Explaining Obesity Disparities by Urbanicity, 2006 to 2016: A Decomposition Analysis

Author(s): 

Emma Zang, Josefina Flores Morales, Liying Luo, and Drishti Baid

ISPS ID: 
ISPS23-01
Full citation: 
Zang, E, Flores Morales, J, Luo, L, Baid, D. (2023). Explaining Obesity Disparities by Urbanicity, 2006 to 2016: A Decomposition Analysis. Obesity (Silver Spring). First published online: January 9, 2023. DOI:10.1002/oby.23608.
Abstract: 
Objective: A large, and potentially growing, disparity in obesity prevalence exists between large central metros and less urban United States counties. This study examines its key predictors. Methods: Using a rich county-year data set spanning 2006 to 2016, the authors conducted a Gelbach decomposition to examine the relative importance of demographic, socioeconomic, environmental, and behavioral factors in shaping the baseline obesity gap and the growth rate over time between large central metros and other counties. Results: Predictors included in this model explain almost the entire obesity gap between large central metros and other counties in the baseline year but can explain only ~32% of the growing gap. At baseline, demographic predictors explain more than half the obesity gap, and socioeconomic and behavioral predictors explain the other half. Behavioral and socioeconomic predictors explain more than half the growing gap over time whereas controlling for environmental and demographic predictors decreases the obesity gap by urbanicity over time. Conclusions: Results suggest policy makers should prioritize interventions targeting health behaviors of residents in non-large central metros to slow the growth of the obesity gap between large central metros and other counties. However, to fundamentally eliminate the obesity gap, in addition to improving health behaviors, policies addressing socioeconomic inequalities are needed.
Supplemental information: 

Link to article here (gated).

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Publication date: 
2023
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