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Weight and place: a multilevel cross-sectional survey of area-level social disadvantage and overweight/obesity in Australia
journal contribution
posted on 2006-01-01, 00:00 authored by T King, A Kavanagh, Damien Jolley, Gavin Turrell, David CrawfordDavid CrawfordObjective: To estimate variation between small areas in adult body mass index (BMI), and assess the importance of area level socioeconomic disadvantage in predicting BMI.
Methods: We identified all census collector districts (CCDs) in the 20 innermost Local Government Areas in metropolitan Melbourne, Australia, and ranked them by the percentage of low income households (<$400/week). In all, 50 CCDs were randomly selected from the least, middle and most disadvantaged septiles of the ranked list and 4913 residents (61.4% participation rate) completed one of two surveys. Multilevel linear regression was used to estimate area level variance in BMI and the importance of area level socioeconomic disadvantage in predicting BMI.
Results: There were significant variations in BMI between CCDs for women, even after adjustment for individual and area SES (P=0.012); significant area variation was not found for men. Living in the most versus least disadvantaged areas was associated with an average difference in BMI of 1.08 kg/m2 (95% CI: 0.48–1.68 kg/m2) for women, and of 0.93 kg/m2 (95% CI: 0.32–1.55 kg/m2) for men. Living in the mid versus least disadvantaged areas were associated with an average difference in BMI of 0.67 kg/m2 (95% CI: 0.09–1.26 kg/m2) for women, and 0.43 kg/m2 for men (95% CI: -0.16–1.01).
Conclusion: These findings suggest that area disadvantage is an important predictor of adult BMI, and support the need to focus on improving local environments to reduce socioeconomic inequalities in overweight and obesity.
Methods: We identified all census collector districts (CCDs) in the 20 innermost Local Government Areas in metropolitan Melbourne, Australia, and ranked them by the percentage of low income households (<$400/week). In all, 50 CCDs were randomly selected from the least, middle and most disadvantaged septiles of the ranked list and 4913 residents (61.4% participation rate) completed one of two surveys. Multilevel linear regression was used to estimate area level variance in BMI and the importance of area level socioeconomic disadvantage in predicting BMI.
Results: There were significant variations in BMI between CCDs for women, even after adjustment for individual and area SES (P=0.012); significant area variation was not found for men. Living in the most versus least disadvantaged areas was associated with an average difference in BMI of 1.08 kg/m2 (95% CI: 0.48–1.68 kg/m2) for women, and of 0.93 kg/m2 (95% CI: 0.32–1.55 kg/m2) for men. Living in the mid versus least disadvantaged areas were associated with an average difference in BMI of 0.67 kg/m2 (95% CI: 0.09–1.26 kg/m2) for women, and 0.43 kg/m2 for men (95% CI: -0.16–1.01).
Conclusion: These findings suggest that area disadvantage is an important predictor of adult BMI, and support the need to focus on improving local environments to reduce socioeconomic inequalities in overweight and obesity.
