• Joanna M N Guimarães, Ana Paula Vasconcelos, Marcelo Cunha, and Eduardo Faerstein.
• Center for Data and Knowledge Integration for Health-CIDACS, Fiocruz, Salvador, Brazil. joannaguimaraes@hotmail.com.
• J Urban Health. 2025 Jan 6.

AbstractNeighborhoods or residential environments have physical and social attributes which may contribute to inequalities in the overweight and obesity pandemic. We examined the longitudinal associations of baseline neighborhood-level income and racial residential segregation (using the Gi* statistic: low, medium, high) with changes in body mass index (BMI in kg/m2), using geocoded data from 1821 civil servants in the municipality of Rio de Janeiro, Brazil, followed-up for approximately 13 years (baseline wave 1: 1999, wave 2: 2001-2002, wave 3: 2006-2007, wave 4: 2012-2013). Linear mixed effects models using BMI measured in all four study waves were performed, accounting for gender, race, length of residence, education and time-dependent age, and per capita family income. After adjustments, both income and racial segregation were positively associated with BMI differences (but not BMI changes) over time, in a dose-response pattern. For income segregation, mean differences in BMI for participants living in high and medium vs. low segregated neighborhoods were 1.04 kg/m2 (β = 1.04; 95% CI 0.47, 1.62) and 0.86 kg/m2 (0.86; 0.33, 1.39), respectively. For racial segregation, mean differences in BMI for participants living in high and medium vs low segregated neighborhoods were 0.71 kg/m2 (0.71; 0.14, 1.29) and 0.30 kg/m2 (0.30; - 0.24, 0.83), respectively. We also showed a moderate to strong correlation between racial and income segregation at baseline. Strategies to reduce BMI and obesity-related health inequalities should include special efforts aimed at segregated neighborhoods and its obesogenic environments.© 2025. The New York Academy of Medicine.

5 keywords...

hide…