Evidence map›Paper›PMID 42151828›Full record

ArticleBMC geriatrics2026

Spatial heterogeneity and influencing factors of cognitive impairment among elderly hypertensive patients: evidence from rural communities in China.

Jiaxin Han, Yudong Miao, Zhanlei Shen, Jingbao Zhang, Dongfang Zhu, Xinran Li, Mingyue Zhen, Jiajia Zhang, Jinxin Cui, Lingxiao Mou and 8 more

Abstract read
In one paragraph

Article in BMC geriatrics, 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

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

18 authors.

Jiaxin HanDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Yudong MiaoDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Zhanlei ShenDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Jingbao ZhangDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Dongfang ZhuDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Xinran LiDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Mingyue ZhenDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Jiajia ZhangDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Jinxin CuiDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Lingxiao MouDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Qingyong LuDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Yixi WangDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Jingwei QinDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Jingming WeiInstitute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
Clifford Silver TarimoDepartment of Health Management, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
Qiuping ZhaoHenan Key Laboratory for Health Management of Chronic Diseases, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 451450, Henan, China.
Rongmei LiuHenan Key Laboratory for Health Management of Chronic Diseases, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 451450, Henan, China.
Wenyong DongHenan Provincial People's Hospital, Zhengzhou University People's Hospital, Jinshui District, No. 7, Weiwu Road, Zhengzhou, 450003, Henan, China. vanny89@163.com.

Funding

Henan Provincial Philosophy and Social Sciences Innovative Talent Project 2023-CXRC-06National Science and Technology Major Project of China 2024ZD0526801
6 · The paper itself

Abstract

backgroundCognitive impairment is frequent but often overlooked among elderly hypertensive individuals in rural settings. Existing studies have predominantly relied on global statistical models that assume uniform effects across space, failing to capture geographic heterogeneity in risk factor mechanisms and limiting the development of geographically targeted intervention strategies.

methodsA cross-sectional survey was conducted among 18,963 patients aged ≥ 65 years with diagnosed hypertension in Jia County, Henan Province, China (August 2023). The Bayesian Spatial Variable Coefficient (BSVC) model was applied to quantify each determinant's spatial contribution using the Spatial Target Variable Contribution Index (STVPI). The Multi-Scale Geographically Weighted Regression (MGWR) model was subsequently employed to characterize the spatial scale and directional variation of each factor's effect. Together, these complementary models enable both ranking of factor importance and mapping of spatially heterogeneous effects.

resultsCentral-northern rural communities exhibited the most pronounced high-high spatial clustering of cognitive impairment (Global Moran's I = 0.17, p < 0.001). Lifestyle factors accounted for the largest share of spatial variation (25.34%), identifying behavioral determinants as the primary modifiable drivers of geographic disparities. Physical activity (STVPI = 8.62%, 95% CI: 5.64%-13.01%) and adequate sleep (STVPI = 5.21%, 95% CI: 2.26%-10.36%) demonstrated spatially stable protective effects consistent across all communities. In contrast, per capita household income, distance to major roads, and number of hospitalizations showed significant spatial heterogeneity, with effects varying substantially by location.

conclusionCognitive impairment among rural elderly hypertensive patients exhibits significant spatial clustering, with high-burden communities concentrated in the central-northern region. Physical activity and adequate sleep are spatially stable protective factors suitable for county-wide behavioral intervention, while income, healthcare access, and cooking environment require geographically differentiated responses-income support in north-central communities, inpatient care improvement in peripheral areas, and clean cooking promotion in western communities. The BSVC-MGWR framework provides a replicable tool for identifying high-risk areas and guiding precision resource allocation in resource-limited rural settings.

Indexed as

Cognitive DysfunctionHypertensionRural PopulationAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleRisk FactorsCognitive impairmentElderlyHypertensionSpatial heterogeneity

Identifiers

PMID42151828
PMCPMC13488023

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