Impact of Cardiovascular Health in South India
DOI:
https://doi.org/10.15662/IJEETR.2026.0803007Keywords:
Cardiovascular Disease, Machine Learning, Random Forest, South India, Risk Prediction, HbA1c, Hypertension, BMI, Predictive AnalyticsAbstract
Cardiovascular diseases (CVD) are the leading cause of death in South India, driven by the growing epidemic of diabetes mellitus, unhealthy dietary habits, sedentary lifestyles, and genetic predisposition across Tamil Nadu, Kerala, Karnataka, Andhra Pradesh, and Telangana. Persistent hyperglycaemia damages endothelial cells, promotes atherogenesis, elevates blood pressure, and disrupts lipid metabolism, collectively amplifying cardiovascular risk. This research analyses the impact of diabetes on cardiovascular health in South India, identifies major risk factors, and proposes a Machine Learning (ML)-based predictive model using the Random Forest algorithm to assess CVD risk in diabetic patients. Key input features include age, blood glucose level (HbA1c), blood pressure, cholesterol, and BMI. The system enables early identification of high-risk individuals, supports timely medical intervention, and enhances clinical decision-making
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