Physical Activity and Mortality in Individuals With Diabetes Mellitus

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Physical Activity and Mortality in IndividualsWith Diabetes Mellitus

A Prospective Study and Meta-analysis

Diewertje Sluik, MSc; Brian Buijsse, PhD; Rebecca Muckelbauer, PhD; Rudolf Kaaks, PhD; Birgit Teucher, PhD;Nina Føns Johnsen, PhD; Anne Tjønneland, PhD; Kim Overvad, PhD; Jane Nautrup Østergaard, PhD;Pilar Amiano, MSc; Eva Ardanaz, PhD; Benedetta Bendinelli, PharmD; Valeria Pala, PhD; Rosario Tumino, MD;Fulvio Ricceri, MSc; Amalia Mattiello, MD; Annemieke M. W. Spijkerman, PhD; Evelyn M. Monninkhof, PhD;Anne M. May, PhD; Paul W. Franks, PhD; Peter M. Nilsson, MD, PhD; Patrik Wennberg, PhD;Olov Rolandsson, MD, PhD; Guy Fagherazzi, PhD; Marie-Christine Boutron-Ruault, MD, PhD;Francoise Clavel-Chapelon, PhD; Jose Marıa Huerta Castano, PhD; Valentina Gallo, PhD;Heiner Boeing, PhD; Ute Nothlings, DrPH

Background: Physical activity (PA) is considered a cor-nerstone of diabetes mellitus management to prevent com-plications, but conclusive evidence is lacking.

Methods: This prospective cohort study and meta-analysis of existing studies investigated the associationbetween PA and mortality in individuals with diabetes.In the EPIC study (European Prospective InvestigationInto Cancer and Nutrition), a cohort was defined of 5859individuals with diabetes at baseline. Associations of lei-sure-time and total PA and walking with cardiovasculardisease (CVD) and total mortality were studied using mul-tivariable Cox proportional hazards regression models.Fixed- and random-effects meta-analyses of prospectivestudies published up to December 2010 were pooled withinverse variance weighting.

Results: In the prospective analysis, total PA was asso-ciated with lower risk of CVD and total mortality. Com-pared with physically inactive persons, the lowest mor-tality risk was observed in moderately active persons:

hazard ratios were 0.62 (95% CI, 0.49-0.78) for total mor-tality and 0.51 (95% CI, 0.32-0.81) for CVD mortality.Leisure-time PA was associated with lower total mortal-ity risk, and walking was associated with lower CVD mor-tality risk. In the meta-analysis, the pooled random-effects hazard ratio from 5 studies for high vs low totalPA and all-cause mortality was 0.60 (95% CI, 0.49-0.73).

Conclusions: Higher levels of PA were associated withlower mortality risk in individuals with diabetes. Eventhose undertaking moderate amounts of activity were atappreciably lower risk for early death compared with in-active persons. These findings provide empirical evi-dence supporting the widely shared view that persons withdiabetes should engage in regular PA.

Arch Intern Med.Published online August 6, 2012.doi:10.1001/archinternmed.2012.3130

D IABETES MELLITUS IS A MA-jor cause of illness andpremature death in mostcountries.1 Efforts to re-duce the impact of diabe-

tes complications have been predomi-nantly aimed at controlling hyperglycemia,

hypertension, and dyslipidemia by usingmedication strategies, despite the lack ofevidence of long-term benefits.2,3 How-ever, diabetes management should ex-tend to an overall intervention strategy thatincludes lifestyle modification to reducethe risk of complications.4

Lifestyle measures, including physicalactivity (PA), are key factors for self-management in patients with diabetes toprevent macrovascular complications andpremature mortality.5 Increased PA has longbeen considered a cornerstone of diabetesmanagement. Persons with diabetes are rec-ommended to engage in at least 150 min-utes per week of moderate-intensity aero-bic PA.5,6 Walking has been of particularinterest because it requires no specific fa-cilities, can be easily implemented in thedaily routine, and is relatively safe.7

In the general population, being physi-cally active has been associated with alower risk of overall and cardiovascular dis-ease (CVD) mortality compared with being

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inactive.8 Because persons with dia-betes are at higher risk for CVD andpremature death, it is important todetermine whether PA can pro-duce similar beneficial effects in thishigh-risk population. Indeed, a meta-analysis9 of 14 controlled trials indiabetic persons showed that exer-cise programs had beneficial effectson glycemic control. Several pro-spective cohort studies10-21 havefound that higher PA levels were as-sociated with reduced CVD and totalmortality rates, but conclusive high-level evidence is lacking.

The objective was to investigatewhether PA—total, leisure time, andwalking—was associated with CVDand total mortality in a large co-hort of individuals with diabetes. Ameta-analysis summarizing evi-dence from prospective studies wasperformed to put the present find-ings in context and to provide ahigher level of evidence.

METHODS

STUDY DESIGN ANDPOPULATION

The EPIC study (European Prospec-tive Investigation Into Cancer and Nu-trition) is an ongoing prospective studyof 519 978 men and women aged 35 to70 years from 23 study centers in 10 Eu-ropean countries.22 Within the EPICstudy, a cohort was established of par-ticipants with a confirmed diagnosis ofdiabetes mellitus at baseline between1992 and 2000. As described previ-ously,23,24 15 study centers from 6 coun-tries provided additional data on diabe-tes diagnosis and medications. Noinformation was available to distin-guish type 1 and 2 diabetes mellitus. Tobe considered diabetic, a self-reporteddiagnosis at baseline had to be con-firmed by at least 1 additional informa-tion source. Depending on the avail-able options in the study centers, thesesources included contact with a physi-cian, self-reported use of diabetes medi-cation, confirmation of self-reported dia-betes status during follow-up, linkage todiabetes registries, and a baseline gly-cated hemoglobin (HbA1c) level greaterthan 6%. The cohort comprised 6412 in-dividuals with confirmed diabetes atstudy enrollment. After the exclusion ofparticipants without follow-up informa-tion on vital status (n = 27), partici-pants with extreme or implausible en-ergy intakes (n=177), and participants

with missing PA data (n=349, includ-ing the cohort in Umea, Sweden), theanalytical sample included 5859 indi-viduals.

