Objective A recent analysis of the Australian National Health Survey (2011–2012) reported that the patterning of overweight and obesity among men, unlike for women, was not associated with neighbourhood socioeconomic disadvantage. The purpose of this study was to examine whether this gender difference in potential neighbourhood ‘effects’ on adult weight status can be observed in analyses of a different source of data.
Design, setting and participants A cross-sectional sample of 14 693 people aged 18 years or older was selected from the 2012 wave of the ‘Household, Income and Labour Dynamics in Australia’ (HILDA). Three person-level outcomes were considered: (1) body mass index (BMI); (2) a binary indicator of ‘normal weight’ versus ‘overweight or obese’; and (3) ‘normal weight or overweight’ versus ‘obese’. Area-level socioeconomic circumstances were measured using quintiles of the Socio Economic Index For Areas (SEIFA). Multilevel linear and logistic regression models were used to examine associations while accounting for clustering within households and neighbourhoods, adjusting for person-level socioeconomic confounders.
Results Neighbourhood-level factors accounted for 4.9% of the overall variation in BMI, whereas 20.1% was attributable to household-level factors. Compared with their peers living in deprived neighbourhoods, mean BMI was 0.7 kg/m2 lower among men and 2.2 kg/m2 lower among women living in affluent areas, with a clear trend across categories. Similarly, the percentage of overweight and obese, and obesity specifically, was lower in affluent areas for both men and women. These results were robust to adjustment for confounders.
Conclusions Unlike findings from the national health survey, but in line with evidence from other high-income countries, this study finds an inverse patterning of BMI by neighbourhood disadvantage for men, and especially among women. The potential mediators which underpin this gender difference in BMI within disadvantaged neighbourhoods warrant further investigation.
- PUBLIC HEALTH
- SOCIAL MEDICINE
- STATISTICS & RESEARCH METHODS
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