Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach. Issue 12 (16th June 2021)

• Record Type: Journal Article
• Authors: Zgodic, Anja; Eberth, Jan M; Breneman, Charity B; Wende, Marilyn E; Kaczynski, Andrew T; Liese, Angela D; McLain, Alexander C
• Is Part Of: American journal of epidemiology. Volume 190:Issue 12(2021)
• Page Start: 2618
• Page End: 2629
• Publication Date: 2021-06-16
• Subjects: childhood obesity -- childhood overweight -- poststratification -- small-area estimation -- survey; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwab176
• Languages: English
• ISSNs: 0002-9262

Abstract

Abstract: 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.