Correspondence: Mr Adrian J Cameron, Department of Epidemiology, International Diabetes Institute, 250Kooyong Road, Caulfield, VIC 3162.
The age and pattern of BMI is consistent with a number of other studies.221Both the prevalence of obesity and mean BMI are lower in young women than in young men, but a more rapid rise in BMI in women results in women overtaking men by the age of 35–44 years for obesity prevalence and by age 55–64 years for mean BMI. The impact of age on waist circumference is almost identical for men and for women, suggesting that the ctors leading to increasing waist circumference with age are much more similar between men and women than are the ctors affecting BMI. Increasing peripheral t in women related to childbirth and the menopause may well be the critical difference.1
Prevalences and 95% confidence intervals were calculated using Stata Statistical Software,11accounting for the clustered and stratified nature of the survey. Logistic regression11was used to analyse associations between obesity and each of the potential risk ctors. For participants living in mily units, total household income was recorded, with individual incomes calculated using a modified version of the Organisation for Economic Cooperation and Development (OECD) equivalence scale12to adjust for the number of adults and children in the household. For all other participants, individual income was recorded.
When interpreting these results, some caution should be exercised. As the AusDiab study was cross-sectional, causality cannot be determined from the associations observed. For example, obese people may be less active as a consequence of their obesity. This is unlikely to be the entire explanation for the associations reported, as decreased physical activity has been linked to obesity in prospective studies.27The level of response to the study should also be considered, as well as the small differences between responders and non-responders.7Additionally, even though AusDiab was designed to provide estimates representative of the adult Australian population, the exclusion criteria may have resulted in under-representation of some population groups (eg, Indigenous and rural Australians).
In conclusion, Australia has been shown to have alarming rates of both central and general obesity. This urgently demands action on many levels to prevent further rises in the prevalence of diseases such as type 2diabetes. The strong relationship we found between obesity and surrogate indices of energy expenditure needs to be confirmed in prospective studies, but suggests that reducing time spent in sedentary activities could be an important target for preventing and treating obesity.
The ethics committee of the International Diabetes Institute approved the study design, and all subjects provided written consent to participate.
—Sample selection
Dunstan DW, Zimmet PZ, Welborn TA, et al. The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study.2002; 25: 829-834.<PubMed>
&169;The Medical Journal of Australia 2003
The prevalence rates for overweight and obesity were 39.0% (95% CI, 37.7–40.3) and 20.8% (95% CI, 18.4–23.1), respectively, defined by BMI, and 30.5% (95% CI, 26.4–34.5) and 25.5% (95% CI, 23.8–27.2) by waist circumference (Box 1). By either measure, approximately 60% of the population was overweight or obese. The prevalence of obesity by waist circumference was higher in women (34.1%) than in men (26.8%) (<0.01). Using BMI, however, the difference was not significant.
¶ Quintiles of television viewing: <300minutes=lowest, ≥1260 minutes=highest.
Lean M, Han T, Morrison C. Waist circumference as a measure for indicating need for weight management.1995; 311: 158-161.<PubMed>
The AusDiab study methods are described in detail elsewhere.7A stratified cluster sample was drawn from 42 randomly selected Census Collector Districts across Australia (six in each of the six States and the Northern Territory). Those districts containing fewer than 100people aged 25 years and over, those classified as 100% rural, or those in which 10% or more of the population were Aboriginals or Torres Strait Islanders, were excluded. Within each district, all homes were approached, and all usual residents aged 25 years and over were invited to take part in the survey.
Macdonald SM, Reeder BA, Chen Y, et al. Obesity in Canada: a descriptive analysis. Canadian Heart Health Surveys Research Group.1997; 157Suppl 1: S3-S9.<PubMed>
World Health Organization. Obesity — preventing and managing the global epidemic: report of a WHO consultation on obesity. Geneva: WHO, 1998.
3: Association between obesity (measured using body mass index [BMI] [=4996] and waist circumference [=4984]) and potential risk ctors among Australian men
Comparing the association of television viewing and physical activity time with obesity, television viewing clearly showed the stronger relationship (Box 5). Within each tertile of physical activity, the odds of being obese were highly dependent on television viewing time. While increased physical activity decreased the odds of obesity among each tertile of television viewing time, its influence was not as strong as that of television viewing time.
—Results
—References
Waist circumference provides an alternative measure of adiposity that correlates reasonably well with BMI,18but appears to be a better indicator of visceral t, type 2diabetes and cardiovascular disease.19There are few published studies of the age and distribution of obesity according to waist circumference. In the second MONICA survey20only two centres (Germany, Czech Republic) had higher mean waist circumferences for men than in our study, and four centres (Germany, Czech Republic, Spain and Yugoslavia) had higher mean waist circumferences for women.
