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The association between physical inactivity and obesity is modified by five domains of environmental quality in U.S. adults: A cross-sectional study
Christine L. Gray, 1 Lynne C. Messer, 2 Kristen M. Rappazzo, 3 Jyotsna S. Jagai, 4 Shannon C. Grabich, 5 Danelle T. Lobdell 3
1  Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
2  School of Public Health, Oregon Health & Sciences University-Portland State University, Portland, Oregon, United States of America
3  National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, USEPA Human Studies Facility, Chapel Hill, North Carolina, United States of America
4  Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois Chicago, Chicago, Illinois, United States of America
5  Oak Ridge Institute for Science and Education at the U.S. Environmental Protection Agency, USEPA Human Studies Facility, Chapel Hill, North Carolina, United States of America

Published: 30 August 2018 by Public Library of Science (PLoS) in PLOS ONE
Public Library of Science (PLoS), Volume 13; 10.1371/journal.pone.0203301
Abstract: Physical inactivity is a primary contributor to the obesity epidemic, but may be promoted or hindered by environmental factors. To examine how cumulative environmental quality may modify the inactivity-obesity relationship, we conducted a cross-sectional study by linking county-level Behavioral Risk Factor Surveillance System data with the Environmental Quality Index (EQI), a composite measure of five environmental domains (air, water, land, built, sociodemographic) across all U.S. counties. We estimated the county-level association (N = 3,137 counties) between 2009 age-adjusted leisure-time physical inactivity (LTPIA) and 2010 age-adjusted obesity from BRFSS across EQI tertiles using multi-level linear regression, with a random intercept for state, adjusted for percent minority and rural-urban status. We modelled overall and sex-specific estimates, reporting prevalence differences (PD) and 95% confidence intervals (CI). In the overall population, the PD increased from best (PD = 0.341 (95% CI: 0.287, 0.396)) to worst (PD = 0.645 (95% CI: 0.599, 0.690)) EQI tertile. We observed similar trends in males from best (PD = 0.244 (95% CI: 0.194, 0.294)) to worst (PD = 0.601 (95% CI: 0.556, 0.647)) quality environments, and in females from best (PD = 0.446 (95% CI: 0.385, 0.507)) to worst (PD = 0.655 (95% CI: 0.607, 0.703)). We found that poor environmental quality exacerbates the LTPIA-obesity relationship. Efforts to improve obesity through LTPIA may benefit from considering this relationship.
Keywords: Physical activity, obesity, air pollution, Built environment, Public and occupational health, crime, Socioeconomic aspects of health, Census
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