Rising Cardiovascular Disease Burden in India: Epidemiology, Risk Factors, Trends, and Strategic Interventions

N. Muniselvam, C. Balasundar, R. Dhivarshana, P. Abisha Rose, R. Soundharya

doi:10.15662/IJRAI.2026.0903013

Authors

N. Muniselvam, C. Balasundar, R. Dhivarshana, P. Abisha Rose, R. Soundharya Department of Information Technology, AAA College of Engineering and Technology, Sivakasi, Tamil Nadu, India Author

DOI:

https://doi.org/10.15662/IJRAI.2026.0903013

Keywords:

Cardiovascular disease, India, epidemiology, risk factors, public health, non-communicable diseases, hypertension, diabetes, AI in healthcare, prevention

Abstract

Cardiovascular diseases (CVDs) have emerged as the leading cause of mortality and morbidity in India, contributing significantly to the country's overall health burden. Rapid urbanization, lifestyle transitions, and demographic changes have accelerated the prevalence of CVD risk factors such as hypertension, diabetes, obesity, and physical inactivity. This work systematically examines the epidemiology, risk factors, trends, and public health challenges associated with CVD in India. It also evaluates the role of socio-economic determinants and proposes evidence-based strategies for prevention and control. The study underscores the urgent need for integrated healthcare approaches, robust policy interventions, and technology-driven solutions — including artificial intelligence and telemedicine — to mitigate the escalating burden of cardiovascular disease across the Indian population

References

1) Huberts et al., "Predictive Analytics for Cardiovascular Patient Readmission and Mortality using EHR Data and Machine Learning," J. Am. Coll. Cardiol. Informatics, 2024.

2) Karuppasamy, M., & Poorani, K. (2025). Metaheuristic Feature Selection for Diabetes Prediction with PGS Approach. Procedia Computer Science, 252, 165-171.

3) W. S. Weintraub, "Big Data in Cardiovascular Research: Opportunities and Challenges," JACC: Cardiovascular Imaging, 2019.

4) Upendra, H. S., Suman, S., Vishnu, S. S., & Dharani, J. (2021). Real-Time Face Mask Detection using OpenCV and Deep Learning. In ICET (Vol. 2021).

5) D. Prabhakaran et al., "Systematic Review on Cardiovascular Disease Prevalence in India," Indian Heart Journal, 2024.

6) Prabha, M., Karuppasamy, M., Saraswathi, P., Poorani, K., & Aswin Kumar, S. (2024, November). Personal Protective Equipment Detector Using Computer Vision. In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE) (pp. 38-41). IEEE.

7) V. Mohan et al., "Epidemiological transition studies in the Indian subcontinent: a narrative review," Lancet Reg. Health Southeast Asia, 2022.

8) Karuppasamy, M., Jansi Rani, M., & Poorani, K. (2025, February). Transfer Learning-Based Hybrid Deep Learning Model for COVID Detection. In International Conference On Innovative Computing And Communication (pp. 551-559). Singapore: Springer Nature Singapore.

9) X. Li et al., "Development of a Cardiovascular Clinical Research Data Warehouse with NLP-Based EMR Processing," J. Biomed. Informatics, 2025.

10) Jeyavani, M., & Karuppasamy, M. (2022). EEG in optic nerves disorder based on FSVM using kernel membership function. In ICT with Intelligent Applications: Proceedings of ICTIS 2022, Volume 1 (pp. 145-154). Singapore: Springer Nature Singapore.

11) K. S. Reddy and S. Yusuf, "Emerging epidemic of cardiovascular disease in developing countries," Circulation, vol. 97, no. 6, pp. 596–601, 1998.

12) Karuppasamy, M., & Balakannan, S. P. (2023). Retraction Note: An improving data delivery method using EEDD algorithm for energy conservation in green cloud network: M. Karuppasamy, SP Balakannan.

13) Ministry of Health and Family Welfare, Government of India, National Programme for Prevention and Control of NCDs — Programme Guidelines, 2023.

14) Gao, H., Wang, Z., & Ji, S. (2018, July). Large-scale learnable graph convolutional networks. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 1416-1424).

15) A. Rajpurkar et al., "AI in cardiovascular medicine: a position paper of the European Society of Cardiology," Eur. Heart J. Digit. Health, vol. 4, no. 4, pp. 255–264, 2023.

16) Karuppasamy, M., Prabha, M., & Jansi Rani, M. (2023, May). Future Worth: Predicting Resale Values with Machine Learning Techniques. In International Conference on Information, Communication and Computing Technology (pp. 1101-1112). Singapore: Springer Nature Singapore.

