This study investigated neighborhood geographic disparities in myocardial infarction (MI) and stroke mortality risks in middle Tennessee and identified determinants of observed disparities. Descriptive and spatial analyses were performed on MI and stroke mortality data covering the time period 1999?2007. Besag, York and Mollie (BYM) model was used to investigate spatial patterns. Global (BYM) and local models [Poisson Geographically Weighted Generalized Linear Models (GWGLM)] were used to investigate determinants of the identified spatial patterns. Significant (p <0.05) differences in mortality risks by sex, race, age and education were observed. Rural census tracts (CT) and those with higher proportions of the older populations were associated with high MI and stroke mortality risks. Additionally, CTs with high proportions of widows had significantly higher mortality risks for stroke. There was evidence of geographical variability of all regression coefficients implying that local models complement the findings of the global models and provide useful information to guide local and regional disease control decisions and resource allocation. Identification of high risk CTs is essential for targeting resources and will aid the development of more needs-based prevention programs.