Estimated county-level prevalence of diabetes and obesity - United States, 2007.

Comprehensive disease surveillance systems are important for developing preventive health policies and tracking their impact in populations at high risk. Although existing chronic disease surveillance systems function well at the national or state level, few provide data at the local level, where many policies and interventions ultimately are implemented. To overcome this limitation, Bayesian multilevel models have been applied to reliably estimate disease prevalence at the local level. CDC adapted this methodology to estimate diabetes and obesity prevalence in all 3,141 U.S. counties in 2007. This report provides an overview of the methodology used and a descriptive analysis of the resulting estimates. The results indicated distinct geographic patterns in diabetes and obesity prevalence in the United States, including high prevalence rates for diabetes (>or=10.6%) and obesity (>or=30.9%) in West Virginia, the Appalachian counties of Tennessee and Kentucky, much of the Mississippi Delta, and a southern belt extending across Louisiana, Mississippi, middle Alabama, south Georgia, and the coastal regions of the Carolinas. Isolated counties, including tribal lands in the western United States, also had high prevalence of diabetes and obesity. This report demonstrates how model-based estimates can identify areas with populations at high risk, providing local public health officials with important data to assist them in developing targeted programs to reduce diabetes and obesity.