≥ 30.0. 1 Cardiovascular disease encompassed previous diagnosis heart disease or previously having suffered a heart attack. 1 Cardiovascular disease encompassed previous heart attack, angina, heart disease and/or stroke. **P<0.01 vs PRT. CVD, Cardiovascular disease. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 214

6.6.2 Study Attrition

Study Attrition

A CONSORT flow-chart of the study design including information for all

withdrawals and participants lost to follow-up is presented in Figure 6.2. Following

randomisation and prior to the 12-week assessment, an equal proportion of

participants from both the PRT+ProD (n=3) and PRT (n=5) groups were lost to

follow-up (e.g. could not be contacted or did not reply to phone, email or postal

requests) (Chi-square, P=0.721). In addition, a further 13 participants withdrew from

the study during the initial 12-weeks, the number of withdrawals was significantly

greater in the PRT than the PRT+ProD group (PRT+ProD n=2; PRT n=11; Chi-

square, P=0.011). The main reasons for withdrawal are discussed below. Following

the 12-week assessment, a further five participants in the PRT+ProD group were lost

to follow-up compared to only one participant in the PRT group (Chi-square,

P=0.084). An additional three participants in the PRT group withdrew from the trial

during this period, with no withdrawals in the PRT+ProD group. Thus, a total of 14

participants were lost to follow-up throughout the study with an equal proportion

from each group (PRT+ProD, n=8; PRT, n=6, Chi-square, P=0.553) and 16

participants withdrew from the trial, with a greater proportion in the PRT group

(14%, n=14) compared to the PRT + ProD group (2%, n=2) (Chi-square, P=0.002).

Three participants in the PRT+ProD and 11 in PRT group never commenced the

exercise program following randomisation. One participant in each of these groups

who never commenced the training program returned for follow-up testing

appointments at 12- and 24-weeks. These participants were not excluded from final

analysis. Overall, a total of 168 (85%) participants completed the trial and had data

available for final analysis, with slightly fewer drop-outs (withdrawals or lost to

follow-up) in the PRT+ProD group (n=88 included in final analysis) compared to the

PRT group (n=80 included in final analysis) (Chi-square, P=0.055).

Reasons for Withdrawal

During the first 12-weeks, the reasons for withdrawal in the PRT+ProD group were

health-related (n=1) and dislike of the training program (n=1). For the PRT group,

the reasons were health-related (n=5), carer/work commitments (n=4) and dislike of

the training program (n=2). Following the 12-week assessment, another three

Chapter 6

Page | 215

participants in the PRT group withdrew for either health-related reasons (n=2) or a

dislike of the training program (n=1). Overall, there were no significant differences

between the groups for the various reasons for withdrawing from the trial, with the

exception that a greater proportion of participants in the PRT group (n=4) withdrew

for health-related reasons compared to the PRT+ProD group (n=0) (Chi-square,

P=0.045).

When comparing those who either were lost to follow-up or withdrew from the

intervention to those who remained in the study, there were no differences observed in

any of the baseline outcome measures with the following exceptions; those who were

lost to follow-up/withdrew had a higher mean (± SD) baseline HbA1c (7.46 ± 1.30 vs

6.92 ± 1.10, P=0.01), FPG (9.36 ± 2.99 vs 8.04 ± 2.10, P=0.003), fasting insulin levels

(125.1 ± 163.4 vs 89.8 ± 51.7, P=0.03) and lower serum adiponectin levels (1.86 ±

0.91 vs 2.93 ± 0.12, P=0.001) compared to those who remained in the study.

Chapter 6

Page | 216

Figure 6.2: CONSORT flow diagram of participants through the trial. Progressive resistance training (PRT); protein and vitamin D supplements (ProD).

Chapter 6

Page | 217

6.6.3 Compliance

Lift for Life® Exercise Program Compliance

Compliance (the percentage of PRT sessions attended out of the total 64 prescribed

over the 24-week intervention) with the PRT program was significantly greater for

the PRT+ProD [mean (95% CI): 67.5% (62.0, 72.9)] compared to the PRT group

[57.9% (51.7, 64.2)] (P=0.023 for the between-group difference). Figure 6.3 shows

the histogram for the compliance (as a percentage) with the PRT program by group.

For the per protocol analysis, the cut point was set at 66% compliance or

approximately two PRT sessions per week. In the PRT group, 50% (n=50) of

participants achieved this level of compliance compared to 57% (n=56) in the

PRT+ProD groups. As the cost of training differed slightly across all the training

locations, we assessed whether there was any associated between the cost of training

and compliance with the PRT program yet found no significant association.

Figure 6.3: Histogram of the percentage exercise compliance by participants in the progressive resistance training plus protein and vitamin D supplementation (PRT+ProD, panel A) and PRT (panel B) group.

Whey Protein and Vitamin D Supplement Compliance

Mean (95% CI) compliance with both the whey protein drink and vitamin D

supplements in the PRT+ProD group, which was calculated as the percentage of the

Chapter 6

Page | 218

protein sachets and vitamin D capsules consumed over the 24-week period, was

78.6% (72.3, 84.9) and 91.5% (87.9, 95.1), respectively. Figure 6.4 shows the

histograms of the percentage compliance with the whey-protein drink and vitamin D

supplements. For the per protocol analysis, the cut-point was set at ≥80%

compliance. Overall 79% (n=78) of participants in the PRT+ProD group achieved a

mean compliance of ≥ 80% with the supplements. However, only 42% (n=41) of the

participants in the PRT+ProD group attained a mean compliance of ≥ 66% with the

PRT program and a mean compliance of ≥ 80% with the whey and vitamin D

supplements, thus only 41 participants in the PRT+ProD group were included in the

per-protocol analysis.

Figure 6.4: Histogram of the percentage compliance with the whey protein drink (panel A) and vitamin D supplements (panel B) in the progressive resistance training plus protein and vitamin D supplementation (PRT+ProD) group.

6.6.4 Adverse Events

Lift for Life® Exercise Program

In total, 42 musculoskeletal complaints or injuries were reported by 37 participants

with no significant differences between the groups (PRT+ProD, n=20, PRT, n=17;

P=0.538). One participant in each group reported two adverse events and an

additional participant in the PRT group reported three adverse events. As shown in

Table 6.2 the most common complaints were for the shoulder/neck and elbow/wrist

in both groups. The most common reason provided for reporting a neck/shoulder

complaint was neck tension/pain which led to a headache following a training

session. For elbow/wrist and back complaints, these were most commonly associated

Chapter 6

Page | 219

with aggravation of previously diagnosed tennis or golfers elbow or aggravation of

previous pain or injury in the back.

In the PRT+ProD group, 12 of the 20 participants continued their training with slight

modification to the program, six ceased training for a short period (1- to 2-weeks),

one participant reduced their training to two sessions per week for 6-weeks and one

individual withdrew from the exercise program but agreed to return for follow-up

testing. In the PRT group, nine of the 17 participants could continue with their

training by making small modifications or removing the specific exercise responsible

for the complaint/injury until recovery, six participants ceased training for a short

duration (1- to 3-weeks) and two discontinued the exercise program but returned for

follow-up testing. Of all the musculoskeletal complaints or injuries, eight participants

in the PRT+ProD and six participants in the PRT groups reported their complaints

were aggravations of a pre-existing injury.

Table 6.2: Number and proportion of musculoskeletal complaints reported by participants in the PRT+ProD and PRT groups that were deemed to be associated with the PRT program. Categorised by skeletal/muscular site.

Study Group

Adverse Event Location PRT+ProD PRT

Shoulder/Neck, n (%) 5 (24) 8 (38)

Elbow/wrist, n (%) 6 (29) 6 (28)

Gluteal, n (%) - 1 (5) Knee, n (%) 4 (19) 2 (10)

Back, n (%) 5 (24) 2 (9)

Hamstring, n (%) 1 (4) -

Groin, n (%) - 1 (5) Achilles, n (%) - 1 (5)

Total Number 21 21

Whey Protein and/or Vitamin D Supplements

No adverse events were reported with the ingestion of vitamin D supplements. A

total of 44 gastrointestinal (GI) related adverse events in 27 (28%) participants were

reported in relation to the whey protein drink in the PRT+ProD group over the 24-

Chapter 6

Page | 220

week period (Table 6.3). Of the participants reporting an adverse event, twelve

(44%) discontinued consuming the whey protein drink (n=10 prior to week 8) and

eight (30%) reduced or modified their supplement intake. Participants who modified

or reduced their supplement intake were instructed to reduce the dose to half a sachet

and gradually increase to the full sachet again over time if tolerated. A further seven

(26%) participants continued to consume the whey protein drink as prescribed

despite experiencing GI discomfort.

Table 6.3: Physical symptom(s) and number of adverse events related to the whey protein supplement in the PRT+ProD supplement group.

Physical Symptom(s) Number of Adverse Events

Bloating 6

Diarrhoea/Loose bowel movement 23

Nausea 4 Flatulence 4

Constipation 2

Abdominal Pain 5

Total Number 44

6.6.5 Physical Activity and Diet

At baseline, the mean moderate-vigorous physical activity habits of participants in

the PRT+ProD group was significantly less than those in the PRT group (mean

difference 3,559 kJ per week, P<0.01) (Table 6.4). There were no differences

between the groups for average daily energy intake (kJ), protein (g/day or g/kg/day),

fat and carbohydrates (g/day) or the percentage of energy intake from protein,

carbohydrates or fat at baseline (Table 6.5 and Table 6.6)

After 24-weeks, a significant increase in energy expenditure from moderate-vigorous

physical activity exclusive of the PRT program was observed in the PRT+ProD

group [mean change 4,556 kJ per week (95% CI, 2,396, 6,717), P=0.001] with no

change in the PRT group, which led to a significant between-group difference for the

change over time (interaction P=0.007) (Table 6.4).

Chapter 6

Page | 221

For all habitual dietary measures (total energy, fat, carbohydrates and alcohol), there

were no differences between the groups for the change over time after 12- or 24-

weeks except for dietary protein intake (Table 6.5). There were also no between

group differences for the change in dietary saturated fat, cholesterol, sodium,

potassium, magnesium and calcium (Appendix 9). For total energy intake, there was

a similar reduction in both groups after 24-weeks (PRT+ProD 437 kJ/day, P>0.05;

PRT 647 kJ/day, P<0.05). At baseline, an equal number and proportion of

participants in both groups reported consuming alcohol [(PRT+ProD, n=63 (64%)

and PRT, n=61 (61%)], with no differences between the groups (Chi-square analysis,

P=0.619).

Habitual Protein Intake plus Whey Protein Supplementation

The mean habitual dietary protein intake at baseline was 1.21 and 1.13 g/kg and 103

and 100 g/day in the PRT+ProD and PRT group, respectively (Table 6.6). There was

a small but significant 8 g reduction in habitual protein intake in the PRT+ProD

group at 24-weeks (there was no change in protein intake expressed as g/kg/day) but

no differences for the change over time between the group (Table 6.6 and Figure

6.5). Based on compliance with the whey protein supplement, at 12-weeks an

additional 11.2 g/day [(95% CI, 3.6, 18.9) P=0.014] or 0.13 g/kg ([95% CI, 0.09,

0.19) P=0. 011] of protein was consumed on non-training days (single supplement

day) and an additional 27.3 g/day [(95% CI, 19.3, 35.3) P=0.001] or 0.33 g/kg/day

[(95% CI, 0.27, 0.38) P=0.001] on training days (two supplements per day) relative

to baseline. As a result, protein intakes (at 12-weeks) were significantly greater in the

PRT+ProD compared to PRT group (between-group difference P<0.01 on both

training and non-training days). By 24-weeks the whey protein supplement provided

an additional 7.3 g/day [(95% CI, -2.6, 17.1) P=0.237] or 0.11 g/kg/day [(95% CI,

0.04, 0.18) P=0.061] on non-training days and 22.6 g per day [(95% CI, 12.5, 32.6)

P=0.001] or 0.29 g/kg of protein/day [(95% CI, 0.22, 0.36) P=0.001] relative to

baseline on top of habitual intakes (Table 6.6 and Figure 6.5). At 24-weeks, only the

increase in protein intake on training days was significantly higher relative to

baseline (P=0.001) in the PRT+ProD group. Similarly, there was a significant group-

by-time interaction for the change in protein intake on the training days only

(P=0.001) with intakes higher in the PRT+ProD compared to the PRT group.

Page | 222

Table 6.4: Baseline values and absolute within-group changes in the PRT+ProD and PRT group and the net between-group differences for the change at 12- and 24-weeks relative to baseline for moderate-vigorous physical activity.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3

Moderate-vigorous Physical Activity (kJ/week)

Baseline 8,194 ± 8,067b 11,753 ± 10,885

∆ 12-weeks 1,670 (-58, 3,399) 0.067 -314 (-2,101, 1,472) 0.986 1,985 (-484, 4,453) 0.248 | 0.223

∆ 24-weeks 4,556 (2,396, 6,717) 0.001 -73 (-3,080, 2,933) 0.772 4,630 (991, 8,268) 0.007 | 0.006

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from model 1 – unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjusting for baseline values, age, gender, ethnicity and BMI. b P<0.01 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 223

Table 6.5: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for all macronutrients, excluding protein intake and the protein-vitamin D supplements.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3

Energy Intake (kJ/day)

Baseline 8,514 ± 2,584 8,687 ± 2,202

∆ 12-weeks -357 (-898, -184) 0.158 -155 (-711, 401) 0.550 -201 (-972, 568) 0.640 | 0.835

∆ 24-weeks -437 (-994, -120) 0.059 -647 (-1,347, 52) 0.042 210 (-670, 1,091) 0.763 | 0.845

Carbohydrate (g/day)

Baseline 202.3 ± 82.7 200.3 ± 60.4

Δ 12-weeks -12.1 (-29, 4.8) 0.198 9.7 (-9.2, 28.6) 0.378 -21.8 (-46.9, 3.2) 0.124 | 0.144

Δ 24-weeks -12.2 (-31.0, 6.7) 0.097 -12.0 (-31.4, 7.4) 0.167 -0.18 (-27.0, 26.7) 0.935 | 0.856

Fat (g/day)

Baseline 76.6 ± 34.4 83.5 ± 37.5

Δ 12-weeks -1.8 (-9.6, 6.0) 0.334 -4.6 (-12.6, 3.4) 0.298 2.8 (-8.3, 13.8) 0.856 | 0.623

Δ 24-weeks -2.3 (-10.0, 5.4) 0.447 -8.2 (-18.2, 1.8) 0.080 5.9 (-6.5, 18.2) 0.393 | 0.420

Page | 224

% Energy Protein

Baseline 20.7 ± 5.4 19.6 ± 5.4

Δ 12-weeks 0.1 (-1.4, 1.2) 0.881 -0.7 (-2.1, 0.6) 0.608 0.6 (-1.3, 2.4) 0.780 | 0.731

Δ 24-weeks -0.9 (-2.6, 0.7) 0.374 -0.6 (-2.5, 1.3) 0.077 -0.3 (-2.9, 2.2) 0.059 | 0.060

% Energy Fat

Baseline 33.2 ± 9.8 34.9 ± 9.9

Δ 12-weeks 0.6 (-1.7, 2.9) 0.984 -1.0 (-3.1, 1.2) 0.295 1.6 (-1.6, 4.8) 0.467 | 0.394

Δ 24-weeks 1.1 (-4.0, 1.7) 0.686 -3.2 (-6.3, 0.0) 0.440 2.0 (-2.2, 6.2) 0.403 | 0.387

% Energy Carbohydrates

Baseline 39.6 ± 9.2 39.3 ± 9.7

Δ 12-weeks -0.4 (-2.6, 1.8) 0.925 2.0 (-0.4, 4.4) 0.116 -2.4 (-5.6, 0.8) 0.204 | 0.147

Δ 24-weeks -1.7 (-4.5, 1.0) 0.858 -2.5 (-5.9, 0.9) 0.983 -0.8 (-3.5, 5.1) 0.936 | 0.860

Alcohol§ (g/day)

Baseline 10.2 ± 12.8 12.7 ±15.3

Δ 12-weeks -0.4 (-2.3, 1.6) 0.567 -2.7 (-5.1, -0.2) 0.094 2.3 (-0.7, 5.4) 0.180 | 0.158

Δ 24-weeks 0.6 (-1.5, 2.7) 0.155 -1.2 (-3.1, 0.7) 0.477 1.8 (-1.0, 4.6) 0.515 | 0.486 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjusting for age, gender, ethnicity, BMI and moderate-vigorous physical activity § Baseline alcohol intake and the change in alcohol intake was calculated only on the number of participants in each group who reported being a consumer of alcohol at respective time points. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 225

Table 6.6: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for habitual protein intake and protein intake inclusive of supplemental protein on non-training and training days in g/day and g/kg/day.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Protein (g/day)

Habitual Protein (Excluding Whey Supplement)

Baseline 103.4 ± 33.8 99.9 ± 30.7

∆ 12-weeks -4.8 (-12.3, 2.6) 0.229 -5.8 (-13.1, 1.5) 0.200 1.0 (-9.5, 11.4) 0.966 | 0.824

∆ 24-weeks -8.0 (-17.9, 1.9) 0.025 -3.2 (-12.1, 5.7) 0.330 -4.8 (-18.0, 8.5) 0.321 | 0.263

Habitual Protein plus Whey Supplement (Non-Training Day)

Baseline 103.4 ± 33.8 99.9 ± 30.8

Δ 12-weeks 11.2 (3.6, 18.9) 0.014 -5.8 (-13.1, 1.6) 0.200 17.1 (6.5, 27.6) 0.008 | 0.003

Δ 24-weeks 7.3 (-2.6, 17.1) 0.237 -0.5 (-8.7, 7.7) 0.330 7.8 (-5.1, 20.6) 0.125 | 0.167

Habitual Protein plus Whey Supplement (Training Day)

Baseline 103.4 ± 33.8 99.9 ± 30.8

Δ 12-weeks 27.3 (19.3, 35.3) 0.001 -5.8 (-13.1, 1.6) 0.200 33.1 (22.3, 43.9) 0.001 | 0.001

Δ 24-weeks 22.6 (12.5, 32.6) 0.001 -0.5 (-8.7, 7.7) 0.330 23.0 (10.1, 36.0) 0.001 | 0.001

Page | 226

Protein (g/kg/day)

Habitual Protein (Excluding Whey Supplement)

Baseline 1.21 ± 0.37 1.13 ± 0.39

Δ 12-weeks -0.05 (-0.14, 0.03) 0.263 -0.06 (-0.14, 0.02) 0.224 0.01 (-0.11, 0.12) 0.985 | 0.808

Δ 24-weeks -0.08 (-0.20, 0.04) 0.102 -0.03 (-0.13, 0.08) 0.370 -0.02 (-0.20, 0.11) 0.576 | 0.513 Habitual Protein plus Whey Supplement (Non-Training Day)

Baseline 1.21 ± 0.37 1.13 ± 0.39

Δ 12-weeks 0.13 (0.09, 0.19) 0.011 -0.06 (-0.10, -0.01) 0.224 0.20 (0.13, 0.27) 0.007 | 0.003

Δ 24-weeks 0.11 (0.04, 0.18) 0.061 -0.03 (-0.09, 0.03) 0.370 0.14 (0.05, 0.23) 0.044 | 0.062

Habitual Protein plus Whey Supplement (Training Day)

Baseline 1.21 ± 0.37 1.13 ± 0.39

Δ 12-weeks 0.33 (0.27, 0.38) 0.001 -0.06 (-0.10, -0.01) 0.224 0.4 (0.3, 0.5) 0.001 | 0.001

Δ 24-weeks 0.29 (0.22, 0.36) 0.001 -0.03 (-0.09, 0.03) 0.370 0.32 (0.23, 0.42) 0.001 | 0.001 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjusting for age, gender, ethnicity, BMI and moderate-vigorous physical activity PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training

Chapter 6

Page | 227

Figure 6.5: Total dietary protein intakes (habitual plus supplemental) in older adults with type 2 diabetes at baseline, 12- and 24-weeks. The x-axis represents the two intervention groups (PRT (black bars) and PRT+ProD (white bars)) with the protein intake in the PRT+ProD presented on both non-training (NT) days and training (T) days. Data presented as mean ± SD. * P<0.05 vs baseline (within-group change). a P<0.05, b P<0.01, c P<0.001 between-group interaction.

6.6.6 Glycaemic and Insulinaemic Outcomes

Oral Hypoglycaemic Medication Use and Change

Table 6.7 shows the number of participants in each group at each time point who

were prescribed oral hypoglycaemic medication for the management of their T2DM.

At baseline, there were no differences between the groups, however at 12- and 24-

weeks a slightly higher proportion of participants in the PRT+ProD group were

taking prescribed oral hypoglycaemic medication compared to the PRT group (both

P<0.001). Throughout the study period there were no significant within-group

changes or differences between the groups for the number of participants that

increased or decreased their number of prescribed oral hypoglycaemic medication

(Table 6.7). Similarly, only a small number of participants changed (increased or

decreased) their oral hypoglycaemic medication dose, with no differences between

the groups with the exception that a greater proportion of participants in the PRT

group increased their doses after 24-weeks (PRT+ProD 3% vs PRT 11%, P<0.05).

Type of Oral Hypoglycaemic Medication

As shown in Table 6.8, the majority of participants prescribed oral hypoglycaemic

medication were taking biguanides (PRT+ProD 67%; PRT 58%) and/or

Chapter 6

Page | 228

sulphonylureas (PRT+ProD 27%; PRT 23%). There were no within-group changes

or between-group differences for the type of oral hypoglycaemic medication

prescribed to participants, with the exception of the following; 1) at 12- and 24-

weeks significantly more participants in the PRT+ProD group were prescribed

biguanides (P<0.001 and P<0.05, respectively) compared to the PRT group; 2) at all

time periods the PRT+ProD participants were more likely to be prescribed a

dipeptidyl peptidase 4 (DPP-4) (all P<0.001), and 3) participants in the PRT group

were more likely to be on combination therapy for their diabetes (all P<0.001).

Table 6.7: Total number and proportion of participants taking oral hypoglycaemic medications and the changes at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

Baseline 12-weeks 24-weeks

Prescribed Medication, n (%) PRT+ProD 71 (72) 69 (75)*** 65 (74)***

PRT 68 (68) 53 (63) 52 (65)

Increased | Decreased Number, n (%)

PRT+ProD - 3 (3) | 4 (4) 6 (7) | 7 (8) PRT - 0 (0) | 2 (2) 2 (3) | 2 (3)

Increased | Decreased Dose, n (%)

PRT+ProD - 2 (2) | 3 (3) 3 (3)* | 5 (6) PRT - 5 (6) | 1 (1) 9 (11) | 4 (5)

Commenced | Ceased Medication, n (%)

PRT+ProD - 1 (1) | 2 (2) 2 (2) | 2 (2)

PRT - 0 (0) | 0 (0) 0 (0) | 0 (0) The percentages of participants on a type of oral hypoglycaemic agent was calculated from the total participants on a type of agent divided by the total number of participants multiplied by 100. *P<0.05, ***P<0.001 between-group difference. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 229

Table 6.8: Total number and proportion of participants taking oral hypoglycaemic medications at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

Baseline 12-weeks 24-weeks Biguanides, n (%) PRT+ProD 66 (67) 65 (71)*** 61 (69)* PRT 58 (58) 44 (52) 43 (54) Sulphonylureas, n (%) PRT+ProD 26 (27) 24 (26) 23 (26) PRT 23 (23) 16 (19) 16 (20) Thiazolidinediones, n (%) PRT+ProD 0 (0) 0 (0) 0 (0) PRT 3 (3) 2 (2) 2 (3) Alpha Glucosidase Inhibitors, n (%)

PRT+ProD 0 (0) 0 (0) 0 (0) PRT 2 (2) 2 (3) 2 (3) DPP-4 Inhibitors, n (%) PRT+ProD 24 (24)*** 21 (23)*** 20 (23)*** PRT 9 (9) 6 (7) 5 (6) Incretin Mimetics, n (%) PRT+ProD 3 (3) 2 (2) 2 (2) PRT 6 (6) 6 (7) 7 (9) Sodium-glucose Co-transporter 2 Inhibitors, n (%) PRT+ProD 4 (4) 5 (5) 5 (4) PRT 1 (2) 2 (5) 2 (2) Insulin, n (%) PRT+ProD 0 (0) 0 (0) 1 (1) PRT 0 (0) 0 (0) 0 (0) Combination therapy1, n (%) PRT+ProD 0 (0)*** 0 (0)*** 0 (0)*** PRT 11 (11) 8 (10) 8 (10)

The percentages of participants on a type of oral hypoglycaemic agent was calculated from the total participants on a type of agent divided by the total number of participants multiplied by 100. *P<0.05, ***P<0.001 between-group difference. 1 Combination therapy included poly-pills such as Janumet, Glucovance, Avandamet, Metaglip or Avandaryl. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 230

Baseline Glycaemic Control and Insulin Sensitivity

There were no differences between the groups at baseline for HbA1c, insulin, insulin

sensitivity (HOMA2%S) or C-peptide levels (Table 6.9), with the exception that the

PRT+ProD group had slightly lower FPG levels (P<0.05) and higher insulin

sensitivity (HOMA2%S, P<0.01).

HbA1c and Fasting Plasma Glucose

At 12-weeks, both groups experienced a similar significant absolute 0.13 to 0.15%

(P=0.039 and P=0.060) reduction in HbA1c. While this modest improvement in

HbA1c persisted only in the PRT group after 24-weeks, there were no between-group

differences for the changes over time after 12- or 24-weeks (Table 6.9 and Figure

6.6). Levels of FPG improved by 4.3% and 6.6% after 12- and 24-weeks in the PRT

group (P<0.01 and P<0.001, respectively), with no changes observed in the

PRT+ProD group, which resulted in significant group-by-time interaction at 24-

weeks. However, after adjusting for the covariates in model 3 this result was no

longer significant (Table 6.9).

Fasting Insulin, C-peptide and Insulin Sensitivity

The PRT+ProD group experienced a significant reduction in fasting insulin after 12-

and 24-weeks relative to baseline [mean -9.89 pmol/L (95% CI, -16.99, -2.79)

P=0.003 and -6.2 pmol/L (95% CI, -13.6, 1.1) P=0.045]. There were no within-group

changes in fasting insulin in the PRT group. A trend (P=0.060) towards a significant

between-group difference at 12-weeks was noted following adjustment for covariates

(model 3). After adjusting for baseline fasting insulin a significant between-group

interaction was seen at both 12- and 24-weeks (P=0.028 and P=0.038). C-peptide

levels did not change at any time in either group and there were no group-by-time

interactions. For insulin sensitivity (HOMA2%S), there were no within-group

changes or between-group differences for the changes over time (Table 6.9 and

Figure 6.6). All results were similar whether adjusted for covariates included in

model 3.

Page | 231

Table 6.9: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change relative to baseline for HbA1c, fasting plasma glucose, insulin, insulin sensitivity and C-peptide.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3 HbA1c % Baseline 6.86 ± 1.11 7.14 ± 1.17 Δ 12-weeks -0.13 (-0.24, -0.02) 0.039 -0.15 (-0.28, -0.03) 0.006 0.02 (-0.14, 0.19) 0.627 | 0.668

Δ 24-weeks -0.10 (-0.24, 0.05) 0.072 -0.17 (-0.32, -0.03) 0.002 0.08 (-0.13, 0.28) 0.325 | 0.595

HbA1c (IFCC mmol/mol) Baseline 51.48 ± 12.11 54.46 ± 12.86

Δ 12-weeks -1.63 (-2.80, -0.45) 0.016 -1.64 (-3.05, -0.22) 0.008 0.01 (-1.80, 1.83) 0.827 | 0.845

Δ 24-weeks -1.08 (-2.68, 0.52) 0.064 -1.88 (-3.46, -0.31) 0.002 -0.80 (-1.43, 3.04) 0.328 | 0.573

Fasting Glucose (mmol/L)

Baseline 7.88 ± 2.21a 8.60 ± 2.33

Δ 12-weeks -0.12 (-0.39, 0.16) 0.493 -0.37 (-0.64, -0.10) 0.004 0.25 (-0.13, 0.63) 0.143 | 0.072

Δ 24-weeks 0.00 (-0.32, 0.32) 0.586 -0.57 (-0.90, -0.24) 0.001 0.57 (0.11, 1.02) 0.018 | 0.087 Continued over page

Page | 232

Fasting Insulin (pmol/L)

Baseline 94.9 ± 102.8 95.2 ± 46.7 Δ 12-weeks -9.9 (-17.0, -2.8) 0.003 -2.5 (-10.3, 5.3) 0.515 -7.4 (-17.9, 3.1) 0.093* | 0.060

Δ 24-weeks -6.2 (-13.6, 1.1) 0.045 0.8 (-5.1, 6.7) 0.995 -7.0 (-16.5, 2.5) 0.151* | 0.271

Insulin sensitivity (HOMA2%S)

Baseline 78.1 ± 46.8b 60.4 ± 24.5 Δ 12-weeks 6.6 (-1.5, 14.6) 0.092 3.6 (-3.2, 10.3) 0.247 3.0 (-7.5, 13.5) 0.603 | 0.594 Δ 24-weeks 2.7 (-5.2, 10.6) 0.389 2.5 (-3.8, 8.8) 0.341 0.2 (-10.0, 10.5) 0.986 | 0.967

C-peptide (nmol/L)

Baseline 1.13 ± 0.58 1.20 ± 0.36 Δ 12-weeks -0.06 (-0.11, 0.00) 0.027 -0.03 (-0.09, 0.03) 0.291 -0.02 (-0.10, 0.06) 0.451 | 0.530 Δ 24-weeks -0.03 (-0.08, 0.03) 0.084 -0.02 (-0.09, 0.05) 0.371 -0.02 (-0.10, 0.06) 0.595 | 0.588

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, oral hypoglycaemic use and moderate-vigorous physical activity. a P<0.05, b P<0.01 vs PRT at baseline. * P<0.05 significant between-group difference when adjusted for baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 233

Figure 6.6: Mean absolute changes from baseline (95% CI) in HbA1c (%) (A), fasting glucose (mmol/L) (B), fasting insulin (pmol/L) (C) and HOMA2%S (D) in the PRT+ProD (●) and PRT (○) groups. * P<0.05, † P<0.01 and ‡ P<0.001 within-group difference from baseline. # P<0.05 between-group differences for the changes over time (group-by-time interaction) in the unadjusted model (Model 1).

Chapter 6:

Page | 234

6.6.7 Body Composition and Muscle Strength

As shown in Tables 6.10 to 6.13, no significant differences were observed between

the groups at baseline for any anthropometric, DXA-derived or pQCT (25% femur

site) assessed body composition or muscle strength parameters with the exception of

the following; (1) BMI was on average 1.5 kg/m2 higher in the PRT group (P<0.05)

and (2) the PRT+ProD group had a lower mean total body fat mass compared to the

PRT group (P<0.05). The proportion of participants categorised as normal weight,

overweight and obese is described above in Table 6.1. For waist circumference, there

were no differences between the groups at baseline for those classified as having a

normal (<94 cm men; <80 cm women) (PRT+ProD 12.4% and PRT 10.1%; Chi-

square P=0.615), or at risk waist circumference (≥ 94 cm men; ≥ 80 cm women)

(PRT+ProD 87.6% and PRT 89.9%; Chi-square P=0.123).

Anthropometry

Over the 24-week intervention, there were no significant between-group differences

for the change over time for weight, BMI or waist circumference (Table 6.10).

However, there was a significant mean 0.65 kg reduction in weight in the PRT group

after 24-weeks compared to baseline (P<0.05). Both groups experienced a similar

significant 1 to 2 cm reductions in waist circumference after 12- and 24-weeks when

compared to baseline (both P<0.05).

DXA Body Composition

In both the PRT+ProD and PRT groups, there were similar significant within-group

improvements over time in total body fat mass, percentage fat and total body lean

mass (P ranging <0.001 to 0.05), with no between group differences (group-by-time

interactions) for the changes over 24-weeks whether the results were unadjusted or

adjusted for covariates (model 3). For arm and leg lean mass, the PRT+ProD group

experienced a significant 0.15 kg [(95% CI, 0.09, 0.22) P=0.001] and 0.19 kg [(95%

CI, 0.07, 0.31) P=0.002] gain relative to baseline, but there were no significant

changes in the PRT group. While there was a trend towards a significant between

group difference for the change over time (group-by-time interaction, P=0.056) in

arm lean mass in the unadjusted model, this was not significant after adjustments

were made for covariates in model 3. There were no within-group changes or

Chapter 6:

Page | 235

between-group differences for the change over time in arm or leg fat mass, with the

exception that the PRT group had a 0.18 kg (95% CI, -0.34, -0.03) P=0.017]

reduction in leg fat mass relative to baseline. For appendicular lean mass (ALM),

there was a trend for a significantly greater gain in the PRT+ProD relative to PRT

group after 24-weeks (group-by-time interaction) in model 1 (P=0.075) and model 3

(P=0.064), which was driven by a 0.34 kg [(95% CI, 0.19, 0.49) P=0.001] gain in the

PRT+ProD group relative to a 0.14 kg [(95% CI, -0.02, 0.30) P=0.081] gain in the

PRT group (Table 6.11).

pQCT Body Composition

After 24-weeks, 25% femur muscle CSA increased significantly by 3.5% in the

PRT+ProD (P=0.001) and 1.8% in the PRT groups (P=0.086), but there was no

difference between the groups (group-by-time interaction, P=0.087) for these

changes over time (Table 6.12). A significant 0.9% [(95% CI, 0.3, 1.5) P=0.016]

increase in muscle density was observed in the PRT group compared to baseline,

indicating a reduction in intramuscular fat infiltration with a significant between-

group difference (P=0.047) observed only after adjusting for covariates in model 3.

For thigh (25% femur) intermuscular fat and subcutaneous CSA, there were no

significant within-group changes or between-group differences throughout the study.

Muscle Strength

Over time, both groups experienced similar significant mean 7 to 19% (all P=0.001)

increases in both upper and lower body strength measures with no between-group

differences (group-by-time interactions) for the changes over time (all P>0.05)

(Table 6.13).

Page | 236

Table 6.10: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups for weight, body mass index (BMI) and waist circumference and the net between-group differences for the change relative to baseline.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Body Weight (kg)

Baseline 86.1 ± 16.6 90.4 ± 15.2

Δ 12-weeks -0.05 (-0.45, 0.35) 0.865 -0.05 (-0.39, 0.30) 0.852 0.00 (-0.53, 0.53) 0.972 | 0.980

Δ 24-weeks -0.26 (-0.75, 0.24) 0.185 -0.65 (-1.30, -0.01) 0.010 0.39 (-0.41, 1.19) 0.271 | 0.229

BMI (kg/m2)

Baseline 29.6 ± 4.7a 31.1 ± 4.6

Δ 12-weeks 0.01 (-0.14, 0.13) 0.972 -0.05 (-0.19, 0.08) 0.568 0.05 (-0.14, 0.25) 0.625 | 0.629

Δ 24-weeks -0.09 ( -0.26, 0.09) 0.211 -0.24 (-0.50, 0.01) 0.019 0.16 (-0.14, 0.46) 0.231 | 0.213

Waist Circumference (cm)

Baseline 101.1 ± 12.6a 104.7 ± 12.0

Δ 12-weeks -1.0 (-1.5, -0.40) 0.005 -1.4 (-1.8, -0.9) 0.001 0.4 (-0.4, 1.1) 0.395 | 0.423

Δ 24-weeks -1.3 (-2.1, -0.64) 0.001 -1.9(-2.5, -1.3) 0.001 0.7 (-0.3, 1.6) 0.328 | 0.189 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 237

Table 6.11: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for total body and regional (arms and legs) lean mass, fat mass and appendicular lean mass.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Total Body

Fat Mass (kg)

Baseline 30.5 ± 9.5a 33.4 ± 10.0

Δ 24-weeks -0.57 (-1.02, -0.12) 0.010 -0.92 (-1.42, -0.41) 0.001 0.35 (-0.32, 1.02) 0.301 | 0.320

Lean Mass (kg)

Baseline 51.6 ± 10.7 53.2 ± 10.2

Δ 24-weeks 0.50 (0.18, 0.82) 0.002 0.37 (0.04, 0.70) 0.001 0.13 (-0.33, 0.58) 0.616 | 0.381

Percentage Fat Mass (%)

Baseline 36.8 ± 8.1 38.2 ± 8.4

Δ 24-weeks -0.63 (-1.04, -0.21) 0.003 -0.88 (-1.29, -0.46) 0.001 0.25 (-0.33, 0.84) 0.367 | 0.486

Appendicular Lean Mass (kg)

Baseline 23.2 ± 5.4 24.1 ± 5.2

Δ 24-weeks 0.34 (0.19, 0.49) 0.001 0.14 (-0.02, 0.30) 0.081 0.20 (-0.02, 0.42) 0.075 | 0.064

Page | 238

Arm

Fat Mass (kg)

Baseline 3.1 ± 1.3 3.5 ± 1.5

Δ 24-weeks -0.03 (-0.09, 0.02) 0.240 -0.05 (-0.13, 0.04) 0.225 0.02 (-0.08, 0.12) 0.723 | 0.952

Lean Mass (kg)

Baseline 6.1 ± 1.6 6.2 ± 1.4

Δ 24-weeks 0.15 (0.09, 0.22) 0.001 0.05 (-0.02, 0.20) 0.129 0.10 (0.03, 0.20) 0.056 | 0.111

Leg

Fat Mass (kg)

Baseline 8.3 ± 3.6 9.3 ± 4.1

Δ 24-weeks -0.04 (-0.18, 0.09) 0.475 -0.18 (-0.34, -0.03) 0.017 0.14 (-0.06, 0.3) 0.168 | 0.195

Lean Mass (kg)

Baseline 17.1 ± 3.9 17.9 ± 3.9

Δ 24-weeks 0.19 (0.07, 0.31) 0.002 0.08 (-0.04, 0.21) 0.168 0.10 (-0.07, 0.28) 0.259 | 0.189 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 239

Table 6.12: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for 25% femur muscle cross-sectional area (CSA), muscle density, intermuscular and subcutaneous fat CSA.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Muscle CSA

Baseline (cm2) 62.4 ± 14.6 64.8 ±16.0

% Δ 24-weeks 3.5 (1.7, 5.3) 0.001 1.8 (0.3, 3.4) 0.086 1.7 (-0.7, 4.1) 0.087 | 0.137

Muscle Density

Baseline (mg/cm3) 73.6 ± 11.0 73.5 ± 11.9

% Δ 24-weeks -0.1 (-0.9, 0.8) 0.655 0.9 (0.3, 1.5) 0.016 -1.0 (-2.0, 0.2) 0.127 | 0.047

Intermuscular Fat Area

Baseline (cm2) 21.7 ± 7.7 23.1 ± 8.2

% Δ 24-weeks 1.7 (-1.5, 4.8) 0.623 -0.7 (-3.6, 2.2) 0.290 2.4 (-1.9, 6.6) 0.267 | 0.247

Subcutaneous Fat Area

Baseline (cm2) 38.7 ± 24.9 44.6 ± 29.3

% Δ 24-weeks -0.8 (-3.7, 2.1) 0.745 -1.4 (-4.1, 1.4) 0.602 0.6 (-3.4, 4.6) 0.807 | 0.738 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. CSA, Cross sectional area; PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 240

Table 6.13: Baseline values and within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change relative to baseline in leg press and seated row one-repetition maximum muscle strength and knee extensor isometric muscle strength.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

1-RM Leg Press

Baseline (kg) 186.9 ± 74.4 195.5 ± 79.2

% Δ 24-weeks 15.7 (9.7, 21.6) 0.001 14.7 (7.2, 22.2) 0.001 0.9 (-8.4, 10.4) 0.889 | 0.736

1-RM Seated Row

Baseline (kg) 53.4 ± 17.3 55.9 ± 17.1

% Δ 24-weeks 11.3 (5.7, 16.9) 0.001 7.3 (2.9, 11.6) 0.001 4.0 (-3.0, 11.1) 0.299 | 0.330

Knee Extensor Strength

Baseline (kg) 39.5 ± 14.1 40.9 ± 13.0

% Δ 12-weeks 12.1 (6.4, 17.8) 0.001 12.7 (7.3, 18.1) 0.001 -0.6 (-8.4, 7.2) 0.646 | 0.703

% Δ 24-weeks 18.9 (12.3, 25.5) 0.001 18.2 (12.2, 24.1) 0.001 0.8 (-8.1, 9.6) 0.954 | 0.953 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 241

6.6.8 Cardiovascular Health

Anti-Hypertensive and Lipid-Lowering Medications

At baseline, 55% and 58% of participants in the PRT+ProD and PRT group were

taking anti-hypertensive medication. Similarly, just over 50% of participants in each

group at baseline were taking lipid-lowering medication. There were no significant

within-group changes or differences between-groups for the proportion of

participants taking anti-hypertensive or lipid-lowering medications at any point

during the intervention (Table 6.14). Similarly, there was no significant within-group

changes or between-group differences regarding a change in the number or dose of

these medications or whether participants commenced or ceased these medications

over the duration of the intervention (Table 6.14).

Chapter 6

Page | 242

Table 6.14: Total number and proportion of participants prescribed anti-hypertensive and/or lipid-lowering medications at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

Baseline 12-weeks 24-weeks

Anti-Hypertensive Medications, n (%)

PRT+ProD 54 (55) 52 (56) 49 (56)

PRT 58 (58) 45 (54) 43 (54)

Increased | Decreased Number, n (%)

PRT+ProD - 0 (0) | 0 (0) 0 (0) | 1 (1)

PRT - 0 (0) | 0 (0) 1 (1) | 0 (0)

Increased | Decreased Dose, n (%)

PRT+ProD - 2 (2) | 1(1) 3 (3) | 3 (3)

PRT - 1 (1) | 0(0) 2 (3) | 0 (0)

Commenced | Ceased Medication, n (%)

PRT+ProD - 1 (1) | 0 (0) 1 (1) | 2 (2)

PRT - 0 (0) | 0 (0) 1 (1) | 1 (1)

Lipid-lowering Agents, n (%)

PRT+ProD 53 (54) 48 (52) 45 (51)

PRT 56 (56) 47 (55) 44 (54)

Increased | Decreased Number, n (%)

PRT+ProD - 0 (0) | 0 (0) 0 (0) | 0 (0)

PRT - 0 (0) | 0 (0) 0 (0) | 0 (0)

Increased | Decreased Dose, n (%)

PRT+ProD - 0 (0) | 3 (7) 1 (2) | 3 (7)

PRT - 2 (4) | 1 (2) 2 (4) | 2 (4)

Commenced | Ceased Medication, n (%)

PRT+ProD - 2 (2) | 1 (1) 1 (1) | 4 (5)

PRT - 1 (1) | 0 (0) 1 (1) | 1 (1)

The proportion of participants on anti-hypertensive or lipid-lowering medications was calculated based on the total number of participants in each group at each time point. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training. The percentages were calculated from the total participants prescribed anti-hypertensive or lipid-lowering medication or had a change in either of these medications divided by the total number of participants multiplied by 100. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 243

Type of Anti-Hypertensive Medication

There were no between-group differences at any time point for the proportion of

participants prescribed different types of anti-hypertensive medications (Table 6.15).

Table 6.15: Types of anti-hypertensive medications participants were prescribed at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

Baseline 12-weeks 24-weeks

ACE Inhibitors, n (%) PRT+ProD 11 (11) 11 (12) 8 (9)

PRT 20 (20) 16 (19) 15 (19)

Calcium-Channel Blocker, n (%)

PRT+ProD 5 (5) 4 (4) 3 (3)

PRT 7 (7) 4 (5) 2 (3)

β-Blocker, n (%)

PRT+ProD 10 (10) 8 (9) 7 (8)

PRT 10 (10) 7 (8) 6 (8)

AT1-Receptor Blocker, n (%)

PRT+ProD 3 (3) 3 (3) 3 (3)

PRT 2 (2) 1 (1) 1 (1)

Angiotensin II Receptor Antagonists, n (%)

PRT+ProD 13 (13) 12 (13) 11 (13)

PRT 16 (16) 12 (14) 12 (15)

Combination Therapy1, n (%)

PRT+ProD 31 (32) 30 (32) 30 (34)

PRT 23 (23) 19 (23) 20 (25) The percentages were calculated from the total number of anti-hypertensive drugs prescribed divided by the total number of participants on a type of anti-hypertensive medication multiplied by 100. 1 Combination therapy reflected those on combined anti-hypertensive drugs, an anti-hypertensive combined with a thiazide diuretic and hypertensive medication not otherwise classified. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 244

Baseline Hypertensive Status and Lipid Profile

At baseline, there were 50% and 39% of participants in the PRT+ProD and PRT

groups respectively, with measured blood pressure levels indicative of hypertension

with no differences between the groups. Including those prescribed anti-hypertensive

medications, this prevalence increased to 70% and 65% in the PRT+ProD and PRT

groups respectively, with no difference between the groups (data not shown). At

baseline, a similar number and proportion of participants in both groups presented

with high serum total cholesterol, triglyceride and LDL cholesterol and low HDL

cholesterol levels (Table 6.16).

Table 6.16: Number and proportion of participants in the PRT+ProD and PRT groups presenting with hyperlipidaemia.

