BACKGROUND: Chronic Diseases are the leading causes of death in the US as well as in Shelby County, Tennessee, where six chronic diseases; heart, malignant neoplasms, cerebrovascular diseases, Alzheimer’s, chronic lower respiratory disease and diabetes are among the top 10 leading causes of death. Sub-County analysis (zip code level) of chronic disease mortality in Shelby County has shown heterogeneity in the distribution of chronic diseases within County zip codes. However, this information alone is not enough considering the complex interaction between social determinants and behavior as major contributors to chronic diseases morbidity and mortality rates. Additional information is required to highlight hot-spots requiring immediate intervention as well as identifying specific drivers contributing to those problems. One solution to this problem is to combine sub-County analysis of chronic disease with Sub-County Analysis of Life Expectancy (SCALE) along with the Economic Hardship Index (EHI). Combining the three analyses allow for a more complete understanding and targeted intervention.
METHODS: Age Adjusted mortality rates and SCALE were calculated using the Age-Adjuster tool by (Matt Byers). EHI was calculated based on the “Intercity Hardship Index.” By Richard P. Nathan and Charles F. Adams, Jr. The EHI score focuses on 6 social determinant indicators; unemployment (over age of 16 year), education (over 25 years without high school diploma), Income level per capita, poverty (below federal poverty level), crowded housing (housing with more than one person per room) and dependency (under18 and over 64). The scale is rated from 0-100, where the higher the number indicates economic hardship. The data was mapped using GIS ArcMap software from ESRI.
RESULTS: Sub-county analysis of chronic disease mortality rates identified various hotpots which corresponded closely to the SCALE and EHI hotspots. These areas are located on the western side of the County. Four specific zip code areas stood out; 38127, 38126+38106, 38107+38108 and 38118. Further analysis of each of the 6 EHI indicators highlighted specific problems within each zip code area: the major problem in 38127 is income; in 38126+38106, unemployment, poverty and income are major problems; in 38107+38108 crowded housing and education; and in 38118, low income.
CONCLUSIONS: In addition to the sub-County analysis of chronic disease mortality rates, local health departments should examine patterns of Life expectancy and Economic hardship index as important methods of understanding the patterns and determinants of disease. This information allows limited funds to be used to target specific problems within a community.