PA ASSESSMENT

At baseline, participants received a life-style questionnaire by mail, which theycompleted at home. This questionnaireasked about occupational activity andduration and frequency of walking, cy-cling, gardening (average values of sum-mer and winter), household work, do-it-yourself activities, and sports duringthe past year.

Total PA was investigated using theCambridge Physical Activity Index,25

which combines self-reported occupa-tional activity with time participating incycling and sports. Occupational activ-ity was categorized as sedentary, stand-ing, manual, or heavy manual. The sumof hours per week spent on cycling andsports was categorized into 4 levels.Based on a 4�4 matrix, participantswere divided into 4 categories, that is,inactive (sedentary job and no recre-ational activity), moderately inactive,moderately active, and active (seden-tary job with �1 hour of recreational ac-tivity per day, standing or physical jobwith some recreational activity, or aheavy manual job). The index has beenshown to have acceptable repeatability,and it was positively associated with ob-jective measures of the ratio of daytimeexpenditure to resting metabolic rate andcardiorespiratory fitness.25

Leisure-time PA included walking,cycling, gardening, sports, householdwork, and do-it-yourself activities. Du-ration and frequency were directly as-sessed, and intensity, that is, energy ex-penditure, was estimated by assigningmetabolic equivalents (METs), rangingfrom 3 for walking and household ac-tivities to 6 for sports.26 A MET is de-fined as the ratio of work metabolic rateto a standard metabolic rate of 1.0 kcal(4.184 kJ)�kg−1�h−1. One MET isthe energy expended by a person whilesitting quietly.

COVARIATE ASSESSMENT

Diabetes duration was calculated by sub-tracting the self-reported year of diag-nosis or, when available, the exact dateof diagnosis supplied by the physicianfrom the year of baseline examination.Insulin therapy or use of oral hypogly-cemic agents was either self-reportedduring the visit at the study center or wasobtained through medical verification;this information was not collected inSpain and Denmark. Moreover, the life-

style questionnaire included a questionabout insulin therapy. When a partici-pant did not report the use of diabetesmedication during the visit or reportedinsulin therapy in the questionnaire, weassumed that the participant did not takemedication.

Dietary intake, including alcohol con-sumption during the past year, was as-sessed using country-specific instru-ments.22 Weight and height weremeasured with participants not wear-ing shoes. Systolic and diastolic bloodpressures were measured by trained per-sonnel at baseline except in Navarra,Spain. The HbA1c level was measured inerythrocytes of blood collected at base-line except in Denmark. Smoking be-havior, educational level, and preva-lence of myocardial infarction, stroke,and cancer were assessed using ques-tionnaires.

OUTCOME ASCERTAINMENT

Sixty-one participants (1%) were lost tofollow-up. For those completely fol-lowed up, causes and dates of deathswere ascertained using record linkageswith local, regional, or central cancer reg-istries, boards of health, or death indi-ces. An exception was Germany, wheredeceased participants were identifiedwith follow-up mailings and subse-quent inquiries to municipality regis-tries, regional health departments, phy-sicians, or hospitals. Mortality data werecoded according to the InternationalClassification of Diseases, Injuries, andCauses of Death, Tenth Revision, using thecodes I00-I99 for CVD mortality.

STATISTICAL ANALYSIS

Hazard ratios (HRs) and 95% CIs of totaland CVD mortality were calculated usingCox proportional hazards regression anda commercially available software pro-gram (SAS, version 9.2; SAS Institute,Inc).27 Total PA was analyzed in 4 cat-egories, and leisure-time PA (MET-hours per week) and walking (hours perweek) were analyzed in quartiles. Thelowest category or quartile was the ref-erence. Center and age at recruitment in1-year categories were entered as stra-tum variables.28 Age was used as the un-derlying time scale, with entry time de-fined as the participant’s age (in years)at recruitment and exit time defined asthe participant’s age (in years) at deathor censoring.

The HRs were adjusted for sex(model 1); disease duration (years); useof diabetes-related medication (none, in-sulin, oral hypoglycemic agents, orboth); self-reported myocardial infarc-




tion, stroke, or cancer; alcohol consump-tion (grams per day); smoking status(never, former [quit �10, 11-20, or �20years ago], or current), smoking dura-tion (�10, 11-20, 21-30, 31-40, or �41years), and number of cigarettes cur-rently smoked (�15, 15-24, or �25 perday); education (5 categories); energy in-take (kilocalories per day); and factorscores for the first 3 patterns derivedfrom factor analysis on 16 food groups(model 2).

Among the covariates, proportions ofmissing data were 31% for diabetes medi-cation, 8% for disease duration, 5% forprevalence of cancer, 1% for preva-lence of myocardial infarction or stroke,and less than 1% for diet and educa-tion. These missing values were im-puted using the multiple imputationtechnique.29 All the variables includedin the multivariable adjustment modelwere included in the imputation proce-dure, and 20 duplicate data sets weresampled.30

In sensitivity analyses, it was checkedwhether additional adjustment for HbA1c

level, BMI, and systolic blood pressureaffected the risk estimates. Prevalentcases of myocardial infarction, stroke,and cancer and participants with fol-low-up of less than 2 years (n=5039)were excluded. Statistical interaction bysex, body mass index (BMI), and insu-lin therapy was tested by adding a prod-uct term to the multivariable adjust-ment model. Finally, results werecompared with analyses without mul-tiple imputation (n=5376), in whichparticipants with missing values for con-tinuous variables were excluded, andmissing values for categorical variableswere modeled as a separate indicatorvariable.

META-ANALYSIS

A systematic literature search inMEDLINE and ISI Web of Knowledge forprospective studies on PA published upto December 2010 yielded 4344 publi-cations, of which 12 were included in themeta-analysis (eFigure 1; http://www.archinternmed.com). Study qualityscores were assigned using the Newcastle-Ottawa Scale (eTable); quality criteria in-cluded representativeness, exposure andoutcome ascertainment, adjustment, fol-low-up, and attrition.31 The most com-plete adjusted HRs and 95% CIs of thehighest vs the lowest activity categorywere extracted. Study selection, qualityassessment, and data extraction was per-formed by 2 of us (D.S. and B.B.) inde-pendently; any discrepancies between the2 were resolved by discussion. Fixed- andrandom-effects meta-analyses with in-

verse variance weighting were per-formed using R package “meta” (ver-sion 2.12.2). Heterogeneity was assessedby the Q statistic and the I2 index.