PRT+ProD PRT

Cholesterol and Lipoprotein Status

Total cholesterol >5.5 mmol/L, n (%) 15 (15) 18 (18)

LDL cholesterol <2.0 mmol/L, n (%) 38 (39) 36 (36)

HDL cholesterol ≥1.0 mmol/L, n (%) 14 (14) 21 (21)

Triglycerides >1.7 nmol/L, n (%) 36 (37) 49 (49)

Elevated lipid(s) + lipid-lowering medication,3 n (%) 67 (68) 57 (57)

The percentage of participants suffering from any of the above conditions was calculated based on the total number of participants in that group divided by those who reported a comorbid condition multiplied by 100. 1 SBP ≥140 and/or DBP ≥90 mmHg; 2 SBP ≥140 and/or DBP ≥90 mmHg and/or taking anti-hypertensive medication; 3 Elevated triglycerides and/or taking lipid-lowering medication. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Baseline Blood Pressure, Serum Lipids and Cholesterol

There were no differences between the groups at baseline for SBP or DBP or any

serum lipid and lipoprotein concentrations (Table 6.17 and 6.18).

Blood Pressure

Throughout the intervention no significant changes in SBP were observed in either

group. However, a significant 2.5 and 2.6 mmHg reduction in DBP at both 12- and

24-weeks compared to baseline was observed in the PRT+ProD group (P=0.004 and

Chapter 6

Page | 245

P=0.010), with the PRT group also experiencing a 2.5 mmHg reduction in DBP only

after 24-weeks (P=0.010). However, there were no between-group differences for the

change over time in either SBP or DBP whether the results were unadjusted, adjusted

for covariates in model 3 as shown in Table 6.17.

Serum Lipid and Lipoprotein Levels

After 12-weeks the PRT+ProD group experienced a mean reduction in total and LDL

cholesterol of 0.20 mmol/L and 0.19 mmol/L, respectively (P=0.011 and P=0.005),

but these changes were not maintained after 24-weeks. There were no other within

group changes in any other measure in either group, and there were no between

group differences (group-by-time interactions) for the changes over 24-weeks

whether the results were unadjusted or adjusted for covariates (age, gender, ethnicity,

BMI, lipid-lowering medication and moderate-vigorous habitual physical activity)

(Table 6.18).

Page | 246

Table 6.17: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for systolic and diastolic blood pressure.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Systolic Blood Pressure (mmHg)

Baseline 136.0 ± 15.7 134.9 ± 15.2

Δ 12-weeks -2.5 (-5.5, 0.4) 0.144 0.4 (-3.6, 4.4) 0.965 -2.9 (-7.8, 1.9) 0.267 | 0.397

Δ 24-weeks -4.3 (-8.8, 0.2) 0.023 -2.4 (-6.2, 1.4) 0.093 -1.9 (-7.9, 4.0) 0.825 | 0.811

Diastolic Blood Pressure (mmHg)

Baseline 85.2 ± 9.0 83.1 ± 8.3

Δ 12-weeks -2.8 (-4.6, -1.0) 0.004 -0.9 (-3.1, 1.4) 0.392 -2.0 (-4.8, 0.8) 0.175 | 0.219

Δ 24-weeks -2.6 (-4.7, -0.5) 0.010 -2.5 (-4.6, -0.3) 0.010 -0.1 (-3.1, 2.8) 0.933 | 0.854 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, anti-hypertensive use and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 247

Table 6.18: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum total, HDL and LDL cholesterol and triglycerides.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Total Cholesterol (mmol/L)

Baseline 4.40 ± 1.06 4.51 ± 1.08

Δ 12-weeks -0.20 (-0.35, -0.05) 0.011 -0.03 (-0.18, 0.13) 0.689 -0.18 (-0.39, 0.03) 0.131 | 0.197

Δ 24-weeks -0.11 (-0.27, 0.06) 0.171 0.00 (-0.16, 0.15) 0.889 -0.10 (-0.33, 0.12) 0.390 | 0.538

HDL Cholesterol (mmol/L)

Baseline 1.30 ± 0.34 1.24 ± 0.30

Δ 12-weeks -0.02 (-0.05, 0.02) 0.355 0.00 (-0.03, 0.04) 0.955 -2.0 (-4.8, 0.8) 0.488 | 0.436 Δ 24-weeks 0.00 (-0.04, 0.03) 0.934 0.00 (-0.03, 0.04) 0.997 -0.1 (-3.1, 2.8) 0.946 | 0.507

LDL Cholesterol (mmol/L)

Baseline 2.37 ± 0.92 2.44 ± 0.93

Δ 12-weeks -0.19 (-0.31, -0.07) 0.005 -0.09 (-0.20, 0.03) 0.233 -0.10 (-0.27, 0.06) 0.275 | 0.652

Δ 24-weeks -0.12 (-0.25, 0.02) 0.113 0.02 (-0.12, 0.16) 0.712 -0.13 (-0.33, 0.06) 0.175 | 0.245

Continued over page

Page | 248

Triglycerides (mmol/L)

Baseline 1.62 ± 1.03 1.82 ± 0.86

Δ 12-weeks 0.00 (-0.22, 0.23) 0.963 0.10 (-0.15, 0.36) 0.431 -0.10 (-0.44, 0.24) 0.546 | 0.275

Δ 24-weeks 0.03 (-0.10, 0.16) 0.907 0.03 (-0.15, 0.22) 0.993 0.00 (-0.23, 0.21) 0.920 | 0.761 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, lipid-lowering medication and moderate habitual physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 249

6.6.9 Other Medication Use and Change

The number and proportion of participants prescribed diuretics and NSAIDs are

presented in Table 6.19. There were no significant within-group changes or between-

group differences for any of the above medications, with the exception that a lower

number (and proportion) of participants in the PRT+ProD group were prescribed

diuretics in comparison to the PRT group at baseline (Chi-square; P<0.01)

Table 6.19: Total number and type of other medications prescribed to participants at baseline, 12- and 24-weeks in the PRT+ProD and PRT groups.

Baseline 12-weeks 24-weeks

Diuretics, n (%)

PRT+ProD 4 (4)* 5 (5) 4 (5)

PRT 14 (14) 8 (9) 8 (10)

NSAIDs, n (%)

PRT+ProD 8 (8) 6 (6) 8 (9)

PRT 5 (5) 4 (5) 4 (5)

The proportion of participants on any of the above medications was calculated based on the total number of participants in each group at each time point. NSAIDs, nonsteroidal anti-inflammatory drugs. PRT+ProD, Progressive resistance training plus whey protein and vitamin D supplements; PRT, progressive resistance training. * P<0.01 versus PRT.

6.6.10 Inflammatory Cytokines, Hormonal and Biochemical Factors

There were no differences between the groups in any of the inflammatory markers at

baseline with the exception that serum levels of IL-8 (P<0.05), TNF-a (P<0.01) and

hs-CRP (P<0.01) were all significantly lower in the PRT+ProD group (Table 6.20).

As shown in Table 6.20, there were no differences between the groups at baseline for

serum creatinine, eGFR, serum 25(OH)D or IGF-1 levels.

Inflammatory Cytokines

After 12- and 24-weeks, the PRT+ProD group experienced significant gains (48.8%

and 40.0%, respectively, both P=0.001) in the anti-inflammatory marker IL-10

compared to baseline. This increase combined with a 14% non-significant and 22%

significant (P=0.023) reduction in the PRT group resulted in a significant between-

group difference for the change over time (P=0.001). A significant between-group

Chapter 6

Page | 250

difference (group-by-time interaction) was also observed for the change in IL-8

(P=0.010) at 12-weeks. This was driven by a 6% (P=0.174) increase in the

PRT+ProD group and a 7% (P=0.103) reduction in the PRT group. Further, a

significant 7% reduction in TNF-α levels after 12-weeks in the PRT group relative to

baseline drove a significant between-group interaction (P=0.047) in the unadjusted

model. This was no longer significant following adjustment for covariates (model 3)

(P=0.057). At 24-weeks again a significant between-group difference (group-by-time

interaction) was observed for TNF-α, yet at this time-point the significant interaction

was driven by an 11% [(95% CI, 0.10, 20.6) P=0.033] significant increase in the

PRT+ProD group (Table 6.20 and Figure 6.7). This result was retained when

adjusting for covariates. However, after adjusting for the baseline values there were

no significant between-group differences at 12-weeks (P=0.620) or 24-weeks

(P=0.241). In addition to the results above, there was a non-significant within-group

reduction in serum adiponectin in the PRT+ProD group [mean change -4.0% (95%

CI, (-7.9, -0.1) P=0.115] after 24-weeks which resulted in a trend towards a

significant between-group difference (P=0.069) for the change over time when

adjusting for covariates in model 3. For all other inflammatory cytokines, there were

no within-group changes or between-group differences for the change over time

(Table 6.20 and Figure 6.7).

Hormonal and Biochemical Measures

After 12- and 24-weeks, the PRT+ProD group experienced a mean significant 25

nmol/L and 28 nmol/L increase in serum 25(OH)D (both P=0.001), with no change

observed in the PRT group (Table 6.21). This led to significant between-group

differences at both 12- and 24-weeks (both P=0.001). No within-group changes or

between-group differences were observed for serum IGF-1 following the 24-week

intervention (Table 6.21). Both groups experienced similar significant reductions in

serum creatinine and eGFR by 24-weeks (both P=0.001) with no group-by-time

interactions observed.

Page | 251

Table 6.20: Baseline values and percent changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum levels of interleukin (IL)-10, IL-6, IL-8, tumor necrosis factor-alpha (TNF-α), adiponectin and high-sensitive C-reactive protein (hs-CRP).

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

IL-10

Baseline (pg/ml) 8.1 ± 13.7 11.6 ± 18.9

%Δ 12-weeks 48.8 (27.7, 70.0) 0.001 -13.8 (-33.3, 5.6) 0.109 62.7 (34.1, 91.3) 0.001 | 0.001

%Δ 24-weeks 40.0 (18.1, 61.8) 0.001 -21.5 (-42.6, -0.3) 0.023 61.4 (31.0, 91.9) 0.001 | 0.001

IL-6

Baseline (pg/ml) 2.8 ± 2.5 3.2 ± 3.7

%Δ 12-weeks 10.5 (-7.4, 28.4) 0.211 -11.9 (-28.5, 4.7) 0.196 22.4 (-1.9, 46.7) 0.072 | 0.165

%Δ 24-weeks 13.7 (-2.2, 29.6) 0.139 -9.9 (-26.9, 7.1) 0.415 23.5 (0.4, 46.6) 0.105 | 0.160

IL-8

Baseline (pg/ml) 15.1 ± 7.1a 20.9 ± 25.3

%Δ 12-weeks 5.7 (-3.8, 15.3) 0.174 -7.0 (-18.1, 4.2) 0.103 12.7 (-1.8, 27.2) 0.033 | 0.010

%Δ 24-weeks 2.0 (-4.1, 8.4) 0.493 -3.7 (-16.1, 8.6) 0.377 5.9 (-7.2, 19.0) 0.262 | 0.158

Continued over page

Page | 252

TNF-α

Baseline (pg/ml) 7.6 ± 2.5b 9.2 ± 5.3

%Δ 12-weeks 6.3 (-4.5, 17.2) 0.355 -6.7 (-13.8, 0.0) 0.046 13.0 (0.0, 26.0) 0.047c | 0.057

%Δ 24-weeks 10.6 (0.10, 20.6) 0.033 -4.8 (-12.9, 3.2) 0.141 15.5 (2.5, 28.5) 0.009c | 0.009c

Adiponectin

Baseline (µg/mL) 2.9 ± 1.8 2.6 ± 1.3

%Δ 12-weeks -1.6 (-6.5, 3.3) 0.839 -2.9 (-6.5, 0.1) 0.201 1.3 (-4.7, 7.3) 0.582 | 0.716

%Δ 24-weeks -4.0 (-7.9, -0.1) 0.115 -0.5 (-4.8, 3.7) 0.985 -3.5 (-9.2, 2.3) 0.195 | 0.069

High sensitive-CRP

Baseline (mg/mL) 1.7 ± 1.5b 3.3 ± 5.7

%Δ 12-weeks -10.3 (-26.3, 5.8) 0.204 -4.1 (-23.4, 15.2) 0.606 -6.2 (-31.0, 18.7) 0.514 | 0.528

%Δ 24-weeks -2.0 (-16.2, 12.1) 0.854 0.0 (-20.0, 20.2) 0.910 -2.1 (-26.2, 21.9) 0.719 | 0.922 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate habitual physical activity. a P<0.05 b P<0.01 vs PRT at baseline. * Group-by-time interaction lost when model was adjusted for baseline serum levels. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 253

Figure 6.7: Mean percentage change from baseline (95% CI) in log transformed serum interleukin (IL)-6 (A), IL-10 (B), IL-8 (C), TNF-α (D), adiponectin (E) and high sensitive hs-CRP (F) in the PRT+ProD (●) and PRT (○) groups. * P<0.01 ‡ P<0.001 within-group change from baseline # P<0.05, ^ P<0.001 between-group difference for the changes over time (group-by-time interaction). All p-values are based upon results adjusted for covariates. Please note the different scales for different graphs.

Page | 254

Table 6.21: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum creatinine, estimated glomular filtration (eGFR), 25-hydroxyvitamin D (25(OH)D) and insulin-like growth factor-1 (IGF-1).

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P-values

Model 1 | Model 3

Creatinine (mol/L)

Baseline 75.5 ± 15.8 79.7 ± 17.5

Δ 12-weeks 0.6 (-1.2, 2.4) 0.499 0.3 (-1.8, 2.3) 0.679 -0.4 (-2.3, 3.1) 0.876 | 0.994

Δ 24-weeks 3.1 (1.2, 5.0) 0.001 3.2 (1.2, 5.3) 0.001 -0.2 (-3.0, 2.6) 0.783 | 0.988

eGFR (ml/min/1.73m2)

Baseline 84.8 ± 8.3b 81.2 ± 12.2

Δ 12-weeks -0.1 (-1.1, 1.0) 0.843 -0.3 (-2.1, 1.4) 0.661 0.3 (-1.7, 2.2) 0.822 | 0.640

Δ 24-weeks -2.6 (-4.0, -1.2) 0.001 -2.4 (-4.1, -0.7) 0.001 0.2 (-2.3, 2.0) 0.880 | 0.964

25(OH)D (nmol/L)

Baseline 75.5 ± 22.1a 68.7 ± 22.4

Continued over page

Page | 255

Δ 12-weeks 25.2 (20.7, 29.6) 0.001 0.2 (-3.9, 4.3) 0.754 24.9 (18.9, 31.0) 0.001 | 0.001

Δ 24-weeks 28.0 (22.8, 33.2) 0.001 3.3 (-2.0, 8.5) 0.155 24.7 (17.4, 32.0) 0.001 | 0.001

IGF-1 (nmol/L)

Baseline 20.0 ± 7.4 18.9 ± 6.2 Δ 12-weeks 0.0 (-0.6, 0.7) 0.813 -0.1 (-0.8, 0.6) 0.970 0.1 (-0.9, 1.0) 0.834 | 0.699

Δ 24-weeks 0.5 (-0.2, 1.1) 0.169 0.1 (-0.8, 1.1) 0.508 0.3 (-0.8, 1.4) 0.663 | 0.409 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate habitual physical activity. a P<0.05, b P<0.01 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 256

6.6.11 Per Protocol Analysis

The per protocol analysis was limited to participants who achieved ≥ 66%

compliance with the PRT program and those in the PRT+ProD group who also

achieved ≥ 80% compliance with the whey protein and vitamin D supplements.

This sensitivity analysis was limited to a total of 41 participants in the PRT+ProD

group and 50 participants in the PRT group. Baseline characteristics for

participants included in the per protocol analysis are presented below in Table

6.22 with the remaining results tables found in Appendix 10 at the end of this

thesis.

Baseline Characteristics

The baseline characteristics were not different between the groups with the

exception that the PRT+ProD group were found to have a significantly higher

number (proportion) of individuals with a family history of diabetes (PRT+ProD,

n=30 (73%) vs PRT, n=20 (41%), P<0.05) and participants classified as normal

weight (BMI 18.5-24.9 kg/m2) (PRT+ProD, n=8 (19%) vs PRT, n=1 (2%),

P<0.05). As a result, the number and proportion of participants classified as

overweight (BMI 25.0-29.9 kg/m2) and obese (BMI >30 kg/m2) was lower in the

PRT+ProD compared to the PRT group (overweight, PRT+ProD, n=13 (32%) vs

PRT, n=18 (19%) and obese, PRT+ProD, n=20 (49%) vs PRT, n=31 (62%), both

P<0.05).

Chapter 6

Page | 257

Table 6.22: Baseline characteristics of participants included in the per protocol analysis of the PRT+ProD and PRT groups.

PRT+ProD PRT

n 41 50 Male / Female, n 23/18 33/17

Age (years) 70.0 ± 6.2 61.8 ± 5.5

Height (cm) 168.8 ± 10.3 170.5 ± 9.7

Ethnicity Caucasian, n (%) 36 (88) 46 (92)

Asian, n (%) 4 (10) 1 (2)

Other, n (%) 1 (2) 3 (6)

Age at diagnosis (years) 53.2 ± 7.2 54.4 ± 7.4

Duration of diabetes (years) 7.8 ± 5.7 7.5 ± 5.0 Family history of diabetes, n (%) 30 (73)* 20 (41)

Diabetes management (lifestyle / medication), n 12/29 18/32

Overweight/Obese

Normal weight, n (%) 8 (19)* 1 (2)

Overweight, n (%) 13 (32)* 18 (36) Obese, n (%) 20 (49)* 31 (62)

Ex-smoker, n (%) 17 (42) 21 (43)

Self-reported co-morbid condition

Hypertension, n (%) 26 (63) 26 (53) Hypercholesterolaemia, n (%) 12 (29) 13 (27)

CVD1, n (%) 5 (12) 5 (10)

Employment status

Working full-time, n (%) 20 (49) 16 (33)

Working part-time/Semi-retired, n (%) 3 (7)** 15 (31) Not-working/Retired, n (%) 18 (44) 18 (36)

Values presented are mean ± SD unless stated. The classification of overweight and obese was completed using the following BMI cut-offs, overweight BMI ≥ 25.0- ≤ 29.9 and obese BMI ≥ 30.0. 1 Cardiovascular disease encompassed previous diagnosis heart disease or previously having suffered a heart attack. 1 Cardiovascular disease encompassed previous heart attack, angina, heart disease and/or stroke. *P<0.05, **P<0.01 vs PRT. CVD, Cardiovascular disease. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Chapter 6

Page | 258

Intervention Results

The findings from the per protocol analysis were similar to those from the

intention-to-treat analysis apart from the following results. Refer to Appendix 10

for all the per protocol results tables.

Diet

A significant between-group difference at 24-weeks was observed in all measures

of habitual protein intake (g, g/kg and percent energy per day, respectively),

which was due to a significant reduction in dietary protein intake (excluding the

supplement) of 12 g/day in the PRT+ProD group along with a non-significant 6 g

increase in the PRT group. A significant between-group difference was also

observed for the change in potassium intake at 24-weeks (P=0.019) only after

adjusting for covariates including age, gender, ethnicity, BMI and moderate-

vigorous physical activity. This between-group difference was driven by a non-

significant 254 mg reduction in the PRT+ProD group and the 338 mg non-

significant increase in the PRT group.

Anthropometry and pQCT

Significant between-group differences at 24-weeks were observed for weight and

BMI (P=0.030 and P=0.046) after adjusting for age, gender, ethnicity and

moderate-vigorous physical-activity, which was driven by significant reductions

(-1.02 kg and -0.42 kg/m2, both P<0.001) in the PRT group along with no change

in the PRT+ProD group. A significant 1.3 cm reduction in waist circumference

(P<0.001) in the PRT group was observed at 12-weeks although this difference

was not different to the PRT+ProD group. A similar significant reduction in waist

circumference in both the PRT+ProD and PRT groups was observed at 24-weeks,

although the magnitude of reduction was slightly greater in the PRT group (mean

change, PRT -2.6 cm and PRT+ProD -1.3 cm). In addition to the above results,

there was a 4.9% increase in 25% femur muscle CSA in the PRT+ProD group

(P=0001) with no change in the PRT group. This led to a trend towards a

significant between-group difference in both the unadjusted model (P=0.056) and

model 3 (P=0.078). Additionally, there was a significant 0.53 kg [(95% CI, 0.31,

0.74) P=0.001] increase in ALM in the PRT+ProD group which greater that the

Chapter 6

Page | 259

gain in the PRT group [0.21 kg (95% CI, 0.01, 0.40) P=0.031] (group-by-time

interaction, P=0.027), but this was not significant after adjustment for the

covariates in model 3 (P=0.184).

Muscle Strength

For the PRT+ProD group, there was a significantly greater gain in upper body

strength compared to the PRT group [net difference for change 16.8% (95% CI,

7.8, 25.8), group-by-time interaction, P=0.033], which remained following

adjustment for covariates in model 3 (P=0.041).

Serum Lipids

The PRT+ProD group experienced a significantly greater reduction in total

cholesterol and LDL cholesterol after 24-weeks compared to the PRT group [net

differences for change: cholesterol -0.24 mmol/L (95% CI, -0.49, 0.01) P=0.049;

LDL -0.20 mmol/L (95% CI, -0.49, -0.05), P=0.011], which remained after

adjusting for covariates (model 3).

Inflammatory Markers

For IL-6, there was a significant between-group difference (group-by-time

interaction) observed at 12- and 24-weeks only in the unadjusted model (P=0.037

and P=0.036). The interaction was driven by a non-significant 23% (P=0.073)

increase in the PRT+ProD group at 12-weeks and a significant 31% (P=0.016)

increase in the PRT+ProD group at 24-weeks with no change in the PRT group at

either 12- or 24-weeks. However, these results were attenuated following

adjustment for covariates in model 3.

6.7 Discussion

The main findings from this 24-week two-arm parallel, RCT in older adults with

T2DM was that the provision of a whey-protein drink (20 g daily and 20 g after

each of the three weekly PRT sessions) and 2,000 IU/day vitamin D did not

enhance the effects of the community-based Lift for Life® PRT program on

glycaemic control, body composition, muscle strength, blood pressure or blood

lipids. However, there was a significantly greater reduction in serum insulin

Chapter 6

Page | 260

concentrations after 12- and 24-weeks in the PRT+ProD compared to PRT group.

Further, there was a significant beneficial effect of PRT combined with whey

protein and vitamin D relative to PRT alone on the anti-inflammatory marker IL-

10, but there were no between-group differences for the change in hs-CRP, TNF-

α, adiponectin, IL-8 or IL-6 after 24-weeks. However, we did find that the PRT

program was safe and effective for improving glycaemic control, total body and

regional (arm and leg) lean mass, thigh muscle size, upper and lower body muscle

strength and lowering waist circumference, fat mass, percentage body fat and

DBP.

Secondary pre-planned analysis examining those who achieved ³66% exercise

adherence combined with ³80% adherence with the whey protein and vitamin D

supplements revealed that there were significant net gains in the PRT+ProD group

for upper body muscle strength and serum IL-6, and a greater reduction in total

cholesterol and LDL cholesterol with a trend for a greater gain in thigh (25%

femur) muscle CSA and arm lean mass. Importantly, there were no serious

adverse events associated with the intervention, and kidney function (eGFR)

improved significantly in both groups. The following sections will provide a

critical discussion of the above findings.

6.7.1 Effects of PRT, Whey Protein and Vitamin D on Lean Mass, Muscle

Size and Strength

Previous research has shown that older adults with T2DM typically experience an

accelerated loss in lean mass and/or strength compared to age-matched, non-

glycaemic controls (146-148). Given the importance of skeletal muscle for

glucose uptake from the circulation, there has been considerable interest in

identifying strategies to optimise lean mass in this group. In this 6-month

community-based RCT, we showed, for the first time, that a daily whey-protein,

leucine enriched, drink combined with vitamin D supplementation, both of which

have shown promise to influence muscle outcomes, did not significantly enhance

the effects of PRT on total body and regional lean mass and thigh muscle size in

older adults with T2DM. However, there was a trend for a modest 0.2 kg (95%

Chapter 6

Page | 261

CI, -0.02, 0.42) greater gain in ALM in the PRT+ProD compared to the PRT

group (P=0.075), which may be due in part, to the significantly higher adherence

to the exercise program in the PRT+ProD group (68% vs 58%). Similarly, the

PRT-related gains in arm and leg lean mass and thigh muscle CSA were 0.5 to

1.8% greater in the PRT+ProD group, but none of these gains were significantly

different from those observed in PRT alone. There are several factors which are

likely to have contributed to the lack of a significant additive effect of the protein-

vitamin D supplement on PRT on muscle outcomes in our study. This includes,

but is not limited to, the baseline habitual protein intakes of participants, the dose

of protein consumed and the subsequent spread in protein intake between the

groups and/or change (increase) over time and the initial vitamin D status of the

participants.

For healthy older adults and the elderly, current guidelines and expert committee

statements recommend PRT be combined with a dietary protein intake level of at

least 1.2 g/kg/day with at least 25–30 g of high-quality protein ingested post-

exercise in order to overcome the anabolic resistance associated with ageing

muscle (495, 619). However, several recent systematic reviews and meta-analyses

have reported that protein/essential amino acid supplementation does not

significantly augment the effects of PRT on muscle mass and/or strength in older

adults (486, 487) or only provides small additional benefits to lean mass (485). In

our study, the lack of any marked additive muscular benefits may be related to the

already high baseline habitual protein intakes of the participants, which averaged

1.21 g/kg/day in the PRT+ProD group and 1.13 g/kg/day in the PRT group. In

support of this notion, a number of other intervention trials in healthy older adults

which found that greater protein intake did not enhance the effects of PRT on

muscle mass or strength also had participants that had initial habitual protein

intakes of ~1.0 to 1.2 g/kg/day (283, 284, 493, 620). However, it is possible that

the type, dose and distribution of protein intake in these studies also contributed

to the lack of any added skeletal muscle benefits to PRT.

Previous research has shown that consuming a bolus of protein (amino acid) can

act as a strong stimuli for endogenous insulin release by the beta–cells of the

Chapter 6

Page | 262

pancreas, particularly when combined with PRT (52, 621). This is important

because insulin stimulates an increase in MPS and suppresses breakdown (622),

and thus insulin resistance in T2DM may contribute further to age-related

anabolic resistance. In our study, long-term supplementation with whey protein

combined with PRT was associated with significantly greater reductions in insulin

levels relative to PRT alone after adjusting for baseline values. This finding is

supported by several acute studies which have shown that whey protein ingestion

post-PRT can increase plasma insulin levels and assist in enhancing the MPS

response in older adults and those with T2DM (276, 281, 379, 623). Conversely,

several other longer-term (≥12-week) trials in healthy or overweight/obese elderly

adults (282-285) and those with T2DM (286) have reported no additive effect of

increased protein consumption with PRT on serum insulin levels. Nevertheless,

the finding that serum insulin levels decreased in the PRT+ProD group in our trial

is consistent with the findings from a previous RCT examining the effects of PRT

plus whey protein supplementation in overweight/obese adults which reported a

significant reduction in plasma insulin area under the curve (AUC) (285). The

reason(s) for this reduction in circulating insulin levels with a combination of

PRT and protein supplementation remains uncertain, and requires further

investigation, but will be discussed in further detail below.

The lack of a significant additive effect of the whey protein supplement with PRT

on muscle outcomes may also be related to the lack of any increases in serum

IGF-1 levels, which is a key growth factor important for muscle hypertrophy

(624, 625). Several previous studies have shown that PRT, particularly high-

intensity PRT, increased protein intake (or supplementation), and the combination

of these factors, can stimulate an increase in IGF-1 in older adults (42, 513, 620).

While the precise reason(s) for the lack of any changes in serum IGF-1 levels in

either group in our study is unclear, it may be related to the modest adherence

with the exercise program, which averaged two session out of the prescribed three

per week, issues related to adhering to the prescribed training intensity (since the

program was implemented within a community-setting), the high level of protein

intake at baseline and/or the relatively modest increase in overall dietary protein

throughout the study.

Chapter 6

Page | 263

Another important factor that has been shown to influence whether protein can

augment the effects of PRT on muscle outcomes in older adults is the type and

dose of protein prescribed. It is well established that whey protein (with an

adequate dose of leucine) can elicit greater increases in postprandial MPS than

other sources of protein (e.g. casein, soy) (39). Acute studies in the elderly have

reported that at least 20 g of whey protein is required to stimulate an increase in

MPS above exercise alone (10 g was ineffective), but 40 g elicited the greatest

response (51). Moreover, there is evidence that 20 g of high-quality protein

containing 2-3 g of leucine maximally stimulates MPS (626-628). In our study,

participants were prescribed a daily dose of 20 g of whey protein providing ~2.4 g

leucine to be consumed prior to breakfast and an additional 20 g after each of the

three weekly PRT sessions. Mean adherence to the supplement was 79%, which

indicates that participants consumed on average, an additional 15.8 g of protein

per day on the non-training days and 31.6 g in a divided dose on the training days.

It is possible that the lack of a significant additive effect on muscle outcomes in

our study relates to the fact that participants were not provided with a single 40 g

dose of whey protein post-exercise. In part support of this notion, the results from

a 6-month trial in 80 mobility limited adults aged 70-85 years found that 40 g of

whey protein divided into 20 g after breakfast and 20 g after the evening meal

combined with PRT led to a non-significant 0.26 kg net gain in total body lean

mass compared to PRT alone (377). Furthermore, in this study by Chale and

colleagues the average increase in protein intake in the whey protein group was

only 18 g when both supplement adherence (mean 72%) and dietary protein

intake was considered, a level similar to that observed in our trial. In the study by

Chale and colleagues this was due to a reduction in habitual total energy and

protein intake, which suggests that the supplement may have been a partial meal

replacements or that there was possibly a satiety effect of the supplement leading

to a reduction in total food intake. Indeed, an acute study in 15 young resistance

training males found that whey protein consumption after PRT reduced

subsequent energy intake by a mean of 437 kJ (348). Consistent with these

results, we also observed a significant reduction in both total energy (mean 437

kJ/day) and protein intake (mean 8 g/day) in the PRT+ProD group.

Chapter 6

Page | 264

The lack of a significant interaction of PRT and whey protein on PRT-related

gains in muscle outcomes in our study may also be explained by an insufficient

spread (difference) in protein intake between the groups (373). After taking into

consideration the changes in habitual protein intake over the course of the

intervention and the adherence to whey protein supplements, we found that there

was an 18% and 36% spread between the groups or a 0.2 g/kg/day and 0.4

g/kg/day between-group spread on the non-training and training days,

respectively. In a previous review of 17 intervention trials examining the effects

of additional protein combined with PRT in both younger and older adults, Bosse

and colleagues (373) found that in studies which detected an additive or

synergistic benefit on muscle outcomes, there was an average 66% g/kg/day

between group spread (difference) in protein intake; a spread of protein intake of

10.2% g/kg/day was found to be ineffective (373). When we performed the pre-

planned per-protocol analysis in participants with ≥66% exercise adherence

(equivalent to two sessions per week) and ≥80% adherence to the whey-protein

and vitamin D supplements the spread in protein intake between-groups on

training and non-training days was around 50% (0.5 g/kg/day) and 20% (0.2

g/kg/day), respectively. This may help to explain the trend towards significantly

greater gains in ALM and thigh muscle CSA in the PRT+ProD compared to PRT

group with this secondary analysis. However, the findings from a 9-month trial in

middle-aged overweight and obese adults found that exercise (PRT 2 days and

aerobic training 1 day per week) combined with an additional 20, 40 or 60 g of

whey protein (divided into two doses and consumed with breakfast and lunch)

and which increased habitual intakes from around 1.0 g/kg/day to 1.15, 1.44 and

1.68 g/kg/day yet compared to control (0.94 g/kg/day) did not increase exercise-

induced responses to total body lean body mass (285). This was despite a 78%

spread in protein intake between the control group and those receiving the highest

dose (60 g/day) of whey protein. However, these findings must be interpreted

with caution given that 43% of participants withdrew from the study, and thus the

study may have been underpowered to detect any differences.

The timing of protein intake when performing PRT and the distribution of protein

intake throughout the day may also influence the skeletal muscle responses to

Chapter 6

Page | 265

exercise (49). Although data on the optimal timing of protein to maximise PRT-

related gains in older adults is limited, a study in elderly men found that ingestion

of 10 g of protein immediately following exercise resulted in greater gains in

muscle size and strength compared to delaying intake by 2 hours after PRT (496).

In addition, the results from a 24-week trial in frail elderly found that providing

additional protein (2 x 15 g) at breakfast and lunch to ensure a more even

distribution of protein throughout the day enhanced the effects of PRT on lean

mass (283). In our study, participants were instructed to consume the whey

protein enriched drink prior to breakfast and as soon as possible following each

PRT session. Unfortunately, no information was collected on the actual times that

the protein supplements were consumed, and data on the dietary protein intakes of

the participants at each meal was not examined. While there is some evidence that

muscles remain sensitive to protein ingestion for up to 24-hours following

training (629), the findings from our study are consistent with several previous

trials in healthy older adults which found that consumption of protein in close

proximity to exercise (282, 497) or through a divided dose (148) did not

significantly augment the effects of PRT on muscle hypertrophy. However, it is

clear that further research is still needed to determine whether a divided dose of

protein when combined with exercise is necessary to enhance the skeletal muscle

responses to training in older adults or those with chronic conditions like T2DM.

A unique aspect of our trial is that it included the combination of PRT with whey

protein and the provision of 2,000 IU vitamin D per day. Vitamin D deficiency

has been associated with reduced muscle mass, strength and function (630-

632)and insulin resistance (633, 634). There is also some evidence that vitamin D

treatment can have a positive effect on muscle protein metabolism (635, 636) and

may act synergistically with leucine and insulin to stimulate MPS (637).

However, the findings from our intention-to-treat analysis indicate that

supplementing with vitamin D and whey protein does not enhance the effects of

PRT on the mass, size or strength of muscle in older adults with T2DM.

Furthermore, pre-planned per protocol analysis in participants with ≥66%

exercise adherence and ≥80% adherence to the whey-protein drink and vitamin D

supplements revealed that there was a significantly greater gain upper body

Chapter 6

Page | 266

muscle strength, ALM (unadjusted only) plus a strong trend towards a greater

gain in thigh (25% femur) muscle CSA and arm lean mass. Several previous

human intervention trials which have investigated the effects of exercise

combined with vitamin D (including fortified milk) or multi-nutrient supplements

with additional vitamin D and protein (503, 512-514, 638-640) on muscle mass

and strength have reported mixed findings. This is likely due to differences in the

dose of vitamin D and protein prescribed (and subsequent changes over time), the

baseline serum 25(OH)D level and habitual protein intake of the participant, and

the health status of cohorts (healthy, elderly/frail or sarcopenic). In our trial, both

groups presented with a sufficient serum 25(OH)D levels at baseline (pooled

mean 72 nmol/L), but as expected, the provision of 2,000 IU of vitamin D daily in

the PRT+ProD group resulted in a significant increase in 25(OH)D levels (mean

change 28 nmol/L) with no change in the PRT group. While there is some

evidence (and expert opinion) that serum 25(OH)D levels of 50 to 75 nmol/L are

required for optimal muscle health and function (641), a recent meta-analysis

found that the greatest benefits of vitamin D treatment on muscle strength were

evident in those with 25(OH)D levels <30 nmol/L and when levels increased by at

least 25 nmol/L; there was no effect of vitamin D on lean mass (462). While it is

difficult to differentiate between the potential effects of protein and vitamin D on

the outcomes in our trial, it is likely that any potential beneficial effects of the

vitamin D on muscle outcomes in our study were blunted by the already high

serum 25(OH)D levels of the participants at baseline.

6.7.2 Effects of PRT, Whey Protein and Vitamin D on Fat Mass and Body

Weight

Along with PRT, long-term whey-protein supplementation or greater protein

intake in older overweight/obese adults has been associated with reductions in fat

mass and total body weight compared to control, (12, 352, 354, 642-644). Whey

protein is believed to improve satiety with the action of satiety hormones

contributing to this effect (348). Vitamin D is another dietary supplement shown

that has been shown to have a positive influence on fat mass and fat distribution,

although the data is very limited (451, 452). Whilst the exact mechanistic

pathways by which vitamin D can achieve this are not known, it has been

Chapter 6

Page | 267

speculated that high intakes of vitamin D can repress fatty acid synthase enzyme

by decreasing intracellular calcium in adipocytes (645). In our trial, no additive

effect of protein and vitamin D was seen on fat mass or total body weight

reductions, but there was a small but non-significant 0.5 kg reduction in fat mass.

The lack of a more pronounced effect on fat mass may have related to several

factors including the dose of protein, the change in total energy intake over the

course of the trial or metabolic adaptations to the intervention. There is also the

possibility that the already sufficient serum 25(OH)D levels of our participants at

baseline influenced the effect supplementary vitamin D had on such outcomes.

Due to whey proteins thermic effect of feeding, high satiety value and ability to

alter hunger hormones such as ghrelin, the regular addition of whey protein

supplements to adults with T2DM diet could plausibly limit total energy intake,

promote weight loss and have a positive effect on fat mass whilst preserving lean

mass (520). When supplementing whey protein with the aim of enhancing

PRT/exercise induced reductions in fat mass the quantity of whey protein has

been suggested to be an important factor influencing such a response (285). In our

trial, we provided 20 g of whey protein on the non-training days or two 20 g doses

on the training days. Whilst these doses of whey protein significantly increased

total protein intake from 1.2 to ~1.5 g/kg/day, there was not a concomitant

reduction in total energy intake. We speculate that the dose of protein on non-

training days (20 g) and the divided dose on training days (one 20 g serving in the

morning and another following training) was inadequate to attenuate energy

intake. Previously studies have shown that whey protein effects subsequent

energy intake in a dose-dependent manner (646) with some studies reporting

significant reductions in body weight, fat mass and even visceral adipose tissue

following the consumption of a~60 g bolus dose of whey protein in older

overweight adults performing exercise or PRT (355, 520). Coinciding with these

body composition improvements in one of the studies, significant reduction in

appetite and energy intake was also observed (355). In contrast to these findings,

a 36-week study providing whey protein in doses ranging from 20 g, as in our

trial, up to 60 g per day observed no significant between group differences for the

change in fat mass or total body weight between the group or controls receiving

Chapter 6

Page | 268

no additional protein (285). The lack of a difference between the groups in fat

mass reduction in that study was proposed to be due to the participants already

consuming an adequate level of protein intake at baseline (>0.9 g/kg/day) which

may have blunted the satiety effect of additional whey protein (285). Participants

in our trial also had high intakes of protein at baseline which may explain the

absence of a significant reduction in energy intake and/or differences for the

change in body composition.

In our study changes in fat mass and body weight were small and similar in both

groups. These results are consistent with another trial which found that the

combination of exercise, whey protein and vitamin D was no different to exercise

alone in reducing fat mass or total body weight in older sarcopenic adults (513).

Indeed, the magnitude of change in fat mass and weight loss in this study by

Rondanelli et al (513) was similar to that observed in our trial. Similarly, another

trial also observed no added benefit of a high-whey protein and vitamin D

enriched supplement plus PRT on fat mass or total body weight in obese adults,

although this trial also included a caloric restricted diet making comparisons

difficult. (512). Nevertheless, the small improvements in fat mass and total body

weight in our trial are similar to some other PRT trials in older overweight/obese

adults with T2DM in the absence of caloric restriction (203, 216, 250), yet others

have reported much greater losses in weight and fat mass (7, 8, 202, 208, 217).

These differences could be related to the fact that we conducted a ‘real-world’

community-based program which contrasts with many others which were

performed in clinically controlled exercise laboratories.

6.7.3 Effects of PRT, Whey Protein and Vitamin D on Glycaemic and

Insulinaemic Outcomes

Previous research has shown that whey protein (and a high protein diet) can have

an insulinotropic effect, and thus stimulate insulin secretion to enhance glucose

clearance from the blood (333, 403, 647). Moderate- to high-intensity PRT has

also been shown to improve glycaemic control and insulin sensitivity, but whether

whey protein supplementation can enhance the effects of PRT on these outcomes

in older adults with T2DM remains uncertain. In this 6-month RCT in 198

Chapter 6

Page | 269

overweight and obese older adults with T2DM there was a 0.56 mmol/L (6.8%)

greater reduction in FPG in the PRT compared to PRT+ProD group after 24-

weeks, but this was not significant after adjusting for covariates. Conversely,

there was a significant reduction in serum insulin concentrations in the

PRT+ProD after 12- and 24-weeks, that differed from the PRT group after

adjusting for baseline values, which would indicate an improvement in insulin

sensitivity. However, there was no evidence to support an additive effect of PRT

with 20 g of whey protein consumed daily prior to breakfast and an additional 20

g within two hours of each of the two to three weekly PRT sessions, on the

clinically relevant outcome measures of HbA1c or insulin sensitivity as assessed

via the HOMA model.

Consistent with the results from our 6-month RCT in older adults with T2DM, a

number of previous intervention trials in healthy older adults and those with

metabolic syndrome or T2DM have also failed to detect any additive effect of

increased dietary protein, whey protein or a milk-based protein supplementation

with PRT on glycaemic and insulinaemic outcomes when compared to exercise

/PRT (283-285, 305, 519-521, 648). For instance, a 16-week intervention

involving an energy-restricted diet with either a standard or high protein intake

(19% vs 33%), with or without PRT performed three days per week, in

overweight and obese adults with T2DM resulted in similar significant reductions

in HbA1c, FPG and serum insulin, despite greater weight and fat loss in the high

protein plus PRT group (286). Similarly, the findings from a 36-week RCT in

middle-aged overweight and obese adults with FPG levels within the ‘normal’

range (<6.1 mmol/L) revealed that whey protein supplementation at 0, 20, 40 or

60 g per day combined with twice weekly PRT and aerobic training had no effect

on glucose levels [OGTT glucose area under the curve (AUC)] or insulin

resistance (HOMA-IR) yet insulin AUC decreased significantly by 2.6% across

the groups (285). There are a number of factors which may explain the lack of an

added benefit of increased protein combined with PRT on glycaemic outcomes in

both our study and previous trials. This could include the baseline HbA1c or FPG

status of the participants, the use of oral hypoglycaemic medications, the habitual

protein intake of participants, the type, timing and dose of protein prescribed and

Chapter 6

Page | 270

subsequent spread (difference) in protein intake between groups, and differences

in duration of the intervention period.

For people with T2DM it is generally recommended that they maintain a HbA1c

level ≤ 7% and FPG between 6-8 mmol/L as this has been associated with a

reduced risk of long term T2DM-related complications (649, 650). In our study,

the mean baseline HbA1c level of participants in the PRT+ProD and PRT group

was 6.9 and 7.1%, respectively (mean FPG levels were 7.9 and 8.6 mmol/L,

respectively). Overall less than half of the participants (44%) had an initial HbA1c

>7%, and there was a significantly higher proportion of participants with a level

above this cut-point in the PRT compared to PRT+ProD group (51% vs 37%).

This may explain, in part, our finding that the combination of PRT with whey

protein supplementation did not lead to greater benefits on glycaemic control and

insulin sensitivity compared to PRT alone. However, secondary analysis revealed

that there was no significant interaction by baseline HbA1c status (≤7 vs >7%).

Consistent with our findings, nearly all previous studies which reported no added

benefit of increased dietary or supplemental protein with PRT on HbA1c, insulin

sensitivity or insulin resistance included participants with adequate glycaemic

control (148, 283, 285, 520, 521, 648). Given that there are some reported

benefits of whey protein supplementation or a higher protein intake (without

PRT) on HbA1c or FPG levels in participants with poor glycaemic control (HbA1c

>7.5%) (38, 263, 272, 396), further research is warranted to investigate whether

the combination of exercise with increased dietary protein or protein

supplementation can improve glycaemic measures in older adults with poorly

controlled T2DM.

One of the challenges when conducting lifestyle-related intervention trials in

individuals with T2DM is that many participants are taking oral hypoglycaemic

medications to maintain their blood glucose levels. Given the marked effect that

these agents have on measures of glycaemic control, it is possible that they may

mask or attenuate any potential beneficial effects of lifestyle-related approaches.

In our study, 70% of the participants were taking a prescribed oral hypoglycaemic

agent at baseline, with an equal proportion within each group. Although the

Chapter 6

Page | 271

number of participants taking such medication did not change significantly in

either group throughout the study (and there was no marked change in dosage),

there was a higher proportion (~10% difference) of participants in the PRT+ProD

group taking oral hypoglycaemic medications at 12- and 24-weeks. However, this

is unlikely to have influenced the findings as all results remained unchanged after

adjusting for the use of oral hypoglycaemic medications, and secondary analysis

revealed that there was no interaction by diabetes management (lifestyle alone

versus medication) for any of the glycaemic outcome measures. However, given

the small number of participants that were managing their diabetes through

lifestyle approaches alone, it is likely that we were underpowered to detect any

potential added benefits of the whey protein supplement on PRT related changes

in glycaemic outcomes in this subgroup.

As already indicated, there is considerable evidence supporting an insulinotropic

effect of protein, but whether there is an optimal level of intake (intake at

g/kg/day) or dose of protein necessary to cause this effect and improve glycaemic

control or enhance the glycaemic improvements of PRT over the long-term

remains uncertain. Yet the findings from various acute studies indicate that there

are positive effects on postprandial glucose levels and insulin secretion with 10 to

55 g of whey protein provided with a meal or pre-meal (52, 342, 621, 651, 652).

Based on these findings one would anticipate that a 20 g daily dose of whey

protein consumed prior to breakfast and an additional 20 g taken after each PRT

session would be sufficient to elicit a positive response when combined with PRT.

