OBJECTIVE: 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 (< dollar 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.
OBJECTIVE: 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 (< dollar 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.
Authors: Andrew Rundle; Sam Field; Yoosun Park; Lance Freeman; Christopher C Weiss; Kathryn Neckerman Journal: Soc Sci Med Date: 2008-10-25 Impact factor: 4.634
Authors: Kylie Ball; Verity Cleland; Jo Salmon; Anna F Timperio; Sarah McNaughton; Lukar Thornton; Karen Campbell; Michelle Jackson; Louise A Baur; Gita Mishra; Johannes Brug; Robert W Jeffery; Abby King; Ichiro Kawachi; David A Crawford Journal: Int J Epidemiol Date: 2012-12-18 Impact factor: 7.196