Regression methods for analyzing the risk factors for a life style disease among the young population of India

Abstract

Background: With modernization, rapid urbanization and industrialization, the price that the society is paying is tremendous load of “Non-Communicable” diseases, referred to as “Lifestyle Diseases”. Coronary artery disease (CAD), one of the lifestyle diseases that manifests at a younger age can have divesting consequences for an individual, the family and society. Prevention of these diseases can be done by studying the risk factors, analyzing and interpreting them using various statistical methods. Objective: To determine, using logistic regression the relative contribution of independent variables according to the intensity of their influence (proven by statistical significance) upon the occurrence of values of the dependent cardio vascular risk scores. Additionally, we wanted to assess whether non parametric smoothing of the cardio vascular risk scores can be used as a better statistical method as compared to the existing methods. Materials and methods: The study includes 498 students in the age group of 18–29 years. Findings: Prevalence of over weight (BMI 23–25 kg/m2) and obesity (BMI > 25 Kg/m2) was found among individuals of 22 years and above. Non smokers had decreased odds (OR = 0.041, CI = 0.015–0.107) and also increase in LDL Cholesterol (OR = 1.05, CI = 1.021–1.055) and BMI (OR = 1.42, CI = 1.244–1.631) were significantly contributing towards the risk of CVD. Localite students had decreased odds of developing CVD in the next 10 years (OR = 0.27, CI = 0.092–0.799) as compared to students residing in hostel or paying guests.

Keywords

• Cardio vascular risk assessment score
• Binary logistic regression analysis
• Non parametric smoothing
• Kernel local linear regression function
• Statistical methods of risk assessment