Associations of Neighborhood and School Socioeconomic and Social Contexts With Body Mass Index Among Urban Preadolescent Students

Am J Public Health. 2015 Dec;105(12):2496-502. doi: 10.2105/AJPH.2015.302882. Epub 2015 Oct 15.

Abstract

Objectives: We examined independent and synergistic effects of school and neighborhood environments on preadolescent body mass index (BMI) to determine why obesity rates nearly double during preadolescence.

Methods: Physical measures and health surveys from fifth and sixth graders in 12 randomly selected schools in New Haven, Connecticut, in 2009 were matched to student sociodemographics and school- and residential census tract-level data, for a total of 811 urban preadolescents. Key independent variables included school connectedness, neighborhood social ties, and school and neighborhood socioeconomic status. We estimated cross-classified random-effects hierarchical linear models to examine associations between key school and neighborhood characteristics with student BMI.

Results: Greater average connectedness felt by students to their school was significantly associated with lower BMI. This association was stronger among students living in neighborhoods with higher concentrations of affluent neighbors.

Conclusions: How schools engage and support students may affect obesity rates preferentially in higher-income neighborhoods. Further research should explore the associations between multiple environments to which children are exposed and obesity-related behaviors and outcomes. This understanding of the multiple social-spatial contexts that children occupy has potential to inform comprehensive and sustainable child obesity prevention efforts.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Mass Index*
  • Child
  • Connecticut / epidemiology
  • Diet / statistics & numerical data
  • Female
  • Health Surveys
  • Humans
  • Male
  • Pediatric Obesity / epidemiology
  • Pediatric Obesity / etiology
  • Residence Characteristics / statistics & numerical data*
  • Schools / statistics & numerical data*
  • Social Support
  • Socioeconomic Factors*
  • Students / statistics & numerical data
  • Urban Population / statistics & numerical data