OBJECTIVES: To identify individual and contextual factors contributing to overall prostate cancer mortality in Florida. METHODS: Using men diagnosed with prostate cancer between 10/1/2001 and 12/31/2007 in the Florida Cancer Data System, the following patient’s information were extracted: demographics, type of health insurance at diagnosis, tumor stage, treatment and all-cause death. Census-tract level socioeconomic status & farm house presence were extracted from Census 2000 and linked to patient data. Comorbidity was computed following Elixhauser Index. Multi-level logistic regression was conducted to identify significant individual and contextual factors to overall mortality among the prostate cancer patients.  RESULTS: 60,497 patients were identified, among whom 8,125 died. Being older at diagnosis, unmarried, current smoker, uninsured, diagnosed at late stage, undifferentiated or unknown tumor grade and poorly differentiated tumor grade were significantly associated with overall mortality. Interaction between stage and grade showed more detrimental late-stage effect as grade worsened and increasingly disadvantageous grade effect at later stage of diagnosis. Low educational attainment of the census tract where patient lived was significantly related to mortality. After adjusting for age, stage and tumor grade, patients who received other treatment categories, except for those who received combined surgery and radiation therapy, were more likely to die compared to those received surgery only. A large number of major comorbidities such as congestive heart failure, peripheral vascular disorder, paralysis, chronic pulmonary disease, diabetes, renal failure, liver disease, a number of other malignancies, etc. were associated with increased risk of mortality. CONCLUSIONS: Multi-level modeling allows examination of factors at various levels in relation to patient overall mortality.  Patient’s demographics, disease stage, comorbidity and available treatment are associated with overall mortality among prostate cancer patients. Although disease specific mortality was not examined, these findings suggest the importance of careful consideration of multiple patient and disease characteristics in treatment decision making.