Identifying risk factors of cardiovascular diseases through generalized linear model.

Cardiovascular diseases (CVDs) is one of the most prominent Non-communicable diseases (NCDs) that influenced the increasing trend in world's mortality rate. Though this fact is commonly known, preventive and control measure should be made in an urgent manner to help reduce the risk of more death cases of CVDs. Hence, it is crucially important to understand the cause and effect of CVDs to lead effective preventive intervention from the individual, community and government level. In this paper, the objective of the study is to identify significant variables which are prominent risk factors of CVDs using Generalized Linear Model (GLM). The study focuses on non-laboratory risk factors of CVDs as an alternative for a non-clinical approach in understanding CVDs risk factors. The performance of the proposed method is investigated using available real data sets which focus on coronary heart disease (CHD). The results show that the significant risk factors of the CHD are sex, age, cigarettes per day, total cholesterol, systolic blood pressure (SBP), and glucose level. This finding shows that the factors affected the CHD are about the same with other types of CVDs. Hence, the risk factors for CHD for non-laboratory model can be considered in future research are sex, age, cigarettes per day, SBP, diastolic blood pressure, prevalent hypertension, body mass index and education. The result of this study is useful as a guide to all parties such as health practitioners, academicians, and ministries to provide and develop an effective preventive strategy to reduce the CVDs related to the mortality rate. [ABSTRACT FROM AUTHOR]