It is possible that the lack of any exercise-protein interaction in our study may

relate to the habitual protein intake of the participants which exceeded 1.1

g/kg/day at baseline (~20% protein). However, the results from a 5-week

randomised, calorie-controlled crossover study in 12 adults with T2DM (mean

HbA1c 8.0%) revealed that a high-protein diet (30% protein) led to a 40%

reduction in the 24-hour glucose area response and a 0.5% absolute greater

reduction in HbA1c (-0.8 vs -0.3%) compared to an isocaloric conventional low-

fat diet (15% protein) (263). A possible reason for the positive effect in this study

by Gannon and colleagues is the large between-group difference in protein intake

(30% vs 15%). However, in our study similar between-group differences were

Chapter 6

Page | 272

observed. The average protein intake (diet plus supplement) differed by

approximately 10-18% and 26-35% on the non-training and training days,

respectively. Another potential explanation may be that older adults with T2DM

require a higher dose of protein to experience a similar response. Indeed, several

acute studies have shown that 50 to 55 g of whey protein consumed prior to a

meal significantly improved postprandial glycaemia in adults with T2DM (342,

379), although others have reported that a dose of ~20-25g is also effective (341,

653). Further research is needed in adults with T2DM to evaluate the effects of

whey protein alone and combined with PRT on long-term glycaemic control.

Contrary to the findings from many acute studies examining the effects of whey

protein on insulin responses, we found that there was a significant reduction in

serum insulin concentrations in the PRT+ProD group after 12- and 24-weeks,

which differed from the changes in the PRT group after adjusting for baseline

values. In line with these findings, a 12-week study in overweight and obese

adults found that daily consumption of 55 g of whey protein resulted in a

significant 10-11% reduction in plasma insulin concentrations (351). However,

unlike the findings from our trial this study by Pal and colleagues also detected a

significant decrease in HOMA assessed insulin resistance, suggesting that there

was an improvement in long-term insulin sensitivity. While a number of previous

intervention trials ranging from 12- to 36-weeks in healthy older adults and those

with metabolic syndrome or T2DM have reported a significant reduction in serum

insulin levels following increased dietary protein or whey protein

supplementation with and without exercise, none of these studies observed an

added benefit of protein combined with exercise or between-group differences

when different doses of protein were combined with exercise (285, 286, 520,

648). Furthermore, secondary analysis of a 36-week trial in overweight and obese

adults who performed resistance and aerobic exercise twice weekly and were

supplemented with either 0, 20, 40 or 60 g per day of whey protein found that

neither total protein intake nor the change in protein intake expressed as g/kg/day

throughout the study was associated with changes in insulin, HOMA-IR or insulin

sensitivity (494). The finding that there was a greater reduction in insulin levels in

the PRT+ProD group in our study may be explained, in part, by the higher level

Chapter 6

Page | 273

of adherence to the training as there is some evidence that training volume is

related to the magnitude of decrease in serum insulin concentrations (654).

Furthermore, since there was a decrease in C-peptide levels in the PRT+ProD

group, which provides a measure of insulin secretion, this suggests that the

decrease in insulin was driven by a reduction in insulin secretion. However, the

clinical significance of these changes remains uncertain given that there were no

significant long-term benefits on insulin sensitivity.

Increased levels of pro-inflammatory markers (e.g. hs-CRP, IL-6 and TNF-α)

have also been associated with poor glycaemic control in adults with T2DM

(525). While there is some data showing that PRT-related improvements in

inflammatory markers in older overweight adults coincide with improvements in

insulin resistance and/or glycaemic control (236, 237, 555), from the limited data

available (most studies have only measured hs-CRP) there appears to be no

evidence that increasing protein intake or protein supplementation can enhance

this response (285, 286). However, in our study there was a significant increase in

the level of the anti-inflammatory marker IL-10 in the PRT+ProD compared to

PRT group, but this was also associated with a greater increase in the pro-

inflammatory marker IL-8 at week 12. It is difficult to explain these findings,

particularly as there was little shift in the remaining pro- and anti- inflammatory

markers (adiponectin, IL-6, hs-CRP) in either group, which may be related to the

modest reductions in fat mass, a well-known contributor to increased

inflammation. Given these mixed findings, it is possible that the lack of a more

systemic between-group difference or improvement in the various inflammatory

markers in our study may have contributed to the lack of any between-group

differences in the glycaemic outcome measures, but this requires further study.

Evidence exists to support a direct relationship between serum 25(OH)D

concentrations and insulin sensitivity and HbA1c (634, 655, 656). Further,

correcting vitamin D deficiency with supplementation has been shown to improve

insulin sensitivity in some studies (657, 658), However, as reviewed by others,

the evidence from intervention trials assessing the effects of vitamin D

supplementation on glycaemic outcomes in adults with normal glucose tolerance

Chapter 6

Page | 274

and people with T2DM remained mixed (659) with any potential benefits likely to

be most prominent in people with prediabetes and insufficient/deficient baseline

serum 25(OH)D levels (571). In our study, the mean baseline serum 25(OH)D

level of the participants in the PRT+ProD and PRT group was well within the

normal range (mean 75 and 69 nmol/L, respectively); only 19% of participants

had a level below 50 nmol/L which some consider insufficient. Although

treatment with 2,000 IU daily increased serum 25(OH)D levels by an average of

28 nmol/L after 6-months, given that adequate basal serum 25(OH)D levels (and

HbA1c status) it is unlikely that such an increase provided any added benefits. If

vitamin D treatment does influence glycaemic measures in adults T2DM, further

research is still needed to determine if there is an optimal dose and serum

25(OH)D concentration that is likely to provide any benefits, and whether it is

restricted to those with poorly controlled diabetes.

Despite the lack of any significant exercise-protein-vitamin D interaction on the

glycaemic outcome measures, there was a significant 0.13% to 0.15% absolute

reduction in HbA1c in both the PRT+ProD and PRT group after 12-weeks, which

tended to persist in both groups after 24-weeks. Over the past two decades, there

have been many intervention trials and subsequent meta-analyses which have

reported that PRT, particularly supervised and structured in well controlled

laboratory, clinic or gymnasium settings, can improve glycaemic control and/or

insulin sensitivity in people with T2DM (12, 157, 203, 212, 228, 612, 660). In the

most recent meta-analysis of PRT trials of at least 8-weeks duration in older

adults aged at least 60 years with T2DM (n=8), Lee et al. (660) found that PRT

significantly lowered (absolute reduction) HbA1c by 0.50%. Other meta-analyses

have reported similar absolute mean 0.34% to 0.57% improvements in HbA1c

following PRT (227, 228), although it was noted that there was considerable

heterogeneity among the studies. Nevertheless, these changes are considerably

greater than the mean changes observed in our study, which may be explained by

a number of factors, including the baseline HbA1c status of our participants.

Subgroup analysis from several previous meta-analyses have shown that

participants with higher baseline HbA1c levels (>7.0 or 7.5%) experience greater

PRT-related improvements when compared with those with baseline levels below

Chapter 6

Page | 275

these cut-points (8, 228, 661). Thus, the modest reductions observed in our study

are likely related to the fact that the mean basal HbA1c levels of the participants in

the PRT+ProD and PRT group was 6.9 and 7.1%, respectively. However, it is

worth noting that no significant interaction by baseline HbA1c status (≤7 vs >7%)

was observed in our study, but less than half of all participants had a baseline

HbA1c level >7%.

Another likely explanation for the modest improvements in our study was that the

PRT program was conducted across 80 different local health and fitness and not

within a controlled clinical setting. Although all participants were enrolled within

the community-based Lift for Life® program, which is a structured PRT program

based on evidence from clinical trials that is implemented and supervised by

exercise trainers who have received specialised training as part of the Lift for

Life® accreditation process, it was not possible to control or standardise the

prescription of exercise across all facilities. A previous cluster RCT examining

the effectiveness of the standard compared to an enhanced behaviourally focused

Lift for Life® program in overweight adults and those with T2DM reported no

changes in HbA1c following the standard program and a modest net 0.13%

absolute improvement after 24-weeks in those who received the enhanced

program; when the analysis was restricted to those participants with T2DM the

net benefit was 0.3% (662). On this basis, it is difficult to explain why such

modest improvements were observed in HbA1c in our cohort of overweight and

obese adults with T2DM.

A previous meta-analysis of community-based physical activity interventions for

adults with T2DM reported a trend toward a lowering of HbA1c (mean -0.32%,

P<0.06) (23), but another meta-analysis found that structured exercise training of

>150 minutes per week was associated with greater reductions in HbA1c in adults

with T2DM than that of ≤150 minutes per week (227). While neither of these

studies focused specifically on PRT, the findings from several meta-analyses have

indicated that the characteristics of PRT programs (volume, intensity, frequency

or duration) appear to have little influence on the changes in HbA1c or other

related measures (227, 228, 660). While this may be due to the similarity in the

Chapter 6

Page | 276

design of many of the previous PRT programs, a potential explanation for the

small improvements in glycaemic control in our study may relate to the adherence

to the training (PRT+ProD 68%; PRT 58%). However, this still equates to

approximately two out of three PRT sessions per week, which is in line with most

current exercise guidelines for people with T2DM. An alternative reason for the

small improvements in HbA1c in our study may relate to the relatively modest

gains in lean mass (mean 0.4 to 0.5 kg), which was lower than that observed in

another laboratory clinical trials which observed greater benefits on glycaemic

control (12). However, as indicated earlier there is some evidence that PRT-

related reductions in HbA1c can occur without any marked changes in lean mass

(660, 663).

The cessation of a single bout of PRT/exercise causes improvements in both

glucose disposal and metabolism which may last for several hours or possibly

days (664). Due to this it is unknown whether the improvements typically

observed in insulin sensitivity following exercise training in those with T2DM is

due to the accumulative effects of the individual exercise sessions or an

adaptation induced from long-term training (665). To avoid any residual effect of

the final PRT session on FPG and insulin levels, participants in our trial were

instructed to provide a fasted blood sample at least 48-hours following their last

PRT session. It is possible that this timing may explain the lack of a significant

difference between the PRT+ProD and PRT groups in FPG and insulin sensitivity

as assessed by the HOMA model. It is also possible that the major effect of the

PRT program was on postprandial glucose and insulin sensitivity which were not

assessed but are dependent on muscle insulin sensitivity.

In summary, this study indicates that a community-based PRT intervention in

older adults with T2DM was associated with modest improvements HbA1c, but

there no evidence of any added benefits of whey protein and vitamin D treatment

on either glycaemic control or insulin sensitivity.

Chapter 6

Page | 277

6.7.4 Effects of PRT, Whey Protein and Vitamin D on Blood Pressure and

Lipids

Despite reports from some reviews and meta-analyses that PRT, high protein diets

and supplementation with whey/dairy proteins or vitamin D can improve various

cardiovascular outcomes (38, 212, 333, 659, 666-670), few intervention trials

have investigated whether such nutritional approaches can provide additive

benefits to exercise in people with T2DM. In our 6-month RCT in older

overweight and obese adults with T2DM, we found that there was no additive

benefits of daily whey protein and vitamin D supplementation to a community-

based PRT program on any cardiovascular outcomes. After 24-weeks there were

similar significant reductions in DBP in both groups along with a small reduction

in total cholesterol and LDL cholesterol in the PRT+ProD group at 12-weeks, but

these benefits were not maintained to 24-weeks. The reason(s) why we did not

observe more meaningful improvements in these outcomes following either PRT

alone or PRT in combination with whey protein and vitamin D supplements may

be due to a number of factors, including the small changes in weight and fat mass,

the relatively high proportion of participants taking anti-hypertensive and lipid-

lowering medication, the basal blood pressure and lipid levels of the participants,

the adequate basal dietary protein and serum 25(OH)D status of participants

and/or differences in the adherence to the intervention. Indeed, per-protocol

analysis of participants who achieved ≥66% compliance with the PRT program

and ≥80% compliance with the whey protein and vitamin D supplements revealed

that the PRT+ProD group experienced a significantly greater reduction in both

total cholesterol and LDL cholesterol after 24-weeks compared to the PRT alone.

In line with the findings from the intention-to-treat analysis of our 6-month trial,

several previous intervention trials in older overweight adults and those with

metabolic syndrome or T2DM have failed to detect any added benefits of whey

protein supplementation or increased dietary protein in combination with PRT on

change in cholesterol or lipid profiles and blood pressure compared to PRT alone

(42, 284-286, 513, 648, 671). The lack of an interactive effect in our study and

many of these previous trials is likely related to the fact that most participants had

baseline lipid and/or blood pressure profiles within the normal healthy range. In

Chapter 6

Page | 278

addition, more than 50% of participants in our study were taking anti-

hypertensive or lipid-lowering medication, which may attenuate any potential

benefits. We detected no interaction by use of lipid-lowering or anti-hypertensive

medication in our study for any blood pressure or lipid profile measure and like

our findings one 12-week trial in 28 overweight men with hyperlipidaemia also

failed to detect any added benefit of 26.6 g per day of whey protein combined

with PRT on blood lipids levels compared to PRT alone (671). While this may be

related to the small sample size in the previous study, an alternative explanation is

that a higher dose of whey protein may be needed to elicit a positive response.

Subgroup analysis of a previous meta-analysis of 13 RCTs found that the effects

of whey protein (without exercise) on serum triglyceride levels were greatest at

doses of ≥30 g (670). Moreover, a 12-week non-exercise trial in overweight and

obese adults (not taking lipid-lowering or anti-hypertensive medication)

demonstrated that supplementation with 27 g of whey protein isolate twice daily

(total 54 g per day) decreased total cholesterol and LDL cholesterol compared to

either casein and a control group (351). In part support of these findings, the per

protocol analysis in our study revealed that participants who were ≥80%

compliant with the whey protein and vitamin D supplements (and ≥66%

compliant with PRT) experienced a significantly greater reduction in total

cholesterol and LDL cholesterol compared to the non-supplemented group.

Interestingly however, the mean daily protein intakes after 12- and 24-weeks in

the PRT+ProD group increased by only 15 and 7 g and 34 and 26 g relative to

baseline on the non-training and training days, respectively. While further

research is still needed to determine if there is an optimal dose of protein to

enhance cardiovascular health outcomes, secondary analysis of a previous 36-

week exercise-whey protein supplementation trial in middle-aged overweight and

obese adults revealed that neither total protein intake (mean 1.18 g/kg/day) or

change in protein intake (mean 0.15 g/kg/day) throughout the study combined

with exercise were associated with changes in any cardiovascular index (blood

pressure or lipid measures) (494).

Chapter 6

Page | 279

We hypothesised that combining a whey protein drink with vitamin D

supplements would provide added benefits to PRT on cardiovascular risk factors.

To our knowledge, no previous studies have examined the effects of additional

protein plus vitamin D treatment with PRT with both protein and vitamin D on

blood pressure or lipids levels in older adults or those with T2DM. However, data

from a 12-week trial in vitamin D deficient elderly women discussed already in

section 2.11.1 was more effective at lowering blood lipids than either exercise or

vitamin D alone or even controls (502). Thus, in our study the lack of any additive

benefits of the vitamin D (plus protein) supplementation with PRT on blood

pressure or serum lipid measures may be related to the fact that a large proportion

of the participants had serum 25(OH)D levels that would be considered sufficient

(>50 nmol/L). Interestingly, a 20-week RCT in 130 hypertensive patients found

that 3,000 IU cholecalciferol per day had no effect on blood pressure, but

subgroup analysis revealed that participants with 25(OH)D levels <80 nmol/L did

experience a decrease in blood pressure (672). Whether there is an optimal serum

25(OH)D concentration to improve cardiovascular health outcomes remains

uncertain, but other long-term trials where participants had insufficient/deficient

levels of serum 25(OH)D levels (<30 nmol/L) have more consistently

demonstrated improvements in cardiovascular health following vitamin D

supplementation, including SBP and/or lipid measures (177, 502)

In older adults with T2DM the findings from two meta-analyses of RCTs have

reported a positive effect of PRT on blood pressure (212, 673). In our study, there

was a similar significant mean 2.4 to 2.6 mmHg reduction in DBP in both groups

after 24-weeks; SBP also decreased by an average of 2.4 mmHg in the PRT and

2.6 mmHg in the PRT+ProD group, but these within-group changes were not

statistically significant (P=0.08 and P=0.10, respectively). Nevertheless, a

previous meta-analysis of RCTs of blood pressure lowering regimens reported

that a reduction in SBP and DBP of 2.1 and 0.9 mmHg was associated with a 10%

reduced risk of major cardiovascular events (674). While this suggests that the

changes in our study are clinically meaningful, the magnitude of the changes were

slightly lower than these weighted mean differences of -4.44 mmHg for SBP and

-2.84 mmHg for DBP between PRT and controls from a meta-analysis of 10

Chapter 6

Page | 280

interventions in adults with T2DM (247). The reason(s) for these differences,

particularly regarding SBP, may relate to the modest mean 0.6 to 0.9 kg

reductions in total body fat mass in both groups in our study. Indeed, the findings

from a meta-analysis of 6,754 participants in 11 studies examining the effects of

weight loss from lifestyle interventions (diet and/or physical activity) over 12-

months on blood pressure in overweight and obese adults with T2DM found that

less than 5% weight loss was not associated with any marked improvements

(675). Other potential reasons for the modest improvements in blood pressure in

our study may relate to the implementation of the PRT within community-based

facilities which may have contributed to marked inter-individual variability in the

training intensity, the finding that only 44% of participants in the study were

classified as hypertensive based on SBP (≥140 mmHg) and/or DBP (≥90 mmHg)

and/or that more than 50% of the participants were taking anti-hypertensive

medication. However, subgroup analysis of several meta-analysis has found that

any between group differences for the change in blood pressure following PRT

were not related to either baseline blood pressure level or training intensity (228,

247), but there is some evidence that structured and longer duration programs

(>40-weeks) are most effective for improving blood pressure (676).

With regard to the effects of our PRT program on blood lipid levels, we found

that there were no marked benefits in either group after 24-weeks, despite some

initial benefits in the PRT+ProD group after 12-weeks. This appears to be in

contrast with the findings from a 2014 meta-analysis comparing aerobic and PRT

interventions in adults with T2DM which reported significant improvements in

total cholesterol, LDL cholesterol and triglycerides following PRT; there was no

effect of PRT on HDL cholesterol (212). There are likely to be a number of

factors that contributed to the lack of any improvements in blood lipids levels

following our 24-week PRT intervention. First, the baseline blood lipid profiles of

the participants in our study were generally within the healthy range; for each

lipid measure 60 to 83% of participants were classified as ‘normal’. In a previous

6-month RCT in older overweight and obese adults with T2DM with mean basal

lipid levels generally within the healthy range, Dunstan et al. (12) found that high-

intensity PRT combined with moderate weight loss had no effect on any blood

Chapter 6

Page | 281

lipid measure. Second, more than 50% of the participants in our study were taking

lipid-lowering medication, although no interaction by lipid-lowering medication

use was detected for any measure which may again be related to the basal lipid

profiles of our participants. Finally, the magnitude of the change (loss) in weight

and fat mass in our study was small. Previous research has shown that reductions

in weight of less than 5% following PRT or a multi-modal exercise program

failed to alter blood lipid levels in older adults with T2DM in interventions lasting

from 22-weeks to 24-months (8, 677).

6.7.5 Effects of PRT, Whey Protein and Vitamin D on Markers of

Inflammation

Since T2DM has been associated with chronic low grade systemic inflammation

which has been linked to poor glycaemic control and an increased risk of

diabetes-related complications, there has been considerable interest in identifying

strategies to improve the inflammatory profile of people with this condition.

There is emerging evidence that PRT (230, 244), vitamin D supplementation

(678) and dairy or whey protein supplementation (325, 326) may improve various

circulating pro- and/or anti- inflammatory markers in older adults and those with

T2DM, but whether the combination of vitamin D and whey protein

supplementation interact to enhance the effects of exercise on inflammatory

markers remains uncertain. In our 24-week RCT in overweight and obese adults

with T2DM, we observed mixed effects for the combination of PRT with whey

protein and vitamin D supplementation compared to PRT alone on various

circulating inflammatory markers. There was a significantly greater increase in

the anti-inflammatory marker IL-10 in the PRT+ProD compared to PRT group

after 12- and 24-weeks. While there were no significant between group

differences for the change in hs-CRP, TNF-α, adiponectin, IL-8 or IL-6 after 24-

weeks, an interesting observation was that all inflammatory markers tended to

increase relative to baseline in the PRT plus supplemented group and decrease in

the PRT group.

While it is difficult to explain the contrasting findings from our study and the

clinical relevance of the results, the most profound changes and between-group

Chapter 6

Page | 282

differences were for the anti-inflammatory marker IL-10 which increased in the

PRT+ProD group and decreased in the PRT group. A previous 16-week

intervention in free living overweight/obese adults found that whey protein

supplementation (20 g three times per day) combined with either PRT or a

multimodal exercise program (4 times per week) increased serum adiponectin

levels, another anti-inflammatory cytokine, by 18 to 23% compared to protein

supplementation alone (-6% change) (520). However, since there was no exercise

alone group in this study it is difficult to compare these findings with our results.

The reason(s) why some circulating inflammatory cytokines appear to improve

and others do not change in response to a given intervention remains uncertain,

particularly given that many cytokines (e.g., IL-6, TNF-α, adiponectin) are

produced at the same site (e.g. adipose tissue) and the pro-inflammatory markers

IL-6 and TNF-α are known to induce hepatic production of hs-CRP. Nevertheless,

this mixed response is a consistent observation from many previous exercise

and/or nutrition interventions (679-681).

One of the most common inflammatory markers that has been measured in many

previous exercise and nutrition interventions is the pro-inflammatory cytokine hs-

CRP. The inflammatory marker hs-CRP is a substance produced by the liver that

increases in the presence of inflammation in the body, and has been linked to

cardiovascular disease (682-684). In our study, hs-CRP levels did not change or

differ between the groups at any time throughout the 24-week intervention.

Consistent with these results, several previous intervention trials in

overweight/obese adults or those with T2DM reported that increased dietary

protein (286), whey protein supplementation (285) or vitamin D supplementation

(685) did not augment the effects of PRT on serum hs-CRP levels. This may be

due in part, to the fact that baseline hs-CRP levels were not elevated (only 19% of

participants in our study had an hs-CRP level >3 mg/L which is considered high).

Indeed, subgroup analysis of a 2015 meta-analysis reported that there was a small,

but significant effect of whey protein on lowering serum hs-CRP levels in those

with baseline values ≥3 mg/L (326). However, a 12-week study in 130 sarcopenic

elderly people with apparently normal hs-CRP levels found that there was still a

significant net benefit on hs-CRP levels following supplementation with a multi-

Chapter 6

Page | 283

nutrient drink containing whey protein (22 g), essential amino acids (10.9 g,

including 4 g leucine) and vitamin D (100 IU/day) in combination with a

moderate-intensity strength and balance exercise program (5 days per week)

compared to exercise plus placebo (513). This was due to a non-significant

reduction in the supplement group (P=0.329) and a non-significant increase

(P=0.061) in the placebo group. Unfortunately, nearly all the above trials did not

measure other pro- or anti-inflammatory cytokines, and thus it is not possible to

determine whether exercise combined with increased protein and/or vitamin D

has an effect on improving systemic inflammatory markers. However, the

findings from a 3-month intervention in 36 patients with chronic obstructive

pulmonary disease found that circulating levels of TNF-α, IL-6 and IL-8 all

decreased significantly after daily consumption of a whey protein enriched drink

combined with a low-intensity exercise program compared with those in the

control group, which may be related in part, to the elevated levels of inflammation

at baseline (386).

In overweight/obese adults previous research has consistently shown that diet

induced weight loss has a positive effect on lowering circulating pro-

inflammatory markers and increasing anti-inflammatory cytokines (549, 686,

687). Given that there was a significant, albeit modest, similar reduction in

weight, fat mass and waist circumference in both groups in our study, it is

somewhat surprising that we did not see consistent reductions in the measured

pro-inflammatory cytokines after 24-weeks, particularly in the PRT+ProD group

as exercise adherence was significantly higher in this group. Indeed, a 4-month

RCT in elderly women found that PRT combined with a protein enriched diet

achieved through the consumption of lean red meat (daily protein intake of ~1.3

g/kg/day) was associated with a 16% significantly greater reduction in the pro-

inflammatory marker IL-6 compared to PRT alone (42). Consistent with our

findings however, was the observation that there was no effect on any other pro-

or anti-inflammatory markers including TNF-α (42). Peake et al. (569) reported a

trend for an increase in serum IL-6 concentrations in older men following

supplementation with calcium-vitamin D fortified milk for 18-months, but this

was attenuated after adjusting for changes in fat mass. In our study, all results

Chapter 6

Page | 284

remained unchanged after including total body fat mass in the model. Based on

these mixed findings, further research is warranted to evaluate if there are any

potential additive or synergistic effects of exercise with various nutritional factors

on a range of circulating systemic markers of inflammation.

6.8 Strengths and Limitations

The strengths of this study lie in its randomised controlled design, the 24-week

intervention period, the large sample size of older adults with T2DM, the high

retention rate (85%), the low number of adverse events associated with the

intervention, and the successful implementation of the intervention within the

community. However, there are a number of limitations which may help to

explain some of the findings from this trial.

First, the older men and women with T2DM recruited to this trial had an average

HbA1c level of 7.0% which is indicative of good glycaemic control. Further,

around 70% of the participants were prescribed oral anti-hyperglycaemic

medication to manage their T2DM. Similarly, many had blood pressure and lipid

levels within the normal range which may also be explained by the high

proportion of participants taking anti-hypertensive and lipid-lowering medication.

In addition, mean dietary protein intakes and vitamin D status were adequate at

baseline based upon current recommendations. Collectively, these factors may

have limited the ability to detect potential improvements or between group

differences with the intervention.

Second, the PRT program was implemented across 80 different health and fitness

centres throughout Melbourne and surrounding regions. This was more sites than

originally we had planned but it was a necessity that we expand to this many

training sites when recruitment slowed. Mean adherence to the exercise program

averaged 63% which is equivalent to approximately two sessions out of the

prescribed three per week. This level of adherence is comparable or slightly lower

to that reported in many other PRT interventions over a similar period in older

adults and those with T2DM, even when training was performed under a

supervised laboratory based setting (42, 514). However, the fact that participants

Chapter 6

Page | 285

exercised at 80 different health and fitness centres across Melbourne and

surrounding regions with each location having their own exercise trainers made it

difficult to ensure consistency with regard to the prescription of exercise across

all programs. However, we did attempt to control for this variability by having all

trainers attend a two-day training workshop prior to any participants being

allocated to their respective training location. Similarly, the intensity of training

(or each exercise) was recorded using the RPE scale, but since this is a subjective

rather than a quantifiable measure it is possible that the intensity of training

between individuals varied considerably. However, the collection of the exercise

cards monthly for review by trial staff meant any drop in self-reported intensity

was readily observed and promptly rectified. In addition, the PRT program

consisted of equal parts upper and lower body exercises, however, given the

lower body has some of the largest muscle groups it is possible that the training

program underemphasised major muscle groups of the hips and legs. This

limitation in the design of the PRT program inadvertently may have had an

impact on the change in strength, body composition and even glycaemic control.

Third, a placebo or energy matched control drink was not used in this trial as it

became evident during the initial establishment phase of the study that the

ingredients used to develop such a placebo product had the potential to alter blood

glucose levels or influence muscle mass which were the two key outcomes of this

trial. The absence of a placebo or energy matched drink meant participants were

not blinded to which treatment group they were in which could have created a

certain bias towards performing the PRT program in the study or that the non-

supplemented group may have increased their protein and/or vitamin D intake.

However, the findings from the dietary analysis indicate that this did not occur. In

addition, the supplement may have also acted as an incentive to perform the PRT

program, which may possibly explain the significantly higher adherence to the

training in the PRT+ProD group. Also, the glycaemic effects of meals adjacent to

the consumption of the protein supplement was not considered and is a limitation

of our analysis. For instance, a 25 g bolus of protein consumed prior to a high

carbohydrate meal has been associated with marked reductions in postprandial

glycaemia in both acute and long-term settings (688). Fourth, we were not able to

Chapter 6

Page | 286

assess the distinct effects of the vitamin D supplements from the whey protein

drink, as we did not have a whey protein plus PRT or vitamin D plus PRT group

which would have allowed such a comparison. However, the inclusion of a

protein-vitamin D supplement group would have further increased the sample

size, and this study was designed to specifically evaluate whether whey protein

plus vitamin D could enhance the health benefits of PRT.

Fifth, there were also some limitations related to the outcomes measured and the

procedures used during our data collection. To assess insulin sensitivity, we relied

on the commonly used HOMA2%S formula which requires only FPG and insulin

concentrations to be measured. We acknowledge that this method is more variable

compared to the euglycaemic hyperinsulinaemic clamp method (689, 690) and is

more reflective of hepatic as opposed to muscular insulin sensitivity (691, 692).

However, performing euglycaemic hyperinsulinaemic clamps on all participants

on three occasions over the 24-week intervention period would not have been

feasible. Furthermore, previous studies have confirmed that the HOMA-2 method

for assessing insulin sensitivity/resistance is precise, reproducible and strongly

correlated to the results achieved by the glucose clamp technique (690). Another

potential limitation is the use of a 24-hour dietary recall to assess habitual dietary

intakes. Assessment of dietary intake is typically difficult with several

opportunities for misreporting of energy intake; typically, these include conscious

underreporting, undereating if the food recall is planned, respondent memory

lapses and misrepresentation of portion sizes (693). Further, misreporting (either

over- or under-reporting) has been found to occur more commonly in those with a

BMI >25 kg/m2, females compared to males and those of older age are also more

likely to misreport their energy intake (typically under-reporting as opposed to

over-reporting) (693). Despite these limitations, this dietary assessment technique

was the most appropriate for our trial given the large sample size and length of the

intervention. Further, when completing the 24-hour food recalls, we consistently

used a food model booklet with a clear description of portion-size measurements

and many household items (glasses, mugs etc.) to accurately estimate food,

energy and nutrient intake. Further, all trial staff conducting the food recalls and

subsequently entering this information into FoodWorks Professional (Version 8,

Chapter 6

Page | 287

Xyris Software, Queensland, Australia) to calculate total dietary energy intake

and dietary macronutrient composition were all highly trained and experienced in

performing such assessments.

Finally, not all research staff involved in the testing were blinded to the group

allocation, which may have introduced some observational bias. However, staff

who were not blinded were not involved in outcome assessments which could

have been altered based on this knowledge. Further, staff performing the

statistical analysis in this trial were blinded to treatment allocation.

6.9 Conclusion

In conclusion, this study has demonstrated that PRT improved glycaemic control,

total body and regional (arm and leg) lean mass, thigh muscle size, upper and

lower body muscle strength, waist circumference, fat mass, percentage body fat

and DBP. However the addition of 20 g of daily whey protein supplementation

with a further 20 g consumed following each PRT session (2 to 3 times per week)

with 2,000 IU of daily vitamin D did not enhance the effects of PRT on total body

or regional lean mass, fat mass, glycaemic control, insulin sensitivity or

cardiovascular risk factors in older overweight and obese adults with type 2

diabetes. While there was a greater beneficial effect of PRT combined with whey

protein and vitamin D relative to PRT alone on the anti-inflammatory marker IL-

10, there were no between group differences in any other pro- or anti-

inflammatory markers, and thus the clinical relevance of these findings are

unclear. Despite the lack of any consistent additive benefits following the

intention-to-treat analysis, secondary pre-planned analysis revealed that those

who achieved (≥66% exercise adherence) in upper body muscle strength and

serum IL-6, and a greater reduction in total cholesterol and LDL cholesterol.

While these findings must be interpreted with caution, they provide some

evidence that supplementation with whey-protein and vitamin D may provide

some added benefits to PRT in older overweight and obese adults with T2DM.

Another key finding from our intervention was that the community-based Lift for

Life® PRT program used in this study was safe and succesfully improved

glycaemic control, total body and regional (arm and leg) lean mass, thigh muscle

Chapter 6

Page | 288

size, upper and lower body muscle strength, waist circumference, fat mass,

percentage body fat and DBP. Importantly, there were no serious adverse events

associated with the intervention, and kidney function (eGFR) improved

significantly in both groups. Collectively, these findings add to the growing body

of literature to support the role of exercise, particularly PRT, as a safe, feasible,

and effective approach to improve multiple clinical risk factors associated with

T2DM in older overweight and obese adults with this condition.

Page | 289

Chapter 7

Summary, Conclusion and Future Recommendations

Chapter 7

Page | 290

7.1 Summary

Lifestyle management focusing on regular exercise and nutrition is the first line in

the treatment of older adults with type 2 diabetes mellitus (T2DM) (5, 6). Optimising

lean mass is critical for those with this condition, particularly older adults with

T2DM, as this is the largest mass of insulin-sensitive tissue and the predominant

reservoir for glucose disposal (9). Supervised and structured high-intensity PRT

programs in controlled laboratory settings have been found to be safe, well-tolerated

and effective for improving glycaemic control as well as lean mass, size and strength

in older adults with T2DM (8, 12, 14, 204, 212, 225, 250, 612). There is also some

evidence that exercise alone, including PRT, or combined with weight loss can

improve various cardiovascular risk factors, including blood pressure, lipids and

various circulating inflammatory markers. This is important because increased

inflammation has been implicated in the pathophysiology of insulin resistance and

several comorbidities associated with this condition including CVD (22). Whether

these same benefits can be achieved by participating in ‘real-world’ community

based PRT interventions has received less attention.

Dietary or nutritional modification in addition to physical activity is also an integral

component in the management of T2DM. Yet the most appropriate diet or

macronutrient distribution for the management of T2DM remains a continued topic

of debate among peak health authorities. Traditionally, caloric restriction is

recommended for those with T2DM due to the beneficial effects on body weight and

fat mass, however such an approach has been associated with poor long-term

adherence and weight re-gain. Further, whether caloric restriction plus PRT can

influence markers of systemic inflammation in older adults with T2DM remains

uncertain. In recent years, novel dietary approaches focusing on alternate macro- and

micronutrients including protein and vitamin D, alone or in combination with

exercise/PRT have been proposed as potential nutritional strategies to improve

several health outcomes in those with T2DM. This is largely driven by the findings

from acute studies demonstrating that these dietary factors alone, particularly protein,

or combined with exercise, can have a positive effect on MPS and stimulate beta-

cells of the pancreas to secrete insulin. However, few long-term human intervention

Chapter 7

Page | 291

trials in adults with T2DM have investigated whether such a combination transcribe

into measurable health outcomes. Thus, the aim of this thesis was to investigate if

lifestyle strategies such as caloric restriction, to promote weight loss, or nutritional

supplementation with protein and vitamin D, in combination with exercise/PRT

could promote greater improvements in glycaemic control, body composition,

cardiovascular related risk factors and systemic inflammation compared to PRT

alone in older overweight and obese adults with T2DM.

The specific aims are:

1. To compare the effect of PRT plus a moderate weight loss program versus

weight loss alone on systemic and endothelial markers of inflammation in

older overweight adults with T2DM (Chapter 3).

2. To report on the challenges of recruiting older adults with T2DM into a 6-

month community-based PRT and nutrition program along with reporting on

strategies which successfully resulted in participants randomised to the

intervention (Chapter 5).

3. To investigate whether ingestion of a daily whey-protein drink in

combination with vitamin D supplementation can enhance the effects of a

community-based PRT program on glycaemic control and insulin sensitivity

in older adults with T2DM (Chapter 6).

4. To examine whether a community-based PRT program combined with a

whey-protein drink and vitamin D supplementation is more effective for

enhancing total body and regional lean mass, muscle cross-sectional area

(CSA), muscle strength and reducing inter-/intra-muscular fat infiltration,

than PRT alone in older adults with T2DM (Chapter 6).

5. To compare the effects of a community-based PRT program combined with

whey-protein and vitamin D supplementation versus PRT alone, on

cardiovascular risk factors, including blood pressure and blood lipid levels,

and pro-inflammatory and anti-inflammatory cytokines. (Chapter 6).

Chapter 7

Page | 292

While the discussion sections within each previous chapter (3-6) consider the

limitations and methodological issues specific to these studies, section 7.2 below will

focus on the key research findings, limitations and corresponding directions for

future research arising from the studies in this thesis. This chapter closes with the

overarching clinical and public health implications of this research and a final

summary and conclusion for this thesis (section 7.3)

7.2 Key Research Findings, Limitations and Directions for Future Research

Below is a brief summary of the key findings from this thesis

1. Recruitment of older adults with T2DM into a community-based exercise and

nutrition intervention trial took longer than anticipated, was costly, required

continual sustained efforts and necessitated flexibility within the recruitment

strategies used to ensure the final target was achieved. Overall, 1,157

expressions of interest (EOI) were received over a 21-month period from which

959 (83%) individuals were screened and found to be ineligible for the trial or

chose not to participate. A total of 198 participants were deemed to be eligible

and randomised to the 24-week intervention. The most effective recruitment

strategies were targeted mass mail-outs (39% of the total participant sample) and

state (27%) print media. These strategies were also the most expensive each

accounting for 38% of total expenditure. Recruitment expenditure totalled

AUD$40,421, which equated to AUD$35 per enquiry and AUD$204 per eligible

participant.

2. Resistance training performed under supervised, clinically controlled and

structured settings or within local community-based facilities can improve

several clinically relevant outcomes important for adults with T2DM, including

lean mass, glycaemic control and muscular strength whilst also reducing fat

mass, DBP and some systemic markers of inflammation. However, the greatest

benefits were associated within the highly-controlled settings. Home-based PRT

program was largely ineffective at maintaining body composition and glycaemic

improvements gained under a supervised-laboratory controlled environment with

only slight improvements in some systemic markers of inflammation observed.

Chapter 7

Page | 293

3. Six-months of weight loss combined with high-intensity PRT did not have any

marked effects on any marker of systemic inflammation or endothelial function

in older adults with poorly controlled T2DM, despite reduction in weight and fat

mass and an improvement in lean mass. However, continued participation in

PRT over 12-months, independent of change in weight, was associated with

some improvements in certain inflammatory markers in older overweight adults

with type 2 diabetes.

4. PRT was associated with improved glycaemic control, total body and regional

(arm and leg) lean mass, thigh muscle size, upper and lower body muscle

strength, waist circumference, fat mass, percentage body fat and DBP. The

addition of once to twice daily 20 g of whey protein and 2,000 IU of vitamin D

per day did not further enhance these outcomes. there was a greater reduction in

serum insulin levels and a beneficial effect on the anti-inflammatory marker IL-

10 in the those supplemented with whey protein and vitamin D, the clinical

relevance of these findings remains uncertain given that lack of any additional

benefits on the clinically important outcome measures of glycaemic control and

insulin sensitivity.

5. In older overweight and obese adults who had greater adherence to the

community-based PRT and whey protein-vitamin D supplements there was some

evidence for additive benefits to upper body muscle strength, serum IL-6 and

total cholesterol and LDL cholesterol and to a lesser extent thigh muscle size

(CSA) and arm lean mass compared to those undertaking PRT alone.

This next section discusses these key findings, including their strengths and

limitations, and the corresponding future research directions.

7.2.1 Recruiting ‘at risk’ older adults with T2DM into exercise and nutrition

intervention trials is challenging and expensive

Ineffective or slow recruitment of participants into RCTs can lead to extended study

duration, greater resource usage and findings that are not as statistically precise as

intended if the required sample size is not obtained. A detailed and thorough

description of the recruitment strategies used for the 24-week community-based

Chapter 7

Page | 294

exercise-nutrition trial, the strategies which were successful (and not successful) and

the costs associated with recruiting older adults with T2DM into this trial is reported

in Chapter 5 of this thesis. At present, there is limited available data on successful

recruitment strategies which are suitable for recruiting older adults with a chronic

disease such as T2DM into community-based exercise and nutrition programs.

Further, no information is available on estimated costs associated with such

recruitment, which has important budget implications when planning such trials.

A wide range of recruitment strategies were implemented which included state and

local newspaper and radio advertisements, targeted mail-outs, doctor and allied

health referrals, community presentations, web-based media and word of mouth. Our

consistent monitoring of the effectiveness of strategies implemented and the vast

array of recruitment methods used meant we identified successful methods of

recruitment early and could focus our efforts and funds on such strategies. We found

the most successful and proliferative strategies (e.g. those which resulted in a high

number of expressions of interest and eligible participants and were subsequently

performed multiple times) were targeted mass mail-outs (39% of the total participant

sample), state (27%) and local (15%) print media. A total of 1,157 EOI over a 21-

month period were received for this intervention. Overall 83% of these participants

were deemed to be ineligible or chose not to participate. Physical activity status (e.g.

exceeding the national physical activity guidelines) and medication/supplement use

(e.g. taking vitamin D supplements >500 IU/day or being prescribed insulin for

diabetes management) were the two key reasons why individuals were not eligible

for the trial. A total of 198 participants (21% of all those screened) were found to be

eligible and were randomised to the 24-week intervention.

At present, there is limited literature on successful recruitment strategies suitable for

older adults with T2DM into community based exercise and nutrition programs and

no information on cost estimates. There were several key lessons from our study. We

had originally allocated 12-months for the recruitment for this trial, but this was

extended to 21-months due to the lower than expected success rate from those

screened. The strategies which were successful (targeted mail-outs and state print

Chapter 7

Page | 295

media) were the most expensive. Overall a total AUD$40,421 was spent, which

equated to AUD$35 per enquiry and AUD$204 per eligible participant.

In reporting the challenges, successes, failures and costs associated with recruiting

older adults with T2DM into our trial it is hoped studies in the future can learn from

these experiences and formulate an appropriate timeline of strategies to remain

within budget and trial timelines whilst expediently recruiting the target number of

participants. Whilst our reporting in Chapter 5 of our recruitment strategies and

experiences for our 24-week exercise and nutrition intervention was comprehensive

and methodical, limitations are still present.

Limitations

A limitation of our reporting of the success of recruitment strategies was that only

one recruitment strategy was recorded per EOI received. It is possible given the

numerous strategies we used for this intervention that individuals were exposed to

more than one recruitment strategy. Further, for each EOI received individuals were

informed about the opportunity for monetary re-imbursement equivalent to the Lift

for Life® training costs. Offering payment to clinical research participants, in an

effort to enhance recruitment by providing an incentive to take part or enabling

participants to participate without financial sacrifice, is common. Whether the

opportunity to receive the monetary reward offered in our intervention unduly

influenced participation of some participants or population groups was not addressed

nor recorded and thus cannot be commented on.

Future Recommendations

Other RCTs should report on the success or limitations of their chosen methods of

recruitment on a range of population groups and not just in those with T2DM. Cost-

benefit analysis of all recruitment strategies used should also be reported to help

guide future RCTs recruitment efforts. Further, knowing more about the effect

monetary reimbursement has on decisions to participate in such RCTS among

different age and population groups is required. Whilst we acknowledge that

payment may not be necessary for recruiting participants, particularly those with a

chronic condition such as T2DM who may be motivated to participate by the

Chapter 7

Page | 296

opportunity for therapeutic benefit, if the goal of payment is to reduce the financial

sacrifice that research participants must make and/or to compensate people for their

time, the influence this has on willingness to participate and bias on those who do

participate should be investigated.

7.2.2 Structured and supervised as well as community-based PRT results in

relevant cardiometabolic health improvements important to those with T2DM.

In Chapter 3 of this thesis, secondary analysis was performed on existing data from a

12-month RCT to investigate the effects of supervised high-intensity PRT plus

weight loss (caloric restriction) compared to a weight loss intervention alone had on

systemic and endothelial markers of inflammation in older overweight adults with

poorly controlled T2DM. After the first 6-month supervised phase of training, similar

significant reductions in body weight and fat mass were observed in both groups.

However, the PRT plus weight loss group experienced a net gain in total body lean

mass in comparison to weight loss alone, and a greater absolute improvement in

glycated haemoglobin. Despite these greater net benefits, there were no significant

changes in any markers of systemic inflammation or endothelial function in either

group. Interestingly, 6-months of continued home-based PRT (without weight loss)

was associated with some modest but significant improvements in various

inflammatory markers, suggesting that long-term training may lead to some

beneficial effects on markers of systemic inflammation.

Many previous studies have demonstrated the independent benefits that regular

exercise, including PRT, can have on several health outcomes in people with T2DM,

yet most of these studies to date have been conducted under clinically controlled

supervised gymnasium-based settings with little understanding of the clinical

relevance of a community-based program (8, 12, 154, 203, 207, 215, 216, 220, 224,

227, 566, 694). In Chapter 6, we reported the findings following our 24-week

nutrition and exercise intervention which incorporated whey protein and vitamin D

supplementation plus participation in a community-based PRT program. We

observed significant PRT-related improvements in a number of cardiometabolic

outcomes following this community-based intervention, including HbA1c, fasting

Chapter 7

Page | 297

glucose and insulin levels, waist circumference, upper and lower body muscular

strength, fat mass, lean mass and DBP. Although the magnitude of these health

improvements was considerably less than those achieved in Chapter 3 from the

supervised, clinically controlled PRT gymnasium-based program, it is important to

remember the intervention in Chapter 6 was more representative of a ‘real-world’

PRT program. Community-based programs have the potential to be far wider

reaching and accessed by a greater proportion of the population than those performed

in clinically controlled environments. Thus, the results found in Chapter 6 remain

important as they provide high-level scientific evidence to support a translational

research-to-practice community-based PRT program as a safe, feasible and effective

strategy to improve multiple cardiometabolic health outcomes in older overweight

and obese adults with T2DM.

Despite the strengths of both trials, such as the well-designed and independently

tailored PRT programs, the relatively high level of exercise adherence, the small

number of drop-outs and adverse events related to the PRT program plus the

significant improvements in a range of outcomes measured, these studies were not

without limitations.

Limitations

A limitation of our investigations in both these studies was the potential recruitment

bias. As mentioned in Chapters 3 and 5 of this thesis, individuals were required to

meet a number of eligibility requirements and were recruited to participate in long-

term exercise interventions, demonstrating a willingness and ability to exercise that

might be misrepresentative of the overall Australian population with T2DM or other

chronic diseases. Further, anyone with an HbA1c above 10%, a BMI greater than 40

kg/m2 or prescribed insulin for the management of their condition was ineligible for

the study. Such a selection bias may limit the relevance and applicability of our

findings in this thesis to those individuals with T2DM who are in a more advanced

stage of this disease.

