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Using data from 2022 Nepal Demographic and Health Survey and other sources, we assessed the relationships between geographical accessibility and the utilisation of the three major healthcare services (ie, four or more antenatal care (ANC) visits, institutional delivery and postnatal care (PNC) check-up), by applying Bayesian geostatistical models. High-resolution maps on coverage of the above services were produced.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The geographical accessibility showed high in the central and southern Terai belt but low in the northern mountains, with average travel-mode adjusted travel time for ANC, institutional delivery and PNC 26.74, 40.72 and 29.09\u2009min, respectively. Negative correlations were found between geographical accessibility with four or more ANC visits (OR 0.76, 95% Bayesian credible interval, BCI 0.65 to 0.90), institutional delivery (OR 0.76, 95% BCI 0.64 to 0.90) and PNC check-up (OR 0.87, 95% BCI 0.76 to 0.99), respectively. Population-weighted coverages for four or more ANC visits, institutional delivery and PNC check-up were estimated 83.25% (95% BCI 80.43% to 85.35%), 84.26% (95% BCI 81.30% to 86.08%) and 73.19% (95% BCI 69.43% to 76.09%), respectively, across Nepal. The northern mountains and southeastern Terai showed low coverage for the three healthcare services, while the central, eastern and western hilly regions exhibited good coverage.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Geographical accessibility is important in utilisation of maternal health services in Nepal. The high-resolution maps enable an evidence-based assessment for better health planning.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/bmjgh-2024-017229","type":"journal-article","created":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T13:05:23Z","timestamp":1739451923000},"page":"e017229","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":4,"title":["Spatial profiling of geographical accessibility to maternal healthcare and coverage of maternal health service utilisation in Nepal: a geospatial analysis based on demographic and health survey"],"prefix":"10.1136","volume":"10","author":[{"given":"Heng-Qian","family":"Huang-fu","sequence":"first","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biraj","family":"Karmacharya","sequence":"additional","affiliation":[{"name":"Departments of Public Health and Community Programs, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Uttam Kumar","family":"Koirala","sequence":"additional","affiliation":[{"name":"Epidemiology and Disease Control Division, Department of Health Services, Kathmandu, Nepal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang-Wen","family":"Ke","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory for Emergency Detection and Research on Pathogen of Emerging Infectious Disease, Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9881-6504","authenticated-orcid":false,"given":"Chun","family":"Hao","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China"},{"name":"Sun Yat-Sen Global Health Institute, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4324-5465","authenticated-orcid":false,"given":"Ying-Si","family":"Lai","sequence":"additional","affiliation":[{"name":"Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China"},{"name":"Sun Yat-Sen Global Health Institute, Sun Yat-sen University, Guangzhou, China"},{"name":"Research Center of Health Informatics, Sun Yat-sen University, Guangzhou, China"},{"name":"Guangdong Key Laboratory of Health Informatics, Guangzhou, China"},{"name":"Guangzhou Joint Research Center for Disease Surveillance, Early Warning and Risk Assessment, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2025,2,13]]},"reference":[{"key":"2025073014451524000_10.2.e017229.1","unstructured":"World Health Organization . 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