Analyzing risk factors of Black to White prostate cancer rate based on simulation model

Prostate cancer is a major health concern for men over 50 years of age.  More than 200,000 new cases in the United States are diagnosed annually, and around 30,000 die from it each year. Risk factors that increase chances of one getting this disease include family history, race (especially African American), steadily consuming fatty foods, being physically inactive, and frequent exposure to cadmium, an extremely toxic metal found in industrial workplaces. Studies have also shown risk factors such as age, smoking, drinking, socioeconomic status, physical inactivity, obesity, and lifestyle can play a major role in the development of prostate cancer. This presentation will describe a study done to determine which risk factors contribute significantly to the prospect of acquiring prostate cancer so that interventions can be developed to either prevent or control the disease.  A Monte Carlo simulation model in IBM SPSS was constructed to determine the relationship between U.S. state-level Black-to-White prostate cancer rate and related risk factors. Simulation model was run on the initial analysis for multiple linear regression function. Of the 12 risk factors related to state-level Black-to-White prostate cancer rate, the most influential four factors were identified as cigarette smoking, per capita income, alcohol consumption, and obesity. The study results from simulation model were consistent with those in the literature. Analyzing multiple risk factors of prostate cancer in the communities may lead to the proposal of more comprehensive and integrated policies and intervention programs to solve the population-based problem.