(2007) 135–142www.elsevier.com/locate/ypmed

Preventive Medicine 44

Health-related behaviours as predictors of mortality and morbidity inAustralian Aborigines

V. Burke a,⁎, Y. Zhao b, A.H. Lee b, E. Hunter c, R.M. Spargo d, M. Gracey e, R.M. Smith f,L.J. Beilin a, I.B. Puddey a

a University of Western Australia School of Medicine and Pharmacology, Royal Perth Hospital Unit, Box X2213 GPO, Perth 6847, Australiab School of Public Health, Curtin University of Technology, Australiac School of Population Health, University of Queensland, Australia

d Puntukurnu Aboriginal Medical Service, Pilbara Region, Western Australiae Unity of the First People of Australia, Perth, Western Australia

f Miln Walker and Associates Pty Ltd., PO Box 167, Belair, South Australia

Available online 27 October 2006

Abstract

Objective. To examine predictors of coronary heart disease (CHD) and all-cause mortality in Aboriginal Australians.Method. In 1988–89, a survey of Western Australian Aborigines (256 women, 258 men) aged 15–88 years documented diet, alcohol and

smoking habits. Linkage to mortality and hospital admissions to the end of 2002 provided longitudinal data for modelling of coronary heartdisease endpoints and all-cause mortality using Cox regression.

Results. Coronary heart disease risk increased with smoking (HR 2.62, 95% CI: 1.19, 5.75), consumption of processed meats >once/week (HR2.21, 95% CI: 1.05, 4.63), eggs >twice/week (HR 2.59, 95% CI: 1.11, 6.04) and using spreads on bread (HR 3.14. 95% CI: 1.03, 9.61). All-causemortality risk was lower with exercise >once/week (HR 0.51, 95% CI 0.26, 1.05), increased in ex-drinkers (HR 3.66, 95% CI: 1.08, 12.47), heavydrinkers (HR5.26, 95% CI: 1.46, 7.52) and with consumption of takeaway foods >nine times/month (HR 1.78, 95% CI 0.96, 3.29). Greateralcohol intake, smoking and adverse dietary choices clustered in 53% of men and 56% of women and increased risk of coronary heart disease (HR2.1, 95% CI: 1.1, 4.0) and all-cause mortality (HR 2.3, 95% CI: 1.2, 4.2).

Conclusion. Lifestyle in Aboriginal Australians predicts coronary heart disease and all-cause mortality. Clustering of adverse behaviours iscommon and increases risk of coronary heart disease and death.© 2006 Elsevier Inc. All rights reserved.

Keywords: Aborigines; Coronary heart disease; All-cause mortality; Lifestyle

Introduction

Mortality among indigenous Australians is almost three-foldthat of the non-indigenous Australian population (Trewin andMadden, 2005). Among indigenous Australians, lifestylediseases, particularly cardiovascular disease and diabetes, aremajor causes of deaths in excess of expected age- and sex-specific rates (Trewin and Madden, 2005). In cross-sectionalanalyses, behavioural risk factors, such as a sedentary lifestyle,poor nutrition, drinking alcohol at hazardous levels andsmoking, have been implicated as contributors to these adverse

⁎ Corresponding author. Fax: +61 8 9224 0246.E-mail address: vburke@cyllene.uwa.edu.au (V. Burke).

0091-7435/$ - see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.ypmed.2006.09.008

outcomes and are more prevalent among indigenous Australians(Trewin and Madden, 2005). Clustering of risk behaviours iscommon in this population and effects of multiple adversehealth-related behaviours are additive or interactive.

There is a lack of longitudinal data linking health-relatedbehaviours to outcomes in indigenous Australians. AmongAborigines in the Northern Territory of Australia followed-upfor about 8 years, body mass index (BMI) predicted all-causemortality in analyses adjusted for smoking and alcohol-drinkingbehaviours (Wang and Hoy, 2002), but findings relating to thesehealth behaviours were not reported. In a 10-year follow-up ofan Aboriginal community in the Northern Territory, firstcardiovascular events were predicted by BMI, waist and hipgirth in analyses adjusted for smoking (Wang and Hoy, 2004),

Table 1Characteristics at baseline among 514 Western Australian Aborigines 15–88 years of age who were surveyed in 1988–1989 and followed up through 2002

