Evidence map›Paper›PMID 41029665›Full record

ArticleBMC public health2025

Understanding the factors associated with hypertension in the Western Himalaya: a GIS integrated analysis.

Arshad Ahmed, Kheraj, Alireza Mohammadi, Zata Ismah, Robert Bergquist

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Arshad AhmedDepartment of Geography, School of Basic Sciences, Central University of Haryana, Mahendergarh, India.ORCID http://orcid.org/0000-0002-5196-928X
KherajDepartment of Geography, School of Basic Sciences, Central University of Haryana, Mahendergarh, India.ORCID http://orcid.org/0000-0002-1107-5628
Alireza MohammadiDepartment of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran. a.mohammadi@uma.ac.ir.ORCID http://orcid.org/0000-0002-3327-0942
Zata IsmahState Islamic University of Sumatera Utara, Medan, Indonesia.
Robert BergquistIngerod, Brastad, SE-454 94, Sweden.ORCID http://orcid.org/0000-0002-0190-1084

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study investigates the prevalence and determinants of hypertension among the Gujjar Bakarwals tribe in multi-altitude zones (314-4,713 m) of the western Himalaya. The aim is to assess the association of geographic altitude along with key demographic, socioeconomic, environmental, and behavioral variables on hypertension prevalence using integrated Geographic Information Systems (GIS) and statistical methods.

methodsUsing stratified sampling, we selected a representative sample (n = 816) from 50 villages. A binary logistic regression model (BLRM) was used to identify hypertension-associated factors, assessing model fit using Pseudo R². GIS mapped hypertension prevalence and associated factors across the study region. Receiver operating characteristics (ROC or area under the curve) was used for validation of the BLRM accuracy.

resultsOverall, 29.9% of the study region reported hypertension in the year 2022. Those at the highest altitude had significantly higher odds of hypertension (adjusted odds ratio [AOR]: 2.19, 95% CI: 1.28-3.74, p = 0.004). Males exhibited notably higher prevalence than females (AOR: 2.77, 95% CI: 1.70-4.51, p < 0.001), and so did married individuals (AOR: 8.79, 95% CI: 5.00-15.46, p < 0.001). The likelihood of hypertension increased significantly with age (p < 0.001). Smoking, reliance on unclean water sources, and certain sanitation practices were linked to increased odds of hypertension with AOR: 1.79, 2.72 and 1.90 respectively. High-risk areas were mainly found in both low and high-altitude zones of Poonch and Rajouri districts. The BLRM demonstrated good fit (Hosmer-Lemeshow p = 0.954, Nagelkerke R² = 0.63), validated by the ROC curve (AUC = 0.93).

conclusionsThis study identifies critical socio-environmental and behavioural determinants of hypertension within high-altitude tribal populations. Findings inform context-specific public health strategies that address the geographic and cultural uniqueness of vulnerable communities. Integrating GIS and epidemiological tools can help policymakers develop altitude-adaptive, equity-driven hypertension interventions to improve cardiovascular outcomes in underserved regions.

Indexed as

AltitudeGeographic Information SystemsHypertensionAdolescentAdultAgedFemaleHumansIndiaMaleMiddle AgedPrevalenceRisk FactorsSocioeconomic FactorsYoung AdultBinary logistic regression model (BLRM)DeterminantsHypertension prevalenceMulti-altitudeSocioeconomic factors

Identifiers

PMID41029665
PMCPMC12487095

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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.