Geography of Adolescent Obesity in the US, 2007-2011

• Authors: Michael Kramer, Emory University; Ilana G. Raskind, Emory University; Miriam E. Van Dyke, Emory University; Stephen A. Matthews, Pennsylvania State University; Jessica Cook-Smith, Community Health of Central Washington
• Journal Title: American Journal of Preventive Medicine
• Volume: Volume 51, Number 6
• Publisher: Elsevier Masson | 2016-12-01, Pages 898-909
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1016/j.amepre.2016.06.016
• Subjects: Health Sciences, Epidemiology; Education, Health; Health Sciences, Public Health
• Keywords: Science & Technology; Life Sciences & Biomedicine; Public, Environmental & Occupational Health; Medicine, General & Internal; General & Internal Medicine; FACTOR SURVEILLANCE SYSTEM; SMALL-AREA ESTIMATION; PHYSICAL-ACTIVITY; UNITED-STATES; NEIGHBORHOOD ENVIRONMENTS; MULTILEVEL REGRESSION; CHILDHOOD OVERWEIGHT; SOCIAL ENVIRONMENTS; BUILT ENVIRONMENT; ADULT OBESITY

Abstract

Introduction Obesity remains a significant threat to the current and long-term health of U.S. adolescents. The authors developed county-level estimates of adolescent obesity for the contiguous U.S., and then explored the association between 23 conceptually derived area-based correlates of adolescent obesity and ecologic obesity prevalence. Methods Multilevel small area regression methods applied to the 2007 and 2011–2012 National Survey of Children's Health produced county-level obesity prevalence estimates for children aged 10–17 years. Exploratory multivariable Bayesian regression estimated the cross-sectional association between nutrition, activity, and macrosocial characteristics of counties and states, and county-level obesity prevalence. All analyses were conducted in 2015. Results Adolescent obesity varies geographically with clusters of high prevalence in the Deep South and Southern Appalachian regions. Geographic disparities and clustering in observed data are largely explained by hypothesized area-based variables. In adjusted models, activity environment, but not nutrition environment variables were associated with county-level obesity prevalence. County vio lent crime was associated with higher obesity, whereas recreational facility density was associated with lower obesity. Measures of the macrosocial and relational domain, including community SES, community health, and social marginalization, were the strongest correlates of county-level obesity. Conclusions County-level estimates of adolescent obesity demonstrate notable geographic disparities, which are largely explained by conceptually derived area-based contextual measures. This ecologic exploratory study highlights the importance of taking a multidimensional approach to understanding the social and community context in which adolescents make obesity-relevant behavioral choices.