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Skill levels: 1— managers, administrators and professionals; 2— associate professionals; 3— tradespersons, advanced clerical and service workers; 4— intermediate clerical, sales and service workers, intermediate production and transport workers; 5— elementary clerical, sales and service workers and labourers; and others — students, retirees, pensioners and unemployed.
The prevalence of overweight and obesity (BMI >25.0kg/m; waist circumference >80.0cm [women] or >94.0cm [men]) in both es was almost 60%, defined by either BMI or waist circumference. The prevalence of obesity was 2.5times higher than in 1980. Using waist circumference, the prevalence of obesity was higher in women than men (34.1% v 26.8%;<0.01). Lower educational status, higher television viewing time and lower physical activity time were each strongly associated with obesity, with television viewing time showing a stronger relationship than physical activity time.
Molarius A, Seidell JC, Sans S, et al. Waist and hip circumferences, and waist-hip ratio in 19 populations of the WHO MONICA Project.1999; 23: 116-125.<PubMed>
4: Association between obesity (measured using body mass index [BMI] [=6071] and waist circumference [=6075]) and each of the potential risk ctors among Australian women
Australian Bureau of Statistics, Department of Health and Family Services. National Nutrition Survey: selected highlights 1995. Canberra: ABS/DHFS, 1997.
Joint Health Surveys Unit on behalf of the Department of Health. Health Survey for England — cardiovascular disease 1998. London: The Stationery Office, 1999.
Correction:This article was published with errors that were corrected on 10 March 2004. The uncorrected text is availablehere. A correction notice appears in the 19 April 2004 issue of the Journal.
The prevalence of obesity defined by BMI showed a steady increase up to the age group 55–64 years, after which the prevalence fell. The corresponding peak in the prevalence of obesity defined by waist circumference occurred at an older age (65–74 years). Mean BMI and waist circumference were 26.9kg/m(95% CI, 26.6–27.2kg/m) and 96.0cm (95.0–97.0cm),respectively, for men, and 26.4kg/m(25.9–26.9kg/m) and 84.2cm (82.4–85.9cm) for women. Mean BMI and waist circumference according to age group are shown inBox 2; it is apparent that, for BMI, the increase with age was much more pronounced in women than men, while, for waist circumference, the association with age was similar between the es. The age-standardised prevalence of obesity defined by BMI has risen from 7.1% in 1980 to 18.4% in 2000.
.School of Health Sciences, Deakin University, Burwood, VIC.
.School of Population Health, University of Queensland, Brisbane, QLD.
Australian Bureau of Statistics, Department of Health and Family Services. National Nutrition Survey: selected highlights 1995. Canberra: ABS/DHFS, 1997.
—Potential risk ctors
The consequences of high rates of overweight and obesity are likely to be profound, with the AusDiab data also showing that Australia now has one of the highest rates of type 2diabetes in the developed world.4
Flegal KM, Carroll MD, Ogden CL, et al. Prevalence and trends in obesity among US adults, 1999-2000.2002; 288: 1723-1727.<PubMed>
Waist circumference was measured halfway between the lower border of the ribs and the iliac crest on a horizontal plane. Two measurements to the nearest 0.5cm were recorded. If the measurements varied by more than 2cm, a third measurement was taken. The mean of the two closest measurements was calculated. Men with a waist circumference 94.0–101.9cm and women with a waist circumference 80.0–87.9cm were classified as overweight. Men with a waist circumference ≥102.0cm and women with a waist circumference ≥88.0cm were classified as obese.1
Obesity is the most obvious manifestation of the global epidemic of sedentary lifestyles and excessive energy intake. Associations have been observed between obesity and type 2diabetes, cardiovascular disease, some cancers and arthritis, each of which has major morbidity, mortality and socio-economic costs. In Australia, the prevalence of diabetes in 2000 was found to be 7.4%, more than twice the estimate for 1981.4
National Heart Foundation of Australia. Risk Factor Prevalence Study No. 1— 1980. Canberra: NHF, 1980.
Odds ratios adjusted for age and .
¶ Quintiles of television viewing: <240minutes=lowest, ≥1200 minutes=highest.