Variable Men, N Women, N Men Women

Age group 248 24015–20 27 (11%) 22 (9%)21–30 43 (17%) 43 (18%)31–40 42 (17%) 40 (17%)41–50 40 (16%) 43 (18%)51–60 39 (16%) 40 (17%)61–70 42 (17%) 36 (15%)>70 15 (6%) 16 (7%)

Seated SBP (mm Hg) 237 222 141 (21) 137 (24)Seated DBP (mm Hg) 237 222 85 (14) 81 (14)Heart rate (beats/min) 237 222 82 (14) 84 (14)Weight (kg) 247 238 70.3 (14.5) 65.5 (17.1)BMI (kg/m2) 247 238 23.7 (4.4) 25.9 (6.7)Waist girth (cm) 249 238 88.5 (12.7) 94.4 (15.9)Cholesterol (mmol/L) 234 223 5.5 (1.3) 5.4 (1.3)HDL-cholesterol (mmol/L) a 106 98 1.27 (0.42) 1.27 (0.37)Hypertension a 239 235 104 (44%) 88 (37%)Diabetes 258 256 10 (4%) 11 (4%)Smoking 194 163Never smokers 59 (30%) 97 (60%)Ex-smokers 8 (4%) 5 (3%)Current smokers 127 (65%) 61 (37%)

Exercise 248 236At least weekly 35 (14%) 25 (11%)Less than once/week 213 (86%) 211 (89%)

Alcohol 258 256Never drinkers 23 (9%) 107 (42%)Ex-drinkers 66 (26%) 53 (21%)Drinks within guidelines b 13 (5%) 8 (4%)Drinks above guidelines 156 (61%) 88 (34%)

Continuous variables are presented as means(SD). Discrete variables are shownas numbers (%).a SBP=140/90 or on treatment for hypertension.b National Health and Medical Research Council (2001).

136 V. Burke et al. / Preventive Medicine 44 (2007) 135–142

but, again, health-related behaviours were not a focus of thereport. In a remote Australian Aboriginal community, albumi-nuria, diabetes and hypertension, but not obesity or dyslipidae-mia, predicted mortality over a mean follow-up period of about4 years; smoking was the only health-related behaviourreported, and did not significantly predict mortality afteradjustment for age and sex (McDonald et al., 1999).

Other studies have examined associations between lifestyleand risk factors for cardiovascular disease in AustralianAborigines in the shorter-term. Reversion to a traditionallifestyle for 7 weeks in adult diabetic Australian Aboriginesresulted in improvement in glucose and insulin metabolism anda decrease in plasma triglycerides (O'Dea, 1984). Improve-ments in insulin responses to a carbohydrate load were also seenin non-diabetic Aborigines who adopted a traditional hunter–gatherer lifestyle for a period of three months (O'Dea et al.,1980). However, longer-term effects of diet and other lifestylefactors on cardiovascular endpoints have not been reported.

In 1988–89, a random sample of Aborigines in Kimberleyregion of Western Australia took part in a survey whichdocumented lifestyle, including physical activity, diet, alcoholconsumption and smoking habits and cardiovascular risk factors(Smith et al., 1992). With the establishment of the WesternAustralian Data Linkage System in 1995, it became possible tolink these participants with outcomes from death records andhospital separations (Holman et al., 1999). With follow-up tothe end of 2002, this data set is unique among AboriginalAustralian populations in providing details of lifestyle inindividuals at baseline linked to outcomes for CHD and all-cause mortality. The present analysis is the first to reportlongitudinal associations between health-related behaviours inindividuals and these endpoints.

Population and methods

During 1988–1989, Aborigines between the ages of 15 and 88 years, in theKimberley region of Western Australia, took part in a survey that assessedlifestyle, with a focus on alcohol consumption, and cardiovascular risk factors(Smith et al., 1992). Briefly, an age- and sex-stratified sample, further stratifiedby location, was randomly selected using the Community Health Client Registerof the Health Department of Western Australia in January 1987 (Hunter et al.,1991). The survey was completed in 1988–1989. The sample size was chosen toallow recognition, with 80% power and p<0.05, of a prevalence of hypertension12% greater than the rate of 25% in the Caucasian population at that time. Ethicalapproval for the original survey was obtained from the Commonwealth Scientificand Industrial Research Organisation (CSIRO, Australia) and from the HealthDepartment of Western Australia. All participants provided individual consent(Hunter et al., 1991).

