Multivariate Analysis of the Impact of Demographic and Clinical Factors on Cardiovascular Health

Abstract

AbstractBackgroundThis study investigates the influence of demographic and clinical factors on cardiovascular health using a multivariate analysis approach. We analyzed data from one of the largest heart-related disease datasets, merging variables such as age, sex, chest pain type, to determine their association with resting blood pressure, cholesterol, and maximum heart rate.MethodsTwo-means comparison is used to investigate the effect of heart disease with response variables, One-way and two-way MANOVA are used to study the relationship between chest pain type, as well as sex and heart disease on the response variables, respectively. Profile analysis and MANCOVA were also conducted to determine a final model.ResultsOur findings indicate significant effects of heart disease on resting blood pressure, cholesterol and maximum heart rate. Chest pain type also has a significant effect on maximum heart rate achieved, but not blood pressure and cholesterol. There are also notable interactions between sex and heart disease status on all response variables. Finally, we formulized a multivariate regression model with age, sex, chest pain type, heart disease, and the interaction between heart disease and sex as predictors.ConclusionThese findings can inform physicians on possible treatment strategies in cardiovascular diseases.