Chapter 7

Page | 298

Future Recommendations

Given that the secondary per protocol analysis for the study in Chapter 6

demonstrated that whey-protein and vitamin D supplementation enhanced the effects

of PRT on a number of important health outcomes in older overweight and obese

adults with T2DM, further trials are needed to evaluate whether various nutritional

factors can provide additive health benefits to exercise in this group. There is also a

need to further evaluate the efficacy and effectiveness (and cost-effectiveness) of

community-based PRT (or related exercise) programs like the current Lift for Life®

program for people with T2DM. This should include an investigation into what

aspects of a community-based PRT (or exercise) program are most appealing to

those with T2DM and which may enhance long-term adherence. Future studies

should also recruit participants in more advanced stages of this disease to be more

representative of the broader T2DM population as such groups have not been

investigated sufficiently, in this thesis or the broader population.

7.2.3 The most effective diet or nutritional approach for the management of

T2DM remains unclear.

This section details the findings from both Chapter 3 and 6 of this thesis regarding

the two dietary related approaches which were prescribed in combination with PRT

for the improvement in glycaemic, insulinaemic, cardiovascular, inflammatory and

body composition outcomes in older adults with T2DM. These studies prescribed

two very different nutritional approaches. Weight loss from caloric restriction is

typically advised in those with T2DM yet the effects of combining PRT with weight

loss on markers of systemic inflammation had not been examined. Promising

evidence exists for the independent effects of high protein diets, whey protein and

vitamin D supplementation on several metabolic and body composition health

outcomes in healthy older adults and those with T2DM. Whether the combination of

these nutritional factors can enhance PRT associated health outcomes in older adults

with T2DM remains uncertain.

Chapter 7

Page | 299

Limited benefits of weight loss and/or PRT on markers of systemic inflammation

The secondary analysis performed in Chapter 3 revealed that 6-months of caloric

restriction alone or performed alongside high-intensity PRT, both of which resulted

in similar significant reductions in body weight and fat mass and an improvement in

HbA1c levels, was not associated with any significant improvement in markers of

systemic inflammation in older adults with poorly controlled T2DM. Given that

strong link between obesity and inflammation, the lack of any marked changes

during the initial 6-months may be related to the relative modest reductions in weight

and fat mass in our trial. However, other studies have also found that participation in

exercise or PRT alone is beneficial for improving markers of inflammation,

independent of changes in weight or fat mass. In partial support of such studies, we

observed 6-months of continued home-based training following the supervised

gymnasium-based program, despite weight and fat mass regain, was associated with

some modest improvements in various inflammation markers compared to sham-

exercise (stretching). However, in Chapter 6 we found that there were no

improvements in any pro- or anti-inflammatory marker following our 24-week

community-based PRT program. While this may be related in part to differences in

the intensity of the training, collectively these findings suggest that long-term

participation (>6-months) in PRT may be required to provide some benefits on

circulating inflammatory markers in older overweight and obese adults with T2DM.

Furthermore, given that there were significant improvements in HbA1c following

both PRT-related interventions, the findings from this thesis also suggest that

changes in circulating inflammatory markers may not play a key role in mediating

exercise-induced changes in glycaemic control, although this hypothesis requires

further investigation.

Whey protein plus vitamin D supplementation provided little or no additive benefits

to PRT in older overweight and obese adults with T2DM

Chapter 6 builds upon the findings in Chapter 3 by examining the potential additive

effects of a novel nutritional approach incorporating whey protein and vitamin D

with PRT in older adults with T2DM. The main findings from this chapter were that

the addition of a daily whey-protein drink and vitamin D supplements did not

enhance the effects of a community-based ‘real-world’ PRT program on measures of

Chapter 7

Page | 300

body composition, glycaemic control or cardiovascular risk factors in older

community-dwelling sedentary adults with T2DM. Although there was a trend for a

greater improvement in appendicular lean mass (ALM), the lack of any marked

additive effect on glycaemic or insulinaemic measures may be due to the adequate

baseline dietary protein intake (mean ~1.1 g/kg/day) and sufficient serum 25(OH)D

levels (mean 72 nmol/L) in this cohort of older adults with T2DM at the

commencement of this trial. The effects of combined whey protein and vitamin D

supplementation with PRT has not previously been examined in those with T2DM,

but of the few studies conducted in non-diabetic older adults the greatest benefits

have typically been observed in high risk groups (e.g., elderly and those with

sarcopenia) and/or those with inadequate protein intakes at baseline (512, 513, 515).

Indeed, in studies examining the independent effects of whey protein or vitamin D

supplementation on glycaemic control, body composition and/or cardiovascular risk

factors there is also some evidence that these nutritional factors provide greater

benefits in individuals with low baseline intakes and serum 25(OH)D levels (41, 452,

483). Collectively, these findings suggest that the greatest benefits of exercise

combined with nutritional supplement(s) are likely to occur in high risk groups that

are inactive and have insufficient intakes at baseline for the targeted nutritional

approach. However, it is evident that further research is need to help define the most

appropriate nutritional approach to be used in combination with PRT for the

management of T2DM.

Limitations

Chapter 3 in this thesis was a secondary analysis that was limited by a relatively

small sample size. Given the known variability in circulating inflammatory

cytokines, it is likely that this study was underpowered to detect any potential

between group differences. Additionally, whilst the caloric restriction imposed

during the supervised-gymnasium based phase of the trial (the first 6-months) was

sufficient to significantly reduce body weight and fat mass, these reductions were not

of the same magnitude observed in other trials which reported significant

improvements in a range of inflammatory markers concomitant to the weight loss.

Chapter 7

Page | 301

The independent contributions whey protein and vitamin D had on the measured

outcomes were not able to be assessed in this trial as there was no group in our trial

who were prescribed whey protein or vitamin D only with or without PRT. Further,

whilst this trial had a large sample size (in comparison to many previous exercise

RCTs in adults with T2DM) and examined the long-term effects, the participants

recruited were found to have intakes of protein and serum 25(OH)D levels at

baseline that are considered adequate (sufficient), and the vast majority were

prescribed some form of oral hypoglycaemic medication, which possibly blunted any

potential effects of the supplements on the measured outcomes in our trial.

Future Recommendations

Further RCTs are needed to investigate whether whey protein and vitamin D can

enhance the effect of community-based or supervised controlled PRT on body

composition, glycaemic and insulinaemic outcomes as well as CVD risk factors in

older adults with T2DM with inadequate dietary protein intakes and/or

deficient/insufficient serum 25(OH)D status. Further, almost 70% of our participants

were taking oral hypoglycaemic medication to management there T2DM. Thus,

future trials should consider recruiting and randomising a weighted proportion of

participants not on any oral hypoglycaemic medication to assess the effects of such

an intervention on those taking and not taking oral hypoglycaemic medication.

7.3 Conclusions and Public Health Implications

In this thesis, a number of different lifestyle approaches including PRT, PRT plus

weight loss and PRT plus whey protein and vitamin D supplementation were

prescribed with the aim of increasing lean mass, improving glycaemic control and

insulin sensitivity plus various cardiovascular risk factors and markers of systemic

inflammation in older adults with T2DM. Several different PRT settings were also

examined including a supervised clinically controlled gym-based setting, home-

based training and community-based health and leisure facilities. The main findings

from the studies in this thesis were that weight and fat mass reductions resultant from

supervised high-intensity PRT plus caloric restriction or caloric restriction alone did

not result in immediate improvement in systemic or endothelial markers of

inflammation. In contrast, there was some evidence that continued long-term

Chapter 7

Page | 302

exercise training was associated with modest improvements in some inflammatory

markers, but the clinical significance of these findings remains to be determined.

Second, participation in a long-term community-based PRT program improved

glycaemic control and lean mass, reduced fat mass and improved some CVD risk

factors, but the addition of a novel dietary approach incorporating increased protein

intake and vitamin D supplementation provided little or no added benefits.

The challenge remains following the completion of long-term exercise and nutrition

intervention studies, such as those in this thesis, of how to foster long-term

compliance and promote ongoing participation in community-based lifestyle

programs for continued health benefits. In addition, despite the large subject numbers

and long follow-up periods required, further studies are needed in older adults to

identify whether ongoing participation in PRT along with nutritional factors which

may enhance improvements in lean mass, translate to long-term improvements in

glycaemic control, insulin sensitivity and improve CVD risk factors in those with

T2DM and potentially lead to co-morbidity and mortality risk reduction benefits.

Below are a series of key messages and public health implications which can be

taken from this thesis and which could be used to guide clinical practice guidelines

or community care programmes and future health recommendations for those with

T2DM. It is important these implications are interpreted in the context of the

limitations outlined previously.

1. Weight loss in the absence of PRT may not be the most effective recommendation

for improving markers of inflammation in those with T2DM.

2. In older overweight and obese adults with T2DM who have adequate dietary

protein intakes and sufficient serum 25(OH)D levels there appears to be little

benefit to be gained in certain health outcomes by supplementing the diet with

daily whey protein and vitamin D. However, given that there was evidence for

some additional health benefits in those who were most compliant with the

exercise and supplements, further research is still needed to address whether such

a nutritional approach can provide added health benefits.

Chapter 7

Page | 303

3. Community-based PRT interventions for older overweight and obese adults with

T2DM are safe and effective for improving various health outcomes, but the

greatest benefits appear apparent when training is supervised and performed at a

high-intensity PRT. Thus, an approach moving forward for people with T2DM

regarding exercise may be to ensure they receive a high level of supervision and

attention during the initial few months of commencing a PRT program.

4. Policies and funding at both local government and national level should be

developed and made available to implement sustainable and accessible health-

oriented community-based PRT or physical activity programs for older adults

with T2DM.

Page | 304

References

1. Chen L, Magliano DJ, Zimmet PZ. The worldwide epidemiology of type 2 diabetes mellitus--present and future perspectives. Nat Rev Endocrinol. 2011;8(4):228-36.

2. Zimmet PZ. Can we avert a diabetes catastrophe in Australia? Med J Aust. 2013;199(4):225-6.

3. International Diabetes Federation. IDF Diabetes Atlas, 7th edn. [Internet]. Brussels, Belgium: International Diabetes Federation; 2015 [cited 2016 Feb 20]. Available from: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas.html.

4. Martin-Timon I, Sevillano-Collantes C, Segura-Galindo A, Del Canizo-Gomez FJ. Type 2 diabetes and cardiovascular disease: Have all risk factors the same strength? World J Diabetes. 2014;5(4):444-70.

5. American Diabetes A, Bantle JP, Wylie-Rosett J, Albright AL, Apovian CM, Clark NG, et al. Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care. 2008;31(Supple 1):S61-78.

6. Colberg SR, Sigal RJ, Fernhall B, Regensteiner JG, Blissmer BJ, Rubin RR, et al. Exercise and type 2 diabetes: ACSM and ADA joint position statement. Diabetes Care. 2010;33(12).

7. Church TS, Blair SN, Cocreham S, Johannsen N, Johnson W, Kimberly Kramer K, et al. Effects of aerobic and resistance training on hemoglobin A1c levels in patients with type 2 diabetes: a randomised controlled trial JAMA. 2010;304(20):2253-62.

8. Sigal RJ, Kenny GP, Boule NG, Wells GA, Prud'homme D, Fortier M, et al. Effects of aerobic training, resistance training, or both on glycemic control in type 2 diabetes: a randomized trial. Ann Intern Med. 2007;147(6):357-69.

9. DeFronzo RA, Tripathy D. Skeletal muscle insulin resistance is the primary defect in type 2 diabetes. Diabetes Care. 2009;32(suppl 2):S157-63.

10. Srikanthan P, Karlamangla AS. Relative Muscle Mass Is Inversely Associated with Insulin Resistance and Prediabetes. Findings from The Third National Health and Nutrition Examination Survey. J Clin Endocrinol Metab. 2011;96(9):2898-903.

11. Park SW, Goodpaster BH, Strotmeyer ES, de Rekeneire N, Harris TB, Schwartz AV, et al. Decreased muscle strength and quality in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes. 2006;55(6):1813-8.

12. Dunstan DW, Daly RM, Owen N, Jolley D, De Courten M, Shaw J, et al. High-intensity resistance training improves glycemic control in older patients with type 2 diabetes. Diabetes Care. 2002;25(10):1729-36.

Page | 305

13. Daly RM, Dunstan DW, Owen N, Jolley D, Shaw JE, Zimmet PZ. Does high-intensity resistance training maintain bone mass during moderate weight loss in older overweight adults with type 2 diabetes? Osteoporos Int. 2005;16(12):1703-12.

14. Dunstan D, Daly R, Owen N, Jolley D, Vulikh E, Shaw J, et al. Home-based resistance training is not sufficient to maintain improved glycemic control following supervised training in older individuals with type 2 diabetes. Diabetes Care. 2005;28(1):3-9.

15. You T, Arsenis NC, Disanzo BL, Lamonte MJ. Effects of exercise training on chronic inflammation in obesity : current evidence and potential mechanisms. Sports Med. 2013;43(4):243-56.

16. Karstoft K, Pedersen BK. Exercise and type 2 diabetes: focus on metabolism and inflammation. Immunol Cell Biol. 2016;94(2):146-50.

17. Khoo J, Dhamodaran S, Chen DD, Yap SY, Chen RY, Tian RH. Exercise-Induced Weight Loss is More Effective than Dieting for Improving Adipokine Profile, Insulin Resistance, and Inflammation in Obese Men. Int J Sport Nutr Exerc Metab. 2015;25(6):566-75.

18. Liberman K, Forti LN, Beyer I, Bautmans I. The effects of exercise on muscle strength, body composition, physical functioning and the inflammatory profile of older adults: a systematic review. Curr Opin Clin Nutr Metab Care. 2017;20(1):30-53.

19. Zhao YF, Feng DD, Chen C. Contribution of adipocyte-derived factors to beta-cell dysfunction in diabetes. Int J Biochem Cell Biol. 2006;38(5-6):804-19.

20. Tilg H, Moschen AR. Inflammatory mechanisms in the regulation of insulin resistance. Mol Med. 2008;14(3-4):222-31.

21. Ehses JA, Ellingsgaard H, Boni-Schnetzler M, Donath MY. Pancreatic islet inflammation in type 2 diabetes: from alpha and beta cell compensation to dysfunction. Arch Physiol Biochem. 2009;115(4):240-7.

22. Pittas AG, Lau J, Hu FB, Dawson-Hughes B. The role of vitamin D and calcium in type 2 diabetes. A systematic review and meta-analysis. J Clin Endocrinol Metab. 2007;92(6):2017-29.

23. Plotnikoff RC, Costigan SA, Karunamuni ND, Lubans DR. Community-based physical activity interventions for treatment of type 2 diabetes: a systematic review with meta-analysis. Front Endocrinol 2013;4:3.

24. Colligan EM, Tomoyasu N, Howell B. Community-based wellness and prevention programs: the role of medicare. Front Public Health. 2014;2:189.

25. Koster-Rasmussen R, Simonsen MK, Siersma V, Henriksen JE, Heitmann BL, de Fine Olivarius N. Intentional Weight Loss and Longevity in Overweight Patients with Type 2 Diabetes: A Population-Based Cohort Study. PLoS One. 2016;11(1).

Page | 306

26. Maggio CA, Pi-Sunyer FX. The prevention and treatment of obesity. Application to type 2 diabetes. Diabetes Care. 1997;20(11):1744-66.

27. Diabetes Prevention Program Research Group. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009;374(9702):1677-86.

28. Jeffery RW, Drewnowski A, Epstein LH, Stunkard AJ, Wilson GT, Wing RR, et al. Long-term maintenance of weight loss: current status. Health Psychol. 2000;19(1S):5-16.

29. Lang A, Froelicher ES. Management of overweight and obesity in adults: behavioral intervention for long-term weight loss and maintenance. Eur J Cardiovasc Nurs. 2006;5(2):102-14.

30. Anderson JW, Konz EC, Frederich RC, Wood CL. Long-term weight-loss maintenance: a meta-analysis of US studies. Am J Clin Nutr. 2001;74(5):579-84.

31. Beavers KM, Ambrosius WT, Nicklas BJ, Rejeski WJ. Independent and combined effects of physical activity and weight loss on inflammatory biomarkers in overweight and obese older adults. J Am Geriatr Soc. 2013;61(7):1089-94.

32. Ryan AS, Ge S, Blumenthal JB, Serra MC, Prior SJ, Goldberg AP. Aerobic exercise and weight loss reduce vascular markers of inflammation and improve insulin sensitivity in obese women. J Am Geriatr Soc. 2014;62(4):607-14.

33. Giannopoulou I, Fernhall B, Carhart R, Weinstock RS, Baynard T, Figueroa A, et al. Effects of diet and/or exercise on the adipocytokine and inflammatory cytokine levels of postmenopausal women with type 2 diabetes. Metabolism. 2005;54(7):866-75.

34. Thompson D, Walhin JP, Batterham AM, Stokes KA, Cooper AR, Andrews RC. Effect of diet or diet plus physical activity versus usual care on inflammatory markers in patients with newly diagnosed type 2 diabetes: the Early ACTivity in Diabetes (ACTID) randomized, controlled trial. J Am Heart Assoc. 2014;3(3).

35. Snel M, van Diepen JA, Stijnen T, Pijl H, Romijn JA, Meinders AE, et al. Immediate and long-term effects of addition of exercise to a 16-week very low calorie diet on low-grade inflammation in obese, insulin-dependent type 2 diabetic patients. Food Chem Toxicol. 2011;49(12):3104-11.

36. Hu FB. Protein, body weight, and cardiovascular health. Am J Clin Nutr. 2005;82(1 Suppl):242S-7S.

37. Comerford KB, Pasin G. Emerging Evidence for the Importance of Dietary Protein Source on Glucoregulatory Markers and Type 2 Diabetes: Different Effects of Dairy, Meat, Fish, Egg, and Plant Protein Foods. Nutrients. 2016;8(8):446.

Page | 307

38. Dong JY, Zhang ZL, Wang PY, Qin LQ. Effects of high-protein diets on body weight, glycaemic control, blood lipids and blood pressure in type 2 diabetes: meta-analysis of randomised controlled trials. Br J Nutr. 2013;110(5):781-9.

39. Pennings B, Koopman R, Beelen M, Senden JM, Saris WH, van Loon LJ. Exercising before protein intake allows for greater use of dietary protein-derived amino acids for de novo muscle protein synthesis in both young and elderly men. Am J Clin Nutr. 2011;93(2):322-31.

40. Norton C, Toomey C, McCormack WG, Francis P, Saunders J, Kerin E, et al. Protein Supplementation at Breakfast and Lunch for 24 Weeks beyond Habitual Intakes Increases Whole-Body Lean Tissue Mass in Healthy Older Adults. J Nutr. 2016;146(1):65-9.

41. Kerstetter JE, Bihuniak JD, Brindisi J, Sullivan RR, Mangano KM, Larocque S, et al. The Effect of a Whey Protein Supplement on Bone Mass in Older Caucasian Adults. J Clin Endocrinol Metab. 2015;100(6):2214-22.

42. Daly RM, O'Connell SL, Mundell NL, Grimes CA, Dunstan DW, Nowson CA. Protein-enriched diet, with the use of lean red meat, combined with progressive resistance training enhances lean tissue mass and muscle strength and reduces circulating IL-6 concentrations in elderly women: a cluster randomized controlled trial. Am J Clin Nutr. 2014;99(4):899-910.

43. Schoenfeld BJ, Aragon AA, Krieger JW. The effect of protein timing on muscle strength and hypertrophy: a meta-analysis. J Int Soc Sports Nutr. 2013;10(1):53.

44. Areta JL, Burke LM, Ross ML, Camera DM, West DW, Broad EM, et al. Timing and distribution of protein ingestion during prolonged recovery from resistance exercise alters myofibrillar protein synthesis. J Physiol. 2013;591(9):2319-31.

45. Guimaraes-Ferreira L, Cholewa JM, Naimo MA, Zhi XI, Magagnin D, de Sa RB, et al. Synergistic effects of resistance training and protein intake: practical aspects. Nutrition. 2014;30(10):1097-103.

46. Wilkinson SB, Tarnopolsky MA, MacDonald MJ, MacDonald JR, Armstrong D, Philips SM. Consumption of fluid skim milk promotes greater muscle protein accretion after resistance exercise than does consumption of an isonitrogenous and isoenergetic soy-protein beverage. Am J Clin Nutr. 2007;85(4):1031-40.

47. Tang JE, Moore DR, Kujbida GW, Tarnopolsky MA, Phillips SM. Ingestion of whey hydrolysate, casein, or soy protein isolate: effects on mixed muscle protein synthesis at rest and following resistance exercise in young men. J Appl Physiol. 2009;107(3):987-92.

48. Draganidis D, Karagounis LG, Athanailidis I, Chatzinikolaou A, Jamurtas AZ, Fatouros IG. Inflammaging and Skeletal Muscle: Can Protein Intake Make a Difference? J Nutr. 2016;146(10):1940-52.

Page | 308

49. Paddon-Jones D, Rasmussen BB. Dietary protein recommendations and the prevention of sarcopenia. Curr Opin Clin Nutr Metab Care. 2009;12(1):86-90.

50. Breen L, Phillips SM. Nutrient interaction for optimal protein anabolism in resistance exercise. Curr Opin Clin Nutr Metab Care. 2012;15(3):226-32.

51. Yang Y, Breen L, Burd NA, Hector AJ, Churchward-Venne TA, Josse AR, et al. Resistance exercise enhances myofibrillar protein synthesis with graded intakes of whey protein in older men. Br J Nutr. 2012;108(10):1780-8.

52. Frid AH, Nilsson M, Holst JJ, Bjorck IM. Effect of whey on blood glucose and insulin responses to composite breakfast and lunch meals in type 2 diabetic subjects. Am J Clin Nutr. 2005;82(1):69-75.

53. Nilsson M, Holst JJ, Bjorck IME. Metabolic effects of amino acid mixtures and whey protein in healthy subjects: studies using glucose-equivalent drinks. Am J Clin Nutr. 2007;85(4):996-1004.

54. Nilsson M, Stenberg M, Frid AH, Holst JJ, Bjorck IM. Glycemia and insulinemia in healthy subjects after lactose-equivalent meals of milk and other food proteins: the role of plasma amino acids and incretins. Am J Clin Nutr. 2004;80(5):1246-53.

55. Ostman EM, Elmstahl HGML, Bjorck IME. Inconsistency between glycemic and insulinemic responses to regular and fermented milk products. Am J Clin Nutr. 2001;74(1):96-100.

56. Belobrajdic DP, McIntosh GH, Owens JA. A high-whey-protein diet reduces body weight gain and alters insulin sensitivity relative to red meat in wistar rats. J Nutr. 2004;134(6):1454-8.

57. Layman DK, Baum JI. Dietary protein impact on glycemic control during weight loss. J Nutr. 2004;134(4):968S-73S.

58. Zhang Y, Guo K, LeBlanc RE, Loh D, Schwartz GJ, Yu YH. Increasing dietary leucine intake reduces diet-induced obesity and improves glucose and cholesterol metabolism in mice via multimechanisms. Diabetes. 2007;56(6):1647-54.

59. Mitri J, Muraru MD, Pittas AG. Vitamin D and type 2 diabetes: a systematic review. Eur J Clin Nutr. 2011;65(9):1005-15.

60. Dawson-Hughes B. Serum 25-hydroxyvitamin D and functional outcomes in the elderly. Am J Clin Nutr. 2008;88(2):537S-40S.

61. Gagnon C, Lu ZX, Magliano DJ, Dunstan DW, Shaw JE, Zimmet PZ, et al. Serum 25-hydroxyvitamin D, calcium intake, and risk of type 2 diabetes after 5 years: results from a national, population-based prospective study (the Australian Diabetes, Obesity and Lifestyle study). Diabetes Care. 2011;34(5):1133-8.

62. Sung CC, Liao MT, Lu KC, Wu CC. Role of vitamin D in insulin resistance. J Biomed Biotechnol. 2012;2012.

Page | 309

63. Ramos-Trautmann G, González L, Díaz-Luquis G, Pérez CM, C. P. Inverse Association between Vitamin D Status and Diabetes in a Clinic Based Sample of Hispanic Adults in Puerto Rico. Diabetes Res. 2015;1(1):5-11.

64. Thorand B, Zierer A, Huth C, Linseisen J, Meisinger C, Roden M, et al. Effect of serum 25-hydroxyvitamin D on risk for type 2 diabetes may be partially mediated by subclinical inflammation: results from the MONICA/KORA Augsburg study. Diabetes Care. 2011;34(10):2320-2.

65. von Hurst PR, Stonehouse W, Coad J. Vitamin D supplementation reduces insulin resistance in South Asian women living in New Zealand who are insulin resistant and vitamin D deficient - a randomised, placebo-controlled trial. Br J Nutr. 2010;103(4):549-55.

66. Ljunghall S, Lind L, Lithell H, Skarfors E, Selinus I, Sorensen OH, et al. Treatment with one-alpha-hydroxycholecalciferol in middle-aged men with impaired glucose tolerance--a prospective randomized double-blind study. Acta Med Scand. 1987;222(4):361-7.

67. Ryu OH, Chung W, Lee S, Hong KS, Choi MG, Yoo HJ. The effect of high-dose vitamin D supplementation on insulin resistance and arterial stiffness in patients with type 2 diabetes. Korean J Intern Med. 2014;29(5):620-9.

68. Barengolts E, Manickam B, Eisenberg Y, Akbar A, Kukreja S, Ciubotaru I. Effect of High-Dose Vitamin D Repletion on Glycemic Control in African-American Males with Prediabetes and Hypovitaminosis D. Endocr Pract. 2015;21(6):604-12.

69. Anyanwu AC, Fasanmade OA, Odeniyi IA, Iwuala S, Coker HB, Ohwovoriole AE. Effect of Vitamin D supplementation on glycemic control in Type 2 diabetes subjects in Lagos, Nigeria. Indian J Endocrinol Metab. 2016;20(2):189-94.

70. Farrokhian A, Raygan F, Bahmani F, Talari HR, Esfandiari R, Esmaillzadeh A, et al. Long-Term Vitamin D Supplementation Affects Metabolic Status in Vitamin D-Deficient Type 2 Diabetic Patients with Coronary Artery Disease. J Nutr. 2017;147(3):384-9.

71. Mohamad MI, El-Sherbeny EE, Bekhet MM. The Effect of Vitamin D Supplementation on Glycemic Control and Lipid Profile in Patients with Type 2 Diabetes Mellitus. J Am Coll Nutr. 2016;35(5):399-404.

72. Evans JM, Newton RW, Ruta DA, MacDonald TM, Morris AD. Socio-economic status, obesity and prevalence of Type 1 and Type 2 diabetes mellitus. Diabet Med. 2000;17(6):478-80.

73. Boyle JP, Engelgau MM, Thompson TJ, Goldschmid MG, Beckles GL, Timberlake DS, et al. Estimating prevalence of type 1 and type 2 diabetes in a population of African Americans with diabetes mellitus. Am J Epidemiol. 1999;149(1):55-63.

Page | 310

74. Tabak AG, Herder C, Rathmann W, Brunner EJ, Kivimaki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012;379(9833):2279-90.

75. Gabir MM, Hanson RL, Dabelea D, Imperatore G, Roumain J, Bennett PH, et al. The 1997 American Diabetes Association and 1999 World Health Organization criteria for hyperglycemia in the diagnosis and prediction of diabetes. Diabetes Care. 2000;23(8):1108-12.

76. Shaw JA, Zimmet PZ, de Courten M, Dowse GK, Chitson P, Gareeboo H, et al. Impaired fasting glucose or impaired glucose tolerance - What best predicts future diabetes in Mauritius? Diabetes Care. 1999;22(3):399-402.

77. Unwin N, Shaw J, Zimmet P, Alberti KGMM. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med. 2002;19:708-23.

78. Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract. 2014;103(2):137-49.

79. Tanamas SK, Magliano DJ, Lynch B, Sethi P, Willenberg L, Polkinghorne KR, et al. AusDiab 2012 The Australian Diabetes, Obesity and Lifestyle Study [Internet]. Melbourne: BakerIDI Heart and Diabetes Institute; 2013 [cited 2015 Nov 08]. Available from: https://www.baker.edu.au/Assets/Files/Baker IDI Ausdiab Report_interactive_FINAL.pdf.

80. Australian Institute of Health and Welfare. Australia's health 2016 [Internet]. Canberra: Australian Institute of Health and Welfare; 2016 [cited 2016 Jun 15]. Cat. no. AUS 199:[Available from: http://www.aihw.gov.au/publication-detail/?id=60129555544.

81. O'Dea K, Patel M, Kubisch D, Hopper J, Traianedes K. Obesity, diabetes, and hyperlipidemia in a central Australian aboriginal community with a long history of acculturation. Diabetes Care. 1993;16(7):1004-10.

82. Vos T, Goss J, Begg S, N. M. Projected health care costs report. Australian Burden of Disease and Injury Study [Internet]. Canberra: University of Queensland and Australian Institute of Health and Welfare; 2005 [cited 2013 Mar 30]. Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.366.5748&rep=rep1&type=pdf.

83. Johnson G, Martin JE, Timoshanko A. Preventing type 2 diabetes: scaling up to create a prevention system. Med J Aust. 2015;202(1):24-6.

84. Shaw J, Tanamas S. Diabetes: the silent pandemic and its impact on Australia [Internet]. Melbourne, Australia: Baker IDI Heart and Diabetes Institute; 2012 [cited 2013 Mar 30]. Available from: https://static.diabetesaustralia.com.au/s/fileassets/diabetes-australia/e7282521-472b-4313-b18e-be84c3d5d907.pdf.

Page | 311

85. Australian Bureau of Statistics. Australian Health Survey: Biomedical Results for Chronic Diseases, 2011-12 [Internet]. Canberra: ABS; 2013 [cited 2014 Mar 14]. 4364.0.55.005:[Available from: http://www.ausstats.abs.gov.au/Ausstats/subscriber.nsf/0/01ECE269AAE6E736CA257C0700114DBA/$File/AHS - Biomedical Results for Chronic Diseases.pdf.

86. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997;20(4):537-44.

87. Goff DC, Jr., Gerstein HC, Ginsberg HN, Cushman WC, Margolis KL, Byington RP, et al. Prevention of cardiovascular disease in persons with type 2 diabetes mellitus: current knowledge and rationale for the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Am J Cardiol. 2007;99.

88. The Action to Control Cardiovascular Risk in Diabetes Study Group. Effects of Intensive Glucose Lowering in Type 2 Diabetes. N Engl J Med. 2008;358(24):2545-59.

89. International Diabetes Federation. IDF Diabetes Atlas, 6th edn. [Internet]. Brussels, Belgium: International Diabetes Federation; 2013 [cited 2015 Mar 12]. 6th:[Available from: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas.html.

90. Laakso M. Hyperglycemia and cardiovascular disease in type 2 diabetes. Diabetes. 1999;48(5):937-42.

91. Fox CS, Golden SH, Anderson C, Bray GA, Burke LE, de Boer IH, et al. Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence: A Scientific Statement From the American Heart Association and the American Diabetes Association. Circulation. 2015;132(8):691-718.

92. Zimmet P, Alberti KG, Shaw J. Global and societal implications of the diabetes epidemic. Nature. 2001;414(6865):782-7.

93. Laakso M. Cardiovascular disease in type 2 diabetes from population to man to mechanisms: the Kelly West Award Lecture 2008. Diabetes Care. 2010;33(2):442-9.

94. World Health Organization. Global Report on Diabetes [Internet]. Geneva, Switzerland World Health Organization; 2016 [cited 2017 Jan 22]. Available from: http://apps.who.int/iris/bitstream/10665/204871/1/9789241565257_eng.pdf.

95. Australian Institute of Health and Welfare. Cardiovascular disease, diabetes and chronic kidney disease—Australian facts: Prevalence and incidence [Internet]. Canberra: AIHW; 2014 [cited 2014 Jan 15]. Cat. no. CDK 2:[Available from: http://www.aihw.gov.au/publication-detail/?id=60129549616.

Page | 312

96. Leon BM, Maddox TM. Diabetes and cardiovascular disease: Epidemiology, biological mechanisms, treatment recommendations and future research. World J Diabetes. 2015;6(13):1246-58.

97. Australian Institute of Health and Welfare. Diabetes expenditure in Australia 2008–09 [Internet]. Canberra: Australian Institute of Health and Welfare; 2013 [Cat. no. CVD 62.:[Available from: http://www.aihw.gov.au/publication-detail/?id=60129543925.

98. Davis WA, Knuiman MW, Hendrie D, Davis TM. The obesity-driven rising costs of type 2 diabetes in Australia: projections from the Fremantle Diabetes Study. Intern Med J. 2006;36(3):155-61.

99. Leahy JL. Pathogenesis of type 2 diabetes mellitus. Arch Med Res. 2005;36(3):197-209.

100. Eriksson J, Franssila-Kallunki A, Ekstrand A, Saloranta C, Widen E, Schalin C, et al. Early metabolic defects in persons at increased risk for non-insulin-dependent diabetes mellitus. N Engl J Med. 1989;321(6):337-43.

101. Kahn SE. The relative contributions of insulin resistance and beta-cell dysfunction to the pathophysiology of Type 2 diabetes. Diabetologia. 2003;46(1):3-19.

102. Stumvoll M, Goldstein BJ, van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy. Lancet. 2005;365(9467):1333-46.

103. DeFronzo RA. Pharmacologic therapy for type 2 diabetes mellitus. Ann Intern Med. 1999;131(4):281-303.

104. DeFronzo RA, Ferrannini E, Simonson DC. Fasting hyperglycemia in non-insulin-dependent diabetes mellitus: contributions of excessive hepatic glucose production and impaired tissue glucose uptake. Metabolism. 1989;38(4):387-95.

105. Duncan BB, Schmidt MI, Pankow JS, Ballantyne CM, Couper D, Vigo A, et al. Low-grade systemic inflammation and the development of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes. 2003;52(7):1799-805.

106. World Health Organization. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus. Report of a World Health Organization Consultation [Internet]. Geneva: World Health Organization; 2011 [cited 2013 Nov 15]. Available from: http://www.who.int/diabetes/publications/report-hba1c_2011.pdf.

107. De Fronzo R, Abdul-Ghani M. Type 2 Diabetes Can Be Prevented With Early Pharmacological Intervention. Diabetes Care. 2011;34(Supp 2):S202-S9.

108. Alberti K, Zimmet P. Definition, Diagnosis and Classification of Diabetes Mellitus and its complications. Part1: Diagnosis and Classification of Diabetes Mellitus Provisional Report of a WHO Consultation Diabet Med. 1998;15:539-53.

Page | 313

109. Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321(7258):405-12.

110. Turner RC, Millns H, Neil HAW, Stratton IM, Manley SE, Matthews DR, et al. Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom prospective diabetes study (UKPDS: 23). BMJ. 1998;316(7134):823-8.

111. Turner RC, Holman RR, Cull CA, Stratton IM, et al. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). The Lancet. 1998;352(9131):837-53.

112. American Diabetes Association. Standards of medical care in diabetes — 2011. Diabetes Care. 2011;34(Suppl 1):S11-S61.

113. d'Emden MC, Shaw JE, Colman PG, Colagiuri S, Twigg SM, Jones GR, et al. The role of HbA1c in the diagnosis of diabetes mellitus in Australia. Med J Aust. 2012;197(4):220-1.

114. Colagiuri S, Lee CM, Wong TY, Balkau B, Shaw JE, Borch-Johnsen K. DETECT-2 Collaboration Writing Group. Glycemic thresholds for diabetes-specific retinopathy: implications for diagnostic criteria for diabetes. Diabetes Care. 2011;34:145-50.

115. Stratton IM, Cull CA, Adler AI, Matthews DR, Neil HA, Holman RR. Additive effects of glycaemia and blood pressure exposure on risk of complications in type 2 diabetes: a prospective observational study (UKPDS 75). Diabetologia. 2006;49(8):1761-9.

116. NCD Risk Factor Collaboration. Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331 288 participants. Lancet Diabetes Endocrinol. 2015;3(8):624-37.

117. Kaprio J, Tuomilehto J, Koskenvuo M, Romanov K, Reunanen A, Eriksson J, et al. Concordance for Type-1 (Insulin-Dependent) and Type-2 (Non-Insulin-Dependent) Diabetes-Mellitus in a Population-Based Cohort of Twins in Finland. Diabetologia. 1992;35(11):1060-7.

118. Flores JC, Hirschhorn J, Altshuler D. The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits. Annu Rev Genomics Hum Genet. 2003;4:257-91.

119. Kacerovsky-Bielesz G, Kacerovsky M, Chmelik M, Farukuoye M, Ling C, Pokan R, et al. A single nucleotide polymorphism associates with the response of muscle ATP synthesis to long-term exercise training in relatives of type 2 diabetic humans. Diabetes Care. 2012;35(2):350-7.

Page | 314

120. Jenkins NT, McKenzie JA, Damcott CM, Witkowski S, Hagberg JM. Endurance exercise training effects on body fatness, VO2max, HDL-C subfractions, and glucose tolerance are influenced by a PLIN haplotype in older Caucasians. J Appl Physiol. 2010;108(3):498-506.

121. Mohlke KL, Boehnke M. Recent advances in understanding the genetic architecture of type 2 diabetes. Hum Mol Genet. 2015;24.

122. McPhee SJ, Papadakis MA. Current Medical Diagnosis & Treatment 2014. New York: McGraw-Hill Medical.; 2014.

123. Australian Institute of Health and Welfare. Type 2 diabetes in Australia’s children and young people: a working paper [Internet]. Canberra: Australian Institute of Health and Welfare; 2014 [cited 2017 Jan 10]. 21. Cat. no. CVD 64.:[Available from: http://www.aihw.gov.au/WorkArea/DownloadAsset.aspx?id=60129546359.

124. Sattar N. Gender aspects in type 2 diabetes mellitus and cardiometabolic risk. Best Pract Res Clin Endocrinol Metab. 2013;27(4):501-7.

125. Fall T, Hagg S, Ploner A, Magi R, Fischer K, Draisma HH, et al. Age- and sex-specific causal effects of adiposity on cardiovascular risk factors. Diabetes. 2015;64(5):1841-52.

126. Geer EB, Shen W. Gender differences in insulin resistance, body composition, and energy balance. Gend Med. 2009;6(Suppl 1):60-75.

127. Pouliot MC, Despres JP, Nadeau A, Moorjani S, Prud'Homme D, Lupien PJ, et al. Visceral obesity in men. Associations with glucose tolerance, plasma insulin, and lipoprotein levels. Diabetes. 1992;41(7):826-34.

128. Lemieux S, Prud'homme D, Nadeau A, Tremblay A, Bouchard C, Despres JP. Seven-year changes in body fat and visceral adipose tissue in women. Association with indexes of plasma glucose-insulin homeostasis. Diabetes Care. 1996;19(9):983-91.

129. Chen W, Wilson JL, Khaksari M, Cowley MA, Enriori PJ. Abdominal fat analyzed by DEXA scan reflects visceral body fat and improves the phenotype description and the assessment of metabolic risk in mice. Am J Physiol Endocrinol Metab. 2012;303(5):635-43.

130. Diabetes Prevention Program Research G. Relationship of body size and shape to the development of diabetes in the diabetes prevention program. Obesity. 2006;14(11):2107-17.

131. Matute ML, Kalkhoff RK. Sex steroid influence on hepatic gluconeogenesis and glucogen formation. Endocrinology. 1973;92(3):762-8.

132. Dantas AP, Sandberg K. Estrogen regulation of tumor necrosis factor-alpha: a missing link between menopause and cardiovascular risk in women? Hypertension. 2005;46(1):21-2.

Page | 315

133. Choi SE, Liu M, Palaniappan LP, Wang EJ, Wong ND. Gender and ethnic differences in the prevalence of type 2 diabetes among Asian subgroups in California. J Diabetes Complications. 2013;27(5):429-35.

134. Shai I, Jiang R, Manson JE, Stampfer MJ, Willett WC, Colditz GA, et al. Ethnicity, obesity, and risk of type 2 diabetes in women: a 20-year follow-up study. Diabetes Care. 2006;29(7):1585-90.

135. Colagiuri R, Thomas M, Buckley A. Preventing Type 2 Diabetes in Culturally and Linguistically Diverse Communities in NSW [Internet]. Sydney: NSW Department of Health; 2007 [cited 2015 Jan 04]. Available from: https://static.diabetesaustralia.com.au/s/fileassets/diabetes-australia/68e22e06-4281-4fb1-8d06-59af53719d85.pdf.

136. Astrup A, Finer N. Redefining Type 2 diabetes: 'Diabesity' or 'Obesity Dependent Diabetes Mellitus'? Obes Rev. 2000;1(2):57-9.

137. Anderson JW, Kendall CW, Jenkins DJ. Importance of weight management in type 2 diabetes: review with meta-analysis of clinical studies. J Am Coll Nutr. 2003;22(5):331-9.

138. Huerta JM, Tormo MJ, Chirlaque MD, Gavrila D, Amiano P, Arriola L, et al. Risk of type 2 diabetes according to traditional and emerging anthropometric indices in Spain, a Mediterranean country with high prevalence of obesity: results from a large-scale prospective cohort study. BMC Endocr Disord. 2013;13:7.

139. Abdullah A, Peeters A, de Courten M, Stoelwinder J. The magnitude of association between overweight and obesity and the risk of diabetes: a meta-analysis of prospective cohort studies. Diabetes Res Clin Pract. 2010;89(3):309-19.

140. Bray GA, Jablonski KA, Fujimoto WY, Barrett-Connor E, Haffner S, Hanson RL, et al. Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program. Am J Clin Nutr. 2008;87(5):1212-8.

141. Meisinger C, Döring A, Thorand B, Heier M, Löwel H. Body fat distribution and risk of type 2 diabetes in the general population: are there differences between men and women? The MONICA/KORA Augsburg Cohort Study. Am J Clin Nutr. 2006;84(3):483-9.

142. Barzilai N, Gupta G. Revisiting the role of fat mass in the life extension induced by caloric restriction. J Gerontol A Biol Sci Med Sci. 1999;54(3).

143. Gastaldelli A, Cusi K, Pettiti M, Hardies J, Miyazaki Y, Berria R, et al. Relationship between hepatic/visceral fat and hepatic insulin resistance in nondiabetic and type 2 diabetic subjects. Gastroenterology. 2007;133(2):496-506.

144. Wolfe RR. The underappreciated role of muscle in health and disease. Am J Clin Nutr. 2006;84(3):475-82.

Page | 316

145. DeFronzo RA, Jacot E, Jequier E, Maeder E, Wahren J, Felber JP. The effect of insulin on the disposal of intravenous glucose. Results from indirect calorimetry and heaptic and femoral venous catheterization. Diabetes. 1981;30(12):1000-7.

146. Park SW, Goodpaster BH, Strotmeyer ES, Kuller LH, Broudeau R, Kammerer C, et al. Accelerated loss of skeletal muscle strength in older adults with type 2 diabetes: the health, aging, and body composition study. Diabetes Care. 2007;30(6):1507-12.

147. Park SW, Goodpaster BH, Lee JS, Kuller LH, Boudreau R, de Rekeneire N, et al. Excessive loss of skeletal muscle mass in older adults with type 2 diabetes. Diabetes Care. 2009;32(11):1993-7.

148. Leenders M, Verdijk LB, van der Hoeven L, Adam JJ, van Kranenburg J, Nilwik R, et al. Patients with type 2 diabetes show a greater decline in muscle mass, muscle strength, and functional capacity with aging. J Am Med Dir Assoc. 2013;14(8):585-92.

149. Kalyani RR, Corriere M, Ferrucci L. Age-related and disease-related muscle loss: the effect of diabetes, obesity, and other diseases. Lancet Diabetes Endocrinol. 2014;2(10):819-29.

150. Barzilay JI, Cotsonis GA, Walston J, Schwartz AV, Satterfield S, Miljkovic I, et al. Insulin resistance is associated with decreased quadriceps muscle strength in nondiabetic adults aged ≥ 70 years. Diabetes Care. 2009;32(4):736-8.

151. Larsen BA, Wassel CL, Kritchevsky SB, Strotmeyer ES, Criqui MH, Kanaya AM, et al. Association of Muscle Mass, Area, and Strength With Incident Diabetes in Older Adults: The Health ABC Study. J Clin Endocrinol Metab. 2016;101(4):1847-55.

152. Mizgier ML, Casas M, Contreras-Ferrat A, Llanos P, Galgani JE. Potential role of skeletal muscle glucose metabolism on the regulation of insulin secretion. Obes Rev. 2014;15(7):587-97.

153. Larsen BA, Allison MA, Laughlin GA, Araneta MR, Barrett-Connor E, Wooten WJ, et al. The association between abdominal muscle and type II diabetes across weight categories in diverse post-menopausal women. J Clin Endocrinol Metab. 2015;100(1):105-9.

154. Hovanec N, Sawant A, Overend TJ, Petrella RJ, Vandervoort AA. Resistance training and older adults with type 2 diabetes mellitus: strength of the evidence. J Aging Res. 2012;2012.

155. Landi F, Onder G, Bernabei R. Sarcopenia and diabetes: two sides of the same coin. J Am Med Dir Assoc. 2013;14(8):540-1.

156. Eriksson J, Lindstrom J, Tuomilehto J. Potential for the prevention of type 2 diabetes. Br Med Bull. 2001;60:183-99.