Questionnaires and measurements

At the time of the survey, there was a particular interest in traditionalAboriginal foods from animal sources which were reported to be low in total fatand high in polyunsaturated fats, with low energy density (Naughton et al.,1986). For that reason, the food frequency questionnaire focused on foods ofanimal origin. Participants completed interviewer-administered questionnairesthat elicited information about demographics, disposal of income, family,language and education. At the time of the survey, the dietary patterns ofAboriginal people in remote Australia were becoming increasingly Westernised.Most of their food sources came from community food stores, from road housesor from shops or, occasionally, from supermarkets in country towns. Hunting,

fishing or gathering of traditional foods was popular but confined mostly torecreational pursuits rather than being a main source of their regular diets. Usualdietary intakes were assessed using an interviewer-administered food frequencyquestionnaire by investigators with years of experience in working with remoteAboriginal communities. Foods recorded included beef, lamb or mutton, mincedmeat, fish, kangaroo, turtle, reptiles, bush turkey, fish, shellfish, sausages, meatpies, pasties, sausage rolls, hamburgers, fried or roasted chicken, “Chinese”meals, processed meats (bacon, canned meat, salami or other sausage) spreadsused on bread, including lard, dripping and ghee; methods of cooking meat andvegetables (fire cooked, roasted, fried, boiled, stewed); whether fat was trimmedfrom meat; the use of salt in cooking and on prepared foods; dairy foods (milk,cream, ice cream and cheese), sweet foods (cakes, biscuits, pastry); eggs.Although questions about dairy foods included assessment of the amount andtype of milk, participants used only powdered full cream milk. No informationwas obtained about consumption of fruit and vegetables, soft drinks orconfectionery.

Alcohol intake was assessed during an interviewer-administered ques-tionnaire (Hunter et al., 1992). All interviewers were known to the participantsand were experienced in communicating with Aboriginal people. Participantswere categorised at interview into those who had never drunk alcohol, ex-drinkers and current drinkers. Drinkers were further categorised into heavydrinkers (≥150 g/day men, ≥100 g/day women), current drinkers with intakebelow these levels, ex-drinkers and never drinkers based on a contextualiseddiary of the last two 48 hour drinking periods.

The amount of physical activity was assessed by three questions that askedabout the frequency (3 times a week, once or twice a week, about once a month,rarely or never) of exercise sufficient to induce sweating or fast breathing,

Table 2Proportion of men and women usually consuming foods as determined frominterviewer-administered food frequency questionnaires (number (%))

Variable Men Women

Meat (beef, sheep, mince)≤22 serves/month 88 (48.1%) 100 (52.6%)>22 serves/month 95 (51.9%) 90 (47.4%)

Bush food (kangaroo, turtle, reptiles, bush turkey, fish cooked in fire, shellfish)≤4 serves/month 100 (54.6%) 92 (48.7%)>4 serves/month 83 (45.4%) 97 (51.3%)

Takeaway (sausages, pies, pasties, hamburgers, chicken (roasted/fried),fried fish, Chinese take away)≤9 serves/month 102 (55.7%) 87 (46.5%)>9 serves/month 81 (44.3%) 100 (53.5%)

Processed meat (bacon, salami and fritz, canned meat)≤4 serves/month 74 (40.9%) 79 (41.4%)>4 serves/month 107 (59.1%) 112 (58.6%)

High fat dairy a

≤91 serves/month 105 (56.5%) 91 (45.7%)>91 serves/month 81 (43.5%) 108 (54.3%)

Sweet foods (biscuits, cake, pastry)≤6 serves/month 151 (79.9%) 150 (75.4%)>6 serves/month 38 (20.1%) 49 (24.6%)

Eggs≤8 a month 50 (27.1%) 61 (30.8%)>8 a month 134 (72.9%) 137 (69.2%)

Adds salt to meal a

Rarely or never 14 (7.5%) 32 (16.1%)Usually 172 (92.5%) 167 (83.9%)

Trims fat from meatRarely or never 95 (51.1%) 85 (43.8%)Usually 91 (48.9%) 109 (56.2%)

Uses spreads on breadRarely or never 30 (17.1%) 26 (13.7%)Usually 145 (82.9%) 164 (86.3%)

The cohort comprises 514 Western Australian Aborigines 15–88 years of agewho were surveyed in 1988–1989 and followed up through 2002.a Significant at 5%.