RESULTS

BASELINE CHARACTERISTICS

Individuals who were more physi-cally active were younger, weremore likely to be male, had a lowerBMI and a lower HbA1c level, andhad a shorter diabetes durationthan did those who were inactive(Table 1). They were also morelikely to use insulin and to reportfewer comorbidities.

PROSPECTIVE ANALYSIS

After median follow-up of 9.4 years,755 participants had died (13%).Death due to CVD accounted for28% of all deaths (n = 212). Total PAwas inversely associated with totaland CVD mortality (Table 2). Thelowest HR was observed in personscategorized as moderately active: theHR in the multivariable adjust-ment model was 0.62 (95% CI, 0.49-0.78) for total mortality. When ex-cluding heavy manual workers andnonworkers from the analyses, thelowest risk was still observed in themoderately active group. Leisure-time PA was also associated with alower risk of CVD and total mortal-ity: the HR in the highest categorywas 0.73 (95% CI, 0.57-0.93) fortotal mortality. The association withCVD mortality was weaker in mag-nitude and nonsignificant butshowed the same trend. Partici-pants who walked more than 2 hoursper week had lower CVD mortalityrisk compared with those in the low-est activity group: the HR in the cat-egory of 2 to 4.5 hours per week was0.54 (95% CI, 0.36-0.82). The rela-tionship of walking with total mor-tality was less pronounced. Addi-tional adjustment for vigorous PAdid not alter the association.

Adjustment for intermediate fac-tors did not affect the risk esti-mates. For total PA, the HR in mod-erately active persons was 0.62 (95%CI, 0.50-0.79) after additional ad-justment for HbA1c and 0.62 (95%CI, 0.49-0.78) after additional ad-

justment for BMI or systolic bloodpressure. Excluding participantswith comorbidities at baseline led tolower HRs: for total PA, the HR inmoderately active persons was 0.58(95% CI, 0.43-0.77) for total mor-tality and 0.31 (95% CI, 0.15-0.60)for CVD mortality. Sex seemed tomodify the association between totalPA and total mortality (P for inter-action = .04, multivariable model).Women had a lower HR across quar-tiles than did men, but the trendshowed the same direction (the HRin the highest category was 0.79[95% CI, 0.59-1.05] in men and 0.59[95% CI, 0.36-0.96] in women). Theanalyses without multiple imputa-tion showed similar results (the HRfor total mortality in the highest cat-egory of total PA was 0.70 [95% CI,0.54-0.90]), indicating that miss-ing observations did not influencethe effect estimates.

META-ANALYSIS

In the 12 cohort studies10,13-15,17-21,32-34

included in the meta-analyses, veri-fication criteria of diabetes statusranged from self-report to an oralglucose tolerance test; 4 studies usedofficial diagnostic criteria (Table3).Sample sizes ranged from 29221 to5859 (the present study), and meanfollow-up was 12.5 years. Physicalactivity was assessed by question-naire in 8 studies10,14,17,19,20,32-34 andby interview in 4.13,15,18,21 Partici-pants were divided into PA catego-ries ranging from inactive to active.All but 1 study13 adjusted for a widerange of multiple risk factors. Studyquality ranged from 613,14,19,34 to 918

stars of a maximum of 9. Three stud-ies19,20,33 reported on total PA butmeasured only leisure-time activi-ties and were, therefore, classified assuch.

The meta-analyses of prospec-tive studies showed that the high-est levels of total and leisure-time PAand walking were associated with alower risk of total and CVD mortal-ity compared with a low activity level(Figures 1, 2, and 3). Magni-tudes of associations were similar fortotal and CVD mortality.

Significant heterogeneity wasfound for total PA and total mortal-ity (I2 = 69%, P = .01) and for walk-ing and total mortality (I2 = 71%;




P = .01). For walking, an influen-tial meta-analysis revealed that thepresent study contributed most

heterogeneity, although excludingthe present study from the meta-analyses did not substantially influ-

ence the pooled HR. Visual inspec-tion of funnel plots did not indicatepublication bias (eFigure 2).

Table 1. Baseline Characteristics of 5859 Individuals With Diabetes Mellitus Across Categories of Total Physical Activity

Variable

Total Physical Activitya

Inactive(n = 1793)

Moderately Inactive(n = 1897)

Moderately Active(n = 1171)

Active(n = 998)

Men, % 47 53 61 61Age, mean (SD), y 58.5 (6.6) 58.0 (6.4) 56.6 (6.6) 56.6 (6.3)HbA1c, mean (SD), % 8.3 (2.0) 8.2 (1.9) 8.1 (1.9) 8.1 (2.0)Disease duration, median (IQR), y 5.2 (2.3-11.0) 5.1 (2.1-10.6) 4.6 (1.9-9.9) 4.2 (2.0-8.2)Medication use, %

None 24 27 26 22Insulin and OHA 8 11 10 13Insulin only 24 25 29 36OHA only 43 38 36 29

Types of physical activity, MET-h/wk, median (IQR)Cycling 0 (0-0) 3 (0-9) 9 (0-24) 23.3 (6-45)Sports 0 (0-0) 0 (0-6) 0 (0-12) 6 (0-21)Gardening 0 (0-8) 3 (0-12) 4 (0-14) 4 (0-12)Do-it-yourself activities 0 (0-4.5) 0 (0-9) 0 (0-9) 0 (0-9)Housework activity 27 (6-63) 18 (6-48) 15 (3-42) 15 (3-36)Walking 13.5 (4.5-27) 13.5 (6-25.5) 13.5 (6-25.5) 15 (7.5-27)Stair climbing 0.5 (0-1.6) 1 (0-2.3) 1.0 (0-2.6) 1.2 (0-2.6)Vigorous physical activity 2 (1-5) 2 (1-3) 2 (1-3) 3 (1-4)

Physical activity at work, %Sedentary occupation 28 26 16 9Standing occupation 0 17 31 21Manual work 0 0 16 32Heavy manual work 0 0 0 12Nonworker 69 54 35 25Unknown 3 3 2 1

