Regional factors affecting the prevalence of hypertension using geographic information system
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 prevalenc...
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Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-14981-2 |
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| author | Hyojeong Lee Jihye Lim |
| author_facet | Hyojeong Lee Jihye Lim |
| author_sort | Hyojeong Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-320d1a081a02458287adbf1f8d76f642 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-320d1a081a02458287adbf1f8d76f6422025-08-20T03:43:11ZengNature PortfolioScientific Reports2045-23222025-08-0115111110.1038/s41598-025-14981-2Regional factors affecting the prevalence of hypertension using geographic information systemHyojeong Lee0Jihye Lim1Graduate Student, Department of Health Science, Dong-A UniversityDepartment of Health Care and Science, College of Health Science, Dong-A UniversityAbstract 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.https://doi.org/10.1038/s41598-025-14981-2HypertensionSpatial autocorrelationHot spotGeographic weighted regressionRegional variation |
| spellingShingle | Hyojeong Lee Jihye Lim Regional factors affecting the prevalence of hypertension using geographic information system Scientific Reports Hypertension Spatial autocorrelation Hot spot Geographic weighted regression Regional variation |
| title | Regional factors affecting the prevalence of hypertension using geographic information system |
| title_full | Regional factors affecting the prevalence of hypertension using geographic information system |
| title_fullStr | Regional factors affecting the prevalence of hypertension using geographic information system |
| title_full_unstemmed | Regional factors affecting the prevalence of hypertension using geographic information system |
| title_short | Regional factors affecting the prevalence of hypertension using geographic information system |
| title_sort | regional factors affecting the prevalence of hypertension using geographic information system |
| topic | Hypertension Spatial autocorrelation Hot spot Geographic weighted regression Regional variation |
| url | https://doi.org/10.1038/s41598-025-14981-2 |
| work_keys_str_mv | AT hyojeonglee regionalfactorsaffectingtheprevalenceofhypertensionusinggeographicinformationsystem AT jihyelim regionalfactorsaffectingtheprevalenceofhypertensionusinggeographicinformationsystem |