157. Sigal RJ, Kenny GP, Wasserman DH, Castaneda-Sceppa C. Physical activity/exercise and type 2 diabetes. Diabetes Care. 2004;27(10):2518-39.

Page | 317

158. Manson JE, Nathan DM, Krolewski AS, Stampfer MJ, Willet WC, Hennekens CH. A prospective study of exercise and incidence of diabetes among US male physicians. JAMA. 1992;268:63-7.

159. Manson JE, Rimm EB, Stampfer MJ, Colditz GA, Willett WC, Krolewski AS, et al. Physical activity and incidence of non-insulin-dependent diabetes mellitus in women. Lancet. 1991;338(8770):774-8.

160. Kriska AM, LaPorte RE, Pettitt DJ, Charles MA, Nelson RG, Kuller LH, et al. The association of physical activity with obesity, fat distribution and glucose intolerance in Pima Indians. Diabetologia. 1993;36(9):863-9.

161. Bassuk SS, Manson JE. Epidemiological evidence for the role of physical activity in reducing risk of type 2 diabetes and cardiovascular disease. J Appl Physiol. 2005;99(3):1193-204.

162. Dunstan DW, Salmon J, Owen N, Armstrong T, Zimmet PZ, Welborn TA, et al. Associations of TV viewing and physical activity with the metabolic syndrome in Australian adults. Diabetologia. 2005;48(11):2254-61.

163. Salmon J, Bauman A, Crawford D, Timperio A, Owen N. The association between television viewing and overweight among Australian adults participating in varying levels of leisure-time physical activity. Int J Obes Relat Metab Disord. 2000;24(5):600-6.

164. Steyn NP, Mann J, Bennett PH, Temple N, Zimmet P, Tuomilehto J, et al. Diet, nutrition and the prevention of type 2 diabetes. Public Health Nutr. 2004;7.

165. Alberti KG, Zimmet P, Shaw J. International Diabetes Federation: a consensus on Type 2 diabetes prevention. Diabet Med. 2007;24(5):451-63.

166. Raymond MJ, Bramley-Tzerefos RE, Jeffs KJ, Winter A, Holland AE. Systematic review of high-intensity progressive resistance strength training of the lower limb compared with other intensities of strength training in older adults. Arch Phys Med Rehabil. 2013;94(8):1458-72.

167. van Dam RM, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Intern Med. 2002;136(3):201-9.

168. de Koning L, Malik VS, Rimm EB, Willett WC, Hu FB. Sugar-sweetened and artificially sweetened beverage consumption and risk of type 2 diabetes in men. Am J Clin Nutr. 2011;93(6):1321-7.

169. Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33(11):2477-83.

170. Hu FB, Manson JE, Stampfer MJ, Colditz G, Liu S, Solomon CG, et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001;345(11):790-7.

Page | 318

171. Fukagawa NK, Anderson JW, Hageman G, Young VR, Minaker KL. High-carbohydrate, high-fiber diets increase peripheral insulin sensitivity in healthy young and old adults. Am J Clin Nutr. 1990;52(3):524-8.

172. Swinburn BA, Boyce VL, Bergman RN, Howard BV, Bogardus C. Deterioration in carbohydrate metabolism and lipoprotein changes induced by modern, high fat diet in Pima Indians and Caucasians. J Clin Endocrinol Metab. 1991;73(1):156-65.

173. Pittas AG, Sun Q, Manson JE, Dawson-Hughes B, Hu FB. Plasma 25-hydroxyvitamin D concentration and risk of incident type 2 diabetes in women. Diabetes Care. 2010;33(9):2021-3.

174. Song Y, Wang L, Pittas AG, Del Gobbo LC, Zhang C, Manson JE, et al. Blood 25-hydroxy vitamin D levels and incident type 2 diabetes: a meta-analysis of prospective studies. Diabetes Care. 2013;36(5):1422-8.

175. de Boer IH, Tinker LF, Connelly S, Curb JD, Howard BV, Kestenbaum B, et al. Calcium plus vitamin D supplementation and the risk of incident diabetes in the Women's Health Initiative. Diabetes Care. 2008;31(4):701-7.

176. Avenell A, Cook JA, MacLennan GS, McPherson GC, Record trial group. Vitamin D supplementation and type 2 diabetes: a substudy of a randomised placebo-controlled trial in older people. Age Ageing. 2009;38(5):606-9.

177. Zittermann A, Frisch S, Berthold HK, Gotting C, Kuhn J, Kleesiek K, et al. Vitamin D supplementation enhances the beneficial effects of weight loss on cardiovascular disease risk markers. Am J Clin Nutr. 2009;89(5):1321-7.

178. Jorde R, Sneve M, Torjesen P, Figenschau Y. No improvement in cardiovascular risk factors in overweight and obese subjects after supplementation with vitamin D3 for 1 year. J Intern Med. 2010;267(5):462-72.

179. Wood AD, Secombes KR, Thies F, Aucott L, Black AJ, Mavroeidi A, et al. Vitamin D3 supplementation has no effect on conventional cardiovascular risk factors: a parallel-group, double-blind, placebo-controlled RCT. J Clin Endocrinol Metab. 2012;97(10):3557-68.

180. Nagpal J, Pande JN, Bhartia A. A double-blind, randomized, placebo-controlled trial of the short-term effect of vitamin D3 supplementation on insulin sensitivity in apparently healthy, middle-aged, centrally obese men. Diabet Med. 2009;26(1):19-27.

181. Grammatiki M, Rapti E, Karras S, Ajjan RA, Kotsa K. Vitamin D and diabetes mellitus: Causal or casual association? Rev Endocr Metab Disord. 2017;10.1007/s11154-016-9403-y.

182. Laakso M. Cardiovascular disease in type 2 diabetes: challenge for treatment and prevention. J Intern Med. 2001;249(3):225-35.

183. Hansson GK, Libby P. The immune response in atherosclerosis: a double-edged sword. Nat Rev Immunol. 2006;6(7):508-19.

Page | 319

184. Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM. C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA. 2001;286(3):327-34.

185. Hordern MD, Dunstan DW, Prins JB, Baker MK, Singh MA, Coombes JS. Exercise prescription for patients with type 2 diabetes and pre-diabetes: a position statement from Exercise and Sport Science Australia. J Sci Med Sport. 2012;15(1):25-31.

186. Johnson M, Jones R, Freeman C, Woods HB, Gillett M, Goyder E, et al. Can diabetes prevention programmes be translated effectively into real-world settings and still deliver improved outcomes? A synthesis of evidence. Diabetes Medicine. 2013;30(1):3-15.

187. Eriksson KF, Lindgarde F. Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmo feasibility study. Diabetologia. 1991;34(12):891-8.

188. Knowler WC, Barret-Connor E, Fowler SE, Hamman RF, Lachin JM. Reduction in the incidence of type 2 diabetes with lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2002;346:393-403.

189. Li G, Zhang P, Wang J, Gregg EW, Yang W, Gong Q, et al. The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study. Lancet. 2008;371(9626):1783-9.

190. Lindstrom J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemio K, et al. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet. 2006;368(9548):1673-9.

191. The Diabetes Prevention Program Research Group. The Diabetes Prevention Program (DPP): Description of lifestyle intervention. Diabetes Care. 2002;25(12):2165-71.

192. Stiegler RS, Zimmet PZ, Cameron AJ, Shaw JE. Lifestyle management: preventing Type 2 diabets and cardiovascular complications. Therapy. 2009;6(4):489-96.

193. Gillies CL, Abrams KR, Lambert PC, Cooper NJ, Sutton AJ, Hsu RT, et al. Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ. 2007;334(7588):299.

194. Yoon U, Kwok LL, Magkidis A. Efficacy of lifestyle interventions in reducing diabetes incidence in patients with impaired glucose tolerance: a systematic review of randomized controlled trials. Metabolism. 2013;62(2):303-14.

195. Hood DA. Invited Review: contractile activity-induced mitochondrial biogenesis in skeletal muscle. J Appl Physiol. 2001;90(3):1137-57.

Page | 320

196. Tipton KD, Rasmussen BB, Miller SL, Wolf SE, Owens-Stovall SK, Petrini BE, et al. Timing of amino acid-carbohydrate ingestion alters anabolic response of muscle to resistance exercise. Am J Physiol Endocrinol Metab. 2001;281(2):197-206.

197. Haskell WL, Lee I, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation. 2007;116(9):1081-93.

198. American Diabetes Association. Standards of Medical Care in Diabetes 2017. Diabetes Care. 2016;40(Suppl 1).

199. Bacchi E, Negri C, Targher G, Faccioli N, Lanza M, Zoppini G, et al. Both resistance training and aerobic training reduce hepatic fat content in type 2 diabetic subjects with nonalcoholic fatty liver disease (the RAED2 Randomized Trial). Hepatology. 2013;58(4):1287-95.

200. Motahari-Tabari N, Ahmad Shirvani M, Shirzad EAM, Yousefi-Abdolmaleki E, Teimourzadeh M. The effect of 8 weeks aerobic exercise on insulin resistance in type 2 diabetes: a randomized clinical trial. Glob J Health Sci. 2014;7(1):115-21.

201. Bloomgarden ZT. American Diabetes Association Annual Meeting, 1999: diabetes and obesity. Diabetes Care. 2000;23(1):118-24.

202. Cauza E, Hanusch-Enserer U, Strasser B, Ludvik B, Metz-Schimmerl S, Pacini G, et al. The relative benefits of endurance and strength training on the metabolic factors and muscle function of people with type 2 diabetes mellitus. Arch Phys Med Rehabil. 2005;86(8):1527-33.

203. Castaneda C, Layne JE, Munoz-Orians L, Gordon PL, Walsmith J, Foldvari M, et al. A randomized controlled trial of resistance exercise training to improve glycemic control in older adults with type 2 diabetes. Diabetes Care. 2002;25(12):2335-41.

204. Dunstan DW, Vulikh E, Owen N, Jolley D, Shaw J, Zimmet P. Community center-based resistance training for the maintenance of glycemic control in adults with type 2 diabetes. Diabetes Care. 2006;29(12):2586-91.

205. Dunstan DW, Puddey IB, Beilin LJ, Burke V, Morton AR, Stanton KG. Effects of a short-term circuit weight training program on glycaemic control in NIDDM. Diabetes Res Clin Pract. 1998;40(1):53-61.

206. Ng CLW, Goh SY, Malhotra R, Ostbye T, Tai ES. Minimal difference between aerobic and progressive resistance exercise on metabolic profile and fitness in older adults with diabetes mellitus: a randomised trial. J Physiother. 2010;56(3):163-70.

207. Cauza E, Hanusch-Enserer U, Strasser B, Kostner K, Dunky A, Haber P. Strength and endurance training lead to different post exercise glucose profiles

Page | 321

in diabetic participants using a continuous subcutaneous glucose monitoring system. Eur J Clin Invest. 2005;35(12):745-51.

208. Kwon HR, Han KA, Ku YH, Ahn HJ, Koo BK, Kim HC, et al. The effects of resistance training on muscle and body fat mass and muscle strength in type 2 diabetic women. Korean Diabetes J. 2010;34(2):101-10.

209. Snowling NJ, Hopkins WG. Effects of different modes of exercise training on glucose control and risk factors for complications in type 2 diabetic patients: a meta-analysis. Diabetes Care. 2006;29(11):2518-27.

210. Praet SF, van Loon LJ. Optimizing the therapeutic benefits of exercise in Type 2 diabetes. J Appl Physiol. 2007;103(4):1113-20.

211. Willey KA, Singh MA. Battling insulin resistance in elderly obese people with type 2 diabetes: bring on the heavy weights. Diabetes Care. 2003;26(5):1580-8.

212. Yang Z, Scott CA, Mao C, Tang J, Farmer AJ. Resistance exercise versus aerobic exercise for type 2 diabetes: a systematic review and meta-analysis. Sports Med. 2014;44(4):487-99.

213. Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, et al. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care. 2016;39(11):2065-79.

214. de Lade CG, Marins JC, Lima LM, de Carvalho CJ, Teixeira RB, Albuquerque MR, et al. Effects of different exercise programs and minimal detectable changes in hemoglobin A1c in patients with type 2 diabetes. Diabetol Metab Syndr. 2016;8:13.

215. Plotnikoff RC, Eves N, Jung M, Sigal RJ, Padwal R, Karunamuni N. Multicomponent, home-based resistance training for obese adults with type 2 diabetes: a randomized controlled trial. Int J Obes. 2010;34(12):1733-41.

216. Honkola A, Forsen T, Eriksson J. Resistance training improves the metabolic profile in individuals with type 2 diabetes. Acta Diabetol. 1997;34(4):245-8.

217. Mavros Y, Kay S, Anderberg KA, Baker MK, Wang Y, Zhao R, et al. Changes in insulin resistance and HbA1c are related to exercise-mediated changes in body composition in older adults with type 2 diabetes: interim outcomes from the GREAT2DO trial. Diabetes Care. 2013;36(8):2372-9.

218. Jorge ML, de Oliveira VN, Resende NM, Paraiso LF, Calixto A, Diniz AL, et al. The effects of aerobic, resistance, and combined exercise on metabolic control, inflammatory markers, adipocytokines, and muscle insulin signaling in patients with type 2 diabetes mellitus. Metabolism. 2011;60(9):1244-52.

219. Balducci S, Zanuso S, Cardelli P, Salvi L, Mazzitelli G, Bazuro A, et al. Italian Diabetes Exercise Study (IDES) Investigators. Changes in physical fitness predict improvements in modifiable cardiovascular risk factors independently of body weight loss in subjects with type 2 diabetes participating in the Italian Diabetes and Exercise Study (IDES). Diabetes Care. 2012;35(6):1347-54.

Page | 322

220. Cuff DJ, Meneilly GS, Martin A, Ignaszewski A, Tildesley HD, Frohlich JJ. Effective exercise modality to reduce insulin resistance in women with type 2 diabetes. Diabetes Care. 2003;26(11):2977-82.

221. Tan SJ, Li W, Wang JX. Effects of six months of combined aerobic and resistance training for elderly patients with a long history of type 2 diabetes. J Sports Sci Med. 2012;11(3):495-501.

222. Liu Y, Liu SX, Cai Y, Xie KL, Zhang WL, Zheng F. Effects of combined aerobic and resistance training on the glycolipid metabolism and inflammation levels in type 2 diabetes mellitus. J Phys Ther Sci. 2015;27(7):2365-71.

223. Black LE, Swan PD, Alvar BA. Effects of intensity and volume on insulin sensitivity during acute bouts of resistance training. J Strength Cond Res. 2010;24(4):1109-16.

224. Ibanez J, Izquierdo M, Arguelles I, Forga L, Larrion JL, Garcia-Unciti M, et al. Twice-weekly progressive resistance training decreases abdominal fat and improves insulin sensitivity in older men with type 2 diabetes. Diabetes Care. 2005;28(3):662-7.

225. Baldi JC, Snowling N. Resistance training improves glycaemic control in obese type 2 diabetic men. Int J Sports Med. 2003;24(6):419-23.

226. Eriksson J, Taimela S, Eriksson K, Parviainen S, Peltonen J, Kujala U. Resistance training in the treatment of non-insulin-dependent diabetes mellitus. Int J Sports Med. 1997;18(4):242-6.

227. Umpierre D, Ribeiro PA, Kramer CK, Leitao CB, Zucatti AT, Azevedo MJ, et al. Physical activity advice only or structured exercise training and association with HbA1c levels in type 2 diabetes: a systematic review and meta-analysis. JAMA. 2011;305(17):1790-9.

228. Ishiguro H, Kodama S, Horikawa C, Fujihara K, Hirose AS, Hirasawa R, et al. In Search of the Ideal Resistance Training Program to Improve Glycemic Control and its Indication for Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis. Sports Med. 2016;46(1):67-77.

229. Richter EA, Hargreaves M. Exercise, GLUT4, and skeletal muscle glucose uptake. Physiol Rev. 2013;93(3):993-1017.

230. Brooks N, Layne JE, Gordon PL, Roubenoff R, Nelson ME, Castaneda-Sceppa C. Strength training improves muscle quality and insulin sensitivity in Hispanic older adults with type 2 diabetes. Int J Med Sci. 2006;4(1):19-27.

231. Sigal RJ, Kenny GP, Wasserman DH, Castaneda-Sceppa C, White RD. Physical activity/exercise and type 2 diabetes: a consensus statement from the American Diabetes Association. Diabetes Care. 2006;29(6):1433-8.

232. Esposito K, Pontillo A, Giugliano F, Giugliano G, Marfella R, Nicoletti G, et al. Association of low interleukin-10 levels with the metabolic syndrome in obese women. J Clin Endocrinol Metab. 2003;88(3):1055-8.

Page | 323

233. Ryan AS, Nicklas BJ. Reductions in plasma cytokine levels with weight loss improve insulin sensitivity in overweight and obese postmenopausal women. Diabetes Care. 2004;27(7):1699-705.

234. Cottam DR, Mattar SG, Barinas-Mitchell E, Eid G, Kuller L, Kelley DE, et al. The chronic inflammatory hypothesis for the morbidity associated with morbid obesity: implications and effects of weight loss. Obes Surg. 2004;14(5):589-600.

235. Hamer M, Sabia S, Batty GD, Shipley MJ, Tabak AG, Singh-Manoux A, et al. Physical activity and inflammatory markers over 10 years: follow-up in men and women from the Whitehall II cohort study. Circulation. 2012;126(8):928-33.

236. Kadoglou NP, Fotiadis G, Athanasiadou Z, Vitta I, Lampropoulos S, Vrabas IS. The effects of resistance training on ApoB/ApoA-I ratio, Lp(a) and inflammatory markers in patients with type 2 diabetes. Endocrine. 2012;42(3):561-9.

237. Swift DL, Johannsen NM, Earnest CP, Blair SN, Church TS. Effect of exercise training modality on C-reactive protein in type 2 diabetes. Med Sci Sports Exerc. 2012;44(6):1028-34.

238. Mavros Y, Kay S, Simpson KA, Baker MK, Wang Y, Zhao RR, et al. Reductions in C-reactive protein in older adults with type 2 diabetes are related to improvements in body composition following a randomized controlled trial of resistance training. J Cachexia Sarcopenia Muscle. 2014;5(2):111-20.

239. Kim KB. Effect of different training mode on Interleukin-6 (IL-6) and C-reactive protein (CRP) in type 2 diabetes mellitus (T2DM) patients. J Exerc Nutrition Biochem. 2014;18(4):371-8.

240. Donges CE, Duffield R, Drinkwater EJ. Effects of resistance or aerobic exercise training on interleukin-6, C-reactive protein, and body composition. Med Sci Sports Exerc. 2010;42(2):304-13.

241. Vieira VJ, Valentine RJ, Wilund KR, Woods JA. Effects of diet and exercise on metabolic disturbances in high-fat diet-fed mice. Cytokine. 2009;46(3):339-45.

242. Vieira VJ, Valentine RJ, Wilund KR, Antao N, Baynard T, Woods JA. Effects of exercise and low-fat diet on adipose tissue inflammation and metabolic complications in obese mice. Am J Physiol Endocrinol Metab. 2009;296(5).

243. Zhang W, Mottillo EP, Zhao J, Gartung A, VanHecke GC, Lee JF, et al. Adipocyte lipolysis-stimulated interleukin-6 production requires sphingosine kinase 1 activity. J Biol Chem. 2014;289(46):32178-85.

244. Hayashino Y, Jackson JL, Hirata T, Fukumori N, Nakamura F, Fukuhara S, et al. Effects of exercise on C-reactive protein, inflammatory cytokine and adipokine in patients with type 2 diabetes: a meta-analysis of randomized controlled trials. Metabolism. 2014;63(3):431-40.

Page | 324

245. Nascimento Dda C, Tibana RA, Benik FM, Fontana KE, Ribeiro Neto F, Santana FS, et al. Sustained effect of resistance training on blood pressure and hand grip strength following a detraining period in elderly hypertensive women: a pilot study. Clin Interv Aging. 2014;9:219-25.

246. Payne WR, Walsh KJ, Harvey JT, Livy MF, McKenzie KJ, Donaldson A, et al. Effect of a low-resource-intensive lifestyle modification program incorporating gymnasium-based and home-based resistance training on type 2 diabetes risk in Australian adults. Diabetes Care. 2008;31(12):2244-50.

247. Figueira FR, Umpierre D, Cureau FV, Zucatti AT, Dalzochio MB, Leitao CB, et al. Association between physical activity advice only or structured exercise training with blood pressure levels in patients with type 2 diabetes: a systematic review and meta-analysis. Sports Med. 2014;44(11):1557-72.

248. Amouzad Mahdirejei H, Fadaei Reyhan Abadei S, Abbaspour Seidi A, Eshaghei Gorji N, Rahmani Kafshgari H, Ebrahim Pour M, et al. Effects of an eight-week resistance training on plasma vaspin concentrations, metabolic parameters levels and physical fitness in patients with type 2 diabetes. Cell J. 2014;16(3):367-74.

249. James AP, Whiteford J, Ackland TR, Dhaliwal SS, Woodhouse JJ, Prince RL, et al. Effects of a 1-year randomised controlled trial of resistance training on blood lipid profile and chylomicron concentration in older men. Eur J Appl Physiol. 2016;116(11-12):2113-23.

250. Misra A, Alappan NK, Vikram NK, Goel K, Gupta N, Mittal K, et al. Effect of supervised progressive resistance-exercise training protocol on insulin sensitivity, glycemia, lipids, and body composition in Asian Indians with type 2 diabetes. Diabetes Care. 2008;31(7):1282-7.

251. Ribeiro AS, Tomeleri CM, Souza MF, Pina FL, Schoenfeld BJ, Nascimento MA, et al. Effect of resistance training on C-reactive protein, blood glucose and lipid profile in older women with differing levels of RT experience. Age (Dordr). 2015;37(6):109.

252. Bacchi E, Negri C, Zanolin ME, Milanese C, Faccioli N, Trombetta M, et al. Metabolic effects of aerobic training and resistance training in type 2 diabetic subjects: a randomized controlled trial (the RAED2 study). Diabetes Care. 2012;35(4):676-82.

253. Sukala WR, Page R, Rowlands DS, Krebs J, Lys I, Leikis M, et al. South Pacific Islanders resist type 2 diabetes: comparison of aerobic and resistance training. Eur J Appl Physiol. 2012;112(1):317-25.

254. Mann S, Beedie C, Jimenez A. Differential effects of aerobic exercise, resistance training and combined exercise modalities on cholesterol and the lipid profile: review, synthesis and recommendations. Sports Med. 2014;44(2):211-21.

Page | 325

255. Minges KE, Cormick G, Unglik E, Dunstan DW. Evaluation of a resistance training program for adults with or at risk of developing diabetes: an effectiveness study in a community setting. Int J Behav Nutr Phys Act. 2011;8(1):50-7.

256. King AC, Rejeski WJ, Buchner DM. Physical activity interventions targeting older adults. A critical review and recommendations. Am J Prev Med. 1998;15(4):316-33.

257. Ackermann RT, Cheadle A, Sandhu N, Madsen L, Wagner EH, LoGerfo JP. Community exercise program use and changes in healthcare costs for older adults. Am J Prev Med. 2003;25(3):232-7.

258. Plotnikoff RC, Karunamuni ND, Johnson JA, Kotovych M, Svenson LW. Health-related behaviours in adults with diabetes: associations with health care utilization and costs. Can J Public Health. 2008;99(3):227-31.

259. Jacobs-van der Bruggen MA, Bos G, Bemelmans WJ, Hoogenveen RT, Vijgen SM, Baan CA. Lifestyle interventions are cost-effective in people with different levels of diabetes risk: results from a modeling study. Diabetes Care. 2007;30(1):128-34.

260. Evidence-Based Nutrition Principles and Recommendations for the Treatment and Prevention of Diabetes and Related Complications. Diabetes Care. 2002;25(1):202.

261. Krauss RM, Eckel RH, Howard BV, Appel LJ, Daniels SR, Deckelbaum RJ, et al. AHA Guidelines Revision 2000: A statement for healthcare professionals from the Nutrition Committee of the American Heart Association Circulation. 2000;102:2284-99.

262. Nutrition Committee of the British Diabetic Association's Professional Advisory Committee. Dietary recommendations for people with diabetes:an update for the 1990's. Diabet Med. 1992;9(2):189-202.

263. Gannon MC, Nuttall FQ, Saeed A, Jordan K, Hoover H. An increase in dietary protein improves the blood glucose response in persons with type 2 diabetes. Am J Clin Nutr. 2003;78(4):734-41.

264. Layman DK, Boileau RA, Erickson DJ, Painter JE, Shiue H, Sather C, et al. A reduced ratio of dietary carbohydrate to protein improves body composition and blood lipid profiles during weight loss in adult women. J Nutr. 2003;133(2):411-7.

265. Layman DK, Shiue H, Sather C, Erickson DJ, Baum J. Increased dietary protein modifies glucose and insulin homeostasis in adult women during weight loss. J Nutr. 2003;133(2):405-10.

266. Skov AR, Toubro S, Ronn B, Holm L, Astrup A. Randomized trial on protein vs carbohydrate in ad libitum fat reduced diet for the treatment of obesity. Int J Obes Relat Metab Disord. 1999;23(5):528-36.

Page | 326

267. Parker B, Noakes M, Luscombe N, Clifton P. Effect of a high-protein, high-monounsaturated fat weight loss diet on glycemic control and lipid levels in type 2 diabetes. Diabetes Care. 2002;25(3):425-30.

268. Ajala O, English P, Pinkney J. Systematic review and meta-analysis of different dietary approaches to the management of type 2 diabetes. Am J Clin Nutr. 2013;97(3):505-16.

269. Farnsworth E, Luscombe ND, Noakes M, Wittert G, Argyiou E, Clifton PM. Effect of a high-protein, energy-restricted diet on body composition, glycemic control, and lipid concentrations in overweight and obese hyperinsulinemic men and women. Am J Clin Nutr. 2003;78(1):31-9.

270. Gannon MC, Nuttall JA, Damberg G, Gupta V, Nuttall FQ. Effect of protein ingestion on the glucose appearance rate in people with type 2 diabetes. J Clin Endocrinol Metab. 2001;86(3):1040-7.

271. Bezerra Duarte SM, Faintuch J, Stefano JT, Sobral de Oliveira MB, de Campos Mazo DF, Rabelo F, et al. Hypocaloric high-protein diet improves clinical and biochemical markers in patients with nonalcoholic fatty liver disease (NAFLD). Nutr Hosp. 2014;29(1):94-101.

272. Gannon MC, Nuttall FQ. Effect of a high-protein, low-carbohydrate diet on blood glucose control in people with type 2 diabetes. Diabetes. 2004;53(9):2375-82.

273. Pedersen E, Jesudason DR, Clifton PM. High protein weight loss diets in obese subjects with type 2 diabetes mellitus. Nutr Metab Cardiovasc Dis. 2014;24(5):554-62.

274. Krebs JD, Elley CR, Parry-Strong A, Lunt H, Drury PL, Bell DA, et al. The Diabetes Excess Weight Loss (DEWL) Trial: a randomised controlled trial of high-protein versus high-carbohydrate diets over 2 years in type 2 diabetes. Diabetologia. 2012;55(4):905-14.

275. Manders RJ, Little JP, Forbes SC, Candow DG. Insulinotropic and muscle protein synthetic effects of branched-chain amino acids: potential therapy for type 2 diabetes and sarcopenia. Nutrients. 2012;4(11):1664-78.

276. van Loon LJ, Kruijshoop M, Menheere PP, Wagenmakers AJ, Saris WH, Keizer HA. Amino acid ingestion strongly enhances insulin secretion in patients with long-term type 2 diabetes. Diabetes Care. 2003;26(3):625-30.

277. Gannon MC, Nuttall FQ, Grant CT, Ercan-Fang S, Ercan-Fang N. Stimulation of insulin secretion by fructose ingested with protein in people with untreated type 2 diabetes. Diabetes Care. 1998;21(1):16-22.

278. Charles S, Henquin JC. Distinct effects of various amino acids on45Ca2+fluxes in rat pancreatic islets. Biochem J. 1983;214(3):899-907.

279. Dixon G, Nolan J, McClenaghan N, Flatt PR, Newsholme P. A comparative study of amino acid consumption by rat islet cells and the clonal beta-cell line

Page | 327

BRIN-BD11 - the functional significance of L-alanine. J Endocrinol. 2003;179(3):447-54.

280. Sener A, Malaisse WJ. L-leucine and a nonmetabolized analogue activate pancreatic islet glutamate dehydrogenase. Nature. 1980;288(5787):187-9.

281. Manders RJ, Hansen D, Zorenc AH, Dendale P, Kloek J, Saris WH, et al. Protein co-ingestion strongly increases postprandial insulin secretion in type 2 diabetes patients. J Med Food. 2014;17(7):758-63.

282. Verdijk LB, Jonkers RAM, Gleeson BG, Beelen M, Meijer K, Savelberg HHCM, et al. Protein supplementation before and after exercise does not further augment skeletal muscle hypertrophy after resistance training in elderly men. Am J Clin Nutr. 2009;89(2):608-16.

283. Tieland M, Dirks ML, van der Zwaluw N, Verdijk LB, van de Rest O, de Groot LC, et al. Protein supplementation increases muscle mass gain during prolonged resistance-type exercise training in frail elderly people: a randomized, double-blind, placebo-controlled trial. J Am Med Dir Assoc. 2012;13(8):713-9.

284. Leenders M, Verdijk LB, Van der Hoeven L, Van Kranenburg J, Nilwik R, Wodzig WK, et al. Protein supplementation during resistance-type exercise training in the elderly. Med Sci Sports Exerc. 2013;45(3):542-52.

285. Weinheimer EM, Conley TB, Kobza VM, Sands LP, Lim E, Janle EM, et al. Whey protein supplementation does not affect exercise training-induced changes in body composition and indices of metabolic syndrome in middle-aged overweight and obese adults. J Nutr. 2012;142(8):1532-9.

286. Wycherley TP, Noakes M, Clifton PM, Cleanthous X, Keogh JB, Brinkworth GD. A high-protein diet with resistance exercise training improves weight loss and body composition in overweight and obese patients with type 2 diabetes. Diabetes Care. 2010;33(5):969-76.

287. Nuttall FQ, Gannon MC. Metabolic response of people with type 2 diabetes to a high protein diet. Nutr Metab. 2004;1(1):6.

288. Brinkworth GD, Noakes M, Buckley JD, Keogh JB, Clifton PM. Long-term effects of a very-low-carbohydrate weight loss diet compared with an isocaloric low-fat diet after 12 mo. Am J Clin Nutr. 2009;90(1):23-32.

289. Mateo-Gallego R, Marco-Benedi V, Perez-Calahorra S, Bea AM, Baila-Rueda L, Lamiquiz-Moneo I, et al. Energy-restricted, high-protein diets more effectively impact cardiometabolic profile in overweight and obese women than lower-protein diets. Clin Nutr. 2017;36(2):371-9.

290. Symons TB, Sheffield-Moore M, Wolfe RR, Paddon-Jones D. A moderate serving of high-quality protein maximally stimulates skeletal muscle protein synthesis in young and elderly subjects. J Am Diet Assoc. 2009;109(9):1582-6.

291. Bosaeus I, Rothenberg E. Nutrition and physical activity for the prevention and treatment of age-related sarcopenia. Proc Nutr Soc. 2016;75(2):174-80.

Page | 328

292. Baum JI, Kim IY, Wolfe RR. Protein Consumption and the Elderly: What Is the Optimal Level of Intake? Nutrients. 2016;8(6).

293. Leidy HJ, Clifton PM, Astrup A, Wycherley TP, Westerterp-Plantenga MS, Luscombe-Marsh ND, et al. The role of protein in weight loss and maintenance. Am J Clin Nutr. 2015;101(6):1320S-9S.

294. Leidy HJ, Hoertel HA, Douglas SM, Higgins KA, Shafer RS. A high-protein breakfast prevents body fat gain, through reductions in daily intake and hunger, in "Breakfast skipping" adolescents. Obesity. 2015;23(9):1761-4.

295. Berryman CE, Agarwal S, Lieberman HR, Fulgoni VL, 3rd, Pasiakos SM. Diets higher in animal and plant protein are associated with lower adiposity and do not impair kidney function in US adults. Am J Clin Nutr. 2016;104(3):743-9.

296. Wycherley TP, Moran LJ, Clifton PM, Noakes M, Brinkworth GD. Effects of energy-restricted high-protein, low-fat compared with standard-protein, low-fat diets: a meta-analysis of randomized controlled trials. Am J Clin Nutr. 2012;96(6):1281-98.

297. Luscombe ND, Clifton PM, Noakes M, Parker B, Wittert G. Effects of energy-restricted diets containing increased protein on weight loss, resting energy expenditure, and the thermic effect of feeding in type 2 diabetes. Diabetes Care. 2002;25(4):652-7.

298. Karst H, Steiniger J, Noack R, Steglich HD. Diet-induced thermogenesis in man: thermic effects of single proteins, carbohydrates and fats depending on their energy amount. Ann Nutr Metab. 1984;28(4):245-52.

299. Westerterp KR, Wilson SA, Rolland V. Diet induced thermogenesis measured over 24h in a respiration chamber: effect of diet composition. Int J Obes Relat Metab Disord. 1999;23(3):287-92.

300. Leibel RL, Rosenbaum M, Hirsch J. Changes in energy expenditure resulting from altered body weight. N Engl J Med. 1995;332(10):621-8.

301. Bessard T, Schutz Y, Jequier E. Energy-Expenditure and Postprandial Thermogenesis in Obese Women before and after Weight-Loss. Am J Clin Nutr. 1983;38(5):680-93.

302. Westman EC, Yancy WS, Edman JS, Tomlin KF, Perkins CE. Effect of 6-month adherence to a very low carbohydrate diet program. Am J Med. 2002;113(1):30-6.

303. Astrup A. The satiating power of protein--a key to obesity prevention? Am J Clin Nutr. 2005;82(1):1-2.

304. Pesta DH, Samuel VT. A high-protein diet for reducing body fat: mechanisms and possible caveats. Nutr Metab. 2014;11(1):53.

305. Layman DK, Evans E, Baum JI, Seyler J, Erickson DJ, Boileau RA. Dietary protein and exercise have additive effects on body composition during weight loss in adult women. J Nutr. 2005;135(8):1903-10.

Page | 329

306. Brinkworth GD, Noakes M, Parker B, Foster P, Clifton PM. Long-term effects of advice to consume a high-protein, low-fat diet, rather than a conventional weight-loss diet, in obese adults with type 2 diabetes: one-year follow-up of a randomised trial. Diabetologia. 2004;47(10):1677-86.

307. Westman EC, Yancy WS, Jr., Mavropoulos JC, Marquart M, McDuffie JR. The effect of a low-carbohydrate, ketogenic diet versus a low-glycemic index diet on glycemic control in type 2 diabetes mellitus. Nutr Metab. 2008;5(1):36.

308. Kouw IW, Gorissen SH, Burd NA, Cermak NM, Gijsen AP, van Kranenburg J, et al. Postprandial Protein Handling Is Not Impaired in Type 2 Diabetes Patients When Compared With Normoglycemic Controls. J Clin Endocrinol Metab. 2015;100(8):3103-11.

309. Paddon-Jones D, Sheffield-Moore M, Zhang XJ, Volpi E, Wolf SE, Aarsland A, et al. Amino acid ingestion improves muscle protein synthesis in the young and elderly. Am J Physiol Endocrinol Metab. 2004;286(3):321-8.

310. Breen L, Phillips SM. Skeletal muscle protein metabolism in the elderly: Interventions to counteract the 'anabolic resistance' of ageing. Nutr Metab. 2011;8(68).

311. Manders RJ, Koopman R, Beelen M, Gijsen AP, Wodzig WK, Saris WH, et al. The muscle protein synthetic response to carbohydrate and protein ingestion is not impaired in men with longstanding type 2 diabetes. J Nutr. 2008;138(6):1079-85.

312. Katsanos CS, Kobayashi H, Sheffield-Moore M, Aarsland A, Wolfe RR. A high proportion of leucine is required for optimal stimulation of the rate of muscle protein synthesis by essential amino acids in the elderly. Am J Physiol Endocrinol Metab. 2006;291(2):381-7.

313. Gougeon R. Insulin resistance of protein metabolism in type 2 diabetes and impact on dietary needs: a review. Can J Diabetes. 2013;37(2):115-20.

314. Pereira S, Marliss EB, Morais JA, Chevalier S, Gougeon R. Insulin resistance of protein metabolism in type 2 diabetes. Diabetes. 2008;57(1):56-63.

315. Papakonstantinou E, Triantafillidou D, Panagiotakos DB, Koutsovasilis A, Saliaris M, Manolis A, et al. A high-protein low-fat diet is more effective in improving blood pressure and triglycerides in calorie-restricted obese individuals with newly diagnosed type 2 diabetes. Eur J Clin Nutr. 2010;64(6):595-602.

316. Tay J, Luscombe-Marsh ND, Thompson CH, Noakes M, Buckley JD, Wittert GA, et al. A very low-carbohydrate, low-saturated fat diet for type 2 diabetes management: a randomized trial. Diabetes Care. 2014;37(11):2909-18.

317. Raymond F, Wang L, Moser M, Metairon S, Mansourian R, Zwahlen MC, et al. Consequences of exchanging carbohydrates for proteins in the cholesterol metabolism of mice fed a high-fat diet. PLoS One. 2012;7(11).

Page | 330

318. Bortolotti M, Kreis R, Debard C, Cariou B, Faeh D, Chetiveaux M, et al. High protein intake reduces intrahepatocellular lipid deposition in humans. Am J Clin Nutr. 2009;90(4):1002-10.

319. Zhang X, Beynen AC. Lowering effect of dietary milk-whey protein v. casein on plasma and liver cholesterol concentrations in rats. Br J Nutr. 1993;70(1):139-46.

320. Hosomi R, Fukunaga K, Arai H, Kanda S, Nishiyama T, Yoshida M. Fish protein hydrolysates affect cholesterol metabolism in rats fed non-cholesterol and high-cholesterol diets. J Med Food. 2012;15(3):299-306.

321. Shukla A, Brandsch C, Bettzieche A, Hirche F, Stangl GI, Eder K. Isoflavone-poor soy protein alters the lipid metabolism of rats by SREBP-mediated down-regulation of hepatic genes. J Nutr Biochem. 2007;18(5):313-21.

322. Lovati MR, Manzoni C, Canavesi A, Sirtori M, Vaccarino V, Marchi M, et al. Soybean protein diet increases low density lipoprotein receptor activity in mononuclear cells from hypercholesterolemic patients. J Clin Invest. 1987;80(5):1498-502.

323. Potter SM. Overview of proposed mechanisms for the hypocholesterolemic effect of soy. J Nutr. 1995;125(3 Suppl):606S-11S.

324. El Khoury D, Anderson GH. Recent advances in dietary proteins and lipid metabolism. Curr Opin Lipidol. 2013;24(3):207-13.

325. Zemel MB, Sun X, Sobhani T, Wilson B. Effects of dairy compared with soy on oxidative and inflammatory stress in overweight and obese subjects. Am J Clin Nutr. 2010;91(1):16-22.

326. Zhou LM, Xu JY, Rao CP, Han S, Wan Z, Qin LQ. Effect of whey supplementation on circulating C-reactive protein: a meta-analysis of randomized controlled trials. Nutrients. 2015;7(2):1131-43.

327. Ball L, Davmor R, Leveritt M, Desbrow B, Ehrlich C, Chaboyer W. The nutrition care needs of patients newly diagnosed with type 2 diabetes: informing dietetic practice. J Hum Nutr Diet. 2016;29(4):487-94.

328. Lichtman SW, Pisarska K, Berman ER, Pestone M, Dowling H, Offenbacher E, et al. Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N Engl J Med. 1992;327(27):1893-8.

329. Sousa GT, Lira FS, Rosa JC, de Oliveira EP, Oyama LM, Santos RV, et al. Dietary whey protein lessens several risk factors for metabolic diseases: a review. Lipids Health Dis. 2012;11:67.

330. Gill HS, Rutherford KJ, Cross ML. Bovine milk: a unique source of immunomodulatory ingredients for functional foods. In: Buttriss J, Saltmarsh M, editors. Functional Foods II –Claims and Evidence. Cambridge, England: Royal Society of Chemistry Press; 2000. p. 82-90.

331. Marshall K. Therapeutic applications of whey protein. Altern Med Rev. 2004;9(2):136-56.

Page | 331

332. Mignone LE, Wu T, Horowitz M, Rayner CK. Whey protein: The "whey" forward for treatment of type 2 diabetes? World J Diabetes. 2015;6(14):1274-84.

333. Pal S, Radavelli-Bagatini S. The effects of whey protein on cardiometabolic risk factors. Obes Rev. 2013;14(4):324-43.

334. Walzem RL, Dillard CJ, German JB. Whey components: millennia of evolution create functionalities for mammalian nutrition: what we know and what we may be overlooking. Crit Rev Food Sci Nutr. 2002;42(4):353-75.

335. Etzel MR. Manufacture and use of dairy protein fractions. J Nutr. 2004;134(4):996S-1002S.

336. Krissansen GW. Emerging health properties of whey proteins and their clinical implications. J Am Coll Nutr. 2007;26(6):713S-23S.

337. Mortensen LS, Holmer-Jensen J, Hartvigsen ML, Jensen VK, Astrup A, de Vrese M, et al. Effects of different fractions of whey protein on postprandial lipid and hormone responses in type 2 diabetes. Eur J Clin Nutr. 2012;66(7):799-805.

338. Walrand S, Gryson C, Salles J, Giraudet C, Migne C, Bonhomme C, et al. Fast-digestive protein supplement for ten days overcomes muscle anabolic resistance in healthy elderly men. Clin Nutr. 2016;35(3):660-8.

339. Luiking YC, Deutz NE, Memelink RG, Verlaan S, Wolfe RR. Postprandial muscle protein synthesis is higher after a high whey protein, leucine-enriched supplement than after a dairy-like product in healthy older people: a randomized controlled trial. Nutr J. 2014;13:9.

340. Devries MC, Phillips SM. Supplemental protein in support of muscle mass and health: advantage whey. J Food Sci. 2015;80(Suppl 1).

341. Ma J, Jesudason DR, Stevens JE, Keogh JB, Jones KL, Clifton PM, et al. Sustained effects of a protein 'preload' on glycaemia and gastric emptying over 4 weeks in patients with type 2 diabetes: A randomized clinical trial. Diabetes Res Clin Pract. 2015;108(2).

342. Ma J, Stevens JE, Cukier K, Maddox AF, Wishart JM, Jones KL, et al. Effects of a protein preload on gastric emptying, glycemia, and gut hormones after a carbohydrate meal in diet-controlled type 2 diabetes. Diabetes Care. 2009;32(9):1600-2.

343. Clifton PM, Galbraith C, Coles L. Effect of a low dose whey/guar preload on glycemic control in people with type 2 diabetes--a randomised controlled trial. Nutr J. 2014;13(103):103.

344. Weigle DS, Breen PA, Matthys CC, Callahan HS, Meeuws KE, Burden VR, et al. A high-protein diet induces sustained reductions in appetite, ad libitum caloric intake, and body weight despite compensatory changes in diurnal plasma leptin and ghrelin concentrations. Am J Clin Nutr. 2005;82(1):41-8.

Page | 332

345. Leidy HJ, Carnell NS, Mattes RD, Campbell WW. Higher protein intake preserves lean mass and satiety with weight loss in pre-obese and obese women. Obesity. 2007;15(2):421-9.

346. Jakubowicz D, Froy O. Biochemical and metabolic mechanisms by which dietary whey protein may combat obesity and Type 2 diabetes. J Nutr Biochem. 2013;24(1):1-5.

347. Tappy L, Jequier E, Acheson K. Thermic effect of infused amino acids in healthy humans and in subjects with insulin resistance. Am J Clin Nutr. 1993;57(6):912-6.

348. Monteyne A, Martin A, Jackson L, Corrigan N, Stringer E, Newey J, et al. Whey protein consumption after resistance exercise reduces energy intake at a post-exercise meal. Eur J Nutr. 2016;10.1007/s00394-016-1344-4.

349. Burd NA, Yang Y, Moore DR, Tang JE, Tarnopolsky MA, Phillips SM. Greater stimulation of myofibrillar protein synthesis with ingestion of whey protein isolate v. micellar casein at rest and after resistance exercise in elderly men. Br J Nutr. 2012;108(6):958-62.

350. Bendtsen LQ, Lorenzen JK, Bendsen NT, Rasmussen C, Astrup A. Effect of dairy proteins on appetite, energy expenditure, body weight, and composition: a review of the evidence from controlled clinical trials. Adv Nutr. 2013;4(4):418-38.

351. Pal S, Ellis V, Dhaliwal S. Effects of whey protein isolate on body composition, lipids, insulin and glucose in overweight and obese individuals. Br J Nutr. 2010;104(5):716-23.

352. Coker RH, Miller S, Schutzler S, Deutz N, Wolfe RR. Whey protein and essential amino acids promote the reduction of adipose tissue and increased muscle protein synthesis during caloric restriction-induced weight loss in elderly, obese individuals. Nutr J. 2012;11:105.

353. Baer DJ, Stote KS, Paul DR, Harris GK, Rumpler WV, Clevidence BA. Whey protein but not soy protein supplementation alters body weight and composition in free-living overweight and obese adults. J Nutr. 2011;141(8):1489-94.

354. Claessens M, van Baak MA, Monsheimer S, Saris WH. The effect of a low-fat, high-protein or high-carbohydrate ad libitum diet on weight loss maintenance and metabolic risk factors. Int J Obes. 2009;33(3):296-304.