BMI, mean (SD)Men 28.8 (4.4) 28.4 (4.1) 28.4 (4.4) 28.0 (4.1)Women 30.0 (5.7) 29.1 (5.5) 28.7 (5.1) 28.7 (5.6)

Waist-height ratio, mean (SD)Men 0.59 (0.07) 0.58 (0.07) 0.58 (0.07) 0.57 (0.06)Women 0.59 (0.09) 0.57 (0.08) 0.56 (0.08) 0.56 (0.09)

Energy intake, mean (SD), kcal/d 2007 (606) 2073 (613) 2138 (648) 2229 (676)Alcohol consumption, median (IQR), g/d 3.2 (0-17.0) 6.9 (0.9-21.6) 8.2 (1.5-25.5) 9.3 (1.7-25.6)Factor scores, mean (SD)b

Healthy pattern −0.01 (0.98) −0.07 (0.98) 0.004 (1.04) 0.13 (1.02)Traditional pattern −0.13 (0.99) −0.04 (0.95) 0.05 (1.00) 0.27 (1.05)Modern pattern −0.04 (0.98) 0.01 (1.01) 0.01 (0.99) 0.03 (1.03)

Smoking status, %Never 41 38 37 37Former 33 38 38 37Current 26 24 25 26

Educational level, %None 6 3 4 3Primary school 43 40 40 43Technical/professional school 22 27 28 31Secondary school 12 11 11 9Higher, including university degree 16 18 17 14

Comorbidities, %Hypertension 59 57 52 52Myocardial infarction 8 7 6 6Stroke 5 4 3 2Cancer 4 5 4 2

Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); HbA1c, glycated hemoglobin; IQR, interquartilerange; MET, metabolic equivalent; OHA, oral hypoglycemic agent.

aClassification of total physical activity level according to the Cambridge Physical Activity Index based on occupational activity and duration of cycling andsports.

bDerived from factor analysis of 16 food groups, the “healthy pattern” (eigenvalue, 2.16) was characterized by high intake of fruit, vegetables, legumes, andfish; the “traditional pattern” (eigenvalue, 2.00) by high intake of potatoes, dairy, eggs, meat, and sugar; and the “modern pattern” (eigenvalue, 1.76) by highintake of cereals, fats, cakes, and biscuits.




COMMENT

In this prospective analysis andmeta-analysis of individuals withdiabetes, higher levels of total PA, lei-sure-time PA, and walking were as-sociated with a lower risk of total andCVD mortality. In the prospectiveanalysis, people who reported beingmoderately physically active hadlower mortality risk compared with

those who reported being physi-cally inactive.

In persons with diabetes, an in-creaseinPAhasbeenshowntoreduceHbA1c levels9,35 and improve insulinsensitivity.36 Moreover, PA has beenshowntohavebeneficialeffectsonin-flammation, hypertension, dyslipid-emia, endothelial function, and ab-dominaladiposityinpersonswithandwithout diabetes.37-40

PROSPECTIVE ANALYSIS

The association between total PAand mortality was slightly J-shaped. This could have been due tomisclassification of activity levels,which may be higher in the mostphysically active group owing to la-beling bias. This result is in con-trast to the other studies15,19,21,32,34 in-cluded in the meta-analysis, which

Table 2. HRs (95% CIs) for Associations Between Total Physical Activity, Leisure-Time Physical Activity, and Walking and Totaland CVD Mortality in 5859 Individuals With Diabetes Mellitus

Variable Inactive Moderately Inactive Moderately Active Active P Trend

Total Physical Activitya

Total mortalityCases/PY 304/15 941 271/17 230 115/10 768 119/9253Incidence rate per 1000 PY 19.1 15.7 10.7 12.9Sex-adjusted HR (95% CI)b 1 [Reference] 0.64 (0.53-0.76) 0.53 (0.42-0.66) 0.62 (0.50-0.78) �.001Multivariable HR (95% CI)c 1 [Reference] 0.69 (0.57-0.83) 0.62 (0.49-0.78) 0.74 (0.59-0.94) .001Multivariable HR (95% CI)d 1 [Reference] 0.68 (0.54-0.66) 0.58 (0.43-0.77) 0.81 (0.61-1.08) .03

CVD mortalityCases/PY 99/15 941 61/17 230 27/10 768 25/9253Incidence rate per 1000 PY 6.2 3.5 2.5 2.7Sex-adjusted HR (95% CI)b 1 [Reference] 0.59 (0.43-0.82) 0.40 (0.26-0.63) 0.53 (0.34-0.85) .001Multivariable HR (95% CI)c 1 [Reference] 0.65 (0.46-0.91) 0.51 (0.32-0.81) 0.62 (0.38-1.01) .004Multivariable HR (95% CI)d 1 [Reference] 0.46 (0.28-0.74) 0.31 (0.15-0.60) 0.48 (0.25-0.94) .001

Leisure-Time Physical Activity, MET-h/wke

�45 45-74 75-113 �113Total mortality

Cases/PY 269/14 809 191/11 976 174/12 864 121/13 544Incidence rate per 1000 PY 18.2 15.9 13.5 8.9Sex-adjusted HR (95% CI)b 1 [Reference] 0.80 (0.66-0.98) 0.74 (0.60-0.91) 0.64 (0.50-0.81) �.001Multivariable HR (95% CI)c 1 [Reference] 0.85 (0.70-1.04) 0.80 (0.64-0.99) 0.73 (0.57-0.93) .007Multivariable HR (95% CI)d 1 [Reference] 0.77 (0.60-0.99) 0.79 (0.60-1.03) 0.62 (0.46-0.85) .003

CVD mortalityCases/PY 67/14 809 66/11 976 50/12 864 29/13 544Incidence rate per 1000 PY 4.5 5.5 3.9 2.1Sex-adjusted HR (95% CI)b 1 [Reference] 1.09 (0.76-1.57) 0.83 (0.56-1.24) 0.57 (0.35-0.93) .02Multivariable HR (95% CI)c 1 [Reference] 1.18 (0.81-1.73) 0.90 (0.60-1.37) 0.63 (0.38-1.04) .06Multivariable HR (95% CI)d 1 [Reference] 0.91 (0.54-1.52) 0.69 (0.39-1.24) 0.30 (0.14-0.64) .002

