Evidence map›Paper›PMID 41417780›Full record

ArticlePloS one2025

Spatial patterning of hypertension and its association with comorbidities and risk factors: A cross-sectional study in South India.

Thenmozhi Mani, Marimuthu Sappani, Melvin Joy, Chhavi Garg, Vishalakshi Jeyaseelan, Malavika Babu, Rajagopal Arunachalam, Jothilakshmi Durairaj, Ivan James Prithishkumar, Sebastian George and 3 more

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Article in PloS one, 2025. 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

What it found

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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

13 authors.

Thenmozhi ManiPopulation Health Research Institute, McMaster University, Hamilton, Ontario, Canada.ORCID https://orcid.org/0000-0002-3932-5625
Marimuthu SappaniDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
Melvin JoyTranslational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
Chhavi GargFaculty of Science, Global Health Research, Vrije Universiteit, Amsterdam, the Netherlands.
Vishalakshi JeyaseelanPolio Eradication, World Health Organization, Geneva, Switzerland.
Malavika BabuCentre for Trials Research, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom.
Rajagopal ArunachalamDepartment of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India.
Jothilakshmi DurairajSchizophrenia Research Foundation (SCARF), Chennai, India.
Ivan James PrithishkumarMohammed Bin Rashid University of Medicine and Health Sciences, Dubai Healthcare City, Dubai, United Arab Emirates.
Sebastian GeorgeDepartment of Statistical Science, Kannur University, Kannur, Kerala, India.
Edwin Sam AsirvathamHealth Systems Research India Initiative (HSRII), Trivandrum, Kerala, India.
Thambu David SudarsanamDepartment of Medicine, Christian Medical College and Hospital, Vellore, Tamil Nadu, India.
Lakshmanan JeyaseelanMohammed Bin Rashid University of Medicine and Health Sciences, Dubai Healthcare City, Dubai, United Arab Emirates.ORCID https://orcid.org/0000-0002-9090-3005

Funding

World Health Organization 001
6 · The paper itself

Abstract

introductionNon-communicable diseases (NCDs), particularly hypertension (HTN), pose a significant global health challenge, accounting for a substantial proportion of premature deaths worldwide. In India, HTN prevalence varies widely across states and districts and is influenced by demographic, socioeconomic, and lifestyle factors. This study aims to assess the spatial distribution of HTN and its correlates in South India. MATERIALS AND

methodsThis study utilized data from the 5th National Family Health Survey (NFHS-5), a nationally representative cross-sectional survey conducted across India between 2019 and 2021. For this analysis, data from five states and one union territory in South India were used. Bayesian spatial modelling was employed to analyse HTN prevalence at the district level, incorporating demographic, socioeconomic, and lifestyle covariates.

resultsThe study included 304,420 adults, both male and female, aged >18 years. The overall prevalence of pre-HTN and HTN was 28.9% and 31.8%, respectively. HTN prevalence varied across states, with Kerala exhibiting the highest prevalence. Spatial clustering analysis identified districts with significantly higher HTN prevalence, often clustering with neighbouring districts showing similar patterns. Spatial autocorrelation analyses revealed a significant association between HTN and diabetes. Other comorbidities and risk factors were not significantly associated with HTN.

conclusionThe findings underscore the spatial heterogeneity of HTN prevalence within South Indian states and districts. The study highlights the need for targeted interventions tailored to local contexts to effectively mitigate the burden of HTN and associated comorbidities.

Indexed as

HypertensionAdolescentAdultAgedBayes TheoremComorbidityCross-Sectional StudiesDiabetes MellitusFemaleHealth SurveysHumansIndiaLife StyleMaleMiddle AgedPrevalence

Identifiers

PMID41417780
PMCPMC12716782

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