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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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional survey was conducted among 18,963 patients aged\u2009\u2265\u200965 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\u2019s 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\u2019s effect. Together, these complementary models enable both ranking of factor importance and mapping of spatially heterogeneous effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Central-northern rural communities exhibited the most pronounced high-high spatial clustering of cognitive impairment (Global Moran\u2019s I\u2009=\u20090.17,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). 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\u2009=\u20098.62%, 95% CI: 5.64%\u201313.01%) and adequate sleep (STVPI\u2009=\u20095.21%, 95% CI: 2.26%\u201310.36%) 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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Cognitive 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\u2014income support in north-central communities, inpatient care improvement in peripheral areas, and clean cooking promotion in western communities. The BSVC\u2013MGWR framework provides a replicable tool for identifying high-risk areas and guiding precision resource allocation in resource-limited rural settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12877-026-07587-4","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T08:09:02Z","timestamp":1779091742000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial heterogeneity and influencing factors of cognitive impairment among elderly hypertensive patients: evidence from rural communities in China"],"prefix":"10.1186","volume":"26","author":[{"given":"Jiaxin","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yudong","family":"Miao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanlei","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingbao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongfang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinran","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyue","family":"Zhen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinxin","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingxiao","family":"Mou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingyong","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yixi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingwei","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingming","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clifford Silver","family":"Tarimo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuping","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongmei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenyong","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"issue":"12","key":"7587_CR1","doi-asserted-by":"publisher","first-page":"e661","DOI":"10.1016\/s2468-2667(20)30185-7","volume":"5","author":"L Jia","year":"2020","unstructured":"Jia L, Du Y, Chu L, et al. 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