Walking, h/wk�2.0 2.0-4.5 4.6-9.0 �9.0

Total mortalityCases/PY 269/15 930 159/11 778 166/13 302 161/12 183Incidence rate per 1000 PY 16.9 13.5 12.5 13.2Sex-adjusted HR (95% CI)b 1 [Reference] 0.83 (0.67-1.02) 0.83 (0.67-1.02) 0.95 (0.75-1.19) .80Multivariable HR (95% CI)c 1 [Reference] 0.88 (0.71-1.09) 0.86 (0.70-1.07) 0.95 (0.75-1.20) .70Multivariable HR (95% CI)d 1 [Reference] 0.87 (0.67-1.12) 0.76 (0.58-1.00) 0.90 (0.67-1.21) .24

CVD mortalityCases/PY 90/15 930 37/11 778 37/13 302 48/12 183Incidence rate per 1000 PY 5.6 3.1 2.8 3.9Sex-adjusted HR (95% CI)b 1 [Reference] 0.52 (0.35-0.78) 0.49 (0.32-0.75) 0.69 (0.46-1.06) .21Multivariable HR (95% CI)c 1 [Reference] 0.54 (0.36-0.82) 0.50 (0.32-0.77) 0.64 (0.41-0.98) .10Multivariable HR (95% CI)d 1 [Reference] 0.40 (0.22-0.74) 0.44 (0.24-0.79) 0.65 (0.35-1.19) .06

Abbreviations: CVD, cardiovascular disease; HR, hazard ratio; MET, metabolic equivalent; PY, person-years.aClassification of total physical activity level according to the Cambridge Physical Activity Index based on occupational activity and duration of cycling and

sports.bModel 1: age and center stratified and adjusted for sex.cModel 2: model 1 additionally adjusted for diabetes medication (no medication, insulin, oral hypoglycemic agents, or both); disease duration; self-reported

myocardial infarction, stroke, or cancer; alcohol consumption; smoking behavior; educational attainment; energy; and scores for the first 3 dietary patterns derivedfrom a factor analysis of 16 food groups.

dModel 3: excluding participants with self-reported myocardial infarction, stroke, or cancer or follow-up of less than 2 years (n = 5039).eLeisure-time physical activity included walking, cycling, gardening, sports, and household and do-it-yourself activities.




Table 3. Identified Published Prospective Cohort Studies on PA and Mortality in Individuals With Diabetes Mellitus

Source

Patients,No./Sex/Age, y

DiabetesVerification

Follow-up,Mean, y Exposure

Outcome,No. of Cases

OutcomeAscertainment Adjustments Starsa

Batty et al,10 2002,Whitehall IIStudy, UnitedKingdom

352/M/40-64

Type 2 diabetesor IGT: oralglucosetolerance test

25.0 Walking pace:slower/same/faster

Leisure-time activity:inactive/moderatelyactive/active(questionnaire)

215 Totalmortality,79 CHDmortality,39 other CVDmortality

National HealthService Register

Age, employmentgrade, systolicblood pressure,cholesterol level,smoking, BMI,forced expiratoryvolume in 1second, disease atstudy entry

7

Ford andDeStefano,13

1991, NationalHealth andNutritionExaminationSurvey IEpidemiologicFollow-up Study(1982-1984),United States

602/M-F/40-77

Self-reporteddiabetes

10.0 Leisure-time PA:mostactive/moderatelyactive/inactive(interview)

233 Totalmortality,92 CHDmortality

National DeathIndex and othertracing methods

None 6

Gaziano et al,14

2002, Physicians’Health Studyenrollmentcohort, UnitedStates

2838/M/40-84


5.2 Vigorous exercise:1-3 times per mo,1 time/wk,2-4 times/wk,�5 times/wk(questionnaire)

356 Totalmortality

Death certificate,medical records,next of kin

Age, smoking,alcohol, history ofangina or transientischemic attack

6

Gregg et al,15 2003,National HealthInterview Survey,United States

2896/M-F/�18


8 Walking: 0, �0-1.9,�2 h/wk

Total PA: 0, �0-1.9,�2 h/wk(interview)

671 Totalmortality, 316CVD mortality

National DeathIndex

Age, sex, race, BMI,self-rated health,smoking status,weight lossapproaches,hospitalizations,hypertension,physician visits,limitations due toCVD and cancer,level of functionallimitation

8

Hu et al,17 2004, sixindependentpopulationsurveys(1972-1997),Finland

3316/M-F/25-74

Type 2 diabetesconfirmed byWHO criteria

18.4 Occupational:light/moderate/active; commuting:0, 1-29, �30min/d; leisure-timeactivity:low/moderate/high(questionnaire)


Statistics Finland Age, sex, study year,BMI, systolic bloodpressure,cholesterol level,smoking status

7

Hu et al,32 2005, sixindependentpopulationsurveys(1972-1997),Finland

3708/M-F/25-74


18.7 Total PA:low/moderate/high(questionnaire)


Statistics Finland Age, sex, study year,educational level,BMI, systolic bloodpressure, totalcholesterol level,smoking status

7

Jonker et al,21 2006,FraminghamHeart Study,United States

292/M-F/28-62

Random bloodglucose �200mg/dL ortreatment withhypoglycemicagent

12.0 (3Pooledfollow-upperiods)

Total PA:low/moderate/high(interview)

292 Totalmortality

Office andhospitalizationrecords,laboratory testresults, deathcertificates, andautopsy reports

Age, sex, educationallevel, maritalstatus, smoking,baseline diseases(CVD, cancer, leftventricularhypertrophy,arthritis, ankleedema, pulmonarydisease),examination at startof follow-up

8

(continued)




showed linear inverse associations,with the lowest observed HR in thehighest quartile. In the present study,participants with heavy manual workoccupations were automatically as-signed to the “active” category. Be-cause such people are more fre-quently exposed to occupational riskfactors and more often have a lowersocioeconomic status, they may havea more unfavorable risk profile.41

However, excluding heavy manualworkers and nonworkers from theanalyses did not change the find-

ings. Thus, diabetic individuals whoare physically inactive seem to havea higher risk of early death, and al-ready being moderately active mayimprove survival.