Table 3Hazard ratios and 95% confidence limits derived from Cox regression modelswith (1) CHD including mortality and first hospital admission and (2) all-causemortality as the endpoints among 514 Western Australian Aborigines 15–88years of age who were surveyed in 1988–1989 and followed up through 2002

Model Hazard ratio (95% CI) p

1. CHD endpointsExercise at least once/week 0.58 (0.29, 1.15) 0.12Current smoker 2.62 (1.19, 5.75) 0.02Ex-smoker 0.95 (0.11, 7.93) 0.96Ex-drinker 0.72 (0.25, 1.98) 0.50Current light-moderate drinker 0.90 (0.29, 2.74) 0.85Current heavy drinker 1.61 (0.59, 4.39) 0.35Processed meat >4 serves/month 2.21 (1.05, 4.63) 0.04Eggs >8/month 2.59 (1.11, 6.04) 0.03Use spreads on bread 3.14 (1.03, 9.61) 0.04

2. All-cause mortalityExercise at least once/week 0.51 (0.26, 1.05) 0.04Current smoker 1.24 (0.63, 2.45) 0.53Ex-smoker 0.16 (0.02, 1.25) 0.89Ex-drinker 3.66 (1.08, 12.47) 0.04Current light-moderate drinker 2.04 (0.55, 7.52) 0.28Current heavy drinker 5.26 (1.46, 18.87) 0.01Take aways >9 serves/month 1.78 (0.96, 3.29) 0.07

Models are adjusted for sex, age, total cholesterol, mean arterial pressure andwaist girth.

137V. Burke et al. / Preventive Medicine 44 (2007) 135–142

playing sports or other activity such as walking, swimming or digging in thegarden. Whether individuals were smokers or ex-smokers and cigarettes per dayfor smokers were recorded.

Blood pressure and anthropometry

Blood pressure (BP) was measured using a portable Dinamap oscillometricmonitor 86249 (Johnson and Johnson, Sydney) as described previously (Smith etal., 1992) with appropriate cuff sizes. BP was initially measured, seated, forfamiliarisation about 15min after entering the survey site. After a further 5–6minseated, three readings of BP were made at intervals of 1 min; the mean of the lasttwo of these was used in analysis. Supine BP was recorded in triplicate after afurther 15 min, followed by standing BP also measured in triplicate at 1 minintervals.

Weight was recorded using a Portable Field Scale Model MPS 120,calibrated daily and height with a stadiometer (Harpenden Survey Set, CMSWeighing Equipment, London), with participants lightly clothed. The sameresearchers were responsible for all interviews (EH) and examinations (RS).

Data linkage and diagnosis coding

All participants who were listed on the Community Health Client Register ofthe Health Department of Western Australia in January 1987 were linked tohospital, cancer and death records from 1 January 1988 to 31 December 2002 bythe Western Australian Data Linkage Unit. Ethical approval relating to datalinkage was obtained from the Western Australian Aboriginal HealthInformation and Ethics Committee, the University of Queensland Health Ethics

Committee and the Kimberley Aboriginal Medical Services Council. While thelinkage step used all available information, subsequent analysis used only de-identified data.

Diagnoses were coded from hospital separation records and death recordsin the period 1988 to 1999 using the ICD-9-CM (National Coding Centre,1995) and from 1999–2000 using the ICD-10-AM (National Centre forClassification in Health, 2000). Mapping of ICD-10-AM codes to ICD-9-CMcodes was carried out using software developed by the National Centre forClassification in Health. Coronary heart disease (CHD) comprised the codes410–414, 427 and 428. Diagnosis codes were included if they appeared inany of 21 diagnosis fields.

Statistical methods

CHD endpoints included mortality from CHD and a first admission tohospital with CHD as a diagnosis. Time to event was calculated from January 1,1988 with a censoring date of 1 January 2002. Endpoints were examined usingCox proportional hazards models in SPSS 13.0 (SPSS, Chicago, IL). Modelswere adjusted for age, using a Box-Tidwell transformation (Hosmer andLemeshow, 2000), sex, mean arterial pressure (MAP), total cholesterol, waistgirth, smoking (never smoker, ex-smoker, current smoker), alcohol drinking(never drinker, ex-drinker, current drinker) and exercise (at least weekly, lessthan weekly).

