Evidence map›Paper›PMID 41289228›Full record

ArticleGerontology2026

State-Level Variations in Hypertension Management and Cardiovascular Disease Risks in India: Public Spending on Health and Socioeconomic Inequalities.

Kanya Anindya, Yang Zhao, Sukumar Vellakkal, Arokiasamy Perianayagam, Sanghamitra Pati, Tiara Marthias, Mansi Malik, John Tayu Lee

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Article in Gerontology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Kanya AnindyaSchool of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Yang ZhaoHealth Services Research Institute, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore, yangz01@nus.edu.sg.
Sukumar VellakkalDepartment of Economic Sciences, Indian Institute of Technology Kanpur, Kalyanpur, India.
Arokiasamy PerianayagamSocial and Economic Survey Research Institute (SESRI), Qatar University, Doha, Qatar.
Sanghamitra PatiICMR-Regional Medical Research Centre, Bhubaneswar, India.
Tiara MarthiasNossal Institute for Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
Mansi MalikDepartment of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Gadjah Mada University, Yogyakarta, Indonesia.
John Tayu LeeInstitute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

<p>Introduction: This study aimed to assess the within- and between-states inequality in hypertension management and cardiovascular disease (CVD) risk across sociodemographic groups in India and the correlation between states/UTs expenditure on health, hypertension management, and CVD risk.

methodsThis study utilized cross-sectional data from 2017/2018 Longitudinal Aging Study in India (LASI), with a total sample of 58,848 respondents aged ≥45 years. Hypertension management was assessed based on hypertension awareness, treatment, and control, while 10-year CVD risk was measured using the 2019 WHO CVD risk. We used multilevel logistic regression models to estimate the socioeconomic inequality in hypertension management and 10-year CVD risk, measured by the relative index of inequality (RII).

resultsRural areas had a substantially poorer coverage of hypertension awareness, treatment, and control compared with urban areas. Richest socioeconomic groups were more likely to be aware of their hypertensive status (RII 1.28, 95% CI: 1.16-1.42), receive antihypertensive treatment (RII 1.47, 95% CI: 1.28-1.69), have their blood pressure controlled (RII 1.60, 95% CI: 1.34-1.90), and have 10-year CVD risk <10% (1.06, 95% CI: 1.01-1.12) compared to the poorest. The variance partition coefficient ranged from 1.5% for 10-year CVD risk to 9.9% for hypertension control. There was no significant correlation between socioeconomic inequality in hypertension management, 10-year CVD risk, and the per capita public health expenditure of states/UTs.

conclusionDifferences in state-level health system capacity may disproportionately affect socioeconomically disadvantaged populations, underscoring the need for more equitable hypertension management and cardiovascular health strategies across India. </p>.

Indexed as

Cardiovascular DiseasesHealthcare DisparitiesHealth ExpendituresHypertensionAgedAntihypertensive AgentsCross-Sectional StudiesFemaleHeart Disease Risk FactorsHumansIndiaLongitudinal StudiesMaleMiddle AgedRural PopulationSocioeconomic FactorsAntihypertensive AgentsCardiovascular risk factorsHealth inequitiesHypertensionIndia

Identifiers

PMID41289228
PMCPMC12788826

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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.