In Australia, national obesity prevalence data have been reported previously.56In the 1995 National Nutrition Survey, 45% of men and 29% of women were found to be overweight, and a further 18% of men and women were classified as obese.6
1: Age-specific prevalence (%) of (A) overweight and (B) obesity defined by body mass index (BMI) (=11 067) and by waist circumference (=11 059) among Australian adults
—Obesity and potential risk ctors
—Competing interests
&167; Obesity defined as a waist circumference of ≥102.0cm men and ≥88.0cm in women.
obesity in australians Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab,→
&167; Quintiles of physical activity: <30 minutes=lowest, ≥550minutes=highest.
Booth ML, Owen N, Bauman A, et al. Relationship between a 14-day recall measure of leisure-time physical activity and a submaximal test of physical work capacity in a population sample of Australian adults.1996; 67: 221-227.<PubMed>
Bennett SA, Magnus P. Trends in cardiovascular risk ctors in Australia: results from the National Heart Foundations Risk Factor Prevalence Study, 1980–1989.1994; 161: 519-527.<PubMed>
National Heart Foundation and Australian Institute of Health. Risk Factor Prevalence Study No. 3— 1989. Canberra: NHF/AIH, 1990.
Obesity defined as BMI ≥30 kg/m, or waist circumference ≥102cm.
Data on education, country of birth, household income, occupation, smoking and physical activity and television viewing habits were obtained by questionnaire.
The high prevalence of obesity found is still considerably lower than the reported rate for 1999–2000 from the United States2(27.5% in men and 33.4% in women), but comparable with those reported from the UK16(17% in men and 21% in women) and (West) Germany17(19.4% in men and 20.9% in women), ranking Australia as one of the most severely affected Europid populations.
Of 20 347eligible people aged >25 years who completed a household interview, 11 247attended the physical examination at local survey sites (response rate, 55%).
A previous analysis of respondents versus non-respondents to the physical examination found small differences in the proportion of English speakers, those born in the United Kingdom and those suspecting they had diabetes (<0.05).7
Overweight defined as a BMI of 25.0–29.9kg/m.
Department of Epidemiology, International Diabetes Institute, Caulfield, VIC.
AusDiab, a cross-sectional study conducted between May 1999 and December 2000, involved participants from 42 randomly selected districts throughout Australia.
Cook P, Rutishauser IHE, Seelig M. Comparable data on food and nutrient intake and physical measurements from the 1983, 1985 and 1995 national nutrition surveys. Canberra: Commonwealth Department of Health and Aged Care, 2001.
Buchowski MS, Sun M. Energy expenditure, television viewing and obesity.1996; 20: 236-244.<PubMed>
—Ethical approval
—Discussion
&8224; Model adjusted for age and all other risk ctors in the table.
&8225; Obesity defined as a BMI of ≥30.0kg/m.
We found that physical activity time and television viewing time were the strongest correlates with obesity. Television viewing time showed a significant positive association with both measures of obesity in men and women, after adjustment for physical activity time and other risk ctors. A corresponding negative association was seen for increased physical activity time, although it was not a significant predictor of BMI in men. Of particular note is the strength of the relationship of obesity with television viewing time — even those in the top tertile of physical activity showed a high risk of obesity if they were also in the top tertile of television viewing time. This dominant effect of television viewing time has been reported previously in another population-based Australian study.22The relative imprecision of recall of physical activity time in comparison with television viewing time may explain part of this finding. Another explanation may be the reduction in incidental (non-structured) physical activity associated with television viewing, which, in an inactive society, has the potential to significantly reduce total energy expenditure.23The association between television viewing time and obesity is important for health education and public health programs. While most such programs focus on increasing the time spent engaged in physical activity, it may be more achievable to recommend reducing the time spent in completely sedentary activities such as watching television. Indeed, a recent interventional trial has shown that measures to limit television viewing in children can be effective in controlling obesity.24
→More articles onNutrition
Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab)
Together with television viewing time and physical activity time, energy intake has an important impact on obesity. From 1983 to 1995, Australian data show that there has been a significant increase in energy intake among adults and children.25Television viewing itself has been linked to higher energy intake (take-away meals) among women,26and this may relate to habits of eating during television viewing.
→Pdf version of this article
Finally, our thanks goes to the local collaborating centres, including Sir Charles Gairdner Hospital (Western Australia), the Prince of Wales Hospital (New South Wales), the Menzies Centre for Population Health Research (Tasmania), the Queen Elizabeth Hospital (South Australia), the Menzies School of Health Research (Northern Territory), Queensland Health, the Monash Medical Centre Department of Nephrology (Victoria), and the Centre for Eye Research Australia (Victoria).
