The cardiovascular system is an significant system which transports various metabolic essential substances to the body and excretes respiratory metabolites from the body to maintain the basic needs of the human. Cardiovascular disease is a widespread disease with a high mortality rate, which poses a great threat to the health of the population. This study analyzed data from the Behavioral Risk Factor Monitoring System (BRFSS) to build a predictive model to assess which behavioral factors are strongly associated with cardiovascular disease. The data included 13,210 clinical samples and 11 variables such as Exercise, Smoking-History. The target variable is whether the patient has been diagnosed with heart disease. In this study, a logistic regression model was used to process the data of BRFSS. It was concluded that the incidence of cardiovascular disease was positively associated with age, history of smoking, having other cancers and having depression, while fruit-consumption and exercise had an inhibitory effect on the incidence of cardiovascular disease. The accuracy of the training set was about 95.95% and the prediction results of the model were found to be acceptable after fitting. In order to better predict the association of heart disease with behavioral factors, more comprehensive clinical data and more advanced analytical techniques are needed. This model provided assistance for studying the induction of heart disease by behavioral factors.