355. Tahavorgar A, Vafa M, Shidfar F, Gohari M, Heydari I. Whey protein preloads are more beneficial than soy protein preloads in regulating appetite, calorie intake, anthropometry, and body composition of overweight and obese men. Nutr Res. 2014;34(10):856-61.

356. Pal S, Ellis V. The acute effects of four protein meals on insulin, glucose, appetite and energy intake in lean men. Br J Nutr. 2010;104(8):1241-8.

Page | 333

357. Cummings DE. Ghrelin and the short- and long-term regulation of appetite and body weight. Physiol Behav. 2006;89(1):71-84.

358. Mellinkoff SM, Frankland M, Boyle D, Greipel M. Relationship between serum amino acid concentration and fluctuations in appetite. J Appl Physiol. 1956;8(5):535-8.

359. Bowen J, Noakes M, Trenerry C, Clifton PM. Energy intake, ghrelin, and cholecystokinin after different carbohydrate and protein preloads in overweight men. J Clin Endocrinol Metab. 2006;91(4):1477-83.

360. Bowen J, Noakes M, Clifton PM. Appetite regulatory hormone responses to various dietary proteins differ by body mass index status despite similar reductions in ad libitum energy intake. J Clin Endocrinol Metab. 2006;91(8):2913-9.

361. Landi F, Calvani R, Tosato M, Martone AM, Ortolani E, Savera G, et al. Protein Intake and Muscle Health in Old Age: From Biological Plausibility to Clinical Evidence. Nutrients. 2016;8(5).

362. Wolfe RR. Regulation of muscle protein by amino acids. J Nutr. 2002;132(10):3219S-24S.

363. Phillips SM, Tang JE, Moore DR. The role of milk- and soy-based protein in support of muscle protein synthesis and muscle protein accretion in young and elderly persons. J Am Coll Nutr. 2009;28(4):343-54.

364. Pennings B, Groen B, de Lange A, Gijsen AP, Zorenc AH, Senden JM, et al. Amino acid absorption and subsequent muscle protein accretion following graded intakes of whey protein in elderly men. Am J Physiol Endocrinol Metab. 2012;302(8):992-9.

365. Floyd JC, Jr., Fajans SS, Pek S, Thiffault CA, Knopf RF, Conn JW. Synergistic effect of certain amino acid pairs upon insulin secretion in man. Diabetes. 1970;19(2):102-8.

366. Manders RJ, Koopman R, Sluijsmans WE, van den Berg R, Verbeek K, Saris WH, et al. Co-ingestion of a protein hydrolysate with or without additional leucine effectively reduces postprandial blood glucose excursions in Type 2 diabetic men. J Nutr. 2006;136(5):1294-9.

367. Churchward-Venne TA, Burd NA, Phillips SM. Nutritional regulation of muscle protein synthesis with resistance exercise: strategies to enhance anabolism. Nutr Metab. 2012;9(40).

368. Drummond MJ, Rasmussen BB. Leucine-enriched nutrients and the regulation of mammalian target of rapamycin signalling and human skeletal muscle protein synthesis. Curr Opin Clin Nutr Metab Care. 2008;11(3):222-6.

369. Norton LE, Wilson GJ, Layman DK, Moulton CJ, Garlick PJ. Leucine content of dietary proteins is a determinant of postprandial skeletal muscle protein synthesis in adult rats. Nutr Metab. 2012;9(1):67.

Page | 334

370. Daly RM. Dietary Protein, Exercise and Skeletal Muscle: Is There a Synergistic Effect in Older Adults and the Elderly? In: Weaver CM, Daly RM, Bischoff-Ferrari HA, editors. Nutritional Influences on Bone Health: 9th International Symposium;10.1007/978-3-319-32417-3_6: Springer International Publishing; 2016. p. 63-75.

371. Zhu K, Kerr DA, Meng X, Devine A, Solah V, Binns CW, et al. Two-Year Whey Protein Supplementation Did Not Enhance Muscle Mass and Physical Function in Well-Nourished Healthy Older Postmenopausal Women. J Nutr. 2015;145(11):2520-6.

372. Pal S, Radavelli-Bagatini S, Hagger M, Ellis V. Comparative effects of whey and casein proteins on satiety in overweight and obese individuals: a randomized controlled trial. Eur J Clin Nutr. 2014;68(9):980-6.

373. Bosse JD, Dixon BM. Dietary protein to maximize resistance training: a review and examination of protein spread and change theories. J Int Soc Sports Nutr. 2012;9(1):42.

374. Morley JE, Argiles JM, Evans WJ, Bhasin S, Cella D, Deutz NE, et al. Nutritional recommendations for the management of sarcopenia. J Am Med Dir Assoc. 2010;11(6):391-6.

375. Arnal MA, Mosoni L, Boirie Y, Houlier ML, Morin L, Verdier E, et al. Protein pulse feeding improves protein retention in elderly women. Am J Clin Nutr. 1999;69(6):1202-8.

376. Rizzoli R, Stevenson JC, Bauer JM, van Loon LJ, Walrand S, Kanis JA, et al. The role of dietary protein and vitamin D in maintaining musculoskeletal health in postmenopausal women: a consensus statement from the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO). Maturitas. 2014;79(1):122-32.

377. Chale A, Cloutier GJ, Hau C, Phillips EM, Dallal GE, Fielding RA. Efficacy of whey protein supplementation on resistance exercise-induced changes in lean mass, muscle strength, and physical function in mobility-limited older adults. J Gerontol A Biol Sci Med Sci. 2013;68(6):682-90.

378. Mortensen LS, Hartvigsen ML, Brader LJ, Astrup A, Schrezenmeir J, Holst JJ, et al. Differential effects of protein quality on postprandial lipemia in response to a fat-rich meal in type 2 diabetes: comparison of whey, casein, gluten, and cod protein. Am J Clin Nutr. 2009;90(1):41-8.

379. Jakubowicz D, Froy O, Ahren B, Boaz M, Landau Z, Bar-Dayan Y, et al. Incretin, insulinotropic and glucose-lowering effects of whey protein pre-load in type 2 diabetes: a randomised clinical trial. Diabetologia. 2014;57(9):1807-11.

380. Adams RL, Broughton KS. Insulinotropic Effects of Whey: Mechanisms of Action, Recent Clinical Trials, and Clinical Applications. Ann Nutr Metab. 2016;69(1):56-63.

Page | 335

381. Gonlachanvit S, Hsu CW, Boden GH, Knight LC, Maurer AH, Fisher RS, et al. Effect of altering gastric emptying on postprandial plasma glucose concentrations following a physiologic meal in type-II diabetic patients. Dig Dis Sci. 2003;48(3):488-97.

382. Hayes M, Stanton C, Fitzgerald GF, Ross RP. Putting microbes to work: dairy fermentation, cell factories and bioactive peptides. Part II: bioactive peptide functions. Biotechnol J. 2007;2(4):435-49.

383. Kerasioti E, Stagos D, Georgatzi V, Bregou E, Priftis A, Kafantaris I, et al. Antioxidant Effects of Sheep Whey Protein on Endothelial Cells. Oxid Med Cell Longev. 2016;2016.

384. Pal S, Ellis V. The chronic effects of whey proteins on blood pressure, vascular function, and inflammatory markers in overweight individuals. Obesity. 2010;18(7):1354-9.

385. Pal S, Ellis V. Acute effects of whey protein isolate on blood pressure, vascular function and inflammatory markers in overweight postmenopausal women. Br J Nutr. 2011;105(10):1512-9.

386. Sugawara K, Takahashi H, Kashiwagura T, Yamada K, Yanagida S, Homma M, et al. Effect of anti-inflammatory supplementation with whey peptide and exercise therapy in patients with COPD. Respir Med. 2012;106(11):1526-34.

387. Yamaguchi M, Uchida M. Alpha-lactalbumin suppresses interleukin-6 release after intestinal ischemia/reperfusion via nitric oxide in rats. Inflammopharmacology. 2007;15(1):43-7.

388. Holmer-Jensen J, Karhu T, Mortensen LS, Pedersen SB, Herzig KH, Hermansen K. Differential effects of dietary protein sources on postprandial low-grade inflammation after a single high fat meal in obese non-diabetic subjects. Nutr J. 2011;10:115.

389. Perrone F, da-Silva-Filho AC, Adorno IF, Anabuki NT, Leal FS, Colombo T, et al. Effects of preoperative feeding with a whey protein plus carbohydrate drink on the acute phase response and insulin resistance. A randomized trial. Nutr J. 2011;10:66.

390. Petyaev IM, Dovgalevsky PY, Klochkov VA, Chalyk NE, Kyle N. Whey protein lycosome formulation improves vascular functions and plasma lipids with reduction of markers of inflammation and oxidative stress in prehypertension. Scientific World Journal. 2012;2012.

391. Herder C, Peltonen M, Koenig W, Kraft I, Muller-Scholze S, Martin S, et al. Systemic immune mediators and lifestyle changes in the prevention of type 2 diabetes: results from the Finnish Diabetes Prevention Study. Diabetes. 2006;55(8):2340-6.

392. de Aguilar-Nascimento JE, Prado Silveira BR, Dock-Nascimento DB. Early enteral nutrition with whey protein or casein in elderly patients with acute ischemic stroke: a double-blind randomized trial. Nutrition. 2011;27(4):440-4.

Page | 336

393. Duff WR, Chilibeck PD, Rooke JJ, Kaviani M, Krentz JR, Haines DM. The effect of bovine colostrum supplementation in older adults during resistance training. Int J Sport Nutr Exerc Metab. 2014;24(3):276-85.

394. Laviolette L, Lands LC, Dauletbaev N, Saey D, Milot J, Provencher S, et al. Combined effect of dietary supplementation with pressurized whey and exercise training in chronic obstructive pulmonary disease: a randomized, controlled, double-blind pilot study. J Med Food. 2010;13(3):589-98.

395. Lee YM, Skurk T, Hennig M, Hauner H. Effect of a milk drink supplemented with whey peptides on blood pressure in patients with mild hypertension. Eur J Nutr. 2007;46(1):21-7.

396. Gouni-Berthold I, Schulte DM, Krone W, Lapointe JF, Lemieux P, Predel HG, et al. The whey fermentation product malleable protein matrix decreases TAG concentrations in patients with the metabolic syndrome: a randomised placebo-controlled trial. Br J Nutr. 2012;107(11):1694-706.

397. Ticinesi A, Meschi T, Lauretani F, Felis G, Franchi F, Pedrolli C, et al. Nutrition and Inflammation in Older Individuals: Focus on Vitamin D, n-3 Polyunsaturated Fatty Acids and Whey Proteins. Nutrients. 2016;8(4):186.

398. Vinagre I, Sanchez-Quesada JL, Sanchez-Hernandez J, Santos D, Ordonez-Llanos J, De Leiva A, et al. Inflammatory biomarkers in type 2 diabetic patients: effect of glycemic control and impact of LDL subfraction phenotype. Cardiovasc Diabetol. 2014;13(34):34.

399. Kawase M, Hashimoto H, Hosoda M, Morita H, Hosono A. Effect of administration of fermented milk containing whey protein concentrate to rats and healthy men on serum lipids and blood pressure. J Dairy Sci. 2000;83(2):255-63.

400. Wu X, Tolvanen JP, Hutri-Kahonen N, Kahonen M, Makynen H, Korpela R, et al. Comparison of the effects of supplementation with whey mineral and potassium on arterial tone in experimental hypertension. Cardiovasc Res. 1998;40(2):364-74.

401. Ballard KD, Bruno RS, Seip RL, Quann EE, Volk BM, Freidenreich DJ, et al. Acute ingestion of a novel whey-derived peptide improves vascular endothelial responses in healthy individuals: a randomized, placebo controlled trial. Nutr J. 2009;8:34.

402. Ballard KD, Kupchak BR, Volk BM, Mah E, Shkreta A, Liptak C, et al. Acute effects of ingestion of a novel whey-derived extract on vascular endothelial function in overweight, middle-aged men and women. Br J Nutr. 2013;109(5):882-93.

403. Graf S, Egert S, Heer M. Effects of whey protein supplements on metabolism: evidence from human intervention studies. Curr Opin Clin Nutr Metab Care. 2011;14(6):569-80.

Page | 337

404. Ricci-Cabello I, Herrera MO, Artacho R. Possible role of milk-derived bioactive peptides in the treatment and prevention of metabolic syndrome. Nutr Rev. 2012;70(4):241-55.

405. McGregor RA, Poppitt SD. Milk protein for improved metabolic health: a review of the evidence. Nutr Metab. 2013;10(1):46.

406. Fluegel SM, Shultz TD, Powers JR, Clark S, Barbosa-Leiker C, Wright BR, et al. Whey beverages decrease blood pressure in prehypertensive and hypertensive young men and women. Int Dairy J. 2010;20(11):753-60.

407. Karpe F. Postprandial lipoprotein metabolism and atherosclerosis. J Intern Med. 1999;246(4):341-55.

408. Holick MF. Vitamin D deficiency. N Engl J Med. 2007;357(3):266-81. 409. Borel P, Caillaud D, Cano NJ. Vitamin D bioavailability: state of the art. Crit

Rev Food Sci Nutr. 2015;55(9):1193-205. 410. Holick MF. McCollum Award Lecture, 1994: vitamin D--new horizons for the

21st century. Am J Clin Nutr. 1994;60(4):619-30. 411. Shearer MJ. The roles of vitamins D and K in bone health and osteoporosis

prevention. Proc Nutr Soc. 1997;56(3):915-37. 412. Harris SS, Dawson-Hughes B. Plasma vitamin D and 25OHD responses of

young and old men to supplementation with vitamin D3. J Am Coll Nutr. 2002;21(4):357-62.

413. Harris SS, Dawson-Hughes B, Perrone GA. Plasma 25-hydroxyvitamin D responses of younger and older men to three weeks of supplementation with 1800 IU/day of vitamin D. J Am Coll Nutr. 1999;18(5):470-4.

414. Christakos S, Ajibade DV, Dhawan P, Fechner AJ, Mady LJ. Vitamin D: metabolism. Endocrinol Metab Clin North Am. 2010;39(2):243-53.

415. Bikle DD. Vitamin D metabolism, mechanism of action, and clinical applications. Chem Biol. 2014;21(3):319-29.

416. Working Group of the Australian and New Zealand Bone and Mineral Society; Endocrine Society of Australia; Osteoporosis Australia. Vitamin D and adult bone health in Australia and New Zealand: a position statement. Med J Aust. 2005;182(6):281-5.

417. Ross AC, Manson JE, Abrams SA, Aloia JF, Brannon PM, Clinton SK, et al. The 2011 report on dietary reference intakes for calcium and vitamin D from the Institute of Medicine: what clinicians need to know. J Clin Endocrinol Metab. 2011;96(1):53-8.

418. Dawson-Hughes B, Mithal A, Bonjour JP, Boonen S, Burckhardt P, Fuleihan GE, et al. IOF position statement: vitamin D recommendations for older adults. Osteoporos Int. 2010;21(7):1151-4.

419. Holick MF, Binkley NC, Bischoff-Ferrari HA, Gordon CM, Hanley DA, Heaney RP, et al. Evaluation, treatment, and prevention of vitamin D

Page | 338

deficiency: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2011;96(7):1911-30.

420. Rosen CJ, Abrams SA, Aloia JF, Brannon PM, Clinton SK, Durazo-Arvizu RA, et al. IOM committee members respond to Endocrine Society vitamin D guideline. J Clin Endocrinol Metab. 2012;97(4):1146-52.

421. Van Belle TL, Gysemans C, Mathieu C. Vitamin D and diabetes: the odd couple. Trends Endocrinol Metab. 2013;24(11):561-8.

422. Wolden-Kirk H, Overbergh L, Christesen HT, Brusgaard K, Mathieu C. Vitamin D and diabetes: its importance for beta cell and immune function. Mol Cell Endocrinol. 2011;347(1-2):106-20.

423. Bland R, Markovic D, Hills CE, Hughes SV, Chan SL, Squires PE, et al. Expression of 25-hydroxyvitamin D3-1alpha-hydroxylase in pancreatic islets. J Steroid Biochem Mol Biol. 2004;89-90(1-5):121-5.

424. Baeke F, Takiishi T, Korf H, Gysemans C, Mathieu C. Vitamin D: modulator of the immune system. Curr Opin Pharmacol. 2010;10(4):482-96.

425. Pittas AG, Harris SS, Stark PC, Dawson-Hughes B. The effects of calcium and vitamin D supplementation on blood glucose and markers of inflammation in nondiabetic adults. Diabetes Care. 2007;30(4):980-6.

426. Ford ES, Ajani UA, McGuire LC, Liu S. Concentrations of serum vitamin D and the metabolic syndrome among U.S. adults. Diabetes Care. 2005;28(5):1228-30.

427. Scragg R, Sowers M, Bell C, Third National H, Nutrition Examination S. Serum 25-hydroxyvitamin D, diabetes, and ethnicity in the Third National Health and Nutrition Examination Survey. Diabetes Care. 2004;27(12):2813-8.

428. Kayaniyil S, Vieth R, Retnakaran R, Knight JA, Qi Y, Gerstein HC, et al. Association of vitamin D with insulin resistance and beta-cell dysfunction in subjects at risk for type 2 diabetes. Diabetes Care. 2010;33(6):1379-81.

429. Jorde R, Figenschau Y. Supplementation with cholecalciferol does not improve glycaemic control in diabetic subjects with normal serum 25-hydroxyvitamin D levels. Eur J Nutr. 2009;48(6):349-54.

430. Witham MD, Dove FJ, Dryburgh M, Sugden JA, Morris AD, Struthers AD. The effect of different doses of vitamin D(3) on markers of vascular health in patients with type 2 diabetes: a randomised controlled trial. Diabetologia. 2010;53(10):2112-9.

431. Sugden JA, Davies JI, Witham MD, Morris AD, Struthers AD. Vitamin D improves endothelial function in patients with Type 2 diabetes mellitus and low vitamin D levels. Diabet Med. 2008;25(3):320-5.

432. Elkassaby S, Harrison LC, Mazzitelli N, Wentworth JM, Colman PG, Spelman T, et al. A randomised controlled trial of high dose vitamin D in recent-onset type 2 diabetes. Diabetes Res Clin Pract. 2014;106(3):576-82.

Page | 339

433. Grubler MR, Gaksch M, Kienreich K, Verheyen N, Schmid J, B OH, et al. Effects of vitamin D supplementation on glycated haemoglobin and fasting glucose levels in hypertensive patients: a randomized controlled trial. Diabetes Obes Metab. 2016;18(10):1006-12.

434. Krul-Poel YH, Ter Wee MM, Lips P, Simsek S. MANAGEMENT OF ENDOCRINE DISEASE: The effect of vitamin D supplementation on glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis. Eur J Endocrinol. 2017;176(1).

435. Haroon N, Anton A, John J, Mittal M. Effect of vitamin D supplementation on glycemic control in patients with type 2 diabetes: a systematic review of interventional studies. J Diabetes Metab Disord. 2015;14:3.

436. Nasri H, Behradmanesh S, Ahmadi A, Rafieian-Kopaei M. Impact of oral vitamin D (cholecalciferol) replacement therapy on blood pressure in type 2 diabetes patients; a randomized, double-blind, placebo controlled clinical trial. J Nephropathol. 2014;3(1):29-33.

437. Jehle S, Lardi A, Felix B, Hulter HN, Stettler C, Krapf R. Effect of large doses of parenteral vitamin D on glycaemic control and calcium/phosphate metabolism in patients with stable type 2 diabetes mellitus: a randomised, placebo-controlled, prospective pilot study. Swiss Med Wkly. 2014;144.

438. Wagner H, Alvarsson M, Mannheimer B, Degerblad M, Ostenson CG. No Effect of High-Dose Vitamin D Treatment on beta-Cell Function, Insulin Sensitivity, or Glucose Homeostasis in Subjects With Abnormal Glucose Tolerance: A Randomized Clinical Trial. Diabetes Care. 2016;39(3):345-52.

439. Kavaric S, Vuksanovic M, Bozovic D, Jovanovic M, Jeremic V, Radojicic Z, et al. Body weight and waist circumference as predictors of vitamin D deficiency in patients with type 2 diabetes and cardiovascular disease. Vojnosanit Pregl. 2013;70(2):163-9.

440. Vitezova A, Muka T, Zillikens MC, Voortman T, Uitterlinden AG, Hofman A, et al. Vitamin D and body composition in the elderly. Clin Nutr. 2017;36(2):585-92.

441. Fornari R, Francomano D, Greco EA, Marocco C, Lubrano C, Wannenes F, et al. Lean mass in obese adult subjects correlates with higher levels of vitamin D, insulin sensitivity and lower inflammation. J Endocrinol Invest. 2015;38(3):367-72.

442. Visser M, Deeg DJ, Lips P, Longitudinal Aging Study A. Low vitamin D and high parathyroid hormone levels as determinants of loss of muscle strength and muscle mass (sarcopenia): the Longitudinal Aging Study Amsterdam. J Clin Endocrinol Metab. 2003;88(12):5766-72.

443. Pourshahidi LK. Vitamin D and obesity: current perspectives and future directions. Proc Nutr Soc. 2015;74(2):115-24.

Page | 340

444. Wood RJ. Vitamin D and adipogenesis: new molecular insights. Nutr Rev. 2008;66(1):40-6.

445. Kong J, Li YC. Molecular mechanism of 1,25-dihydroxyvitamin D3 inhibition of adipogenesis in 3T3-L1 cells. Am J Physiol Endocrinol Metab. 2006;290(5):916-24.

446. Bischoff-Ferrari HA, Borchers M, Gudat F, Durmuller U, Stahelin HB, Dick W. Vitamin D receptor expression in human muscle tissue decreases with age. J Bone Miner Res. 2004;19(2):265-9.

447. Bischoff HA, Borchers M, Gudat F, Duermueller U, Theiler R, Stahelin HB, et al. In situ detection of 1,25-dihydroxyvitamin D3 receptor in human skeletal muscle tissue. Histochem J. 2001;33(1):19-24.

448. Simpson RU, Thomas GA, Arnold AJ. Identification of 1,25-dihydroxyvitamin D3 receptors and activities in muscle. J Biol Chem. 1985;260(15):8882-91.

449. Rejnmark L. Effects of vitamin d on muscle function and performance: a review of evidence from randomized controlled trials. Ther Adv Chronic Dis. 2011;2(1):25-37.

450. Ceglia L, Harris SS. Vitamin D and its role in skeletal muscle. Calcif Tissue Int. 2013;92(2):151-62.

451. Rosenblum JL, Castro VM, Moore CE, Kaplan LM. Calcium and vitamin D supplementation is associated with decreased abdominal visceral adipose tissue in overweight and obese adults. Am J Clin Nutr. 2012;95(1):101-8.

452. Salehpour A, Hosseinpanah F, Shidfar F, Vafa M, Razaghi M, Dehghani S, et al. A 12-week double-blind randomized clinical trial of vitamin D(3) supplementation on body fat mass in healthy overweight and obese women. Nutr J. 2012;11:78.

453. Cangussu LM, Nahas-Neto J, Orsatti CL, Bueloni-Dias FN, Nahas EA. Effect of vitamin D supplementation alone on muscle function in postmenopausal women: a randomized, double-blind, placebo-controlled clinical trial. Osteoporos Int. 2015;26(10):2413-21.

454. Chandler PD, Wang L, Zhang X, Sesso HD, Moorthy MV, Obi O, et al. Effect of vitamin D supplementation alone or with calcium on adiposity measures: a systematic review and meta-analysis of randomized controlled trials. Nutr Rev. 2015;73(9):577-93.

455. Zhou J, Chen H, Wang Z, Li Y, Li M, Xiang H. Effects of vitamin D supplementation on insulin resistance in patients with type 2 diabetes mellitus. Zhonghua Yi Xue Za Zhi. 2014;94(43):3407-10.

456. Tabesh M, Azadbakht L, Faghihimani E, Tabesh M, Esmaillzadeh A. Effects of Calcium Plus Vitamin D Supplementation on Anthropometric Measurements and Blood Pressure in Vitamin D Insufficient People with Type 2 Diabetes: A Randomized Controlled Clinical Trial. J Am Coll Nutr. 2015;34(4):281-9.

Page | 341

457. Barchetta I, Del Ben M, Angelico F, Di Martino M, Fraioli A, La Torre G, et al. No effects of oral vitamin D supplementation on non-alcoholic fatty liver disease in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled trial. BMC Med. 2016;14(1):92.

458. Sadiya A, Ahmed SM, Carlsson M, Tesfa Y, George M, Ali SH, et al. Vitamin D supplementation in obese type 2 diabetes subjects in Ajman, UAE: a randomized controlled double-blinded clinical trial. Eur J Clin Nutr. 2015;69(6):707-11.

459. Hansen KE, Johnson RE, Chambers KR, Johnson MG, Lemon CC, Vo TN, et al. Treatment of Vitamin D Insufficiency in Postmenopausal Women: A Randomized Clinical Trial. JAMA Intern Med. 2015;175(10):1612-21.

460. Sadiya A, Ahmed SM, Carlsson M, Tesfa Y, George M, Ali SH, et al. Vitamin D3 supplementation and body composition in persons with obesity and type 2 diabetes in the UAE: A randomized controlled double-blinded clinical trial. Clin Nutr. 2016;35(1):77-82.

461. Mason C, Tapsoba JD, Duggan C, Imayama I, Wang CY, Korde L, et al. Effects of Vitamin D3 Supplementation on Lean Mass, Muscle Strength, and Bone Mineral Density During Weight Loss: A Double-Blind Randomized Controlled Trial. J Am Geriatr Soc. 2016;64(4):769-78.

462. Beaudart C, Buckinx F, Rabenda V, Gillain S, Cavalier E, Slomian J, et al. The effects of vitamin D on skeletal muscle strength, muscle mass, and muscle power: a systematic review and meta-analysis of randomized controlled trials. J Clin Endocrinol Metab. 2014;99(11):4336-45.

463. Dalan R, Liew H, Assam PN, Chan ES, Siddiqui FJ, Tan AW, et al. A randomised controlled trial evaluating the impact of targeted vitamin D supplementation on endothelial function in type 2 diabetes mellitus: The DIMENSION trial. Diab Vasc Dis Res. 2016;13(3):192-200.

464. Chagas CE, Borges MC, Martini LA, Rogero MM. Focus on vitamin D, inflammation and type 2 diabetes. Nutrients. 2012;4(1):52-67.

465. Ning C, Liu L, Lv G, Yang Y, Zhang Y, Yu R, et al. Lipid metabolism and inflammation modulated by Vitamin D in liver of diabetic rats. Lipids Health Dis. 2015;14:31.

466. Mora JR, Iwata M, von Andrian UH. Vitamin effects on the immune system: vitamins A and D take centre stage. Nat Rev Immunol. 2008;8(9):685-98.

467. Dinca M, Serban MC, Sahebkar A, Mikhailidis DP, Toth PP, Martin SS, et al. Does vitamin D supplementation alter plasma adipokines concentrations? A systematic review and meta-analysis of randomized controlled trials. Pharmacol Res. 2016;107:360-71.

468. Targher G, Bertolini L, Padovani R, Zenari L, Scala L, Cigolini M, et al. Serum 25-hydroxyvitamin D3 concentrations and carotid artery intima-media thickness among type 2 diabetic patients. Clin Endocrinol. 2006;65(5):593-7.

Page | 342

469. Kampmann U, Mosekilde L, Juhl C, Moller N, Christensen B, Rejnmark L, et al. Effects of 12 weeks high dose vitamin D3 treatment on insulin sensitivity, beta cell function, and metabolic markers in patients with type 2 diabetes and vitamin D insufficiency - a double-blind, randomized, placebo-controlled trial. Metabolism. 2014;63(9):1115-24.

470. Sollid ST, Hutchinson MY, Fuskevag OM, Figenschau Y, Joakimsen RM, Schirmer H, et al. No effect of high-dose vitamin D supplementation on glycemic status or cardiovascular risk factors in subjects with prediabetes. Diabetes Care. 2014;37(8):2123-31.

471. Yiu YF, Yiu KH, Siu CW, Chan YH, Li SW, Wong LY, et al. Randomized controlled trial of vitamin D supplement on endothelial function in patients with type 2 diabetes. Atherosclerosis. 2013;227(1):140-6.

472. Tabesh M, Azadbakht L, Faghihimani E, Tabesh M, Esmaillzadeh A. Calcium-vitamin D cosupplementation influences circulating inflammatory biomarkers and adipocytokines in vitamin D-insufficient diabetics: a randomized controlled clinical trial. J Clin Endocrinol Metab. 2014;99(12):2485-93.

473. Neyestani TR, Nikooyeh B, Alavi-Majd H, Shariatzadeh N, Kalayi A, Tayebinejad N, et al. Improvement of vitamin D status via daily intake of fortified yogurt drink either with or without extra calcium ameliorates systemic inflammatory biomarkers, including adipokines, in the subjects with type 2 diabetes. J Clin Endocrinol Metab. 2012;97(6):2005-11.

474. Shab-Bidar S, Neyestani TR, Djazayery A, Eshraghian MR, Houshiarrad A, Kalayi A, et al. Improvement of vitamin D status resulted in amelioration of biomarkers of systemic inflammation in the subjects with type 2 diabetes. Diabetes Metab Res Rev. 2012;28(5):424-30.

475. Pilz S, Marz W, Wellnitz B, Seelhorst U, Fahrleitner-Pammer A, Dimai HP, et al. Association of vitamin D deficiency with heart failure and sudden cardiac death in a large cross-sectional study of patients referred for coronary angiography. J Clin Endocrinol Metab. 2008;93(10):3927-35.

476. Jorde R, Grimnes G. Vitamin D and metabolic health with special reference to the effect of vitamin D on serum lipids. Prog Lipid Res. 2011;50(4):303-12.

477. Burgaz A, Orsini N, Larsson SC, Wolk A. Blood 25-hydroxyvitamin D concentration and hypertension: a meta-analysis. J Hypertens. 2011;29(4):636-45.

478. Li YC, Kong J, Wei M, Chen ZF, Liu SQ, Cao LP. 1,25-Dihydroxyvitamin D(3) is a negative endocrine regulator of the renin-angiotensin system. J Clin Invest. 2002;110(2):229-38.

479. Liu ZM, Woo J, Wu SH, Ho SC. The role of vitamin D in blood pressure, endothelial and renal function in postmenopausal women. Nutrients. 2013;5(7):2590-610.

Page | 343

480. Boon N, Hul GB, Stegen JH, Sluijsmans WE, Valle C, Langin D, et al. An intervention study of the effects of calcium intake on faecal fat excretion, energy metabolism and adipose tissue mRNA expression of lipid-metabolism related proteins. Int J Obes. 2007;31(11):1704-12.

481. Eftekhari MH, Akbarzadeh M, Dabbaghmanesh MH, Hassanzadeh J. The effect of calcitriol on lipid profile and oxidative stress in hyperlipidemic patients with type 2 diabetes mellitus. ARYA Atheroscler. 2014;10(2):82-8.

482. Pilz S, Verheyen N, Grubler MR, Tomaschitz A, Marz W. Vitamin D and cardiovascular disease prevention. Nat Rev Cardiol. 2016;13(7):404-17.

483. Jafari T, Fallah AA, Barani A. Effects of vitamin D on serum lipid profile in patients with type 2 diabetes: A meta-analysis of randomized controlled trials. Clin Nutr. 2016;35(6):1259-68.

484. de Paula TP, Kramer CK, Viana LV, Azevedo MJ. Effects of individual micronutrients on blood pressure in patients with type 2 diabetes: a systematic review and meta-analysis of randomized clinical trials. Sci Rep. 2017;7.

485. Finger D, Goltz FR, Umpierre D, Meyer E, Rosa LH, Schneider CD. Effects of protein supplementation in older adults undergoing resistance training: a systematic review and meta-analysis. Sports Med. 2015;45(2):245-55.

486. Cermak NM, Res PT, de Groot LC, Saris WH, van Loon LJ. Protein supplementation augments the adaptive response of skeletal muscle to resistance-type exercise training: a meta-analysis. Am J Clin Nutr. 2012;96(6):1454-64.

487. Thomas DK, Quinn MA, Saunders DH, Greig CA. Protein Supplementation Does Not Significantly Augment the Effects of Resistance Exercise Training in Older Adults: A Systematic Review. J Am Med Dir Assoc. 2016;17(10):959 e1-9.

488. Godard MP, Williamson DL, Trappe SW. Oral amino-acid provision does not affect muscle strength or size gains in older men. Med Sci Sports Exerc. 2002;34(7):1126-31.

489. Kim HK, Suzuki T, Saito K, Yoshida H, Kobayashi H, Kato H, et al. Effects of exercise and amino acid supplementation on body composition and physical function in community-dwelling elderly Japanese sarcopenic women: a randomized controlled trial. J Am Geriatr Soc. 2012;60(1):16-23.

490. Trabal J, Forga M, Leyes P, Torres F, Rubio J, Prieto E, et al. Effects of free leucine supplementation and resistance training on muscle strength and functional status in older adults: a randomized controlled trial. Clin Interv Aging. 2015;10:713-23.

491. Campbell WW, Crim MC, Young VR, Evans WJ. Increased energy requirements and changes in body composition with resistance training in older adults. Am J Clin Nutr. 1994;60(2):167-75.

Page | 344

492. Iglay HB, Apolzan JW, Gerrard DE, Eash JK, Anderson JC, Campbell WW. Moderately increased protein intake predominately from egg sources does not influence whole body, regional, or muscle composition responses to resistance training in older people. J Nutr Health Aging. 2009;13(2):108-14.

493. Kukuljan S, Nowson CA, Sanders K, Daly RM. Effects of resistance exercise and fortified milk on skeletal muscle mass, muscle size, and functional performance in middle-aged and older men: an 18-mo randomized controlled trial. J Appl Physiol. 2009;107(6):1864-73.

494. Campbell WW, Kim JE, Amankwaah AF, Gordon SL, Weinheimer-Haus EM. Higher Total Protein Intake and Change in Total Protein Intake Affect Body Composition but Not Metabolic Syndrome Indexes in Middle-Aged Overweight and Obese Adults Who Perform Resistance and Aerobic Exercise for 36 Weeks. J Nutr. 2015;145(9):2076-83.

495. Bauer J, Biolo G, Cederholm T, Cesari M, Cruz-Jentoft AJ, Morley JE, et al. Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group. J Am Med Dir Assoc. 2013;14(8):542-59.

496. Esmarck B, Andersen JL, Olsen S, Richter EA, Mizuno M, Kjaer M. Timing of postexercise protein intake is important for muscle hypertrophy with resistance training in elderly humans. J Physiol. 2001;535(Pt 1):301-11.

497. Candow DG, Chilibeck PD, Facci M, Abeysekara S, Zello GA. Protein supplementation before and after resistance training in older men. Eur J Appl Physiol. 2006;97(5):548-56.

498. Cuthbertson D, Smith K, Babraj J, Leese G, Waddell T, Atherton P, et al. Anabolic signaling deficits underlie amino acid resistance of wasting, aging muscle. FASEB J. 2005;19(3):422-4.

499. Atherton PJ, Smith K. Muscle protein synthesis in response to nutrition and exercise. J Physiol. 2012;590(5):1049-57.

500. Moore DR, Robinson MJ, Fry JL, Tang JE, Glover EI, Wilkinson SB, et al. Ingested protein dose response of muscle and albumin protein synthesis after resistance exercise in young men. Am J Clin Nutr. 2009;89(1):161-8.

501. Burd NA, West DW, Moore DR, Atherton PJ, Staples AW, Prior T, et al. Enhanced amino acid sensitivity of myofibrillar protein synthesis persists for up to 24 h after resistance exercise in young men. J Nutr. 2011;141(4):568-73.

502. Kim HJ, Kang CK, Park H, Lee MG. Effects of vitamin D supplementation and circuit training on indices of obesity and insulin resistance in T2D and vitamin D deficient elderly women. J Exerc Nutrition Biochem. 2014;18(3):249-57.

503. Agergaard J, Trostrup J, Uth J, Iversen JV, Boesen A, Andersen JL, et al. Does vitamin-D intake during resistance training improve the skeletal muscle hypertrophic and strength response in young and elderly men? - a randomized controlled trial. Nutr Metab. 2015;12:32.

Page | 345

504. Janssen HC, Samson MM, Verhaar HJ. Vitamin D deficiency, muscle function, and falls in elderly people. Am J Clin Nutr. 2002;75(4):611-5.

505. Thacher TD, Clarke BL. Vitamin D insufficiency. Mayo Clin Proc. 2011;86(1):50-60.

506. Campbell WW, Crim MC, Young VR, Joseph LJ, Evans WJ. Effects of resistance training and dietary protein intake on protein metabolism in older adults. Am J Physiol. 1995;268(6 Pt 1).

507. Rosendahl E, Lindelof N, Littbrand H, Yifter-Lindgren E, Lundin-Olsson L, Haglin L, et al. High-intensity functional exercise program and protein-enriched energy supplement for older persons dependent in activities of daily living: a randomised controlled trial. Aust J Physiother. 2006;52(2):105-13.

508. Carlsson M, Littbrand H, Gustafson Y, Lundin-Olsson L, Lindelof N, Rosendahl E, et al. Effects of high-intensity exercise and protein supplement on muscle mass in ADL dependent older people with and without malnutrition: a randomized controlled trial. J Nutr Health Aging. 2011;15(7):554-60.

509. Buhl SF, Andersen AL, Andersen JR, Andersen O, Jensen JE, Rasmussen AM, et al. The effect of protein intake and resistance training on muscle mass in acutely ill old medical patients - A randomized controlled trial. Clin Nutr. 2016;35(1):59-66.

510. Arnarson A, Gudny Geirsdottir O, Ramel A, Briem K, Jonsson PV, Thorsdottir I. Effects of whey proteins and carbohydrates on the efficacy of resistance training in elderly people: double blind, randomised controlled trial. Eur J Clin Nutr. 2013;67(8):821-6.

511. Fiatarone MA, O'Neill EF, Ryan ND, Clements KM, Solares GR, Nelson ME, et al. Exercise training and nutritional supplementation for physical frailty in very elderly people. N Engl J Med. 1994;330(25):1769-75.

512. Verreijen AM, Verlaan S, Engberink MF, Swinkels S, de Vogel-van den Bosch J, Weijs PJ. A high whey protein-, leucine-, and vitamin D-enriched supplement preserves muscle mass during intentional weight loss in obese older adults: a double-blind randomized controlled trial. Am J Clin Nutr. 2015;101(2):279-86.

513. Rondanelli M, Klersy C, Terracol G, Talluri J, Maugeri R, Guido D, et al. Whey protein, amino acids, and vitamin D supplementation with physical activity increases fat-free mass and strength, functionality, and quality of life and decreases inflammation in sarcopenic elderly. Am J Clin Nutr. 2016;103(3):830-40.

514. Holm L, Olesen JL, Matsumoto K, Doi T, Mizuno M, Alsted TJ, et al. Protein-containing nutrient supplementation following strength training enhances the effect on muscle mass, strength, and bone formation in postmenopausal women. J Appl Physiol. 2008;105(1):274-81.

Page | 346

515. Bauer JM, Verlaan S, Bautmans I, Brandt K, Donini LM, Maggio M, et al. Effects of a vitamin D and leucine-enriched whey protein nutritional supplement on measures of sarcopenia in older adults, the PROVIDE study: a randomized, double-blind, placebo-controlled trial. J Am Med Dir Assoc. 2015;16(9):740-7.

516. Doherty TJ. The influence of aging and sex on skeletal muscle mass and strength. Curr Opin Clin Nutr Metab Care. 2001;4(6):503-8.

517. Deschenes MR. Effects of aging on muscle fibre type and size. Sports Med. 2004;34(12):809-24.

518. Boden G, Chen X, DeSantis RA, Kendrick Z. Effects of age and body fat on insulin resistance in healthy men. Diabetes Care. 1993;16(5):728-33.

519. Meckling KA, Sherfey R. A randomized trial of a hypocaloric high-protein diet, with and without exercise, on weight loss, fitness, and markers of the Metabolic Syndrome in overweight and obese women. Appl Physiol Nutr Metab. 2007;32(4):743-52.

520. Arciero PJ, Baur D, Connelly S, Ormsbee MJ. Timed-daily ingestion of whey protein and exercise training reduces visceral adipose tissue mass and improves insulin resistance: the PRISE study. J Appl Physiol. 2014;117(1):1-10.

521. Iglay HB, Thyfault JP, Apolzan JW, Campbell WW. Resistance training and dietary protein: effects on glucose tolerance and contents of skeletal muscle insulin signaling proteins in older persons. Am J Clin Nutr. 2007;85(4):1005-13.

522. Fekete AA, Giromini C, Chatzidiakou Y, Givens DI, Lovegrove JA. Whey protein lowers blood pressure and improves endothelial function and lipid biomarkers in adults with prehypertension and mild hypertension: results from the chronic Whey2Go randomized controlled trial. Am J Clin Nutr. 2016;104(6):1534-44.

523. Garcia-Unciti M, Izquierdo M, Idoate F, Gorostiaga E, Grijalba A, Ortega-Delgado F, et al. Weight-Loss Diet Alone or Combined with Progressive Resistance Training Induces Changes in Association between the Cardiometabolic Risk Profile and Abdominal Fat Depots. Ann Nutr Metab. 2012;61(4):296-304.

524. Maltais ML, Perreault K, Courchesne-Loyer A, Lagace JC, Barsalani R, Dionne IJ. Effect of Resistance Training and Various Sources of Protein Supplementation on Body Fat Mass and Metabolic Profile in Sarcopenic Overweight Older Adult Men: A Pilot Study. Int J Sport Nutr Exerc Metab. 2016;26(1):71-7.

525. Jung UJ, Choi MS. Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. Int J Mol Sci. 2014;15(4):6184-223.

Page | 347

526. Kadoglou NP, Iliadis F, Angelopoulou N, Perrea D, Ampatzidis G, Liapis CD, et al. The anti-inflammatory effects of exercise training in patients with type 2 diabetes mellitus. Eur J Cardiovasc Prev Rehabil. 2007;14(6):837-43.

527. Abizanda P, Lopez MD, Garcia VP, Estrella Jde D, da Silva Gonzalez A, Vilardell NB, et al. Effects of an Oral Nutritional Supplementation Plus Physical Exercise Intervention on the Physical Function, Nutritional Status, and Quality of Life in Frail Institutionalized Older Adults: The ACTIVNES Study. J Am Med Dir Assoc. 2015;16(5).

528. Chatterjee S, Khunti K, Davies MJ. Type 2 diabetes. Lancet. 2017;10.1016/S0140-6736(17)30058-2.

529. Esser N, Legrand-Poels S, Piette J, Scheen AJ, Paquot N. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes. Diabetes Res Clin Pract. 2014;105(2):141-50.

530. Cesari M, Penninx BW, Pahor M, Lauretani F, Corsi AM, Rhys Williams G, et al. Inflammatory markers and physical performance in older persons: the InCHIANTI study. J Gerontol A Biol Sci Med Sci. 2004;59(3):242-8.

531. Kolb H, Mandrup-Poulsen T. The global diabetes epidemic as a consequence of lifestyle-induced low-grade inflammation. Diabetologia. 2010;53(1):10-20.

532. Van Gaal LF, Mertens IL, De Block CE. Mechanisms linking obesity with cardiovascular disease. Nature. 2006;444(7121):875-80.

533. Lee SY, Chang HJ, Sung J, Kim KJ, Shin S, Cho IJ, et al. The impact of obesity on subclinical coronary atherosclerosis according to the risk of cardiovascular disease. Obesity. 2014;22(7):1762-8.

534. Nicklas BJ, Ambrosius W, Messier SP, Miller GD, Penninx BW, Loeser RF, et al. Diet-induced weight loss, exercise, and chronic inflammation in older, obese adults: a randomized controlled clinical trial. Am J Clin Nutr. 2004;79(4):544-51.

535. Ho TP, Zhao X, Courville AB, Linderman JD, Smith S, Sebring N, et al. Effects of a 12-month moderate weight loss intervention on insulin sensitivity and inflammation status in nondiabetic overweight and obese subjects. Horm Metab Res. 2015;47(4):289-96.

536. Strasser B, Berger K, Fuchs D. Effects of a caloric restriction weight loss diet on tryptophan metabolism and inflammatory biomarkers in overweight adults. Eur J Nutr. 2015;54(1):101-7.

537. van Gemert WA, May AM, Schuit AJ, Oosterhof BY, Peeters PH, Monninkhof EM. Effect of Weight Loss with or without Exercise on Inflammatory Markers and Adipokines in Postmenopausal Women: The SHAPE-2 Trial, A Randomized Controlled Trial. Cancer Epidemiol Biomarkers Prev. 2016;25(5):799-806.

538. Forsythe LK, Wallace JM, Livingstone MB. Obesity and inflammation: the effects of weight loss. Nutr Res Rev. 2008;21(2):117-33.

Page | 348

539. Madsen EL, Rissanen A, Bruun JM, Skogstrand K, Tonstad S, Hougaard DM, et al. Weight loss larger than 10% is needed for general improvement of levels of circulating adiponectin and markers of inflammation in obese subjects: a 3-year weight loss study. Eur J Endocrinol. 2008;158(2):179-87.

540. Messier SP, Mihalko SL, Legault C, Miller GD, Nicklas BJ, DeVita P, et al. Effects of intensive diet and exercise on knee joint loads, inflammation, and clinical outcomes among overweight and obese adults with knee osteoarthritis: the IDEA randomized clinical trial. JAMA. 2013;310(12):1263-73.

541. Cardinal J, Pretorius CJ, Ungerer JP. Biological and diurnal variation in glucocorticoid sensitivity detected with a sensitive in vitro dexamethasone suppression of cytokine production assay. J Clin Endocrinol Metab. 2010;95(8):3657-63.

