45: Logistic Regression Analysis of Predictors for Heart Disease

Thomas M. Menino Convention & Exhibition Center 

Heart disease remains a leading cause of mortality in the United States with substantial implications for public health and healthcare expenditures. This study applied logistic regression to assess associations between various predictors, including chronic conditions, lifestyle habits, social demographics, and healthcare access, and the odds of self-reported coronary disease or heart attack. The data were a subset of the 2015 Behavioral Risk Factor Surveillance System (BRFSS) with 22 features from 253,680 individuals. Variable selection was performed using forward selection and backward elimination based on AIC and BIC criteria, and model performance was evaluated using standard predictive accuracy measures. Key predictors included history of cholesterol screening, prior stroke, inability to afford medical care, sex, and income level. These results may inform healthcare providers and payors about risk stratification and the promotion of preventive care. Notably, the positive association between cost-related barriers to healthcare access and heart disease underscores the potential value of policies aimed at reducing financial obstacles to care in mitigating cardiovascular risk.

logistic regression

odds ratios

coronary heart disease

risk factors

Behavioral Risk Factors Surveillance System (BRFSS)

healthcare access 

Section on Statistics in Epidemiology