Walking may reduce the risk ofCVD in people with diabetes by im-proving glycemic control and otherrisk factors.7 In the present study andmeta-analysis, persons in the high-est quartiles of walking duration hada lower risk of CVD mortality com-pared with those in the lowest quar-tile. In contrast, walking was not re-

lated to significantly lower totalmortality risk in this study, whereasother studies10,15,18,19 in the meta-analysis reported strong inverse re-lationships. In the present study, per-sons in the highest category reportedwalking more than 9 hours per week.Walking levels were lower in theother studies included: in compari-son, persons in the active categoryin the study by Tanasescu et al19

walked more than 16 MET-hours perweek. It is known that Europeans aremore active than North American

Table 3. Identified Published Prospective Cohort Studies on PA and Mortality in Individuals With Diabetes Mellitus (continued)

Source

Patients,No./Sex/Age, y

DiabetesVerification

Follow-up,Mean, y Exposure

Outcome,No. of Cases

OutcomeAscertainment Adjustments Starsa

Nelson et al,33 2010,Third NationalHealth andNutritionExaminationSurvey, UnitedStates

1507/M-F/�17

Self-report 7.6 Leisure-time PA:inactive,insufficient,recommendedlevels(questionnaire)

642 Totalmortality

National DeathIndex

Age, sex,race/ethnicity,educational level,HbA1c level, HDLcholesterol level,BMI, and smokingstatus

8

Smith et al,18 2007,Rancho BernardoStudy, UnitedStates

347/M-F/50-90


10 Walking: nonwalker,�1-mile walker,�1-mile walker(interview)

538 Totalmortality,143 CHDmortality,138 otherCVD mortality

Annual mailingsand telephonecalls, deathcertificatesobtained

Sex, age, smokingstatus, BMI,average drinks perday, exercise,hypertension,triglyceride levels,HDL cholesterollevel, history ofCHD

9

Tanasescu et al,19

2003, HealthProfessionalsFollow-up Study(1986-1998),United States

2803/M/40-75

Self-reporteddiagnosis at�30 yconfirmedwith �1classicsymptomsplus raisedplasmaglucose orOHA use

14 Walking: 0-1.4,1.5-4.1, 4.2-7.9,8.0-16.0, �16.1MET-h/wk

Leisure-time PA:0-5.1, 5.2-12.0,12.1-21.7,21.8-37.1, �37.2MET-h/wk(questionnaire)


Reported in or bylinkage with theNational DeathIndex, CVDconfirmed byreview ofmedical recordsor autopsyreport

Alcohol use, smokingstatus, family MIhistory, vitamin Euse, diseaseduration, OHAs,dietary intake oftrans and saturatedfat, fiber and folicacid, history ofCVD, hypertension,cholesterol level

6

Trichopoulou et al,34

2006, EuropeanProspectiveInvestigation IntoCancer andNutrition, Greece

1013/M-F/�35

Self-reporteddiagnosis anduse ofdiabetesmedication

4.5 Total (occupationaland leisure-time)PA: �30, 30-�32,32-�34, 34-�37,�37 MET-h/d(questionnaire)

80 Totalmortality

Active follow-upby qualifiedphysicians

Sex, age, educationallevel, smokingstatus, waist-heightratio, hipcircumference,insulin use,hypertension, orhyperlipidemiatreatment

6

Wei et al,20 2000,Aerobics CenterLongitudinalStudy, UnitedStates

1188/M/50 Type 2 diabetesdefinedaccording toADA criteria

11.7 Leisure-time PA:active/inactive(questionnaire)

180 Totalmortality

National HealthIndex. Deathcertificatesobtained

Age, examinationyear, CVD history,cholesterol level,smoking status,diabetes status,glucose level,alcohol use,hypertension,overweight

7

Abbreviations: ADA, American Diabetes Association; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CHD,coronary heart disease; CVD, cardiovascular disease; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; IGT, impaired glucose tolerance; MET, metabolicequivalent; MI, myocardial infarction; OHA, oral hypoglycemic agents; PA, physical activity; WHO, World Health Organization.

aStars (maximum = 9) indicate the quality of the studies assessed using the Newcastle-Ottawa Scale.31




populations,42 and it has been ob-served in a Dutch population that ac-tivities of at least moderate inten-sity, but not lower intensity, such aswalking, were related to reducedCVD incidence.43 This seems to be

in contrast to our findings on walk-ing and CVD mortality. However, be-cause no information on walkingpace was available, we cannot drawconclusions about walking inten-sity. In conclusion, although these

results did not reach statistical sig-nificance, from the meta-analysis thepotential benefits of walking on mor-tality are well established.

Reverse causality could have over-estimated the mortality risks if dia-

0.25 0.5 1.0 2.0

Hazard Ratio

A

Source Population HR (95% CI)Gregg et al,15 2003 National Health Interview Survey, United States 0.71 (0.58-0.86)Hu et al,32 2005 Population surveys, Finland 0.52 (0.45-0.60)Jonker et al,21 2006 Framingham Heart Study, United States 0.53 (0.39-0.72)Trichopoulou et al,34 2006 EPIC, Greece 0.33 (0.16-0.71)Present study EPIC, Europe 0.74 (0.59-0.93)

Combined fixed-effects model 0.59 (0.54-0.66)Combined random-effects model 0.60 (0.49-0.73)Heterogeneity: I 2 = 69% (95% CI, 19%-88%), Q = 12.71; (P = .01)

0.25 0.5 1.0 2.0

Hazard Ratio

B

Source Population HR (95% CI)Gregg et al,15 2003 National Health Interview Survey, United States 0.76 (0.57-1.02)Hu et al,32 2005 Population surveys, Finland 0.52 (0.44-0.62)Present study EPIC, Europe 0.62 (0.38-1.01)


Figure 1. Hazard ratios (HRs) and 95% CIs for associations between total physical activity (highest vs lowest category) and total (A) and cardiovascular (B)mortality for individual cohort studies, including the present study, and all the cohort studies combined. EPIC indicates European Prospective Investigation IntoCancer and Nutrition; black squares, estimates for the individual studies; solid horizontal lines, 95% CIs; and white diamonds and dashed vertical lines, combinedestimates for the analysis (the width of the diamond represents the 95% CI).