542. Bastard JP, Maachi M, Lagathu C, Kim MJ, Caron M, Vidal H, et al. Recent advances in the relationship between obesity, inflammation, and insulin resistance. Eur Cytokine Netw. 2006;17(1):4-12.

543. Chae JS, Paik JK, Kang R, Kim M, Choi Y, Lee SH, et al. Mild weight loss reduces inflammatory cytokines, leukocyte count, and oxidative stress in overweight and moderately obese participants treated for 3 years with dietary modification. Nutr Res. 2013;33(3):195-203.

544. Trussardi Fayh AP, Lopes AL, Fernandes PR, Reischak-Oliveira A, Friedman R. Impact of weight loss with or without exercise on abdominal fat and insulin resistance in obese individuals: a randomised clinical trial. Br J Nutr. 2013;110(3):486-92.

545. Samaras K, Viardot A, Lee PN, Jenkins A, Botelho NK, Bakopanos A, et al. Reduced arterial stiffness after weight loss in obese type 2 diabetes and impaired glucose tolerance: the role of immune cell activation and insulin resistance. Diab Vasc Dis Res. 2013;10(1):40-8.

546. Zhou X, Fragala MS, McElhaney JE, Kuchel GA. Conceptual and methodological issues relevant to cytokine and inflammatory marker measurements in clinical research. Curr Opin Clin Nutr Metab Care. 2010;13(5):541-7.

547. Reed JL, De Souza MJ, Williams NI. Effects of exercise combined with caloric restriction on inflammatory cytokines. Appl Physiol Nutr Metab. 2010;35(5):573-82.

548. Christiansen T, Paulsen SK, Bruun JM, Pedersen SB, Richelsen B. Exercise training versus diet-induced weight-loss on metabolic risk factors and inflammatory markers in obese subjects: a 12-week randomized intervention study. Am J Physiol Endocrinol Metab. 2010;298(4):824-31.

549. Imayama I, Ulrich CM, Alfano CM, Wang C, Xiao L, Wener MH, et al. Effects of a caloric restriction weight loss diet and exercise on inflammatory

Page | 349

biomarkers in overweight/obese postmenopausal women: a randomized controlled trial. Cancer Res. 2012;72(9):2314-26.

550. Borruel S, Molto JF, Alpanes M, Fernandez-Duran E, Alvarez-Blasco F, Luque-Ramirez M, et al. Surrogate markers of visceral adiposity in young adults: waist circumference and body mass index are more accurate than waist hip ratio, model of adipose distribution and visceral adiposity index. PLoS One. 2014;9(12).

551. Klein S, Allison DB, Heymsfield SB, Kelley DE, Leibel RL, Nonas C, et al. Waist Circumference and Cardiometabolic Risk: a Consensus Statement from Shaping America's Health: Association for Weight Management and Obesity Prevention; NAASO, the Obesity Society; the American Society for Nutrition; and the American Diabetes Association. Obesity. 2007;15(5):1061-7.

552. Capel F, Klimcakova E, Viguerie N, Roussel B, Vitkova M, Kovacikova M, et al. Macrophages and adipocytes in human obesity: adipose tissue gene expression and insulin sensitivity during calorie restriction and weight stabilization. Diabetes. 2009;58(7):1558-67.

553. Kosteli A, Sugaru E, Haemmerle G, Martin JF, Lei J, Zechner R, et al. Weight loss and lipolysis promote a dynamic immune response in murine adipose tissue. J Clin Invest. 2010;120(10):3466-79.

554. Ribeiro F, Alves AJ, Duarte JA, Oliveira J. Is exercise training an effective therapy targeting endothelial dysfunction and vascular wall inflammation? Int J Cardiol. 2010;141(3):214-21.

555. Balducci S, Zanuso S, Nicolucci A, Fernando F, Cavallo S, Cardelli P, et al. Anti-inflammatory effect of exercise training in subjects with type 2 diabetes and the metabolic syndrome is dependent on exercise modalities and independent of weight loss. Nutr Metab Cardiovasc Dis. 2010;20(8):608-17.

556. Sixt S, Beer S, Bluher M, Korff N, Peschel T, Sonnabend M, et al. Long- but not short-term multifactorial intervention with focus on exercise training improves coronary endothelial dysfunction in diabetes mellitus type 2 and coronary artery disease. Eur Heart J. 2010;31(1):112-9.

557. de Salles BF, Simao R, Miranda F, Novaes Jda S, Lemos A, Willardson JM. Rest interval between sets in strength training. Sports Med. 2009;39(9):765-77.

558. Rohling M, Herder C, Stemper T, Mussig K. Influence of Acute and Chronic Exercise on Glucose Uptake. J Diabetes Res. 2016;2016.

559. Strasser B, Arvandi M, Siebert U. Resistance training, visceral obesity and inflammatory response: a review of the evidence. Obes Rev. 2012;13(7):578-91.

560. Hopps E, Canino B, Caimi G. Effects of exercise on inflammation markers in type 2 diabetic subjects. Acta Diabetol. 2011;48(3):183-9.

561. Wycherley TP, Brinkworth GD, Noakes M, Buckley JD, Clifton PM. Effect of caloric restriction with and without exercise training on oxidative stress and

Page | 350

endothelial function in obese subjects with type 2 diabetes. Diabetes Obes Metab. 2008;10(11):1062-73.

562. Kwon HR, Min KW, Ahn HJ, Seok HG, Lee JH, Park GS, et al. Effects of Aerobic Exercise vs. Resistance Training on Endothelial Function in Women with Type 2 Diabetes Mellitus. Diabetes Metab J. 2011;35(4):364-73.

563. Wegge JK, Roberts CK, Ngo TH, Barnard RJ. Effect of diet and exercise intervention on inflammatory and adhesion molecules in postmenopausal women on hormone replacement therapy and at risk for coronary artery disease. Metabolism. 2004;53(3):377-81.

564. Adamopoulos S, Parissis J, Kroupis C, Georgiadis M, Karatzas D, Karavolias G, et al. Physical training reduces peripheral markers of inflammation in patients with chronic heart failure. Eur Heart J. 2001;22(9):791-7.

565. Zoppini G, Targher G, Zamboni C, Venturi C, Cacciatori V, Moghetti P, et al. Effects of moderate-intensity exercise training on plasma biomarkers of inflammation and endothelial dysfunction in older patients with type 2 diabetes. Nutr Metab Cardiovasc Dis. 2006;16(8):543-9.

566. da Silva CA, Ribeiro JP, Canto JC, da Silva RE, Silva Junior GB, Botura E, et al. High-intensity aerobic training improves endothelium-dependent vasodilation in patients with metabolic syndrome and type 2 diabetes mellitus. Diabetes Res Clin Pract. 2012;95(2):237-45.

567. Cohen ND, Dunstan DW, Robinson C, Vulikh E, Zimmet PZ, Shaw JE. Improved endothelial function following a 14-month resistance exercise training program in adults with type 2 diabetes. Diabetes Res Clin Pract. 2008;79(3):405-11.

568. de Jager W, Bourcier K, Rijkers GT, Prakken BJ, Seyfert-Margolis V. Prerequisites for cytokine measurements in clinical trials with multiplex immunoassays. BMC Immunol. 2009;10(1):52.

569. Peake JM, Kukuljan S, Nowson CA, Sanders K, Daly RM. Inflammatory cytokine responses to progressive resistance training and supplementation with fortified milk in men aged 50+ years: an 18-month randomized controlled trial. Eur J Appl Physiol. 2011;111(12):3079-88.

570. Unick JL, Gaussoin S, Bahnson J, Crow R, Curtis J, Killean T, et al. Validity of Ratings of Perceived Exertion in Patients with Type 2 Diabetes. J Nov Physiother Phys Rehabil. 2014;1(1):102.

571. Gagnon C, Daly RM, Carpentier A, Lu ZX, Shore-Lorenti C, Sikaris K, et al. Effects of combined calcium and vitamin D supplementation on insulin secretion, insulin sensitivity and beta-cell function in multi-ethnic vitamin D-deficient adults at risk for type 2 diabetes: a pilot randomized, placebo-controlled trial. PLoS One. 2014;9(10).

Page | 351

572. Andersen LL, Tufekovic G, Zebis MK, Crameri RM, Verlaan G, Kjaer M, et al. The effect of resistance training combined with timed ingestion of protein on muscle fiber size and muscle strength. Metabolism. 2005;54(2):151-6.

573. GE Healthcare: Lunar enCORE-based X-ray Bone Densitometer User Manual. Madison W, USA; 2010

574. Eser P, Hill B, Ducher G, Bass S. Skeletal benefits after long-term retirement in former elite female gymnasts. J Bone Miner Res. 2009;24(12):1981-8.

575. Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998;21(12):2191-2.

576. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003;83(3):237-52.

577. Miller JP, Pratley RE, Goldberg AP, Gordon P, Rubin M, Treuth MS, et al. Strength training increases insulin action in healthy 50- to 65-yr-old men. J Appl Physiol. 1994;77(3):1122-7.

578. Treuth MS, Ryan AS, Pratley RE, Rubin MA, Miller JP, Nicklas BJ, et al. Effects of strength training on total and regional body composition in older men. J Appl Physiol. 1994;77(2):614-20.

579. Wathen D. Load assignment. In: Baechle TR, editor. Essentials of Strength Training and Conditioning. Ilinois: Champaign; 1994.

580. Knutzen KM, Brilla LR, Caine D. Validity of 1RM prediction equations for older adults. J Strength Cond Res. 1999;13(3):242-6.

581. Frankenfield DC, Rowe WA, Smith JS, Cooney RN. Validation of several established equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc. 2003;103(9):1152-9.

582. EFSA Panel on Dietetic Products NaAN. Scientific Opinion on Dietary Reference Values for energy. EFSA Journal 2013;11(1):3005.

583. Black AE. Critical evaluation of energy intake using the Goldberg cut-off for energy intake : basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord. 2000;24(9):1119-30.

584. Ferrari P, Slimani N, Ciampi A, Trichopoulou A, Naska A, Lauria C, et al. Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2002;5(6B):1329-45.

585. McGowan MJ, Harrington KE, Kiely M, Robson PJ, Livingstone MB, Gibney MJ. An evaluation of energy intakes and the ratio of energy intake to estimated basal metabolic rate (EI/BMRest) in the North/South Ireland Food Consumption Survey. Public Health Nutr. 2001;4(5A):1043-50.

586. Leclercq C, Arcella D, Piccinelli R, Sette S, Le Donne C, Turrini A, et al. The Italian National Food Consumption Survey INRAN-SCAI 2005-06: main

Page | 352

results in terms of food consumption. Public Health Nutr. 2009;12(12):2504-32.

587. Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C. Under-reporting of alcohol consumption in household surveys: a comparison of quantity-frequency, graduated-frequency and recent recall. Addiction. 2004;99(8):1024-33.

588. Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001;33(7):1126-41.

589. National Institute of Ageing. Clinical Research Study Investigator's Toolbox. Advere Events [Internet]. U.S. Department of Health & Human Services; 2016 [updated 21 Nov 2016; cited 2017 14 May]. Available from: https://www.nia.nih.gov/research/dgcg/clinical-research-study-investigators-toolbox/adverse-events.

590. Kelly J, Edney K, Moran C, Srikanth V, Callisaya M. Gender Differences in Physical Activity Levels of Older People With Type 2 Diabetes Mellitus. J Phys Act Health. 2016;13(4):409-15.

591. Qiu S-h, Sun Z-l, Cai X, Liu L, Yang B. Improving Patients' Adherence to Physical Activity in Diabetes Mellitus: A Review. Diabetes Metab J. 2012;36(1):1-5.

592. Oude Rengerink K, Opmeer BC, Logtenberg SL, Hooft L, Bloemenkamp KW, Haak MC, et al. IMproving PArticipation of patients in Clinical Trials--rationale and design of IMPACT. BMC Med Res Methodol. 2010;10(1):85.

593. Johnson EJ, Niles BL, Mori DL. Targeted recruitment of adults with type 2 diabetes for a physical activity intervention. Diabetes Spectr. 2015;28(2):99-105.

594. Caldwell PH, Hamilton S, Tan A, Craig JC. Strategies for increasing recruitment to randomised controlled trials: systematic review. PLoS Med. 2010;7(11).

595. Daly RM, Miller EG, Dunstan DW, Kerr DA, Solah V, Menzies D, et al. The effects of progressive resistance training combined with a whey-protein drink and vitamin D supplementation on glycaemic control, body composition and cardiometabolic risk factors in older adults with type 2 diabetes: study protocol for a randomized controlled trial. Trials. 2014;15:431.

596. American College of Sports Medicine. ACSM Guidelines for Exercise Testing and Prescription. Philadelphia: Lippincott Williams & Wilkins; 2000.

597. Riddell MA, Renwick C, Wolfe R, Colgan S, Dunbar J, Hagger V, et al. Cluster randomized controlled trial of a peer support program for people with diabetes: study protocol for the Australasian Peers for Progress study. BMC Public Health. 2012;12(843):843.

Page | 353

598. Mount DL, Davis C, Kennedy B, Raatz S, Dotson K, Gary-Webb TL, et al. Factors influencing enrollment of African Americans in the Look AHEAD trial. Clin Trials. 2012;9(1):80-9.

599. Church TS, Earnest CP, Skinner JS, Blair SN. Effects of different doses of physical activity on cardiorespiratory fitness among sedentary, overweight or obese postmenopausal women with elevated blood pressure: a randomized controlled trial. JAMA. 2007;297(19):2081-91.

600. Daley AJ, Crank H, Mutrie N, Saxton JM, Coleman R. Patient recruitment into a randomised controlled trial of supervised exercise therapy in sedentary women treated for breast cancer. Contemp Clin Trials. 2007;28(5):603-13.

601. Irwin ML, Cadmus L, Alvarez-Reeves M, O'Neil M, Mierzejewski E, Latka R, et al. Recruiting and retaining breast cancer survivors into a randomized controlled exercise trial: the Yale Exercise and Survivorship Study. Cancer. 2008;112(11 Suppl):2593-606.

602. Rhew I, Yasui Y, Sorensen B, Ulrich CM, Neuhouser ML, Tworoger SS, et al. Effects of an exercise intervention on other health behaviors in overweight/obese post-menopausal women. Contemp Clin Trials. 2007;28(4):472-81.

603. Rubin RR, Fujimoto WY, Marrero DG, Brenneman T, Charleston JB, Edelstein SL, et al. The Diabetes Prevention Program: recruitment methods and results. Control Clin Trials. 2002;23(2):157-71.

604. Sanders KM, Stuart AL, Merriman EN, Read ML, Kotowicz MA, Young D, et al. Trials and tribulations of recruiting 2,000 older women onto a clinical trial investigating falls and fractures: Vital D study. BMC Med Res Methodol. 2009;9:78.

605. Tate DF, LaRose JG, Griffin LP, Erickson KE, Robichaud EF, Perdue L, et al. Recruitment of young adults into a randomized controlled trial of weight gain prevention: message development, methods, and cost. Trials. 2014;15:326.

606. Lovato LC, Hill K, Hertert S, Hunninghake DB, Probstfield JL. Recruitment for controlled clinical trials: literature summary and annotated bibliography. Control Clin Trials. 1997;18(4):328-52.

607. Piantadosi C, Chapman IM, Naganathan V, Hunter P, Cameron ID, Visvanathan R. Recruiting older people at nutritional risk for clinical trials: what have we learned? BMC Res Notes. 2015;8:151.

608. Korde LA, Micheli A, Smith AW, Venzon D, Prindiville SA, Drinkard B, et al. Recruitment to a physical activity intervention study in women at increased risk of breast cancer. BMC Med Res Methodol. 2009;9:27.

609. Bjornson-Benson WM, Stibolt TB, Manske KA, Zavela KJ, Youtsey DJ, Buist AS. Monitoring recruitment effectiveness and cost in a clinical trial. Control Clin Trials. 1993;14(2 Suppl):52S-67S.

Page | 354

610. Fouad MN, Corbie-Smith G, Curb D, Howard BV, Mouton C, Simon M, et al. Special populations recruitment for the Women's Health Initiative: successes and limitations. Control Clin Trials. 2004;25(4):335-52.

611. Glendenning P, Tse-Jiun Chew G. Controversies and consensus regarding vitamin D deficiency in 2015: whom to test and whom to treat? Med J Aust. 2015;202(9):470-1.

612. Hameed UA, Manzar D, Raza S, Shareef MY, Hussain ME. Resistance Training Leads to Clinically Meaningful Improvements in Control of Glycemia and Muscular Strength in Untrained Middle-aged Patients with type 2 Diabetes Mellitus. N Am J Med Sci. 2012;4(8):336-43.

613. Candow DG, Burke NC, Smith-Palmer T, Burke DG. Effect of whey and soy protein supplementation combined with resistance training in young adults. Int J Sport Nutr Exerc Metab. 2006;16(3):233-44.

614. Hulmi JJ, Lockwood CM, Stout JR. Effect of protein/essential amino acids and resistance training on skeletal muscle hypertrophy: A case for whey protein. Nutr Metab. 2010;7:51.

615. Mitri J, Dawson-Hughes B, Hu FB, Pittas AG. Effects of vitamin D and calcium supplementation on pancreatic beta cell function, insulin sensitivity, and glycemia in adults at high risk of diabetes: the Calcium and Vitamin D for Diabetes Mellitus (CaDDM) randomized controlled trial. Am J Clin Nutr. 2011;94(2):486-94.

616. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-95.

617. Simpson KA, Mavros Y, Kay S, Meiklejohn J, de Vos N, Wang Y, et al. Graded Resistance Exercise And Type 2 Diabetes in Older adults (The GREAT2DO study): methods and baseline cohort characteristics of a randomized controlled trial. Trials. 2015;16:512.

618. Perneger TV. What's wrong with Bonferroni adjustments. BMJ. 1998;316(7139):1236-8.

619. Deutz NE, Bauer JM, Barazzoni R, Biolo G, Boirie Y, Bosy-Westphal A, et al. Protein intake and exercise for optimal muscle function with aging: recommendations from the ESPEN Expert Group. Clin Nutr. 2014;33(6):929-36.

620. Zhu K, Meng X, Kerr D, Devine A, Solah V, Binns C, et al. The effects of a two-year RCT of whey protein supplementation on bone structure, IGF-1, and urinary calcium excretion in older postmenopausal women. J Bone Miner Res. 2011;26(2298-306):2298.

621. Gunnerud UJ, Ostman EM, Bjorck IM. Effects of whey proteins on glycaemia and insulinaemia to an oral glucose load in healthy adults; a dose-response study. Eur J Clin Nutr. 2013;67(7):749-53.

Page | 355

622. Abdulla H, Smith K, Atherton PJ, Idris I. Role of insulin in the regulation of human skeletal muscle protein synthesis and breakdown: a systematic review and meta-analysis. Diabetologia. 2016;59(1):44-55.

623. Miller SL, Tipton KD, Chinkes DL, Wolf SE, Wolfe RR. Independent and combined effects of amino acids and glucose after resistance exercise. Med Sci Sports Exerc. 2003;35(3):449-55.

624. Parkhouse WS, Coupland DC, Li C, Vanderhoek KJ. IGF-1 bioavailability is increased by resistance training in older women with low bone mineral density. Mech Ageing Dev. 2000;113(2):75-83.

625. Ahtiainen JP, Hulmi JJ, Lehti M, Kraemer WJ, Nyman K, Selanne H, et al. Effects of resistance training on expression of IGF-I splice variants in younger and older men. Eur J Sport Sci. 2016;16(8):1055-63.

626. Witard OC, McGlory C, Hamilton DL, Phillips SM. Growing older with health and vitality: a nexus of physical activity, exercise and nutrition. Biogerontology. 2016;17(3):529-46.

627. Stark M, Lukaszuk J, Prawitz A, Salacinski A. Protein timing and its effects on muscular hypertrophy and strength in individuals engaged in weight-training. J Int Soc Sports Nutr. 2012;9(1):54.

628. Katsanos CS, Madura JA, 2nd, Roust LR. Essential amino acid ingestion as an efficient nutritional strategy for the preservation of muscle mass following gastric bypass surgery. Nutrition. 2016;32(1):9-13.

629. Burd NA, Tang JE, Moore DR, Phillips SM. Exercise training and protein metabolism: influences of contraction, protein intake, and sex-based differences. J Appl Physiol. 2009;106(5):1692-701.

630. Wicherts IS, van Schoor NM, Boeke AJ, Visser M, Deeg DJ, Smit J, et al. Vitamin D status predicts physical performance and its decline in older persons. J Clin Endocrinol Metab. 2007;92(6):2058-65.

631. Bischoff-Ferrari HA, Dietrich T, Orav EJ, Hu FB, Zhang Y, Karlson EW, et al. Higher 25-hydroxyvitamin D concentrations are associated with better lower-extremity function in both active and inactive persons aged > or =60 y. Am J Clin Nutr. 2004;80(3):752-8.

632. Baczynski R, Massry SG, Magott M, el-Belbessi S, Kohan R, Brautbar N. Effect of parathyroid hormone on energy metabolism of skeletal muscle. Kidney Int. 1985;28(5):722-7.

633. Maestro B, Molero S, Bajo S, Davila N, Calle C. Transcriptional activation of the human insulin receptor gene by 1,25-dihydroxyvitamin D(3). Cell Biochem Funct. 2002;20(3):227-32.

634. Chiu KC, Chu A, Go VL, Saad MF. Hypovitaminosis D is associated with insulin resistance and beta cell dysfunction. Am J Clin Nutr. 2004;79(5):820-5.

635. Halfon M, Phan O, Teta D. Vitamin D: a review on its effects on muscle strength, the risk of fall, and frailty. Biomed Res Int. 2015;2015.

Page | 356

636. Barton-Davis ER, Shoturma DI, Musaro A, Rosenthal N, Sweeney HL. Viral mediated expression of insulin-like growth factor I blocks the aging-related loss of skeletal muscle function. Proc Natl Acad Sci U S A. 1998;95(26):15603-7.

637. Salles J, Chanet A, Giraudet C, Patrac V, Pierre P, Jourdan M, et al. 1,25(OH)2-vitamin D3 enhances the stimulating effect of leucine and insulin on protein synthesis rate through Akt/PKB and mTOR mediated pathways in murine C2C12 skeletal myotubes. Mol Nutr Food Res. 2013;57(12):2137-46.

638. Kukuljan S, Nowson CA, Sanders KM, Nicholson GC, Seibel MJ, Salmon J, et al. Independent and combined effects of calcium-vitamin D3 and exercise on bone structure and strength in older men: an 18-month factorial design randomized controlled trial. J Clin Endocrinol Metab. 2011;96(4):955-63.

639. Bunout D, Barrera G, Leiva L, Gattas V, de la Maza MP, Avendano M, et al. Effects of vitamin D supplementation and exercise training on physical performance in Chilean vitamin D deficient elderly subjects. Exp Gerontol. 2006;41(8):746-52.

640. Uusi-Rasi K, Patil R, Karinkanta S, Kannus P, Tokola K, Lamberg-Allardt C, et al. Exercise and vitamin D in fall prevention among older women: a randomized clinical trial. JAMA Intern Med. 2015;175(5):703-11.

641. Bischoff-Ferrari HA. Optimal serum 25-hydroxyvitamin D levels for multiple health outcomes. Adv Exp Med Biol. 2014;810:500-25.

642. Park BS, Khamoui AV, Brown LE, Kim DY, Han KA, Min KW, et al. Effects of Elastic Band Resistance Training on Glucose Control, Body Composition, and Physical Function in Women With Short- vs. Long-Duration Type-2 Diabetes. J Strength Cond Res. 2016;30(6):1688-99.

643. Straight CR, Dorfman LR, Cottell KE, Krol JM, Lofgren IE, Delmonico MJ. Effects of resistance training and dietary changes on physical function and body composition in overweight and obese older adults. J Phys Act Health. 2012;9(6):875-83.

644. Nicklas BJ, Chmelo E, Delbono O, Carr JJ, Lyles MF, Marsh AP. Effects of resistance training with and without caloric restriction on physical function and mobility in overweight and obese older adults: a randomized controlled trial. Am J Clin Nutr. 2015;101(5):991-9.

645. Zemel MB. Proposed role of calcium and dairy food components in weight management and metabolic health. Phys Sportsmed. 2009;37(2):29-39.

646. Astbury NM, Stevenson EJ, Morris P, Taylor MA, Macdonald IA. Dose-response effect of a whey protein preload on within-day energy intake in lean subjects. Br J Nutr. 2010;104(12):1858-67.

647. Tessari P, Kiwanuka E, Cristini M, Zaramella M, Enslen M, Zurlo C, et al. Slow versus fast proteins in the stimulation of beta-cell response and the

Page | 357

activation of the entero-insular axis in type 2 diabetes. Diabetes Metab Res Rev. 2007;23(5):378-85.

648. Arciero PJ, Gentile CL, Pressman R, Everett M, Ormsbee MJ, Martin J, et al. Moderate protein intake improves total and regional body composition and insulin sensitivity in overweight adults. Metabolism. 2008;57(6):757-65.

649. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837-53.

650. The Royal Australian College of General Practitioners and Diabetes Australia. General practice management of type 2 diabetes – 2016–18 [Internet]. Melbourne, Australia: The Royal Australian College of General Practitioners; 2016 [cited 2017 Jan 10]. Available from: https://static.diabetesaustralia.com.au/s/fileassets/diabetes-australia/5d3298b2-abf3-487e-9d5e-0558566fc242.pdf.

651. Akhavan T, Luhovyy BL, Brown PH, Cho CE, Anderson GH. Effect of premeal consumption of whey protein and its hydrolysate on food intake and postmeal glycemia and insulin responses in young adults. Am J Clin Nutr. 2010;91(4):966-75.

652. Petersen BL, Ward LS, Bastian ED, Jenkins AL, Campbell J, Vuksan V. A whey protein supplement decreases post-prandial glycemia. Nutr J. 2009;8:47.

653. Clifton PM, Condo D, Keogh JB. Long term weight maintenance after advice to consume low carbohydrate, higher protein diets--a systematic review and meta analysis. Nutr Metab Cardiovasc Dis. 2014;24(3):224-35.

654. Dela F, Prats C, Helge JW. Exercise interventions to prevent and manage type 2 diabetes: physiological mechanisms. Med Sport Sci. 2014;60:36-47.

655. Kostoglou-Athanassiou I, Athanassiou P, Gkountouvas A, Kaldrymides P. Vitamin D and glycemic control in diabetes mellitus type 2. Ther Adv Endocrinol Metab. 2013;4(4):122-8.

656. Zhang J, Ye J, Guo G, Lan Z, Li X, Pan Z, et al. Vitamin D Status Is Negatively Correlated with Insulin Resistance in Chinese Type 2 Diabetes. Int J Endocrinol. 2016;2016.

657. Cade C, Norman AW. Vitamin D3 improves impaired glucose tolerance and insulin secretion in the vitamin D-deficient rat in vivo. Endocrinology. 1986;119(1):84-90.

658. Gedik O, Akalin S. Effects of vitamin D deficiency and repletion on insulin and glucagon secretion in man. Diabetologia. 1986;29(3):142-5.

659. Cianferotti L, Bertoldo F, Bischoff-Ferrari HA, Bruyere O, Cooper C, Cutolo M, et al. Vitamin D supplementation in the prevention and management of major chronic diseases not related to mineral homeostasis in adults: research for evidence and a scientific statement from the European society for clinical

Page | 358

and economic aspects of osteoporosis and osteoarthritis (ESCEO). Endocrine. 2017;56(2):245-61.

660. Lee J, Kim D, Kim C. Resistance Training for Glycemic Control, Muscular Strength, and Lean Body Mass in Old Type 2 Diabetic Patients: A Meta-Analysis. Diabetes Ther. 2017;10.1007/s13300-017-0258-3.

661. Umpierre D, Ribeiro PA, Schaan BD, Ribeiro JP. Volume of supervised exercise training impacts glycaemic control in patients with type 2 diabetes: a systematic review with meta-regression analysis. Diabetologia. 2013;56(2):242-51.

662. Teychenne M, Ball K, Salmon J, Daly RM, Crawford DA, Sethi P, et al. Adoption and maintenance of gym-based strength training in the community setting in adults with excess weight or type 2 diabetes: a randomized controlled trial. Int J Behav Nutr Phys Act. 2015;12:105.

663. Irvine C, Taylor NF. Progressive resistance exercise improves glycaemic control in people with type 2 diabetes mellitus: a systematic review. Aust J Physiother. 2009;55(4):237-46.

664. Mikines KJ, Sonne B, Farrell PA, Tronier B, Galbo H. Effect of physical exercise on sensitivity and responsiveness to insulin in humans. Am J Physiol. 1988;254(3 Pt 1):248-59.

665. Schneider SH, Amorosa LF, Khachadurian AK, Ruderman NB. Studies on the mechanism of improved glucose control during regular exercise in type 2 (non-insulin-dependent) diabetes. Diabetologia. 1984;26(5):355-60.

666. Kelley GA, Kelley KS. Impact of progressive resistance training on lipids and lipoproteins in adults: another look at a meta-analysis using prediction intervals. Prev Med. 2009;49(6):473-5.

667. Schwingshackl L, Missbach B, Dias S, Konig J, Hoffmann G. Impact of different training modalities on glycaemic control and blood lipids in patients with type 2 diabetes: a systematic review and network meta-analysis. Diabetologia. 2014;57(9):1789-97.

668. Santesso N, Akl EA, Bianchi M, Mente A, Mustafa R, Heels-Ansdell D, et al. Effects of higher- versus lower-protein diets on health outcomes: a systematic review and meta-analysis. Eur J Clin Nutr. 2012;66(7):780-8.

669. Hidayat K, Du HZ, Yang J, Chen GC, Zhang Z, Li ZN, et al. Effects of milk proteins on blood pressure: a meta-analysis of randomized control trials. Hypertens Res. 2017;40(3):264-70.

670. Zhang JW, Tong X, Wan Z, Wang Y, Qin LQ, Szeto IM. Effect of whey protein on blood lipid profiles: a meta-analysis of randomized controlled trials. Eur J Clin Nutr. 2016;70(8):879-85.

671. Denysschen CA, Burton HW, Horvath PJ, Leddy JJ, Browne RW. Resistance training with soy vs whey protein supplements in hyperlipidemic males. J Int Soc Sports Nutr. 2009;6:8.

Page | 359

672. Larsen T, Mose FH, Bech JN, Hansen AB, Pedersen EB. Effect of cholecalciferol supplementation during winter months in patients with hypertension: a randomized, placebo-controlled trial. Am J Hypertens. 2012;25(11):1215-22.

673. Strasser B, Siebert U, Schobersberger W. Resistance training in the treatment of the metabolic syndrome: a systematic review and meta-analysis of the effect of resistance training on metabolic clustering in patients with abnormal glucose metabolism. Sports Med. 2010;40(5):397-415.

674. Turnbull F, Neal B, Algert C, Chalmers J, Chapman N, Cutler J, et al. Effects of different blood pressure-lowering regimens on major cardiovascular events in individuals with and without diabetes mellitus: results of prospectively designed overviews of randomized trials. Arch Intern Med. 2005;165(12):1410-9.

675. Franz MJ, Boucher JL, Rutten-Ramos S, VanWormer JJ. Lifestyle weight-loss intervention outcomes in overweight and obese adults with type 2 diabetes: a systematic review and meta-analysis of randomized clinical trials. J Acad Nutr Diet. 2015;115(9):1447-63.

676. Hayashino Y, Jackson JL, Fukumori N, Nakamura F, Fukuhara S. Effects of supervised exercise on lipid profiles and blood pressure control in people with type 2 diabetes mellitus: a meta-analysis of randomized controlled trials. Diabetes Res Clin Pract. 2012;98(3):349-60.

677. Loimaala A, Groundstroem K, Rinne M, Nenonen A, Huhtala H, Parkkari J, et al. Effect of long-term endurance and strength training on metabolic control and arterial elasticity in patients with type 2 diabetes mellitus. Am J Cardiol. 2009;103(7):972-7.

678. Chen N, Wan Z, Han SF, Li BY, Zhang ZL, Qin LQ. Effect of vitamin D supplementation on the level of circulating high-sensitivity C-reactive protein: a meta-analysis of randomized controlled trials. Nutrients. 2014;6(6):2206-16.

679. Calle MC, Fernandez ML. Effects of resistance training on the inflammatory response. Nutr Res Pract. 2010;4(4):259-69.

680. Phillips MD, Patrizi RM, Cheek DJ, Wooten JS, Barbee JJ, Mitchell JB. Resistance training reduces subclinical inflammation in obese, postmenopausal women. Med Sci Sports Exerc. 2012;44(11):2099-110.

681. Della Gatta PA, Garnham AP, Peake JM, Cameron-Smith D. Effect of exercise training on skeletal muscle cytokine expression in the elderly. Brain Behav Immun. 2014;39:80-6.

682. Firdous S. Correlation of CRP, fasting serum triglycerides and obesity as cardiovascular risk factors. J Coll Physicians Surg Pak. 2014;24(5):308-13.

683. Vepsalainen T, Soinio M, Marniemi J, Lehto S, Juutilainen A, Laakso M, et al. Physical activity, high-sensitivity C-reactive protein, and total and

Page | 360

cardiovascular disease mortality in type 2 diabetes. Diabetes Care. 2011;34(7):1492-6.

684. Soinio M, Marniemi J, Laakso M, Lehto S, Ronnemaa T. High-sensitivity C-reactive protein and coronary heart disease mortality in patients with type 2 diabetes: a 7-year follow-up study. Diabetes Care. 2006;29(2):329-33.

685. Carrillo AE, Flynn MG, Pinkston C, Markofski MM, Jiang Y, Donkin SS, et al. Vitamin D supplementation during exercise training does not alter inflammatory biomarkers in overweight and obese subjects. Eur J Appl Physiol. 2012;112(8):3045-52.

686. Fayh AP, Lopes AL, da Silva AM, Reischak-Oliveira A, Friedman R. Effects of 5 % weight loss through diet or diet plus exercise on cardiovascular parameters of obese: a randomized clinical trial. Eur J Nutr. 2013;52(5):1443-50.

687. Abd El-Kader SM, Saiem Al-Dahr MH. Weight loss improves biomarkers endothelial function and systemic inflammation in obese postmenopausal Saudi women. Afr Health Sci. 2016;16(2):533-41.

688. Ma J, Jesudason DR, Stevens JE, Keogh JB, Jones KL, Clifton PM, et al. Sustained effects of a protein 'preload' on glycaemia and gastric emptying over 4 weeks in patients with type 2 diabetes: A randomized clinical trial. Diabetes Res Clin Pract. 2015;108(2):e31-4.

689. Matthews D, Hosker J, Rudenski A, Naylor B, Treacher D, Turner R. Homeostasis model assessment: insulin resistance and B-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-9.

690. Bonora E, Saggiani F, Targher G, Zenere MB, Alberiche M, Monauni T, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity - Studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000;23(1):57-63.

691. Radziuk J. Insulin sensitivity and its measurement: structural commonalities among the methods. J Clin Endocrinol Metab. 2000;85(12):4426-33.

692. Pham H, Utzschneider KM, de Boer IH. Measurement of insulin resistance in chronic kidney disease. Curr Opin Nephrol Hypertens. 2011;20(6):640-6.

693. Poslusna K, Ruprich J, de Vries JH, Jakubikova M, van't Veer P. Misreporting of energy and micronutrient intake estimated by food records and 24 hour recalls, control and adjustment methods in practice. Br J Nutr. 2009;101 (Suppl 2):S73-85.

694. Balducci S, Zanuso S, Cardelli P, Salvi L, Bazuro A, Pugliese L, et al. Effect of High- versus Low-Intensity Supervised Aerobic and Resistance Training on Modifiable Cardiovascular Risk Factors in Type 2 Diabetes; The Italian Diabetes and Exercise Study (IDES). PLoS One. 2012;7(11).

Page | 361

Appendices

Page | 362

Appendix 1

Mean baseline and the absolute change from baseline and the net differences for the change for HbA1c and body composition measurements in the PRT+WL and WL groups at 3, 6, 9 and 12-months.

PRT+WL WL Net Difference (95% CI)

HbA1c Baseline (%) 8.1 ± 1.0 7.5 ± 1.1 ∆ 3-months -0.6 (-1.0, -0.3)* -0.1 (-0.5, 0.4) 0.6 (0.0, 1.1)#

∆ 6-months -1.2 (-1.7, -0.7)† -0.4 (-0.9, -0.1)* 0.8 (0.1, 1.5)#

∆ 9-months -0.5 (-1.2, 0.2) 0.0 (-0.4, 0.4) 0.5 (-0.3, 1.4) ∆ 12-months -0.3 (-1.0, 0.4) 0.2 (-0.4, 0.7) 0.5 (-0.4, 1.4)

Body Weight Baseline (kg) 88.7 ± 10.9 89.5 ± 12.1 ∆ 3-months -1.8 (-2.8, -0.7)† -2.0 (-2.9, -1.1) † -0.2 (-1.6, 1.2) ∆ 6-months -2.5 (-4.0, -0.9)† -3.1 (-4.3, 1.8) † -0.6 (-2.6, 1.3)

∆ 9-months -2.3 (-3.8, -0.8)† -3.2 (-4.8, -1.6) † -0.9 (-2.9, 1.2)

∆ 12-months -1.7 (-2.6, -0.6)* -1.6 (-2.9, -0.3)* 0.0 (-1.6,1.6)

Fat Mass Baseline (kg) 33.1 ± 7.4 35.6 ± 6.8 ∆ 6-months -2.4 (-3.8, -0.9)† -2.1 (-3.6, -0.5)† 0.3 (-1.8, 2.3) ∆ 12-months -1.2 (-2.0, -0.3) 0.0 (-1.2, 0.8) 1.0 (-0.2, 2.2)

Lean Mass Baseline (kg) 51.8 ± 8.1 49.7 ± 9.5 ∆ 6-months 0.5 (-0.1, 1.1) -0.4 (-1.1, 0.3) -0.9 (-1.8, 0.0) ∆ 12-months 0.1 (-0.6, 0.8) -0.7 (-1.2, -0.1)* -0.7 (-1.6, 0.2)

Percent Fat Mass Baseline (%) 37.7 ± 6.8 40.6 ± 7.4 %∆ 6-months -2.0 (-3.1, -0.8)† -1.5 (-2.7, -0.2) 0.5 (-1.1, 2.1)

%∆ 12-months -0.7 (-1.5, 0.0) -0.9 (-3.6, 1.7) -0.2 (-2.6, 2.2) DXA measurements for fat mass, lean mass and percent fat mass were only performed at 0-, 6- and 12-months. Baseline values represent mean ± SD; change represents mean (95% CI). * P < 0.05, † P <0.01 vs baseline; # P < 0.05 between-group difference from baseline.

Page | 363

Appendix 2

Mean values ± SD in various inflammatory markers for the PRT+WL and WL groups at 3-, 6-, 9- and 12-months.

PRT + WL WL

IL-10 (pg/ml)

Baseline 14.1 ± 19.2 4.2 ± 5.7

3-months 11.0 ± 17.8 5.2 ± 12.6

6-months 10.7 ± 19.0 4.4 ± 3.4

9-months 10.0 ± 18.7 6.5 ± 8.2

12-months 14.1 ± 23.0 7.4 ± 13.5

IL-6 (pg/ml)

Baseline 3.7 ± 3.1 1.6 ± 1.8

3-months 3.9 ± 4.0 1.3 ± 1.1

6-months 4.4 ± 4.7 3.9 ± 7.9

9-months 6.1 ± 10.5 1.8 ± 1.7

12-months 5.9 ± 7.3 4.3 ± 6.4

TNF-α (pg/ml)

Baseline 8.2 ± 3.6 7.1 ± 5.0

3-months 7.3 ± 2.9 6.9 ± 6.2

6-months 9.1 ± 5.9 13.4 ± 20.2

9-months 7.1 ± 2.9 7.8 ± 4.5

12-months 6.2 ± 2.3 8.9 ± 6.6

Adiponectin (µg/ml)

Baseline 1.7 ± 0.7 2.7 ± 0.9

3-months 1.8 ± 0.5 2.9 ± 0.9

6-months 2.0 ± 0.8 2.9 ± 1.3

9-months 2.2 ± 1.3 3.0 ± 1.1

12-months 2.2 ± 1.5 2.5 ± 0.9 Values are raw means ± SD

Page | 364

Appendix 3

Mean value ± SD in endothelial markers for the PRT+WL and WL groups at 3-, 6-, 9- and 12-months.

PRT+WL PRT

ICAM-1 (ng/ml)

Baseline 134.9 ± 59.6 142.4 ± 69.4

3-months 135.7 ± 51.3 143.0 ± 75.2

6-months 134.3 ± 49.3 121.7 ± 47.5

9-months 113.9 ± 22.6 122.2 ± 54.7

12-months 120.0 ± 32.6 113.8 ± 41.3

Resistin (ng/ml)

Baseline 10.5 ± 5.6 11.0 ± 3.9

3-months 12.2 ± 4.2 10.8 ± 3.7

6-months 11.7 ± 4.6 10.5 ± 4.5

9-months 10.4 ± 4.6 11.5 ± 5.6

12-months 10.6 ± 5.3 10.4 ± 4.2 Values are raw means ± SD

Page | 365

Appendix 4

Page | 366

Appendix 5

sfol

Retracted Stamp

Page | 368

Page | 369

Page | 370

Appendix 7

PLAIN LANGUAGE STATEMENT AND CONSENT FORM

TO: Participants

Plain Language Statement

Date: 3rd April, 2014 Full Project Title: Does a High Protein Enriched Drink and Vitamin D

Enhance the Health Benefits of the Lift for Life® Resistance Training Program in Older Adults with Type 2 Diabetes?

Principal Researcher: Professor Robin Daly Student Researcher: Ms Eliza Miller Associate Researcher(s): Professor David Dunstan, Professor Caryl Nowson,

Associate Professor Deborah Kerr, Associate Professor Vicky Solah, Mr David Menzies, Dr Helen Macpherson, Dr Matthew Hughes

This Plain Language Statement and Consent Form is 9 pages long. Please make sure you have all the pages.

1. Your Consent You are invited to take part in this research project which will investigate the effects of resistance training (lifting weights) alone or resistance training in combination with a protein enriched drink with additional vitamin D on blood glucose levels, body composition and cardiovascular risk factors in people with type 2 diabetes. This Plain Language Statement contains detailed information about the research project. Its purpose is to explain to you as openly and clearly as possible all the procedures involved in this project before you decide whether or not to take part in it. Please read this Plain Language Statement carefully. Feel free to ask questions about any information in the document. You may also wish to discuss the project with a relative or friend or your local health worker. Feel free to do this. Once you understand what the project is about and if you agree to take part in it, you will be asked to sign the Consent Form. By signing the Consent Form, you indicate that you understand the information and that you give your consent to participate in the research project.

Page | 371

You will be given a copy of the Plain Language Statement and Consent Form to keep as a record. Participation in this study is voluntary. If you do not wish to take part you are not obliged to. If you decide to take part and later change your mind, you are free to withdraw from the project at any stage. Your decision whether or not to participate will not affect your relationship with Deakin University.

2. Purpose and Background Regular exercise is important for maintaining blood glucose levels in people with, or at risk of developing, type 2 diabetes because it helps to make the muscles use glucose more effectively. Resistance training (lifting weights) is particularly effective for improving blood glucose levels as well as increasing muscle mass, strength and physical function. To optimise the health benefits of resistance training, it has been suggested that it should be combined with adequate nutrition, particularly an adequate intake of dietary protein. Maintaining adequate vitamin D levels has also been shown to be important for both optimal blood glucose levels and muscle function. Thus, this 6-month study is designed to investigate whether daily consumption of a protein enriched drink and vitamin D can enhance the benefits of participation in the Lift for Life® resistance training program on glycaemic control, body composition and cardiovascular risk factors in people with type 2 diabetes. Lift for Life® is a community-based resistance training program for people with or at risk of developing type 2 diabetes that is being coordinated by Fitness Australia and Baker IDI Heart and Diabetes Institute. A total of 202 men and women with type 2 diabetes who have agreed to participate in the commercial Lift for Life® resistance training program will participate in this project. You are invited to participate in this research project because you have type 2 diabetes and are aged between 50 and 75 years and free of any serious health conditions that might limit your participation in the Lift for Life® resistance training program. If you are not eligible for this study, you may still be able to participate in the standard Lift for Life® program. This study is being sponsored by the National Health and Medical Research Council (NHMRC). This trial has been initiated by the investigator, Professor Robin Daly.

3. Procedures – what you will be asked to do If you decide to participate in this study you will be asked to sign this Participant Information and Consent Form. To participate in this study, you must have passed the initial telephone screening test conducted by one of the research staff. Before you commence the study, you will be required to visit your local doctor who will be required to complete the Lift for Life® recommendation to participate health and medical screening form to make sure that you don’t have any medical conditions that could affect your participation in this study (e.g. unstable heart disease). Upon entry into the study, you will undergo initial baseline testing and then you will be randomly allocated (like the flip of a coin) to one of two groups. You will have a one in two chance of being in either group. This is called randomisation. This is a

Page | 372

standard research method used to ensure that the results of a study are true and correct.