17) S. Anchala et al., "Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control," J. Hypertens., vol. 32, no. 6, pp. 1170–1177, 2014.

18) Prabha, M., Karuppasamy, M., Jansi Rani, M., & Poorani, K. (2025). Large-Scale Learnable Graph Convolutional Networks (LGCNs). In Graph Neural Networks: Essentials and Use Cases (pp. 21-44). Cham: Springer Nature Switzerland.

19) Institute for Health Metrics and Evaluation (IHME), Global Burden of Disease Study — India-Specific Data Sets, University of Washington, 2024.

20) M. Jansi Rani, and M. Prabha, An Efficient Resource Allocation Mechanism Using Intelligent Scheduling for Managing Energy in Cloud Computing Infrastructure, Information and Communication Technology for Competitive Strategies (ICTCS 2021), Lecture Notes in Networks and Systems 401 (2023), 81-86.

21) H. Bhaskaran et al., "Short-term effects of air pollution on cardiovascular events in England and Wales," Lancet, vol. 383, no. 9924, pp. 1196–1203, 2014.

22) Poorani, K., Balakannan, S. P., & Karuppasamy, M. (2025). Mitigating data imbalance for robust diabetes diagnosis using machine learning and explainable artificial intelligence. Journal of Current Science and Technology, 15(3), 111-111.

23) World Health Organization, Global Health Estimates: Cardiovascular Disease Mortality and Burden, WHO Press, 2023.

24) Jeyavani, M., & Karuppasamy, M. (2023, July). Brain Tumor Early Diagnosis Using Hybrid Fuzzy K-Means. In Proceedings of International Conference on Computational Intelligence: ICCI 2022 (p. 113). Springer Nature.

25) L. Loitongbam and W. R. Surin, "The Rising Burden of Cardiovascular Disease and Thrombosis in India," Cureus, 2024.

26) Karuppasamy, M., Jansi Rani, M., & Poorani, K. (2024, June). Recent Advances in Diabetic Monitoring Devices: Present to Future Directions. In International Conference on Soft Computing and Signal Processing (pp. 49-59). Singapore: Springer Nature Singapore.

27) R. Patel et al., "Trends in non-communicable disease burden in India: evidence from National Family Health Surveys," Lancet Glob. Health, vol. 11, no. 4, pp. e509–e519, 2023.

28) Karuppasamy, M., Rani, M. J., Kotha, M., Suma, S., Subburaj, T., Begum, H., & Suthendran, K. (2023, October). Retraction Notice: An Advanced Analysis of Disease Prediction and Prevention Using Machine Learning. In 2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) (pp. 1-1). IEEE.

29) D. Sinha et al., "Wearable sensor-based continuous cardiovascular monitoring: current challenges and future directions," npj Digit. Med., vol. 6, no. 1, p. 75, 2023.

30) Jansi Rani, M., Usha, S., Karuppasamy, M., Poorani, K., & Prabha, M. (2025). Graph Neural Networks Applications: A Dwell into Biomedical Applications and Traffic Flow Analysis. In Graph Neural Networks: Essentials and Use Cases (pp. 381-398). Cham: Springer Nature Switzerland.

31) A. Mishra et al., "Telemedicine for cardiovascular care in rural India: feasibility and outcomes of the eSanjeevani platform," J. Telemed. Telecare, vol. 29, no. 3, pp. 182–190, 2023.

32) M. Jansi Rani, M. K, M. Prabha, and K. Pooran, Detection of COVID-19 CoronaVirus Using ResNet Deep Learning Technique, Signal Processing, Telecommunication and Embedded Systems with AI and ML Applications, Lecture Notes in Electrical Engineering 1281 (2025), 71-83.

33) Park, G., Saranya, A., Karuppasamy, M., & Kim, J. (2024). Enhancing quality of service for IoT application in smart cities: A hybrid split learning and optimized routing approach. IEEE Transactions on Consumer Electronics, 70(3), 5969-5978.

34) Poorani, K., & Karuppasamy, M. (2023, April). Comparative analysis of chronic kidney disease prediction using supervised machine learning techniques. In International Conference on Information and Communication Technology for Intelligent Systems (pp. 87-95). Singapore: Springer Nature Singapore.

35) Sureshkumar, A., Maragatharajan, M., Jangiti, K., Karuppasamy, M., Jayabalan, K., Raut, P. T., & Sivakumar, N. R. (2026). A lattice-integrated AES framework for ultra-secure biometric protection on resource-constrained edge devices. Scientific Reports.