Overweight and obesity defined by body mass index (BMI; kg/m) and waist circumference (cm); sociodemographic ctors (including smoking, physical activity and television viewing time).
Obesity defined as BMI ≥30 kg/m, or waist circumference ≥88 cm.
Skill levels: 1— managers, administrators and professionals; 2— associate professionals; 3— tradespersons, advanced clerical and service workers; 4— intermediate clerical, sales and service workers, intermediate production and transport workers; 5— elementary clerical, sales and service workers and labourers; and others — students, retirees, pensioners and unemployed.
Hodge A, Dowse G, Toelupe P, et al. Dramatic increase in the prevalence of obesity in Western Samoa over the 13 year period 1978-1991.1994; 18: 419-428.<PubMed>
;;;;.Department of Medicine and Public Health, University of Western Australia, Perth, WA.
To account for the clustering and stratification of the survey design, and to adjust for non-response, the data were weighted to match the age and distribution of the 1998 estimated residential population of Australia aged ≥25 years, unless otherwise stated. The weighting ctor was based on the probability of selection in each cluster. Therefore, all prevalences relate to the total 1998 Australian population aged >25 years, with the exception of figures presented for the change in the prevalence of obesity between 1980 and 2000, which have been age-standardised to the 1991 Australian population aged >25 years. The 1980 figures are based on data collected during the NHF Risk Factor Prevalence Survey.5
For their invaluable contribution to the field activities of AusDiab, we are grateful to Annie Allman, Adam Meehan, Claire Reid, Alison Stewart, Robyn Tapp and Fay Wilson.
→Contents list for this issue
&167; Quintiles of physical activity: <20 minutes=lowest, ≥390minutes=highest.
To measure the prevalence of obesity in Australian adults and to examine the associations of obesity with socioeconomic and lifestyle ctors.
→Previous article in this issue
To study the prevalence of obesity over time, the AusDiab data were compared with earlier Australian national surveys. For consistency with the 1980 National Heart Foundation (NHF) Survey, the AusDiab data were confined to capital city participants aged 25–64 years.
—Respondents v non-respondents to the physical examination
→Search PubMed for related articles
&8224; Overweight defined as a waist circumference of 94.0–101.9cm in men and 80.0–87.9cm in women.
Height was measured to the nearest 0.5cm without shoes, using a stadiometer. Weight was measured to the nearest 0.1kg using a mechanical beam balance, after removal of shoes and excess clothing. Body mass index (BMI) was calculated as weight in kilograms divided by height in metres squared. Those with a BMI of 25.0–29.9kg/mwere classified as overweight, while those with a BMI ≥30.0kg/mwere classified as obese.1
of overweight and obesity is increasing at an alarming rate worldwide.1In the United States, for example, the prevalence of obesity rose from 15.0% to 30.9% between 1980 and 2000.2Similar findings have been reported from developing countries.3
;.
Australian Bureau of Statistics. Australian standard classification of occupations (ASCO). 2nd edition. Canberra:obesity in australians Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab ABS, 1997. (Catalogue No. 1220.0.)
Occupation, as defined by the Australian Standard Classification of Occupations (ASCO), was divided into five skill levels (see footnotes toBox 3andBox 4).8
The recent Australian Diabetes, Obesity and Lifestyle Study (AusDiab) yielded a large population-based sample. Here we report the magnitude of the obesity epidemic in Australia, together with an examination of the association of obesity with lifestyle-related ctors.
Jeffery RW, French SA. Epidemic obesity in the United States: are st foods and television viewing contributing?1998; 88: 277-280.<PubMed>
These nationally representative AusDiab data show alarming rates of overweight and obesity. The obesity rates reported here are considerably higher than those of previous Australian urban studies in 1980, 1989 and 1995.1315In 1980, 7.1% of the population aged 25–64 years living in major cities in Australia were obese.13Using the same age and geographical restrictions, the prevalence (defined by BMI) in our study was 18.4%, showing a 2.5-fold rise over 20 years. Across the four surveys in the last 20 years, the prevalence appears to have stabilised in men since 1995, but a continuing rise is apparent for women.