Ten variables were used to summarise eating patterns based on localknowledge about usual dietary habits in the community: red meat (beef, lambor mutton, mince); bush foods (kangaroo, turtle, reptiles, bush turkey, fishcooked in the fire, shellfish); processed meat (bacon, canned meat, salami,other sausage); takeaways (sausages, meat pies, pasties, sausage rolls,hamburger, chicken fried or roasted, fish fried, fish fingers, “Chinese”meals); high fat dairy foods (milk, cheese, cream, ice cream); sweet foods(biscuits, cake, pastry); eggs; adding salt to prepared food; trimming fat frommeat; using spreads on bread. Stepwise regression with adjustment for age andsex was used in examining risk factors with dietary variables as independentvariables available for selection. All covariates were entered into a multivariatemodel (full model) which was then reduced to the final model using thebackward elimination procedure. In Cox regression p values <0.10 wereconsidered significant.

138 V. Burke et al. / Preventive Medicine 44 (2007) 135–142

Two-step cluster analysis was used to identify clustering of lifestylevariables with dietary variables which were statistically significant in Coxregression models, alcohol drinking habits, smoking habits and exercise pattern;

Fig. 1. Endpoints for coronary artery disease (death or first admission to hospital) inAustralian Aborigines 15–88 years of age who were surveyed in 1988–1989 and fo

the process was carried out separately for men and women. Cluster membershipwas then entered in Cox regression models, adjusted for age, sex, waist girth,total cholesterol and mean arterial pressure.

relation to exercise, diet, smoking and alcohol consumption among 514 Westernllowed up through 2002.

139V. Burke et al. / Preventive Medicine 44 (2007) 135–142

One-way analysis of variance was used for comparison of continuousvariables; χ2 tests or Fisher's exact test were used, as appropriate, for categoricalvariables. A p value <0.05 was considered significant.

Results

There were 258 men and 256 women included in the survey.Baseline characteristics are shown in Table 1. Usual dietaryintakes as determined by interviewer-administered food fre-quency questionnaires are shown in Table 2. For coronary heartdisease (CHD), there were 13 deaths and 55 first hospitaladmissions among women and 11 deaths and 51 first hospitaladmissions among men. There were 52 deaths from all causesamong women and 78 among men.

Coronary heart disease endpoints

As shown in Table 3, smoking, greater consumption ofprocessed meats and eggs and the use of spreads on bread weresignificant predictors of CHD endpoints. Greater hazard ratiosassociated with sedentary behaviours and with heavy drinkingof alcohol were not statistically significant. Fig. 1 shows theCHD endpoints during follow-up in relation to exercise, diet,alcohol and smoking.

With adjustment for age and sex, greater consumption ofprocessed meats was related to systolic BP (139 mmHg, SEM 2vs. 134 mm Hg, SEM 2; p=0.053) and diastolic BP (80 mm HgSEM 1 vs. 77 mm Hg, SEM 1; p=0.047). Total cholesterol(5.7 mmol/L, SEM 0.1 vs. 5.6 mmol/L, SEM 0.1; p=0.832) didnot differ significantly between categories of consumption ofprocessed meats.

All-cause mortality

Table 4 shows the predictors of all-cause mortality. Therewere significant associations with sedentary behaviours andgreater consumption of takeaway foods; being an ex-drinker

Table 4Lifestyle variables in men and women in relation to clustering as determined by twoage who were surveyed in 1988–1989 and followed up through 2002

Health behaviour Cluster group men

“Better” N=52 “W

Current smokers*** 10 (19%)Alcohol consumption***

Never drinkers 7 (14%)Ex-drinkers 6 (12%)Light/moderate drinkers 26 (50%)Heavy drinkers 13 (25%)

Uses spreads on bread 40 (77%)Trims fat from meat 36 (69%)*Adds salt to prepared food 50 (96%)Processed meat (serves/month) 6.6 (0.8)* 8Eggs (eggs/month) 14.9 (1.6)* 22Exercise at least once/week 36 (69%)Takeaway foods (serves/month) 11.1 (1.2)* 13

Clusters are labelled as “better” and “worse”. Values are mean (SEM) for continuou* p<0.05; *** p<0.001.

and heavy consumption of alcohol were significant predictors ofall-cause mortality. Fig. 2 shows all-cause mortality duringfollow-up in relation to diet, exercise, alcohol and smoking.

