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

Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
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Int. J. Environ. Res. Public Health 2014, 11(1), 418-428; https://doi.org/10.3390/ijerph110100418
Received: 12 November 2013 / Revised: 19 December 2013 / Accepted: 19 December 2013 / Published: 27 December 2013
(This article belongs to the Special Issue Economics of the Prevention and Treatment of Obesity)
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. View Full-Text
Keywords: obesity; disparities; small-area analysis; multilevel regression; targeted interventions obesity; disparities; small-area analysis; multilevel regression; targeted interventions
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D'Agostino-McGowan, L.; Gennarelli, R.L.; Lyons, S.A.; Goodman, M.S. Using Small-Area Analysis to Estimate County-Level Racial Disparities in Obesity Demonstrating the Necessity of Targeted Interventions. Int. J. Environ. Res. Public Health 2014, 11, 418-428.

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