Group 1: Lift for Life® resistance training with increased dietary protein and vitamin D. If you are allocated to this group you will be prescribed an individually tailored and progressive resistance training program which will be conducted at an accredited Lift for Life® health and fitness centre. You will be required to attend 2 supervised exercise sessions and another non-supervised exercise session each week for 6-months. The supervised sessions will be conducted by qualified Lift for Life® exercise trainers. Each session will last approximately 45-60 minutes, and include a warm-up and cool-down and moderate intensity resistance training. Therefore, the total time commitment for the 6-months of training will be approximately 150 minutes per week, which is the current recommended level of physical activity. To monitor your progress, you will be asked to complete a diary of your participation in the exercise program. You will also be asked to take vitamin D supplements (2000 IU) and consume one protein enriched drink (about 150 ml providing 20g of protein) each morning before breakfast and the same drink after each Lift for Life® training session. You will be supplied with all drinks and supplements at no charge for the duration of the study. To monitor your intake, you will be asked to complete a daily calendar/checklist throughout the study.

Group 2: Lift for Life® resistance training. If you are allocated to this group you will be prescribed the same exercise program as outlined for Group 1, but you will not be asked to consume either the protein drinks or vitamin D supplements. As per group 1, you will also be asked to record your participation in the exercise program in a diary.

For all people involved in the study, we will collect the following information and conduct a number of tests throughout the 6-month study. This testing will be conducted at both the Lift for Life® health and fitness centres and at Deakin University in Burwood.

• You will be asked to complete a general lifestyle and health questionnaire to obtain information on past employment history, education history, marital status, cultural background, menopausal history (women only), dieting and weight history, alcohol intake, smoking history, medical history, use of prescription and non-prescription medications and diabetes history and perceived barriers and obstacles to participating in exercise. We will also measure your weight, height and waist circumference at the beginning of the study and after 3 and 6 months.

• Total body composition (amount of muscle and fat) and bone density of the total body, hip and spine will be measured using a non-invasive method referred to as dual energy X-ray absorptiometry (DXA) at the beginning and end of the study. The assessment of body composition and bone density by DXA involves lying on a bed for approximately 20 minutes whilst a scanning arm moves along the length of your body above you. This test will be conducted at Deakin University and we will arrange transport for you to Deakin from your home if needed.

• Peripheral computed tomography (pQCT) is a non-invasive method that will be used to assess muscle and fat size and density in your thigh at the beginning and end of the study. Your leg will be inserted into the opening of a gantry (ring with x-ray source and detectors) for scanning. This test will involve remaining still for three to five minutes during the measurement. The pQCT scans will

Page | 373

cause no pain or discomfort other than having to remain still. This test will be conducted at Deakin University at the same time as your DXA scan.

• We will take a small blood sample to assess the effects of the program on a number of important markers in your blood, including blood glucose, glycated haemoglobin (HbA1c), insulin, cholesterol and lipids, vitamin D and other markers of muscle and bone metabolism and inflammation. A blood sample of 30 mls (1.5 tablespoon) will be taken from a vein in your arm using a needle at baseline, 3 and 6 months. The blood sample will collected by a trained research nurse in the morning when you have had nothing to eat or drink since the night before.

• We would also like to assess your blood pressure at baseline, 3 and 6 months. • You will be required to undergo some simple balance and walking tests to

measure your muscle function at baseline, 3 and 6 months. We will assess your maximal muscle strength on specific resistance (strength) training equipment. This involves lifting weights until you can only lift a weight three times.

• We would also like to ask you a few questions about your exercise/physical activity and TV/computer habits three times over the study. In addition, we would also like to assess your dietary habits using a food frequency questionnaire at baseline, 3 and 6 months and a 24-hour food recall each month, which will be completed over the telephone with one of the researchers.

• You will be asked to complete a questionnaire which will assess your health-related quality of life at the beginning and end of the study. You will also be asked to complete a simple computer test and questionnaire to assess you cognitive function at baseline, 3 and 6 months.

There will be continual review and monitoring during your participation in this research to enable the early detection of any problems that you may experience.

THIS NEXT ASSESSMENT TASK IS OPTIONAL You will also be invited to have a brain scan using MRI (Magnetic Resonance Imaging) at Swinburne University in Hawthorn (at no cost to you). MRI scanning involves brain imaging techniques that are non-invasive and provide the ability to image the brain whilst completing a simply task. Before the MRI session begins, you will be required to complete a safety questionnaire administered by the neuroimaging technologist regarding any metal you have on or in your body, such as that from any surgery involving metal plates and pace makers. A copy of the MRI safety questionnaire is attached to this document. Due to the nature of MRI that involves magnets, no metal may be taken into the room. The scanner is also quite noisy so you will be provided with some headphones to reduce this noise. Once in the scanner, you will undergo a structural brain scan, a resting state scan, where you will have your eyes closed, and a functional scan where you will perform a simple memory task. The entire time spent in the MRI scanner should not exceed 45 minutes.

4. Collection of Tissue Samples for Research Purposes By consenting to take part in this study, you also consent to the collection, storage and use of tissue samples as specified below. A blood sample of 30 mls (1.5 tablespoon) will be taken from a vein in your arm using a needle at the beginning of the study, 3 and 6 months by a qualified research nurse. The samples will not be labelled with information that directly identifies you.

Page | 374

The samples will be “coded”, which means that it will be labelled with a number that can be linked to you. All samples will be stored securely at Deakin University and only the research staff involved in this study will have access to the samples. Some of the samples will be tested immediately at the end of the study and some will be frozen and stored for 10-years following the publication of study findings. We wish to store these samples to conduct further testing to look for other muscle, bone, inflammatory or cardiometabolic biomarkers when and if funding for this becomes available in the future. This future testing may be conducted by researchers from the present study or by other researchers employed by Deakin University. If any changes to the study are made which affect how these samples will be used, your samples will not be used, without your further consent. These samples will be disposed of according to standard laboratory practice, immediately after testing.

5. Possible Benefits We cannot guarantee or promise that you will receive any benefits from this project. By participating in this project, you will receive information on ways to improve your health. For some people the possible benefits may include an improvement in blood glucose levels and blood lipids and an increase in muscle mass, strength and function (e.g. balance), and a reduction of circulating (blood) markers of inflammation which are linked to common chronic diseases. We also expect that the findings from this study will make an important contribution to the development of exercise and dietary guidelines to improve health outcomes for people with type 2 diabetes.

6. Possible Risks Possible risks, side effects and discomforts include the following: • The exercise program will involve resistance (strength) training and you may

experience some minor and transient muscle soreness initially following the training sessions or the muscle strength testing. However, this form of training has been shown to be safe and acceptable, and the Lift for Life® program is designed in such a way to help minimise risks for participants through (1) supervised and graduated exercise programs; (2) specialised training for Lift for Life® Trainers; (3) requirement for Doctor’s approval prior to commencing the program; (4) pre-exercise assessment; and (5) regular assessments during the program.

• This research study involves exposure to a very small amount of radiation from DXA and pQCT scans of your body. As part of everyday living, everyone is exposed to naturally occurring background radiation and receives a dose of about 2 millisieverts (mSv) each year. The effective dose you will receive from all the DXA and pQCT scans of your body will be approximately 0.065 mSv. At these dose levels, no harmful effects of radiation have been demonstrated, as any effect is too small to measure. The risk is believed to be very low.

• If you have been involved in any other research studies that involve radiation, please inform us. Please keep this Patient Information and Consent Form that includes information about your exposure to radiation in this study for at least five years. You will be required to provide this information to researchers of any future research studies

• When you have blood samples taken for this study, you might feel pain or be light-headed and there is a chance you might get a small bruise on your arm.

Page | 375

• Participants randomised to the protein and vitamin D fortified group (Group 1) will be asked to consume an additional 20-40g of protein and 2000 IU of vitamin D each day for 6 months. The amount of protein is within the recommended range for a healthy diet. We will measure your kidney function from the blood sample that you provide. If we detect any problems we will refer you to your doctor and ask you to withdraw from the study. Treatment with vitamin D is also very safe. There is a very small risk of hypercalcemia (high calcium levels in the blood) and hypercalciuria (high calcium levels in the urine) with vitamin D therapy. If you know you have high levels of blood calcium, then you will not be asked to take part in this study. The amount of vitamin D in the supplement is at the level recommended for health benefits. Thus, normal health will not be adversely affected by consumption of the test product to be used in this study.

• MRI uses radio waves and magnetism to make diagnostic images of the body. There are no known harmful effects. This test involves no radiation. Some people may find the MRI scan unpleasant, and feel claustrophobic, because you have to lie in a chamber while the scan is performed. Certain medical devices must be excluded from the MRI facilities. Such as cardiac pacemakers, cochlear implants, neuro-stimulators, certain metallic dental work, body jewellery and other metallic foreign objects implanted in the body. A complete list is outlined on MRI Pre-Scan Safety Questionnaires. You will be asked to indicate on this questionnaire any previous surgery regarding implanted metal in your body and any surgical operation performed on your head/arm. Some people may find the MRI scan unpleasant, and feel claustrophobic, because you have to lie in a chamber while the scan is performed. In the event that anxiety, claustrophobia or panic attacks are experienced during the scan and you wish to stop the scan, then the scan shall be terminated. After the MRI scans, a Swinburne University’s radiologist will examine the brain scans. There is a rare possibility that an abnormality may be found that is significant and which should be investigated further. Although a significant abnormality is extremely unlikely, if one is detected you will be informed by the radiologist or your nominated health practitioner. If you would prefer not to be exposed to this unlikely (yet possible) experience, then you are advised not to participate in the MRI scan.

There may be additional unforeseen or unknown risks.

7. Other Treatments Whilst on Study It is important to tell your doctor and the research staff about any treatments or medications you may be taking, including non-prescription medications, vitamins or herbal remedies and any changes to these during your participation in the study.

9. Privacy, Confidentiality and Disclosure of Information Any information obtained in connection with this research project that can identify you will remain confidential and will only be used for the purpose of this research project. All collected information will be labelled with a unique study code, and not with your name or any other identifying information, which be kept separate from the information collected. All paper copies of this information will be kept in a locked filing cabinet in the researcher’s office at Deakin University or in a password protected computer. Only researchers involved in this project will have access to this information. The information collected from this study will be kept until the end of the project and then placed in archives for 6 years from the publication of findings. All data will also be kept in a database stored on a computer which will be password

Page | 376

protected and only accessible to the research staff involved in this study, and may be used in future research which is closely related to this project. We wish to store blood samples to conduct further testing to look for other muscle, bone or inflammatory biomarkers when and if funding for this becomes available in the future. This future testing may be conducted by researchers from the present study or by other researchers employed by Deakin University. In any publication, information will be provided in such a way that you cannot be identified; only group findings will be published. In accordance with the Freedom of Information Act 1982 (Vic), you have the right to access and to request correction of information held about you by Deakin University.

10. New Information Arising During the Project During the research project, new information about the risks and benefits of the project may become known to the researchers. If this occurs, you will be told about this new information. This new information may mean that you can no longer participate in this research. If this occurs, the person(s) supervising the research will stop your participation. In all cases, you will be offered all available care to suit your needs and medical condition.

11. Results of Project At the completion of the study, you will be provided with an individual report of your results. You will also receive access to the main findings from the study.

12. Further Information or Any Problems

If you require further information or if you have any problems concerning this project (for example, any side effects) you can contact the principal researcher or associate researcher.

Contact Person Telephone Number

Professor Robin Daly 03 9244 6040

Ms Eliza Miller 03 9244 6739

13. Other Issues If you have any complaints about any aspect of the project, the way it is being conducted or any questions about your rights as a research participant, then you may contact:

The Manager, Research Integrity, Deakin University, 221 Burwood Highway, Burwood Victoria 3125, Telephone: 9251-7129, research-ethics@deakin.edu.au

Please quote project number [2013-050].

14. Participation is Voluntary Participation in any research project is voluntary. If you do not wish to take part you are not obliged to. If you decide to take part and later change your mind, you are free to withdraw from the project at any stage.

Page | 377

Your decision whether to take part or not to take part, or to take part and then withdraw, will not affect your routine treatment, your relationship with those treating you or your relationship with Deakin University. You will also have the option to withdraw your data and tissues from the research project if you wish to do so. Before you make your decision, a member of the research team will be available so that you can ask any questions you have about the research project. You can ask for any information you want. Sign the Consent Form only after you have had a chance to ask your questions and have received satisfactory answers. If you decide to withdraw from this project, please notify a member of the research team before you withdraw. This notice will allow that person or the research supervisor to inform you if there are any health risks or special requirements linked to withdrawing.

15. Reimbursement for your costs As reimbursement for some of the expenses incurred by you for participating in the Lift for Life® resistance training program, you will be eligible to receive up to $240 in vouchers or cash at the completion of the study. The amount you will be reimbursed will be determined each month based on your continued involvement in the study. All protein-based drinks and supplements will be provided to you free of charge if you are randomly allocated to this group. No costs will be incurred by you for the blood collection or any of the other tests.

16. Ethical Guidelines This project will be carried out according to the National Statement on Ethical Conduct in Research Involving Humans (June 1999) produced by the National Health and Medical Research Council of Australia. This statement has been developed to protect the interests of people who agree to participate in human research studies. The ethical aspects of this research project have been approved by the Deakin University Human Research Ethics Committee (project number [2013-050].

17. Termination of the Study This research project may be stopped for a variety of reasons. These may include reasons such as: unacceptable side effects.

Page | 378

PLAIN LANGUAGE STATEMENT AND CONSENT FORM

TO: Participants

Consent Form

Date: 3rd April 2014

Full Project Title: Does a High Protein Enriched Drink and Vitamin D Enhance the Health Benefits of the Lift for Life® Resistance Training Program in Older Adults with Type 2 Diabetes?

Reference Number: [2013-050]

I have read, and I understand the attached Plain Language Statement.

I freely agree to participate in this project according to the conditions in the Plain Language Statement.

As indicated in the plain language statement there is an OPTIONAL component of this study involving the use of Magnetic Resonance Imaging (MRI) to assess the effects of the intervention on brain structure and function. Please indicate below (tick box) whether you are willing to participate in this aspect of the study.

o I AGREE to participate in the MRI sub study to assess brain structure and function.

o I DO NOT wish to participate in the MRI sub study to assess brain structure and function.

I have been given a copy of the Plain Language Statement and Consent Form to keep.

The researcher has agreed not to reveal my identity and personal details, including where information about this project is published, or presented in any public form.

Participant’s Name (printed) …………………………………………………………………………………………

Signature ……………………………………………….. Date………………….........

sfol

Retracted Stamp

Page | 380

Page | 381

Appendix 9

Baseline values and absolute within-group changes in the progressive resistance training (PRT) plus protein and vitamin D supplementation (PRT+ProD) and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for saturated fat, dietary cholesterol and select micronutrients excluding the protein-vitamin D supplements.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Saturated Fat (g/day)

Baseline 26.1 ± 13.0 30.0 ± 17.6

Δ 12-weeks 0.4 (-2.8, 3.6) 0.890 -2.5 (-6.7, 1.7) 0.284 2.9 (-2.3, 8.1) 0.430 | 0.273

Δ 24-weeks -0.6 (-3.5, 2.4) 0.622 -5.0 (-9.1, -1.0) 0.018 4.5 (-0.4, 9.4) 0.105 | 0.087

Cholesterol (mg)

Baseline 279.7 ± 164.3 329.6 ± 278.0

Δ 12-weeks 20.6 (-31.9, 80.0) 0.805 -11.4 (-77.1, 54.2) 0.740 32.0 (-50.7, 114.7) 0.663 | 0.570

Δ 24-weeks 32.5 (-26.7, 91.7) 0.302 -29.0 (-96.3, 38.3) 0.225 61.5 (-27.1, 150.1) 0.101 | 0.092

Sodium (mg)

Baseline 2648 ± 1504 2602 ± 1438

Continued over page

Page | 382

Δ 12-weeks -185 (-536, 166) 0.173 -146 (-494, 202) 0.242 -39 (-530, 452) 0.809 | 0.814

Δ 24-weeks 146 (-275, 567) 0.989 -171.1 (-544, 202) 0.165 317 (-245, 878) 0.337 | 0.241

Potassium (mg)

Baseline 3493 ± 1161 3620 ± 1138

Δ 12-weeks 75 (-233, 383) 0.502 -114 (-414, 186) 0.451 189 (-239, 617) 0.313 | 0.268

Δ 24-weeks -100 (-383, 183) 0.359 -18 (-352, 317) 0.969 -82 (-515, 350) 0.541 | 0.381

Calcium (mg)

Baseline 899 ± 414 945 ± 414

Δ 12-weeks -67 (-156, 21) 0.219 3 (-100, 106) 0.944 -70 (-204, 64) 0.444 | 0.438

Δ 24-weeks 27 (-79, 133) 0.796 -69 (-178, 40) 0.136 96 (-54, 247) 0.205 | 0.216

Magnesium (mg)

Baseline 399 ± 149 421 ± 142

Δ 12-weeks -14 (-50, 23) 0.496 -10 (-44, 24) 0.442 -4 (-53, 46) 0.917 | 0.844

Δ 24-weeks -14 (-51, 23) 0.325 -2 (-41, 38) 0.937 -12 (-65, 41) 0.547 | 0.465 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 383

Appendix 10

Per Protocol Results Tables

Table 1: Baseline values and absolute within-group changes in the PRT+ProD and PRT group and the net between-group differences for the change at 12- and 24-weeks relative to baseline for moderate habitual physical activity. Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Moderate-vigorous Physical Activity (kJ/Week)

Baseline 7,475 ± 8,418a 10,908 ± 8,342

∆ 12-weeks 1,004 (-1,129, 3,137) 0.343 890 (-1,018, 2,797) 0.390 114 (-2,699, 2,928) 0.970 | 0.985 ∆ 24-weeks 3,874 (1,401, 6,347) 0.001 44 (-2,570, 2,658) 0.985 3,830 (212, 7,449) 0.009 | 0.012

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from model 1 – unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjusting for baseline values, age, gender, ethnicity and BMI. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 384

Table 2: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for all macronutrients, excluding protein intake and the protein-vitamin D supplements.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Energy Intake (kJ/day)

Baseline 8498 ± 2618 8382 ± 2305

∆ 12-weeks -186 (-1059, 687) 0.623 -28 (-676, 618) 0.829 -158 (-1210, 893) 0.847 | 0.900 ∆ 24-weeks -532 (-1343, 279) 0.205 -302 (-1266, 662) 0.392 -230 (-1513, 1053) 0.771 | 0.705

Carbohydrate (g/day)

Baseline 213.3 ± 94.7 193.7 ± 54.4 Δ 12-weeks -8.5 (-35.3, 18.3) 0.531 20.1 (-2.4, 42.7) 0.160 -28.6 (-62.9, 5.6) 0.148 | 0.153 Δ 24-weeks -16.9 (-46.9, 13.0) 0.195 -3.8 (-29.2, 21.6) 0.667 -13.1 (-51.6, 25.4) 0.503 | 0.548

Fat (g/day)

Baseline 72.8 ± 30.3 78.8 ± 33.2 Δ 12-weeks -2.2 (-14.4, 10.1) 0.661 -5.7 (-14.8, 3.4) 0.254 3.6 (-11.2, 18.3) 0.600 | 0.542 Δ 24-weeks -0.9 (-12.1, 10.3) 0.932 -5.6 (-18.5, 7.2) 0.297 4.7 (-12.5, 22.0) 0.497 | 0.602

% Energy Protein

Baseline 21.0 ± 6.0 19.2 ± 5.4

Page | 385

Δ 12-weeks -0.5 (-2.3, 1.3) 0.512 -0.6 (-2.3, 1.0) 0.739 0.1 (-2.2, 2.5) 0.824 | 0.838 Δ 24-weeks -0.4 (-2.4, 1.6) 0.279 2.0 (0.1, 3.8) 0.005 -2.3 (-5.0, 0.4) 0.007 | 0.006

% Energy Fat

Baseline 31.9 ± 10.1 34.1 ± 8.5 Δ 12-weeks -0.3 (-3.2, 2.6) 0.819 -2.0 (-5.0, 0.9) 0.154 1.7 (-2.4, 5.8) 0.397 | 0.350 Δ 24-weeks 1.1 (-2.3, 4.5) 0.324 -0.4 (-3.2, 2.4) 0.444 1.5 (-2.8, 5.8) 0.213 | 0.274

% Energy Carbohydrates

Baseline 41.5 ± 9.8 39.5 ± 8.5 Δ 12-weeks 0.2 (-2.7, 3.1) 0.849 3.6 (0.7, 6.5) 0.036 -3.4 (-7.5, 0.7) 0.180 | 0.146 Δ 24-weeks -0.7 (-4.7, 3.3) 0.714 -0.2 (-3.2, 2.8) 0.833 -0.4 (-5.2, 4.3) 0.902 | 0.937

Alcohol§ (g/day)

Baseline 5.8 ± 8.8 10.2 ± 15.7 Δ 12-weeks 0.3 (-1.6, 2.3) 0.670 -2.5 (-4.7, -0.4) 0.010 2.8 (0.0, 5.8) 0.044 | 0.048 Δ 24-weeks 0.77 (-1.1, 2.6) 0.372 -1.1 (-2.3, 0.2) 0.383 1.8 (-0.3, 3.9) 0.221 | 0.268

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjusting for age, gender, ethnicity, BMI and moderate-vigorous physical activity § Baseline alcohol intake and the change in alcohol intake was calculated based only on the number of participants in each group who reported being a consumer of alcohol at respective time points. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 386

Table 3: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for saturated fat, cholesterol, sodium, potassium, calcium and magnesium.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-

value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3

Saturated Fat (g/day)

Baseline 26.2 ± 12.4 27.4 ± 14.8

Δ 12-weeks -0.1 (-5.5, 5.3) 0.958 -2.6 (-6.9, 1.7) 0.264 2.5 (-4.1, 9.2) 0.447 | 0.424

Δ 24-weeks -0.1 (-4.6, 4.5) 0.969 -2.9 (-7.9, 2.1) 0.208 2.9 (-4.0, 9.7) 0.393 | 0.338

Cholesterol (mg)

Baseline 258.6 ± 99.7 272.9 ± 181.9

Δ 12-weeks 44.8 (-25.5, 115.2) 0.261 18.5 (-48.0, 84.9) 0.532 26.4 (-69.2, 121.9) 0.754 | 0.723

Δ 24-weeks 17.7 (-53.8, 89.2) 0.630 15.7 (-56.4, 87.8) 0.640 -2.0 (-99.6, 103.5) 0.999 | 0.974

Sodium (mg)

Baseline 2740 ± 1438 2378 ± 960

Δ 12-weeks -457 (-994, 80) 0.120 79 (-317, 475) 0.824 -536 (-1182, 109) 0.143 | 0.147

Δ 24-weeks 22 (-650, 693) 0.919 48 (-351, 448) 0.848 -26 (-762, 709) 0.865 | 0.982

Continued over page

Page | 387

Potassium (mg)

Baseline 3649 ± 1188 3504 ± 1124

Δ 12-weeks 231 (-241, 703) 0.336 -85 (-428, 259) 0.580 316 (-248, 880) 0.282 | 0.240

Δ 24-weeks -254 (-616, 108) 0.260 338 (-92, 768) 0.128 -592 (-1165, -19) 0.062 | 0.019

Calcium (mg)

Baseline 929 ± 377 897 ± 359

Δ 12-weeks -159 (-279, -38) 0.016 -11 (-127, 104) 0.857 -148 (-312, 17) 0.144 | 0.155

Δ 24-weeks -18 (-139, 103) 0.373 -17 (-164, 130) 0.686 -1 (-193, 190) 0.748 | 0.763

Magnesium (mg)

Baseline 402 ± 184 410 ± 143

Δ 12-weeks -18 (-79, 43) 0.434 -24 (-62, 14) 0.158 5 (-63, 73) 0.769 | 0.720

Δ 24-weeks -44 (-97, 10) 0.116 10 (-37, 57) 0.790 -14 (-49, 22) 0.159 | 0.080 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 388

Table 4: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for habitual protein intake and protein intake inclusive of supplemental protein on non-training and training days in g/day and g/kg/day.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 2 Protein (g/day)

Habitual Protein (Excluding Whey Supplement)

Baseline 103.8 ± 32.4 93.5 ± 26.4

∆ 12-weeks -3.5 (-12.7, 5.8) 0.471 -2.8 (-11.5, 5.9) 0.651 -0.65 (-13.2, 11.9) 0.777 | 0.836

∆ 24-weeks -12.4 (-25.7, 0.8) 0.035 5.9 (-3.8, 15.5) 0.190 -18.3 (-34.1, -2.26) 0.012 | 0.006

Habitual Protein plus Whey Supplement (Non-Training Day)

Baseline 103.8 ± 32.4 93.5 ± 26.4

Δ 12-weeks 15.5 (6.1, 24.8) 0.009 -2.8 (-11.5, 5.9) 0.651 18.2 (5.7, 30.9) 0.018 | 0.014 Δ 24-weeks 6.6 (-6.7, 19.9) 0.219 2.7 (-8.0, 13.3) 0.190 3.9 (-12.7, 20.5) 0.869 | 0.932

Habitual Protein plus Whey Supplement (Training Day)

Baseline 103.8 ± 32.4 93.5 ± 26.4

Δ 12-weeks 34.4 (24.9, 43.8) 0.001 -2.8 (-11.5, 5.9) 0.651 37.2 (24.5, 49.9) 0.001 | 0.001 Δ 24-weeks 25.6 (12.3, 38.9) 0.001 2.7 (-8.0, 13.3) 0.190 22.9 (6.3, 39.5) 0.005 | 0.011

Page | 389

Protein (g/kg/day) Habitual Protein (Excluding Whey Supplement)

Baseline 1.23 ± 0.35 b 1.03 ± 0.28

Δ 12-weeks -0.03 (-0.14, 0.07) 0.561 -0.03 (-0.13, 0.07) 0.633 0.00 (-0.15, 0.14) 0.855 | 0.874

Δ 24-weeks -0.13 (-0.28, 0.03) 0.090 0.08 (-0.02, 0.19) 0.086 -0.21 (-0.39, -0.03) 0.015 | 0.015

Habitual Protein plus Whey Supplement (Non-Training Day)

Baseline 1.23 ± 0.35 b 1.03 ± 0.28

Δ 12-weeks 0.20 (0.09, 0.31) 0.005 -0.03 (-0.13, 0.07) 0.633 0.23 (0.08, 0.37) 0.009 | 0.009 Δ 24-weeks 0.11 (-0.05, 0.27) 0.079 0.08 (-0.02, 0.19) 0.086 0.02 (-0.16, 0.21) 0.656 | 0.688

Habitual Protein plus Whey Supplement (Training Day) Baseline 1.23 ± 0.35 b 1.03 ± 0.28

Δ 12-weeks 0.43 (0.31, 0.54) 0.001 -0.03 (-0.13, 0.07) 0.633 0.46 (0.31, 0.60) 0.001 | 0.001 Δ 24-weeks 0.34 (017, 0.51) 0.001 0.08 (-0.02, 0.19) 0.086 0.26 (0.07, 0.45) 0.001 | 0.002

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values, net differences and interaction effects were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 390

Table 5: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for HbA1c, fasting plasma glucose, C-peptide and measures of insulin resistance, sensitivity and beta-cell function.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 HbA1c (%)

Baseline 6.76 ± 1.00 6.88 ± 1.08 Δ 12-weeks -0.27 (-0.45, -0.08) 0.006 -0.06 (-0.21, 0.09) 0.422 -0.20 (-0.43, 0.02) 0.095 | 0.111 Δ 24-weeks -0.22 (-0.46, 0.02) 0.022 -0.09 (-0.27, 0.10) 0.265 -0.14 (-0.43, 0.16) 0.266 | 0.134 HbA1c (IFCC mmol/mol) Baseline 50.34 ± 10.96 51.64 ± 11.72 Δ 12-weeks -2.98 (-4.94, -1.02) 0.005 -0.54 (-2.16, 1.08) 0.524 -2.44 (-4.92, 0.05) 0.287 | 0.081 Δ 24-weeks -2.44 (-5.05, -0.17) 0.021 -0.90 (-2.92, 1.12) 0.288 -1.54 (-4.74, 1.66) 0.344 | 0.119 Fasting Glucose (mmol/L)

Baseline 7.52 ± 1.80a 8.47 ± 2.12

Δ 12-weeks -0.31 (-0.64, 0.02) 0.153 -0.38 (-0.74, -0.03) 0.036 0.07 (-0.41, 0.56) 0.304 | 0.631 Δ 24-weeks -0.07 (-0.52, 0.38) 0.737 -0.57 (-0.98, -0.17) 0.002 0.50 (-0.10, 2.00) 0.451 | 0.311

Continued over page

Page | 391

Fasting Insulin (pmol/L)

Baseline 84.96 ± 51.08 102.82 ± 50.96 Δ 12-weeks -13.8 (-26.3, -1.4) 0.010 -2.9 (-14.7, 8.9) 0.594 -11.0 (-27.9, 6.0) 0.155 | 0.138 Δ 24-weeks -9.5 (-20.8, 1.8) 0.078 -3.1 (-10.8, 4.6) 0.570 -6.0 (-10.8, 4.6) 0.404 | 0.689

Insulin sensitivity (HOMA2%S)

Baseline 79.4 ± 48.8b 57.3 ± 25.4 Δ 12-weeks 8.3 (-3.7, 20.3) 0.095 5.2 (-4.0, 14.4) 0.314 3.1 (-11.5, 17.8) 0.911 | 0.454 Δ 24-weeks 5.5 (-6.1, 17.1) 0.282 7.3 (-0.7, 15.2) 0.088 -1.7 (-15.4, 11.9) 0.369 | 0.787

C-peptide (nmol/L)

Baseline 1.10 ± 0.44a 1.26 ± 0.36 Δ 12-weeks -0.07 (-0.14, 0.01) 0.058 -0.03 (-0.10, 0.04) 0.453 -0.04 (-0.15, 0.06) 0.394 | 0.425 Δ 24-weeks -0.04 (-0.11, 0.03) 0.254 -0.06 (-0.14, 0.02) 0.093 0.02 (-0.09, 0.12) 0.745 | 0.974

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, oral hypoglycaemic use and moderate-vigorous physical activity. a P<0.05, b P<0.01 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 392

Table 6: Baseline values and absolute within-group changes in the PRT+ProD and PRT groups for weight, body mass index (BMI) and waist circumference and the net between-group differences for the change relative to baseline at 12- and 24-weeks.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Body Weight (kg) Baseline 84.4 ± 16.3a 91.6 ± 12.6 Δ 12-weeks 0.2 (-0.3, 0.7) 0.464 -0.1 (-0.5, 0.4) 0.811 0.3 (-0.4, 1.0) 0.499 | 0.487

Δ 24-weeks -0.2 (-1.0, 0.6) 0.491 -1.0 (-1.8, -0.2) 0.001 0.8 (-0.3, 1.9) 0.064 | 0.030

BMI (kg/m2) Baseline 29.5 ± 4.4a 31.6 ±4.1 Δ 12-weeks 0.9 (-0.1, 0.3) 0.386 0.0 (-0.2, 0.1) 0.864 0.1 (-0.1, 0.3) 0.509 | 0.516

Δ 24-weeks -0.1 (-0.4, 0.1) 0.268 -0.4 (-0.7, -0.1) 0.001 0.3 (-0.1, 0.7) 0.066 | 0.046

Waist Circumference (cm)

Baseline 100.0 ± 12.3a 105.7 ± 10.5 Δ 12-weeks -0.6 (-1.4, 0.3) 0.179 -1.3 (-2.0, -0.7) 0.001 0.8 (-0.2, 1.8) 0.271 | 0.254

Δ 24-weeks -1.3 (-2.4, -0.2) 0.001 -2.6 (-3.4, 1.8) 0.001 12.6 (-0.1, 2.6) 0.083 | 0.180 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments

Page | 393

for age, gender, ethnicity and moderate-vigorous physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 394

Table 7: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for total body and regional (arms and legs) fat mass and lean mass and appendicular lean mass.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Total Body

Fat Mass (kg) Baseline 30.68 ± 8.55 34.14 ± 9.47 Δ 24-weeks -0.73 (-1.41, -0.06) 0.029 -1.33 (-1.98, -0.67) 0.001 -0.60 (-0.34, 1.54) 0.206 | 0.169 Lean Mass (kg) Baseline 49.58 ± 10.97a 53.53 ± 9.33

Δ 24-weeks 0.85 (0.38, 1.31) 0.001 0.51 (0.12, 0.90) 0.008 0.19 (-0.38, 0.76) 0.270 | 0.213 Percentage Fat Mass (%) Baseline 38.05 ± 7.70 38.73 ± 8.35

% Δ 24-weeks -0.89 (-1.48, -0.31) 0.002 -1.25 (-1.78, -0.72) 0.001 0.36 (-0.42, 1.14) 0.357 | 0.334 Appendicular Lean Mass (kg)

Baseline 22.10 ± 5.37a 24.47 ± 4.73

Δ 24-weeks 0.53 (0.31, 0.74) 0.001 0.21 (0.01, 0.40) 0.031 0.32 (0.03, 0.60) 0.027 | 0.184

Page | 395

Arms

Fat Mass (kg) Baseline 3.11 ± 1.09 3.46 ± 1.48

Δ 24-weeks -0.03 (-0.01, 0.06) 0.479 -0.07 (-0.16, 0.02) 0.136 0.04 (-0.10, 0.17) 0.584 | 0.441 Lean Mass (kg) Baseline 5.70 ± 1.56a 6.38 ± 1.28

Δ 24-weeks 0.25 (0.16, 0.34) 0.001 0.13 (0.04, 0.21) 0.003 0.09 (-0.03, 0.22) 0.054 | 0.066

Legs

Fat Mass (kg) Baseline 8.36 ± 3.05 9.56 ± 4.26

Δ 24-weeks -0.13 (-0.32, 0.00) 0.149 -0.26 (-0.46, -0.07) 0.007 0.01 (-0.01, 0.04) 0.334 | 0.357 Lean Mass (kg) Baseline 16.35 ± 3.89a 18.10 ± 3.54

Δ 24-weeks 0.28 (0.01, 0.05) 0.001 0.01 (-0.08, 0.02) 0.305 0.20 (-0.04, 0.43) 0.095 | 0.141 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 396

Table 8: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks from baseline for 25% femur muscle cross-sectional area (CSA), density and intermuscular plus subcutaneous fat CSA.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Muscle CSA Baseline (cm2) 59.1 ± 12.8a 66.3 ± 14.6 % Δ 24-weeks 4.9 (2.2, 7.6) 0.001 2.3 (0.1, 4.4) 0.177 2.6 (-0.7, 6.0) 0.056 | 0.078

Muscle Density

Baseline (mg/cm3) 73.4 ± 3.4 73.4 ± 2.8

% Δ 24-weeks 0.2 (-1.1, 1.5) 0.895 0.8 (0.1, 1.6) 0.041 -0.6 (-2.1, 0.8) 0.336 | 0.497

Intermuscular Fat Area (cm2)

Baseline 21.3 ± 6.3 22.1 ± 4.9

% Δ 24-weeks 1.0 (-3.5, 5.5) 0.964 -1.5 (-5.5, 2.5) 0.244 2.5 (-3.5, 8.4) 0.419 | 0.469

Subcutaneous Fat Area (cm2)

Baseline 40.2 ± 22.2 47.8 ± 32.2 % Δ 24-weeks -3.2 (-7.4, 1.0) 0.362 -2.6 (-5.9, 0.8) 0.620 -0.6 (-5.8, 4.7) 0.906 | 0.616

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-

Page | 397

value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. a P<0.05 vs PRT at baseline. CSA, Cross sectional area; PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 398

Table 9: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 24-weeks relative to baseline in leg press and seated row one-repetition maximum muscle strength and knee extensor isometric muscle strength.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 1-RM Leg Press

Baseline (kg) 177.6 ± 67.8 206.8 ± 90.5

% Δ 24-weeks 18.8 (10.7, 26.8) 0.001 13.5 (4.4, 22.7) 0.003 5.2 (-7.1, 17.5) 0.408 | 0.710

1-RM Seated Row

Baseline (kg) 51.2 ± 17.2a 58.2 ± 16.7

% Δ 24-weeks 16.8 (7.8, 25.8) 0.001 4.2 (-1.2, 9.6) 0.120 12.7 (2.7, 22.6) 0.033 | 0.041

Knee Extensor Strength

Baseline (kg) 36.9 ± 13.7 42.0 ± 14.5

% Δ 12-weeks 7.7 (4.4, 11.0) 0.001 9.4 (6.4, 12.4) 0.001 -1.7 (-6.1, 2.7) 0.391 | 0.227 % Δ 24-weeks 26.3 (14.6, 38.1) 0.001 29.1 (17.1, 41.0) 0.001 -4.8 (-21.1, 11.6) 0.313 | 0.229

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 399

Table 10: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for systolic and diastolic blood pressure.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Systolic Blood Pressure (mmHg)

Baseline 138.0 ± 16.52 135.1 ± 12.58

Δ 12-weeks -4.6 (-9.0, -0.17) 0.167 -0.1 (-5.2, 5.0) 0.965 -4.5 (-11.3, 2.3) 0.273 | 0.244 Δ 24-weeks -3.9 (-8.9, 1.2) 0.017 -3.5 (-7.9, 1.0) 0.166 -0.4 (-7.0, 6.3) 0.273 | 0.181

Diastolic Blood Pressure (mmHg) Baseline 85.7 ± 9.9 83.8 ± 7.4 Δ 12-weeks -2.9 (-5.5, -0.4) 0.032 -1.1 (-3.5, 1.3) 0.378 -1.8 (-5.3, 1.6) 0.315 | 0.307 Δ 24-weeks -8.0 (-15.9, 0.0) 0.040 -3.5 (-8.0, 1.0) 0.010 -4.50 (-13.1, 4.1) 0.789 | 0.999

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, anti-hypertensive use and moderate-vigorous physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 400

Table 11: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum total cholesterol, HDL and LDL cholesterol and triglycerides.

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Total Cholesterol (mmol/L)

Baseline 4.39 ± 1.21 4.17 ± 0.95

Δ 12-weeks -0.21 (-0.45, 0.03) 0.041 -0.02 (-0.15, 0.10) 0.762 -0.19 (-0.44, 0.07) 0.128 | 0.079 Δ 24-weeks -0.22 (-0.44, 0.00) 0.030 0.02 (-0.13, 0.17) 0.783 -0.24 (-0.49, 0.01) 0.049 | 0.014

HDL Cholesterol (mmol/L)

Baseline 1.26 ± 0.35 1.23 ± 0.28

Δ 12-weeks -0.02 (-0.09, 0.04) 0.426 0.03 (-0.01, 0.08) 0.148 -0.05 (-0.12, 0.02) 0.118 | 0.081 Δ 24-weeks 0.00 (-0.06, 0.04) 0.708 0.00 (-0.05, 0.05) 0.973 0.00 (-0.08, 0.06) 0.766 | 0.560

LDL Cholesterol (mmol/L)

Baseline 2.41 ± 1.00 2.11 ± 0.81 Δ 12-weeks -0.18 (-0.37, 0.02) 0.034 -0.04 (-0.14, 0.06) 0.537 -0.13 (-0.35, 0.07) 0.203 | 0.169 Δ 24-weeks -0.20 (-0.38, -0.01) 0.018 0.07 (-0.06, 0.21) 0.271 -0.27 (-0.49, -0.05) 0.011 | 0.003

Page | 401

Triglycerides (mmol/L)

Baseline 1.59 ± 0.75 1.84 ± 0.95 Δ 12-weeks -0.02 (-0.21, 0.16) 0.786 -0.03 (-0.25, 0.19) 0.781 0.01 (-0.28, 0.30) 0.960 | 0.977 Δ 24-weeks -0.03 (-0.19, 0.13) 0.724 0.01 (-0.35, 0.27) 0.931 -0.04 (-0.35, 0.28) 0.782 | 0.704

Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI, lipid-lowering medication and moderate habitual physical activity. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 402

Table 12: Baseline values and percent changes in the PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum levels of interleukin (IL)-10, IL-6, IL-8, tumour necrosis factor-alpha (TNF-α), adiponectin and high-sensitive C-reactive protein (CRP).

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 IL-10

Baseline (pg/ml) 9.45 ± 11.12 11.16 ± 19.69

% Δ 12-weeks 55.9 (22.2, 89.7) 0.001 -12.7 (-28.5, 3.0) 0.061 68.7 (33.9, 103.5) 0.001 | 0.001 % Δ 24-weeks 57.4 (23.2, 91.6) 0.001 -14.8 (-30.9, 1.3) 0.030 72.2 (36.8, 107.5) 0.001 | 0.001

IL-6

Baseline (pg/ml) 2.75 ± 2.31 2.59 ± 2.14

% Δ 12-weeks 22.8 (-4.9, 50.5) 0.073 -12.3 (-32.5, 8.0) 0.267 35.1 (19.4, 68.2) 0.037 | 0.047 % Δ 24-weeks 30.7 (9.3, 52.2) 0.016 -4.4 (-26.5, 17.7) 0.687 35.1 (4.4, 65.8) 0.036 | 0.051

IL-8

Baseline (pg/ml) 15.18 ± 8.18 15.03 ± 7.25

% Δ 12-weeks 10.8 (-2.1, 23.8) 0.062 1.1 (-5.6, 7.8) 0.761 9.7 (-4.0, 23.4) 0.142 | 0.106 % Δ 24-weeks 5.2 (-2.8, 13.1) 0.379 7.4 (-0.3, 15.0) 0.043 -2.2 (-13.1, 8.8) 0.736 | 0.671

Page | 403

TNF-a

Baseline (pg/ml) 7.69 ± 2.23 7.71 ± 2.48 % Δ 12-weeks 2.6 (-3.7, 9.0) 0.369 -3.2 (-9.2, 2.9) 0.343 5.8 (-2.9, 14.5) 0.198 | 0.202

% Δ 24-weeks 3.3 (-2.7, 9.3) 0.260 2.0 (-4.8, 8.9) 0.503 1.3 (-7.8, 10.4) 0.784 | 0.751

Adiponectin

Baseline (µg/mL) 3.23 ± 2.25 2.93 ± 1.25 % Δ 12-weeks -1.0 (-8.2, 6.3) 0.343 -3.5 (-7.8, 0.9) 0.150 2.5 (-5.6, 10.5) 0.532 | 0.512

% Δ 24-weeks -3.7 (-7.8, 0.3) 0.503 -2.2 (-7.5, 3.0) 0.349 -1.5 (-8.2, 5.2) 0.691 | 0.240

High sensitive-CRP

Baseline (mg/mL) 1.59 ± 1.34 2.08 ± 2.36 % Δ 12-weeks -8.4 (-35.6, 18.9) 0.512 -1.4 (-23.5, 20.6) 0.893 -6.9 (-41.1, 27.2) 0.674 | 0.672

% Δ 24-weeks -6.8 (-29.0, 15.3) 0.593 9.6 (-13.9, 33.1) 0.367 -16.4 (-48.8, 15.9) 0.319 | 0.431 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate habitual physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 404

Table 13: Baseline values and absolute within-group changes in PRT+ProD and PRT groups and the net between-group differences for the change at 12- and 24-weeks relative to baseline for serum creatinine, estimated glomular filtration (eGFR), 25-hydroxyvitamin D (25(OH)D) and insulin-like growth factor-1 (IGF-1).

Baseline Values and Within-Group Changes

PRT+ProD PRT Intervention Effects

Mean ± SD or

(95% CI) P-value Mean ± SD or

(95% CI) P-value Net Difference

(95% CI) P- values

Model 1 | Model 3 Creatinine (mol/L)

Baseline 74.41 ± 13.27a 80.70 ± 15.83

Δ 12-weeks 2.27 (-0.47, 5.01) 0.097 -1.02 (-3.58, 1.54) 0.411 3.29 (-0.42, 6.99) 0.075 | 0.113 Δ 24-weeks 5.10 (2.39, 7.80) 0.001 4.24 (1.49, 6.99) 0.001 0.86 (-2.99, 4.70) 0.642 | 0.449

eGFR (ml/min/1.73m2)

Baseline 85.00 ± 6.81a 80.38 ± 11.77

Δ 12-weeks -0.98 (-2.50, 0.53) 0.320 0.80 (-1.21, 2.81) 0.404 -1.78 (-4.35, 0.80) 0.199 | 0.258 Δ 24-weeks -3.83 (-6.00, -1.66) 0.001 -3.10 (-5.23, -0.97) 0.001 -0.73 (-3.75, 2.29) 0.598 | 0.510

25(OH)D (nmol/L)

Baseline 78.77 ± 22.30 68.12 ± 22.21

Δ 12-weeks 26.74 (18.82, 34.66) 0.001 3.06 (-2.09, 8.20) 0.257 23.68 (14.68, 32.69) 0.001 | 0.001 Δ 24-weeks 33.88 (25.82, 41.95) 0.001 5.05 (-1.39, 11.49) 0.061 28.83 (-18.79, 38.88) 0.001 | 0.001

Page | 405

IGF-1 (nmol/L)

Baseline 20.62 ± 6.96 20.4 ± 7.50 Δ 12-weeks 0.48 (-0.56, 1.51) 0.365 -0.82 (-1.53, -0.12) 0.063 1.30 (0.10, 2.51) 0.057 | 0.068

Δ 24-weeks 0.80 (-0.32, 1.93) 0.127 -0.25 (-1.29, 0.79) 0.568 1.06 (-0.46, 2.57) 0.122 | 0.054 Baseline values represent mean ± SD and within group changes and net differences represent means with 95% confidence intervals (CI). Intervention effect refers to the within group change from baseline in the intervention group minus the within group change from baseline in the control group. All change values and net differences were derived from unadjusted values. Significant differences are highlighted in bold. Model 1 represents unadjusted P-values. Model 3 represents the P-value after adjustments for age, gender, ethnicity, BMI and moderate habitual physical activity. a P<0.05 vs PRT at baseline. PRT+ProD, progressive resistance training plus protein and vitamin D supplements; PRT, progressive resistance training.

Page | 406