Spatial Clustering of Cause Specific Mortality
Jeralynn S. Cossman, Mississippi State University
Wesley James, Mississippi State University
Ronald E. Cossman, Mississippi State University
County-level, all-cause age-adjusted mortality in the US has spatial clusters with high mortality clusters largely in the Southeast and low mortality clusters in the West and Great Plains (Cossman, et al. 2004). Though attempts to predict spatial inequalities have been made, no models work for high and low mortality counties across all US regions. Knowing this, we propose that all causes of death are not created equally – patterns of spatial variation in all-cause mortality will vary from patterns of cause-specific mortality? Using Centers for Disease Control data, we calculate age-adjusted cause-specific mortality rates for leading causes of death: cardiovascular disease, cerebrovascular disease, unintentional injuries, respiratory diseases and cancers. analyzes include the statistical testing (via Moran’s I) for spatial clusters of these mortality rates. Additional analyzes explore potential spatial regression models appropriate for each cause. We expect to find that deaths associated with each cause will have distinctive spatial patterns.