A Multilevel Analysis of Race, Community Disadvantage, and Body Mass Index Among Adults in the US
This study examined the contributions of both individual socioeconomic status (SES) and community disadvantage in explaining the higher body mass index (BMI) of black adults in the US. Data from a national survey of adults (1986 American's Changing Lives Study) were combined with tract-level community data from the 1980 census. Results of multilevel regression analyses showed that black women had an age-adjusted BMI score three points higher than non-black women. Individual SES (income, education, assets) was negatively associated with BMI in women, but it only reduced the association between race and BMI from 2.99 to 2.50. Adding community socioeconomic disadvantage index further reduced the race coefficient slightly from 2.50 to 2.21. Nevertheless, living in communities with higher socioeconomic disadvantage was associated with higher BMI net of age, race, individual SES, smoking, physical activity, stress, and social support. Community income inequality (Gini) had an independent positive association with BMI, but did not substantially reduce racial differences among women. Community percent black was not associated with BMI. Results for men demonstrated no statistically significant racial differences in BMI, and no association between BMI and either individual SES or community disadvantage. Although individual SES and community socioeconomic disadvantage each partly explained the higher average BMI among black women, clear racial disparities persisted. Moreover, race, individual SES, community socioeconomic disadvantage, and individual health behaviors were each independent predictors of BMI among women. Unexplained within- and between-community variance in BMI remained among both women and men, with most unexplained variation due to within-community variance. Because our evidence for women suggests that the determinants of obesity are multiple and multilevel, attempts to address this growing social problem will similarly require a multi-faceted and multilevel approach.
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