Built and socioeconomic environments

Patterning and associations with physical activity in U.S. adolescents

Janne Heinonen, Kelly R. Evenson, Yan Song, Penny Gordon-Larsen

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

Background: Inter-relationships among built and socioeconomic environmental characteristics may result in confounding of associations between environment exposure measures and health behaviors or outcomes, but traditional multivariate adjustment can be inappropriate due to collinearity.Methods: We used principal factor analysis to describe inter-relationships between a large set of Geographic Information System-derived built and socioeconomic environment measures for adolescents in the National Longitudinal Study of Adolescent Health (Wave I, 1995-96, n = 17,294). Using resulting factors in sex-stratified multivariate negative binomial regression models, we tested for confounding of associations between built and socioeconomic environment characteristics and moderate to vigorous physical activity (MVPA). Finally, we used knowledge gained from factor analysis to construct replicable environmental measures that account for inter-relationships and avoid collinearity.Results: Using factor analysis, we identified three built environment constructs [(1) homogenous landscape; 2) development intensity with high pay facility count; 3) development intensity with high public facility count] and two socioeconomic environment constructs [1) advantageous economic environment, 2) disadvantageous social environment]. In regression analysis, confounding of built environment-MVPA associations by socioeconomic environment factors was stronger than among built environment factors. In fully adjusted models, MVPA was negatively associated with the highest (versus lowest) quartile of homogenous land cover in males [exp(coeff) (95% CI): 0.91 (0.86, 0.96)] and intensity (pay facilities) [exp(coeff) (95% CI): 0.92 (0.85, 0.99)] in females. Single proxy measures (Simpson's diversity index, count of pay facilities, count of public facilities, median household income, and crime rate) representing each environmental construct replicated associations with MVPA.Conclusions: Environmental characteristics are inter-related. Both built and SES environments should be incorporated into analysis in order to minimize confounding. Single environmental measures may be useful proxies for environmental constructs in longitudinal analysis and replication in external populations, but more research is needed to better understand mechanisms of action, and ultimately identify policy-relevant environmental determinants of physical activity.

Original languageEnglish (US)
Article number45
JournalInternational Journal of Behavioral Nutrition and Physical Activity
Volume7
DOIs
StatePublished - May 20 2010
Externally publishedYes

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Exercise
Public Facilities
Statistical Factor Analysis
Proxy
National Longitudinal Study of Adolescent Health
Environmental Policy
Social Adjustment
Sex Factors
Geographic Information Systems
Social Environment
Health Behavior
Statistical Models
Crime
Regression Analysis
Economics
Research
Population

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Nutrition and Dietetics
  • Physical Therapy, Sports Therapy and Rehabilitation

Cite this

Built and socioeconomic environments : Patterning and associations with physical activity in U.S. adolescents. / Heinonen, Janne; Evenson, Kelly R.; Song, Yan; Gordon-Larsen, Penny.

In: International Journal of Behavioral Nutrition and Physical Activity, Vol. 7, 45, 20.05.2010.

Research output: Contribution to journalArticle

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abstract = "Background: Inter-relationships among built and socioeconomic environmental characteristics may result in confounding of associations between environment exposure measures and health behaviors or outcomes, but traditional multivariate adjustment can be inappropriate due to collinearity.Methods: We used principal factor analysis to describe inter-relationships between a large set of Geographic Information System-derived built and socioeconomic environment measures for adolescents in the National Longitudinal Study of Adolescent Health (Wave I, 1995-96, n = 17,294). Using resulting factors in sex-stratified multivariate negative binomial regression models, we tested for confounding of associations between built and socioeconomic environment characteristics and moderate to vigorous physical activity (MVPA). Finally, we used knowledge gained from factor analysis to construct replicable environmental measures that account for inter-relationships and avoid collinearity.Results: Using factor analysis, we identified three built environment constructs [(1) homogenous landscape; 2) development intensity with high pay facility count; 3) development intensity with high public facility count] and two socioeconomic environment constructs [1) advantageous economic environment, 2) disadvantageous social environment]. In regression analysis, confounding of built environment-MVPA associations by socioeconomic environment factors was stronger than among built environment factors. In fully adjusted models, MVPA was negatively associated with the highest (versus lowest) quartile of homogenous land cover in males [exp(coeff) (95{\%} CI): 0.91 (0.86, 0.96)] and intensity (pay facilities) [exp(coeff) (95{\%} CI): 0.92 (0.85, 0.99)] in females. Single proxy measures (Simpson's diversity index, count of pay facilities, count of public facilities, median household income, and crime rate) representing each environmental construct replicated associations with MVPA.Conclusions: Environmental characteristics are inter-related. Both built and SES environments should be incorporated into analysis in order to minimize confounding. Single environmental measures may be useful proxies for environmental constructs in longitudinal analysis and replication in external populations, but more research is needed to better understand mechanisms of action, and ultimately identify policy-relevant environmental determinants of physical activity.",
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