0.25 0.5 1.0 2.0

Hazard Ratio

A

Source Population HR (95% CI)Batty et al,10 2002 Whitehall Study, United Kingdom 0.61 (0.40-0.92)Ford and DeStefano,13 1991 NHANES, United States 0.84 (0.48-1.47)Gaziano et al,14 2002 Physicians Health Study, United States 0.45 (0.31-0.66)Hu et al,17 2004 Population surveys, Finland 0.73 (0.57-0.94)Nelson et al,33 2010 NHANES III, United States 0.63 (0.49-0.80)Tanasescu et al,19 2003 Health Professionals Follow-up Study, United States 0.58 (0.41-0.83)Wei et al,20 2000 Aerobics Center Longitudinal Study, United States 0.56 (0.40-0.78)Present study EPIC, Europe 0.73 (0.57-0.93)


0.25 0.5 1.0 2.0

Hazard Ratio

B

Source Population HR (95% CI)Batty et al,10 2002 Whitehall Study, United Kingdom 0.39 (0.21-0.72)Ford and DeStefano,13 1991 NHANES, United States 1.35 (0.49-3.71)Hu et al,17 2004 Population surveys, Finland 0.70 (0.51-0.96)Tanasescu et al,19 2003 Health Professionals Follow-up Study, United States 0.55 (0.28-1.08)Present study EPIC, Europe 0.63 (0.38-1.04)


Figure 2. Hazard ratios (HRs) and 95% CIs for associations between leisure-time physical activity (highest vs lowest category) and total (A) and cardiovascular(B) mortality for individual cohort studies, including the present study, and all the cohort studies combined. EPIC indicates European Prospective InvestigationInto Cancer and Nutrition; NHANES, National Health and Nutrition Examination Survey; black squares, estimates for the individual studies; solid horizontal lines,95% CIs; and white diamonds and dashed vertical lines, combined estimates for the analysis (the width of the diamond represents the 95% CI).




betes or comorbidities at baseline ledto inactivity. Excluding participantswith comorbidities at baseline or thefirst 2 years of follow-up strength-enedtheriskestimates, indicatingthatreverse causality is unlikely to ex-plain the results. However, residualconfoundingormisclassificationcan-not be excluded because measures ofdisease severity and comorbiditieswere self-reported.

Adjustment for factors on thecausal pathway may underestimatethe magnitude of the true associa-tion between PA and mortality.11,12

However, risk estimates were not af-fected by additional adjustment forthe intermediate factors HbA1c level,BMI, and systolic blood pressure.

META-ANALYSIS

Physical activity was associated witha lower total mortality risk in dia-betic individuals. These associa-tions are in line with those found inthe general population, where PA re-lates to a 33% lower risk of overallmortality and a 35% lower risk ofCVD mortality compared with in-activity.8 The present meta-analysiswas a “high vs low” comparison. Thisis a common practice for meta-analyses of observational studies, butresults can be difficult to interpret

because absolute levels of PA willvary between studies and are un-known.44 However, this was the bestoption based on the available data.

Statistically significant heteroge-neity was found for the associationsbetween total PA and walking andtotal mortality. Because statisticalheterogeneity is based only on the ef-fect estimates and their precision, itis important to consider clinicalheterogeneity. All the studies in-cludedinthemeta-analysiswerecom-parable in terms of study design, dia-betes population, and outcome.However, an important issue whenperforming meta-analyses of PA iscomparability of the exposure assess-ment, which was heterogeneousacross the included studies. Physi-cal activity was assessed by question-naire or interview, with varying ques-tions, categories, and classifications.Questionnaires, including inter-views, are the most common tools forPA assessment in large epidemio-logic studies because they are inex-pensive and feasible. In general, PAquestionnaires have a low reliabilityand low validity but can be ad-equately used to rank individuals.45

Itwasconsideredappropriate tocom-bine the studies by meta-analyses be-cause all measured common percep-tions of PA levels.

In conclusion, evidence from thepresent study and from previousstudies summarized by meta-analyses supports the widely heldview that PA is beneficially associ-ated with lower mortality in peoplewith diabetes. Although these find-ings highlight that persons with dia-betes should engage in regular PA,5

they need to be confirmed in a long-term randomized controlled trial.Also, because not many patients withdiabetes adhere to this advice,46 fu-ture research should elucidate thedeterminants of physical inactivityand design successful strategies topromote active lifestyles.

Accepted for Publication: May 12,2012.Published Online: August 6, 2012.doi:10.1001/archinternmed.2012.3130Author Affiliations: Department ofEpidemiology, German Instituteof Human Nutrition Potsdam-Rehbrucke, Nuthetal, Germany (MsSluik and Drs Buijsse, Boeing, andNothlings); Berlin School of PublicHealth, Charite University MedicalCenter, Berlin, Germany (Dr Muck-elbauer); Division of Cancer Epide-miology, German Cancer ResearchCenter, Heidelberg, Germany(Drs Kaaks and Teucher); Danish

0.25 0.5 1.0 2.0

Hazard Ratio

A

Source Population HR (95% CI)Batty et al,10 2002 Whitehall Study, United Kingdom 0.42 (0.25-0.69)Gregg et al,15 2003 National Health Interview Survey, United States 0.61 (0.48-0.78)Smith et al,18 2007 Rancho Bernardo Study, United States 0.54 (0.33-0.88)Tanasescu et al,19 2003 Health Professionals Follow-up Study, United States 0.57 (0.39-0.83)Present study EPIC, Europe 0.95 (0.75-1.20)


0.25 0.5 1.0 2.0

Hazard Ratio

B

Source Population HR (95% CI)

Gregg et al,15 2003 National Health Interview Survey, United States 0.66 (0.45-0.96)Smith et al,18 2007 Rancho Bernardo Study, United States 0.66 (0.33-1.32)Present study EPIC, Europe 0.64 (0.41-0.99)


Batty et al,10 2002 Whitehall Study, United Kingdom 0.29 (0.14-0.60)

Figure 3. Hazard ratios (HRs) and 95% CIs for associations between walking (highest vs lowest category) and total (A) and cardiovascular (B) mortality forindividual cohort studies, including the present study, and all the cohort studies combined. EPIC indicates European Prospective Investigation Into Cancer andNutrition; black squares, estimates for the individual studies; solid horizontal lines, 95% CIs; and white diamonds and dashed vertical lines, combined estimatesfor the analysis (the width of the diamond represents the 95% CI).




