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Racial differences in the built environment—body mass index relationship? A geospatial analysis of adolescents in urban neighborhoods

DOI: 10.1186/1476-072x-11-11

Keywords: Spatial epidemiology, Neighborhood effects, Built environment, BMI, Adolescents, Race effects

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Abstract:

Data come from the 2008 Boston Youth Survey, a school-based sample of public high school students in Boston, MA. Analyses include data collected from students who had georeferenced residential information and complete and valid data to compute BMI z-score (n?=?1,034). We built a spatial database using GIS with various features related to access to walking destinations and to community design. Spatial autocorrelation in key study variables was calculated with the Global Moran’s I statistic. We fit conventional ordinary least squares (OLS) regression and spatial simultaneous autoregressive error models that control for the spatial autocorrelation in the data as appropriate. Models were conducted using the total sample of adolescents as well as including an interaction term for race/ethnicity, adjusting for several potential individual- and neighborhood-level confounders and clustering of students within schools.We found significant positive spatial autocorrelation in the built environment features examined (Global Moran’s I most?≥?0.60; all p?=?0.001) but not in BMI z-score (Global Moran’s I?=?0.07, p?=?0.28). Because we found significant spatial autocorrelation in our OLS regression residuals, we fit spatial autoregressive models. Most built environment features were not associated with BMI z-score. Density of bus stops was associated with a higher BMI z-score among Whites (Coefficient: 0.029, p?<?0.05). The interaction term for Asians in the association between retail destinations and BMI z-score was statistically significant and indicated an inverse association. Sidewalk completeness was significantly associated with a higher BMI z-score for the total sample (Coefficient: 0.010, p?<?0.05). These significant associations were found for the 800-meter buffer.Some relationships between the built environment and adolescent BMI z-score were in the unexpected direction. Our findings overall suggest that the built environment does not explain a large proportion of the vari

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