Preventing Chronic Disease | Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data - CDC

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Preventing Chronic Disease | Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data - CDC

Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data

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• Abstract
• Introduction
• Methods
• Results
• Discussion
• Acknowledgments
• Author Information
• References
• Tables
• Appendix

Carlo Davila-Payan, PhD; Michael DeGuzman, MPH; Kevin Johnson, MSc; Nicoleta Serban, PhD; Julie Swann, PhD

Suggested citation for this article: Davila-Payan C, DeGuzman M, Johnson K, Serban N, Swann J. Estimating Prevalence of Overweight or Obese Children and Adolescents in Small Geographic Areas Using Publicly Available Data. Prev Chronic Dis 2015;12:140229. DOI:http://dx.doi.org/10.5888/pcd12.140229.

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Abstract

Introduction
Interventions for pediatric obesity can be geographically targeted if high-risk populations can be identified. We developed an approach to estimate the percentage of overweight or obese children aged 2 to 17 years in small geographic areas using publicly available data. We piloted our approach for Georgia.

Methods
We created a logistic regression model to estimate the individual probability of high body mass index (BMI), given data on the characteristics of the survey participants. We combined the regression model with a simulation to sample subpopulations and obtain prevalence estimates. The models used information from the 2001–2010 National Health and Nutrition Examination Survey, the 2010 Census, and the 2010 American Community Survey. We validated our results by comparing 1) estimates for adults in Georgia produced by using our approach with estimates from the Centers for Disease Control and Prevention (CDC) and 2) estimates for children in Arkansas produced by using our approach with school examination data. We generated prevalence estimates for census tracts in Georgia and prioritized areas for interventions.

Results
In DeKalb County, the mean prevalence among census tracts varied from 27% to 40%. For adults, the median difference between our estimates and CDC estimates was 1.3 percentage points; for Arkansas children, the median difference between our estimates and examination-based estimates data was 1.7 percentage points.

Conclusion
Prevalence estimates for census tracts can be different from estimates for the county, so small-area estimates are crucial for designing effective interventions. Our approach validates well against external data, and it can be a relevant aid for planning local interventions for children.

Acknowledgments

Participants at Children’s Healthcare of Atlanta gave feedback on preliminary results, including potential interpretations, and reviewed the final manuscript for confidentiality and accuracy. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of Georgia Institute of Technology or Children’s Healthcare of Atlanta. Funding for this study was provided by Children’s Healthcare of Atlanta and the Harold R. and Mary Nash professorship at Georgia Institute of Technology. The authors have no financial relationships or conflicts of interest relevant to this article to disclose. When this research was done, Mr DeGuzman was affiliated with Children’s Healthcare of Atlanta, Atlanta, Georgia.

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Author Information

Corresponding Author: Julie Swann, PhD, Department of Industrial and Systems Engineering, Georgia Institute of Technology, 755 Ferst Dr NW, Atlanta, GA 30333. Telephone: 404-385-3054. Email: jswann@isye.gatech.edu.

Author Affiliations: Carlo Davila-Payan, Kevin Johnson, Nicoleta Serban, Georgia Institute of Technology, Atlanta, Georgia; Michael DeGuzman, Columbia University Medical Center, New York, New York.

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