Clustering of health-related behaviours

Table 4 shows health-related behaviours in men and womenaccording to cluster membership determined by two-stepclustering. The “worse” cluster showed significantly higherproportions of current smokers and of those drinking alcoholat hazardous levels; consumption of takeaway foods wasgreater in both men and women in that cluster. Men in the“worse” cluster had significantly lower rates of trimming fatfrom meat and higher consumption of eggs. Women in the“worse” cluster had significantly higher rates of adding salt toprepared foods and significantly higher consumption ofprocessed meats.

In Cox regression, adjusted for age, sex, total cholesterol,mean arterial pressure and waist girth, membership of the“worse” cluster was associated with a hazard ratio of 2.1 (95%CI: 1.1, 4.0; p=0.026) for CHD endpoints and 2.3 (95% CI:1.2, 4.2; p=0.010) for all-cause mortality (Fig. 3).

Discussion

Although there is evidence from cross-sectional data linkinglifestyle with mortality and morbidity in indigenous Austra-lians, this is the first study to examine Aboriginal lifestyle as apredictor of long-term outcome using longitudinal data. Wehave shown that smoking and foods high in fat are significantpredictors of CHD endpoints while sedentary behaviours,alcohol-drinking habits and greater intake of takeaway foodssignificantly predict all-cause mortality.

The survey of this Aboriginal cohort was undertaken at atime of rapid social transformation during which the structureand dynamics of power within Aboriginal communities andfamilies were shifting, with consequences for employment,

-step cluster analysis among 514 Western Australian Aborigines 15–88 years of

Cluster group women

orse” N=59 “Better” N=44 “Worse” N=57

59 (100%) 0 57 (100%)

0 26 (59%) 8 (14%)14 (24%) 17 (39%) 5 (9%)16 (27%) 0 23 (40%)29 (49%) 1 (2%) 21 (37%)51 (86%) 38 (86%) 50 (88%)22 (37%) 25 (58%) 35 (61%)56 (91%) 32 (73%)* 52 (91%).7 (1.2) 4.9 (0.6)* 8.7 (1.3).5 (2.6) 16.6 (2.0) 22.1 (2.6)32 (54%) 23 (52%) 42 (74%).0 (1.7) 9.0 (1.0)* 13.2 (1.6)

s variables and N (%) for categorical data.

140 V. Burke et al. / Preventive Medicine 44 (2007) 135–142

physical activity, nutrition and substance abuse (Hunter, 1999).Previous studies in Aboriginal Australians have examined theeffects of lifestyle and changes in lifestyle on cardiovascularrisk factors but have not reported associations between health-related behaviours and morbidity and mortality. A lifestyleintervention that encouraged reduced intake of saturated fat andsugar and increased intake of fruit and vegetables along withincreased physical activity in an Aboriginal community in theKimberley regions of Western Australia (Rowley et al., 2000,2001), was associated with a decrease in the prevalence ofhypercholesterolaemia up to 4 years later. Short-term improve-ments in weight control were not maintained but with theintervention program there was some attenuation of increases inglucose and triglycerides relative to a self-selected comparisongroup. No effect was seen on the prevalence of diabetes, theonly clinical endpoint examined. A similar nutrition program inan Aboriginal community in the Northern Territory of Australia(Lee et al., 1994) led to decreased intake of fat and sugar, lower

Fig. 2. All-cause mortality in relation to exercise, diet, smoking and alcohol among 511989 and followed up through 2002.

blood cholesterol, lower blood pressure and weight control inthe short-term. Improvements in community dietary patternswere maintained over a period of 3 years (Lee et al., 1995).

However, assessment of diets associated with both theseprograms for indigenous people used the turnover of foods atthe community store; no individual dietary data were collected.In the present study, diets were assessed using an interviewer-administered food frequency questionnaire. Baseline datacollection took place in 1988–1989, at which time there wasa particular interest in meats from traditional Aboriginal sourcesfollowing reports that these were low in fat with a highproportion of polyunsaturated fatty acids (Naughton et al.,1986). For that reason, our dietary questionnaire focused onmeats and, regrettably, did not elicit information about allaspects of dietary intakes, including that of fruits or vegetables.Questions that related to consumption of dairy foods (milk andcheese), adding salt to foods, trimming fat from meats and theuse of spreads on bread were included. Limited information was

4Western Australian Aborigines 15–88 years of age who was surveyed in 1988–

Fig. 3. Endpoints for coronary heart disease (death or first admission to hospital) and for all-cause mortality in relation to cluster membership as determined by two-stepcluster analysis using alcohol drinking, smoking, exercise and dietary variables significant in Cox regression models, among 514 Western Australian Aborigines 15–88 years of age who were surveyed in 1988–1989 and followed up through 2002. Clusters are labelled as “better” and “worse”.

