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We aimed to investigate the association between multiple measures of socio-economic position (SEP) and diet quality, using a diet quality index representing current national dietary guidelines, in the Australian adult population.
Cross-sectional study. Linear regression analyses were used to estimate the association between indicators of SEP (educational attainment, level of income and area-level disadvantage) and diet quality (measured using the Dietary Guideline Index (DGI)) in the total sample and stratified by sex and age (≤55 years and >55 years).
A large randomly selected sample of the Australian adult population.
Australian adults (n 9296; aged ≥25 years) from the Australian Diabetes, Obesity and Lifestyle Study.
A higher level of educational attainment and income and a lower level of area-level disadvantage were significantly associated with a higher DGI score, across the gradient of SEP. The association between indicators of SEP and DGI score was consistently stronger among those aged ≤55 years compared with their older counterparts. The most disadvantaged group had a DGI score between 2 and 5 units lower (depending on the marker of SEP) compared with the group with the least disadvantage.
A higher level of SEP was consistently associated with a higher level of diet quality for all indicators of SEP examined. In order to reduce socio-economic inequalities in diet quality, healthy eating initiatives need to act across the gradient of socio-economic disadvantage with a proportionate focus on those with greater socio-economic disadvantage.
Several studies have suggested that dairy food may reduce the risk of obesity and metabolic abnormalities but few have been able to conclusively demonstrate that it reduces the risk of diabetes. The aim of the present analysis was to investigate if dairy food intake independently reduces the risk of diabetes.
The Australian Diabetes Obesity and Lifestyle Study (AusDiab) is a national, population-based, prospective survey conducted over 5 years. Baseline measurements included a 121-item FFQ, anthropometrics and an oral glucose tolerance test.
Forty-two randomly selected clusters across Australia.
Adults aged ≥25 years who participated in the baseline survey and returned to follow-up 5 years later.
A total of 5582 participants with complete data were eligible for analysis, 209 of whom had incident diabetes. Compared with men in the first tertile of dairy food intake, men in the third tertile had a significantly reduced risk of developing diabetes after adjustment for age, sex, total energy intake, family history of diabetes, education, physical activity, smoking status, fasting serum TAG and HDL cholesterol, systolic blood pressure, waist circumference and hip circumference (OR = 0·53, 95 % CI 0·29, 0·96; P = 0·033). A similar non-significant association was observed in women.
Dietary patterns that incorporate high intakes of dairy food may reduce the risk of diabetes among men. Further investigation into the relationship between dairy food intake and diabetes needs to be undertaken to fully understand the potential mechanism of this observation.
To identify predictors of increasing waist circumference (WC) over a 5-year period in a contemporary population of Australian adults.
Longitudinal national cohort of adults participating in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).
Australian adults in 2000 and 2005.
A total of 2521 men and 2726 women aged ≥25 years at baseline who participated in AusDiab and provided anthropometric measurements at baseline (1999–2000) and follow-up (2005).
A ≥5 % increase of baseline WC occurred in 27 % of men and 38 % of women over the 5-year period. In the multivariate analysis of the total population, there was a higher risk of ≥5 % gain in baseline WC in women, younger people, people with a lower baseline WC, people who never married compared with married/de facto, current smokers compared with never smokers, people with a poorer diet quality and people with a low energy intake. However, there was no significant association with many expected predictors of waist gain such as physical activity. There were some associations between other lifestyle factors and change of WC by sex, age, level of education and across WC categories, but the associations differed across these groups.
A ≥5 % increase of baseline WC occurred in a significant proportion of men and women over the 5-year period. Of the behavioural factors, poor diet quality was the key predictor of the ≥5 % increase of baseline WC in this cohort. The findings highlight the need to understand better the causal role of lifestyle in regard to increasing WC over time.
To analyse changes in the distribution of BMI in Australia between 1980 and 2000.
Data were from the 1980, 1983 and 1989 National Heart Foundation Risk Factor Prevalence Study, the 1995 National Nutrition Survey and the 1999/2000 Australian Diabetes, Obesity and Lifestyle Study. Survey participants were aged 25–64 years and resident in Australian capital cities. BMI was calculated as weight divided by height squared (kg/m2), where weight and height were measured using standard procedures.
Mean BMI was higher in 2000 than 1980 in all sex and age groups. The age-adjusted increase was 1·4 kg/m2 in men and 2·1 kg/m2 in women. The BMI distribution shifted rightwards for all sex and age groups and became increasingly right-skewed. The change between 1980 and 2000 ranged from a decrease of 0·04 kg/m2 at the lower end of the distribution for men aged 25–34 years to an increase of 7·4 kg/m2 at the higher end for women aged 55–64 years. While the prevalence of obesity (BMI ≥ 30 kg/m2) doubled, the prevalence of obesity class III (BMI ≥ 40 kg/m2) increased fourfold.
BMI in urban Australian adults has increased and its distribution has become increasingly right-skewed. This has resulted in a large increase in the prevalence of obesity, particularly the more severe levels of obesity. It will be important to monitor changes in the different classes of obesity and the extent to which obesity interventions both shift the BMI distribution leftwards and decrease the skew of the distribution.
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