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Neighborhood racial/ethnic segregation and BMI: A longitudinal analysis of the Multi-ethnic Study of Atherosclerosis
Journal article   Open access   Peer reviewed

Neighborhood racial/ethnic segregation and BMI: A longitudinal analysis of the Multi-ethnic Study of Atherosclerosis

D Phuong Do, Kari Moore, Sharrelle Barber and Ana Diez Roux
International journal of obesity (2005), v 43(8), pp 1601-1610
Aug 2019
PMID: 30670849
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://europepmc.org/articles/pmc6646102View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

African Americans - statistics & numerical data Aged Aged, 80 and over Atherosclerosis - epidemiology Atherosclerosis - ethnology Body Mass Index Body Weight - ethnology Cross-Sectional Studies Ethnicity - statistics & numerical data Female Health Status Disparities Hispanic or Latino - statistics & numerical data Humans Longitudinal Studies Male Middle Aged Poverty - ethnology Poverty - statistics & numerical data Residence Characteristics Sex Factors Social Segregation Whites - statistics & numerical data
Current knowledge regarding the relationship between segregation and body weight is derived mainly from cross-sectional data. Longitudinal studies are needed to provide stronger causal inference. We use longitudinal data from the Multi-Ethnic Study of Atherosclerosis and apply an econometric fixed-effect strategy, which accounts for all time-invariant confounders, and compare results to conventional cross-sectional analyses. We examine the relationship between neighborhood-level racial/ethnic segregation, neighborhood poverty, and body mass index (BMI) separately for blacks, Hispanics, and whites. Segregation*gender interactions are included in all models. Neighborhood segregation was operationalized by the local G statistic, which assesses the extent to which a neighborhood's racial/ethnic composition is under (G statistic < 0) or over (G statistic > 0) represented, given the composition in the broader (e.g., county) area. For black, Hispanic, and white stratified models, the G statistic reflects the level of black, Hispanic, and white segregation, respectively. The G statistic was scaled such that a unit change represents a 1.96 difference in the score. Cross-sectional models indicated higher segregation to be negatively associated with BMI for white females and positively associated for Hispanic females. No association was found for black females or males in general. In contrast, fixed-effect models adjusting for neighborhood poverty, higher segregation was positively associated with BMI for black females (coeff = 0.25 kg/m ; 95% CI = [0.03, 0.46]; p-value = 0.03) but negatively associated for Hispanic females (coeff = -0.17 kg/m ; 95% CI = [-0.33, -0.01]; p-value  = 0.04) and Hispanic males (coeff = -0.20; 95% CI = [-0.39, -0.01]; p-value = 0.04). Further controls for socioeconomic factors fully explained the associations for Hispanics but not for black females. Fixed-effect results suggest that segregation's impacts might not be universally harmful, with possible null or beneficial impacts, depending on race/ethnicity. The persistent associations after accounting for neighborhood poverty indicate that the segregation-BMI link may operate through different pathways other than neighborhood poverty.

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#10 Reduced Inequalities
#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Endocrinology & Metabolism
Nutrition & Dietetics
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