141V. Burke et al. / Preventive Medicine 44 (2007) 135–142

sought about the use of sweet foods, which included biscuits,cakes, pastries and ice cream, but consumption of confectioneryand sugary drinks was not recorded. Although the dietaryinformation was limited, this is the first report of dietary datafrom Aborigines in the Kimberley region of Western Australiathat relates to individual respondents rather than aggregateddata obtained through the community store.

Processed meats, eggs and takeaway foods were the groupsfound to significantly predict CHD endpoints or all-causemortality in our cohort. Meats obtained by hunting and fishingwere eaten infrequently, with only half of the participantsconsuming these foods at least once weekly. No statisticallysignificant associations were seen between outcomes andconsumption of traditional sources of meats. We did not haveinformation to allow examination of possible inverse associa-tions between high fat consumption and low intake of fruit andvegetables and we acknowledge that the observed dietarypredictors of outcomes may be surrogates for other componentsof the diet. Fresh fruit and vegetables are very expensive inremote Aboriginal communities; their delivery from verydistant sources, their irregularity of supply and lack ofappropriate facilities such as cool rooms for storage in foodstores, and lack of domestic facilities such as refrigeration forsecure storage all discourage their consumption (Sullivan et al.,1987). These factors, lack of family financial resources andinadequate appreciation of the nutritional value of these foodscontribute to increased risk of lifestyle diseases (Willett, 2006).

It is common for adverse health-related behaviours to clusterin Australia's indigenous population (Trewin and Madden,2005) and effects are interactive (AIHW, 2002). IndigenousAustralians more than 15 years old have, on average, 2.3behavioural risk factors and 16% have at least four behaviouralrisk factors. Greater consumption of processed meat, eggs andtakeaway foods, as well as other adverse dietary behaviours,

was associated in our study with drinking alcohol at hazardouslevels, and smoking. Clustering of health-related behaviourswith poor dietary choices, characterised by a high consumptionof fat and low intake of fruit and vegetables, higher alcoholintake and smoking, with variable associations with physicalactivity, is well-recognised in non-Aboriginal populations(Schuit et al., 2002; Villegas et al., 2004; Hulshof et al., 1992;Herbeth et al., 1988). Adverse outcomes associated withclustering of multiple risk behaviours emphasise the importanceof programs, sustainable through community ownership,currently in place to improve health-related behaviours amongAboriginal people (Rowley et al., 2000; Gracey et al., 2006).

Study limitations and strengths

Collection of detailed information about lifestyle at baselinewith long-term follow-up using linkage to data bases forhospital admissions and mortality make this data set a uniqueresource for investigating predictors of endpoints in a cohort ofAboriginal Australians. Although the number of events isrelatively small, no information that allows examination oflifestyle in relation to long-term outcomes is available for otherAboriginal populations, Australia-wide. Missing values forsome variables further reduced the available sample inproportional hazard models. All analyses were adjusted forage but there was a wide age range at the time of recruitment.Furthermore, possible over-representation of older participantsrelative to the expected attenuation with age of an Aboriginalpopulation, may limit the generalisation of our findings. Asnoted above, there were limitations in the scope of the dietarydata acquired, reflecting research questions of current interest atthe time of the initial survey. However, the present analysis hashighlighted lifestyle factors that influence health amongAustralian Aborigines and provided further motivation for

142 V. Burke et al. / Preventive Medicine 44 (2007) 135–142

development of sustainable programs to improve health-relatedbehaviours among Aboriginal people.

Acknowledgments

This study was supported by an Australian ResearchCouncil Discovery Project Grant. We thank the staff of theWestern Australian Data Linkage Unit, particularly CarolGarfield and Diana Rosman, for their contribution to thisproject. We also thank the Western Australian Department ofHealth for access to information on hospital admissions andthe Registrar of Births, Deaths and Marriages for access todeath registrations.

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