https://www.researchgate.net/publication/7397108_Physical_Activity_in_Relation_to_Cardiovascular_Disease_and_Total_Mortality_Among_Men_With_Type_2_Diabetes?el=1_x_8&enrichId=rgreq-c140ccc1-962c-474a-b908-41693d7edf85&enrichSource=Y292ZXJQYWdlOzIzMDYyMzAzNjtBUzoxMDMzMDU0MTM5MjI4MjNAMTQwMTY0MTMzODY3Ng==

Cancer Society, Copenhagen, Den-mark (Drs Johnsen and Tjøn-neland); Department of Epidemiol-ogy, School of Public Health (DrsOvervad and Østergaard), and De-partment of Cardiology, AalborgHospital (Dr Østergaard), AarhusUniversity Hospital, Aalborg, Den-mark; Public Health Division ofGipuzkoa, IIS Institute BioDon-ostia, Health Department Basque Re-gion, San Sebastian, Spain (MsAmiano); Consortium for Biomedi-cal Research in Epidemiology andPublic Health, Spain (Ms Amianoand Drs Ardanaz and HuertaCastano); Navarre Public Health In-stitute, Pamplona, Spain (Dr Ar-danaz); Molecular and NutritionalEpidemiology Unit, Cancer Re-search and Prevention Institute,Florence, Italy (Dr Bendinelli); De-partment of Preventive and Predic-tive Medicine, Nutritional Epidemi-ology Unit , National CancerInstitute, Milan, Italy (Dr Pala); Can-cer Registry and HistopathologyUnit, “Civile–M.P. Arezzo” Hospi-tal, Ragusa, Italy (Dr Tumino); Hu-man Genetics Foundation, Turin,Italy (Mr Ricceri); Department ofClinical and Experimental Medi-cine, Federico II University, Naples,Italy (Dr Mattiello); National Insti-tute for Public Health and the En-vironment, Centre for Preventionand Health Services Research,Bilthoven, the Netherlands (Dr Spi-jkerman); Julius Centre for HealthSciences and Primary Care, Univer-sity Medical Centre Utrecht, Utrecht,the Netherlands (Drs Monninkhofand May); Department of ClinicalSciences, Genetic and Molecular Epi-demiology Unit, Skane UniversityHospital, Lund University, Malmo,Sweden (Dr Franks); Department ofNutrition, Harvard School of Pub-lic Health, Boston, Massachusetts(Dr Franks); Department of Clini-cal Sciences, Internal Medicine,Lund University, Skane UniversityHospital, Malmo (Dr Nilsson); De-partment of Public Health and Clini-cal Medicine, Family Medicine,Umea University, Umea, Sweden(Drs Wennberg and Rolandsson);Institut National de la Sante et de laRecherche Medicale, Center for Re-search in Epidemiology and Popu-lation Health, and Paris-South Uni-versity, Villejuif, France (Drs

Fagherazzi, Boutron-Ruault, andClavel-Chapelon); Department ofEpidemiology, Murcia RegionalHealth Authority, Murcia, Spain (DrHuerta Castano); School of PublicHealth, Imperial College London,London and London School of Hy-giene and Tropical Medicine, Lon-don (Dr Gallo); and EpidemiologySection, Institute for ExperimentalMedicine, Christian-Albrechts-University of Kiel, Kiel, Germany(Dr Nothlings).Correspondence: Diewertje Sluik,MSc, German Institute of HumanNutrition Potsdam-Rehbrucke, Epi-demiology Arthur-Scheunert-Allee, 114-116 Nuthetal 14558, Ger-many ([email protected]).Author Contributions: Ms Sluik hadfull access to all the data in the studyand takes responsibility for the in-tegrity of the data and the accuracyof thedataanalyses.Studyconceptanddesign: Sluik, Amiano, Ardanaz, Tu-mino, Boeing, and Nothlings. Ac-quisition of data: Sluik, Kaaks,Teucher, Tjønneland, Overvad,Amiano, Ardanaz, Bendinelli, Pala,Tumino, Ricceri, Mattiello, Nils-son, Wennberg, Rolandsson,Boutron-Ruault, Clavel-Chapelon,Boeing, and Nothlings. Analysis andinterpretation of data: Sluik, Buijsse,Muckelbauer, Overvad, Øster-gaard, Pala, Spijkerman, Monnink-hof, May, Franks, Nilsson, Rolands-son, Fagherazzi, Huerta Castano,Gallo, and Nothlings. Drafting of themanuscript: Sluik. Critical revision ofthe manuscript for important intellec-tual content: Buijsse, Muckelbauer,Kaaks, Teucher, Johnsen, Tjøn-neland, Overvad, Østergaard,Amiano, Ardanaz, Bendinelli, Pala,Tumino, Ricceri, Mattiello, Spijker-man, Monninkhof, May, Franks,Nilsson, Wennberg, Rolandsson,Fagherazzi, Boutron-Ruault, Clavel-Chapelon, Huerta Castano, Gallo,Boeing, and Nothlings. Statisticalanalysis: Sluik and Buijsse. Ob-tained funding: Overvad, Tumino,and Nothlings. Administrative, tech-nical, and material support: Teucher,Tjønneland, Østergaard, Ardanaz,Nilsson, Rolandsson, Gallo, and Boe-ing. Study supervision: Buijsse, Muck-elbauer, Kaaks, Overvad, Amiano,Ardanaz, Boeing, and Nothlings.Financial Disclosure: None re-ported.

Funding/Support: This study wassupported by a European Founda-tion for the Study of Diabetes/sanofi-aventis grant (Dr Nothlings).Role of the Sponsor: The Euro-pean Foundation for the Study ofDiabetes and sanofi-aventis had norole in the design or conduct of thestudy, collection or analysis of thedata, or preparation or approval ofthe manuscript and did not have anyinfluence on the contents.Online-Only Material: The eFig-ures and eTable are available at http://www.archinternmed.com.

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Physical Activity and Mortality in Individuals With Diabetes Mellitus

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