Evidence map›Paper›PMID 39301516›Full record

ArticleFrontiers in public health2024

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.

Anshul Mamgai, Pritam Halder, Ashish Behera, Kapil Goel, Saumyarup Pal, K S Amudhamozhi, Divya Sharma, Tanvi Kiran

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Depression and Multimorbidity among Older Indians Residing in Front-Runner, Achiever and Aspirant States: Insight from Longitudinal Ageing Study in India (LASI) - Wave I.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2026
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  12. Burden of non-communicable diseases in South Asia: a decomposition analysis.Journal of health, population, and nutrition · 2025
    Article
  13. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Anshul Mamgai *Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Pritam Halder *Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Ashish BeheraDepartment of Internal Medicine, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Kapil GoelDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Saumyarup PalDepartment of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India.
K S AmudhamozhiDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Divya SharmaDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Tanvi KiranDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: 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. Methods: 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 chi-square 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. Result: 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 Conclusion: 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.

Indexed as

Cardiovascular DiseasesHypertensionAgedFemaleHeart Disease Risk FactorsHumansIndiaLongitudinal StudiesMaleMiddle AgedRisk AssessmentRisk FactorsSurveys and QuestionnairesWorld Health Organizationcardiovascular riskhypertensionnon-laboratory basedolder Indian adultsrisk prediction chartWHO CVD risk prediction chart

Identifiers

PMID39301516
PMCPMC11410575

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.