Using Small-Area Analysis to Estimate County-Level Racial Disparities in Obesity Demonstrating the Necessity of Targeted Interventions

International Journal of Environmental Research and Public Health

Lucy D𠆚gostino-McGowan¹  Renee L. Gennarelli²  Sarah A. Lyons² 

[1] Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA;

关键词: obesity;    disparities;    small-area analysis;    multilevel regression;    targeted interventions;   

DOI  :  10.3390/ijerph110100418

来源: mdpi

【 摘 要 】

Data on the national and state levels is often used to inform policy decisions and strategies designed to reduce racial disparities in obesity. Obesity-related health outcomes are realized on the individual level, and policies based on state and national-level data may be inappropriate due to the variations in health outcomes within and between states. To examine county-level variation of obesity within states, we use a small-area analysis technique to fill the void for county-level obesity data by race. Five years of Behavioral Risk Factor Surveillance System data are used to estimate the prevalence of obesity by county, both overall and race-stratified. A modified weighting system is used based on demographics at the county level using 2010 census data. We fit a multilevel reweighted regression model to obtain county-level prevalence estimates by race. We compare the distribution of prevalence estimates of non-Hispanic Blacks to non-Hispanic Whites. For 25 of the 26 states included in our analysis there is a statistically significant difference between within-state county-level average obesity prevalence rates for non-Hispanic Whites and non-Hispanic Blacks. This study provides information needed to target disparities interventions and resources to the local areas with greatest need; it also identifies the necessity of doing so.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.