Geographic Clustering of Obesity, Diabetes, and Hypertension in Nashville, Tennessee (original) (raw)

Purpose: To describe and map the spatial clustering of obesity, diabetes, and hypertension in Nashville, Tennessee. • Method: Data from two random community phone surveys was geocoded and combined into a single dataset. Data was aggregated by census tract, and those tracts with 10 or more interviews (129 of 144, 7,606 cases) were included. • Results: Obesity, hypertension, and diabetes prevalence in the 129 census tracts showed clear geographic clustering when mapped using GIS software. Linear regression analysis shows that spatial distribution of risk factors clusters with diabetes, hypertension, and obesity prevalence. Geographic clusters were similar for the health access, health behaviors, neighborhood safety, demographics, socioeconomic status, and neighborhood contextual measures obtained from census data. • Conclusion: Analysis of geographic clustering can be used to identify high-risk neighborhoods and may be useful in planning and targeting public health interventions.