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ORIGINAL RESEARCH article

Front. Public Health
Sec. Aging and Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1407918
This article is part of the Research Topic Metabolic Diseases and Healthy Aging: Prevention and Public Health Policy Based on Risk Factors View all 9 articles

Cardiovascular Risk Assessment Using Non-Laboratory Based WHO CVD Risk Prediction Chart with Respect to Hypertension Status among Older Indian Adults: Insights from Nationally Representative Survey

Provisionally accepted
  • 1 Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, Haryana, India
  • 2 Department of Internal Medicine, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, Haryana, India
  • 3 Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, National Capital Territory of Delhi, India

The final, formatted version of the article will be published soon.

    Knowledge of the risk of developing cardiovascular diseases (CVD) in the population is an important risk management strategy for the prevention of this disease. This is especially true for India, which has resource-restrained settings with an increased risk in a younger population for the development of the disease. An important modifiable risk factor for CVD is hypertension, with its influence on the development of CVD.The data from the first wave of the Longitudinal Ageing Study in India (LASI) was used to calculate the 10-year CVD Risk Score among older adults > 45 years using a WHO ( 2019) non-laboratory-based chart for South Asia. Univariate analysis was done using Pearson's chisquare test, and multivariable analysis using ordinal logistic regression. Categories of CVD risk score were considered as dependent variable. Socio-demographic variables, regular exercise, history of diabetes and hyperlipidaemia were considered as the independent variables. Relationship between CVD Risk score and hypertensives and self-reported hypertensives were presented using restricted cubic splines.Two-thirds (68.8%) of the population had a 10-year CVD risk of < 10%, and 2.8% had a risk of ≥ 20%. The self-reported hypertensives were distributed linearly in restricted cubic splines, with a more scattered distribution in higher scores, while actual hypertensives showed a sigmoid pattern. Urban residents (OR-0.88), being unmarried (OR-0.86), being in the richer (OR-0.94) and richest (OR-0.86) monthly per capita expenditure (MPCE) quintile and exercising regularly (OR-0.68) decreased the odds of being in a higher CVD risk score. Less than primary schooling (1.21) and diabetics (1.69) had higher odds for a higher CVD risk score.In this population, two-thirds had < 10% risk for the development of CVD. The study shows a higher risk among rural, poor, and those with a lower education and lower CVD risk for those undertaking physical activity. The sigmoid pattern in actual hypertensives highlights the need for early detection. Even those with undiagnosed hypertension but with a higher BP had a similar risk for disease development, thus highlighting the need for an early detection of hypertension.

    Keywords: cardiovascular risk, Non-Laboratory Based, WHO CVD Risk Prediction Chart, Risk Prediction Chart, Hypertension, Indian adults

    Received: 27 Mar 2024; Accepted: 26 Aug 2024.

    Copyright: © 2024 Mamgai, Halder, Behera, Goel, Pal, KS, Sharma and Kiran. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Tanvi Kiran, Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, 160 012, Haryana, India

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