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Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach
Journal article   Open access   Peer reviewed

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach

Anja Zgodic, Jan M. Eberth, Charity B. Breneman, Marilyn E. Wende, Andrew T. Kaczynski, Angela D. Liese and Alexander C. McLain
American journal of epidemiology, v 190(12), pp 2618-2629
01 Dec 2021
PMID: 34132329
url
https://doi.org/10.1093/aje/kwab176View
Published, Version of Record (VoR)Open Access (License Unspecified) Open

Abstract

Life Sciences & Biomedicine Public, Environmental & Occupational Health Science & Technology
Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

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Public, Environmental & Occupational Health
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