Evidence map›Paper›PMID 40781477›Full record

ArticleScientific reports2025

Regional factors affecting the prevalence of hypertension using geographic information system.

Hyojeong Lee, Jihye Lim

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Hyojeong LeeGraduate Student, Department of Health Science, Dong-A University, Busan, Korea.
Jihye LimDepartment of Health Care and Science, College of Health Science, Dong-A University, Busan, Korea. limjiart@dau.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to analyze the regional factors affecting the prevalence of hypertension in Korea using regional hypertension prevalence data. Data from the National Statistical Portal for the past 5 years (2018-2022) were collected and used as indicators of hypertension prevalence and regional variables in 229 regions. The correlation between hypertension prevalence and regional factors was investigated, and spatial statistical techniques such as spatial autocorrelation analysis, hotspot analysis, and geographically weighted regression analysis were performed to identify the spatial dependence of hypertension prevalence, hotspot and coldspot regions, and regional factors affecting regional hypertension prevalence. Regional factors influencing hotspots and coldspots were current smoking, high-risk drinking, obesity prevalence, and number of medical institutions per 100,000. The results of this study suggest that differentiated hypertension prevalence management strategies are needed according to hotspots and coldspots. In the future, this study is expected to be useful as basic data for health business policies to promote national and local health.

Indexed as

Geographic Information SystemsHypertensionFemaleHumansMalePrevalenceRepublic of KoreaRisk FactorsSpatial AnalysisGeographic weighted regressionHot spotHypertensionRegional variationSpatial autocorrelation

Identifiers

PMID40781477
PMCPMC12334712

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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.