Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities

Melissa N Poulsen; Thomas A Glass; Jonathan Pollak; Karen Bandeen-Roche; Annemarie G Hirsch; Lisa Bailey-Davis; Brian S Schwartz

doi:10.1016/j.pmedr.2019.100939

Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities

Prev Med Rep. 2019 Jun 29:15:100939. doi: 10.1016/j.pmedr.2019.100939. eCollection 2019 Sep.

Authors

Melissa N Poulsen¹, Thomas A Glass², Jonathan Pollak³, Karen Bandeen-Roche⁴, Annemarie G Hirsch¹, Lisa Bailey-Davis^{1

5}, Brian S Schwartz^{1

2

3

6}

Affiliations

¹ Department of Epidemiology and Health Services Research, Geisinger, 100 North Academy Avenue, Danville, PA 17822, USA.
² Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
³ Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
⁴ Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
⁵ Obesity Institute, Geisinger, 100 North Academy Avenue, Danville, PA 17822, USA.
⁶ Department of Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.

Abstract

Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors-community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)-which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3-18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age², and age³ to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], P < 0.001) and cities (0.378 [0.036], P < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.

Keywords: BMI, body mass index; Built environment; CSED, community socioeconomic deprivation; Electronic health records; FIT, fitness and recreational assets; FOOD, food outlet abundance; Pediatric obesity; Rural populations; Social environment; UTIL, utilitarian physical activity favorability.