We are grateful to the following for their support of the study: the then Commonwealth Department of Health and Aged Care, Eli Lilly (Aust) Pty Ltd, Janssen-Cilag (Aust) Pty Ltd, Abbott Australasia Pty Ltd, Merck-Lipha s.a., Alphapharm Pty Ltd, Merck Sharp & Dohme (Aust), Roche Diagnostics, Servier Laboratories (Aust) Pty Ltd, SmithKline Beecham International, Pharmacia and Upjohn Pty Ltd, BioRad Laboratories Pty Ltd, HITECH Pathology Pty Ltd, the Australian Kidney Foundation, Diabetes Australia (Northern Territory), Queensland Health, South Australian Department of Human Services, Tasmanian Department of Health and Human Services, Territory Health Services, Victorian Department of Human Services and the Health Department of Western Australia.
See alsoeditorial by Waters
Haffner S, Stern M, Hazuda H, et al. Do upper-body and centralized adiposity measure different aspects of regional body-t distribution? Relationship to non-insulin dependent diabetes mellitus, lipids, and lipoproteins.1987; 36: 43-51.<PubMed>
—Prevalence of overweight and obesity
Salmon J, Owen N, Crawford D, et al. Physical activity and sedentary behavior: a population-based study of barriers, enjoyment, and preference.In press.
Robinson TN. Reducing childrens television viewing to prevent obesity: a randomized controlled trial.1999; 282: 1561-1567.<PubMed>
—Statistical analysis
Salmon J, Bauman A, Crawford D, et al. The association between television viewing and overweight among Australian adults participating in varying levels of leisure-time physical activity.2000; 24: 600-606.<PubMed>
&8225; Significantly different from reference (<0.05).
DeVos K, Zaidi M. Equivalence scale sensitivity of poverty statistics for the member states of the European Community.1997; 4319-333.
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—Methods
Introduction
The prevalence of obesity in Australia has more than doubled in the past 20 years. Strong positive associations between obesity and each of television viewing time and lower physical activity time confirm the influence of sedentary lifestyles on obesity, and underline the potential benefits of reducing sedentary behaviour, as well as increasing physical activity, to curb the obesity epidemic.
The survey, conducted between May 1999 and December 2000, involved a short household interview, followed by a biomedical examination at a local survey centre.
&8225; Significantly different from reference (<0.05).
Of the socioeconomic ctors examined, lower educational attainment showed the most consistent relationship with obesity. This finding is supported by other studies,21although the cause is not clear. The association of obesity with income was specific. In men, minor trends for middle-income groups to be more obese and the most affluent to be thin were observed, although these were not significant. Women, by contrast, showed a strong negative graded association between income and obesity.
—Body mass index
Householders not available at the initial interview were approached again on up to four more occasions. Household questionnaires were completed in 67% of the households (=11 479) that could be contacted and contained at least one eligible person. A total of 20 347eligible individuals were interviewed in these 11 479households. The final survey sample (those attending the biomedical examination) included 11 247adults (5049 men and 6198 women), representing 55% of those completing the household interview.
—Author details
—Trend analysis
Ching PL, Willett WC, Rimm EB, et al. Activity level and risk of overweight in male health professionals.1996; 86: 25-30.<PubMed>
—Acknowledgements
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2: Mean body mass index (BMI) (A) and mean waist circumference (B) by age group for Australian men and women (bars=95% CIs)
—Waist circumference
The associations between obesity and potential risk ctors are shown in Boxes 3and 4, with television viewing time strongly associated with obesity in both es. Physical activity time was related to obesity defined by BMI or waist circumference in women, while in men it was only associated with obesity defined by waist circumference. Lower educational attainment was consistently predictive of obesity in each . Increasing income decreased the risk of obesity in women. Although no such association was significant for men, both the BMI and waist circumference data suggested that middle-income men tended to be more obese than the highest income group. Men with occupations in skill levels 2and 3had the lowest risk of obesity, suggesting a "U"-shaped relationship, although no significant associations between occupation and obesity were observed for women.
The time spent watching TV and/or videos, as well as physical activity time, was estimated for the previous week. Total physical activity time for the previous week was calculated as the sum of the time sobesity in australianspent walking (if continuous and for 10 minutes or more) or performing moderate physical activity, plus double the time spent in vigorous physical activity. Each of these activity types was truncated to 14 hours and the total time was truncated to 28 hours. Gardening, household chores and occupational physical activity were excluded. Quintiles of physical activity and television viewing were calculated separately for men and women. Self-report measures to assess physical activity9and television viewing10have been validated previously.
Dunstan D, Zimmet P, Welborn T, et al. The Australian Diabetes, Obesity and Lifestyle Study (AusDiab) — methods and response rates.2002; 57: 119-129.<PubMed>
&8224; Obesity defined by waist circumference ≥102.0cm (men) or 88.0cm (women).
&8224; Model adjusted for age and all other risk ctors in the table.
