{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T06:22:15Z","timestamp":1787638935101,"version":"build-2736575974"},"reference-count":92,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Public healthcare infrastructure is essential for ensuring equitable access to medical services, particularly in mountainous regions characterized by uneven development and tourism-oriented spatial environments. This study examines the spatial distribution of public healthcare infrastructure in Southwest China from a health geography perspective with particular attention to accessibility, spatial inequality and residential tourism contexts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional spatial analytical framework was applied to examine public healthcare infrastructure in Southwest China. Spatial analysis methods and the geographic detector model were employed to identify distribution patterns and associated factors. Residential tourism was operationalized through tourism-related spatial proxy variables rather than direct measures of tourist mobility or seasonal residence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Public healthcare infrastructure exhibited a significant clustered distribution with high-density areas concentrated in Chengdu, Chongqing, Guiyang and Kunming and extensive low-density areas located in remote mountainous regions. Road network density showed the strongest explanatory power, followed by A-level scenic spot density and residential density. Interaction effects generally exceeded the explanatory power of individual variables with the interaction between road network density and A-level scenic spot density being the strongest. Traditional Village density showed negligible independent explanatory power.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The distribution of public healthcare infrastructure in Southwest China reflects pronounced core-periphery inequality in facility concentration and the combined spatial associations of transportation connectivity, residential concentration, regional development and tourism-oriented environments. The findings extend the contextual application of health geography to residential tourism settings and provide a spatial screening basis for differentiated healthcare infrastructure planning. They should be interpreted as cross-sectional spatial associations rather than evidence of population mobility or seasonal healthcare demand.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1912761","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:34:25Z","timestamp":1787636065000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial distribution and associated factors of public healthcare infrastructure in tourism-oriented environments: evidence from Southwest China in the context of residential tourism"],"prefix":"10.3389","volume":"14","author":[{"given":"Hong","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Tourism Management, South China University of Technology","place":["Guangzhou, China"]},{"name":"Guizhou Minzu University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Tourism Management, South China University of Technology","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shenghua","family":"Yu","sequence":"additional","affiliation":[{"name":"Guizhou Minzu University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoju","family":"Wang","sequence":"additional","affiliation":[{"name":"Guizhou Minzu University","place":["Guiyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"6176","DOI":"10.1061\/jmenea.meeng-6176","article-title":"Dynamic resilience assessment for urban healthcare infrastructure operations considering the spatiotemporal characteristics of public 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