{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Ge Y"],"funding":["Natural Science Foundation of Hunan","National Natural Science Foundation of China","National Science&amp; Technology Foundational Resource Investigation Program of China","Natural Science Foundation of Changsha"],"pagination":["e075088"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10679990"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(11)"],"pubmed_abstract":["<h4>Objective</h4>Little is known about spatial variability of hospitalisation rate (HR) of patients with rheumatoid arthritis (RA) worldwide, especially in China.<h4>Methods</h4>A cross-sectional study was conducted among patients with RA admitted to hospitals in Hunan Province. Global Moran's <i>I</i> and local indicators of spatial association were used to explore the geospatial pattern of the HR of patients with RA. Generalised estimating equation analysis and geographically weighted regression were used to identify the potential influencing factors of the HR of patients with RA.<h4>Results</h4>There were a total of 11 599 admissions, and the average HR was 1.57 per 10 000 population in Hunan. We detected different cluster patterns of the HR among patients with RA by local indicators o"],"journal":["BMJ open"],"pubmed_title":["Geospatial analysis of the hospitalisation rate of patients with rheumatoid arthritis in Hunan: a cross-sectional Chinese study."],"pmcid":["PMC10679990"],"funding_grant_id":["2018FY100900","kq2202409","2022JJ40674","2021JJ30893","81701622","2020JJ4772"],"pubmed_authors":["Tian J","Ge Y","Wang S","Shi Q","Shi J"],"additional_accession":[]},"is_claimable":false,"name":"Geospatial analysis of the hospitalisation rate of patients with rheumatoid arthritis in Hunan: a cross-sectional Chinese study.","description":"<h4>Objective</h4>Little is known about spatial variability of hospitalisation rate (HR) of patients with rheumatoid arthritis (RA) worldwide, especially in China.<h4>Methods</h4>A cross-sectional study was conducted among patients with RA admitted to hospitals in Hunan Province. Global Moran's <i>I</i> and local indicators of spatial association were used to explore the geospatial pattern of the HR of patients with RA. Generalised estimating equation analysis and geographically weighted regression were used to identify the potential influencing factors of the HR of patients with RA.<h4>Results</h4>There were a total of 11 599 admissions, and the average HR was 1.57 per 10 000 population in Hunan. We detected different cluster patterns of the HR among patients with RA by local indicators o","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Nov","modification":"2026-06-03T09:44:30.596Z","creation":"2025-04-07T07:10:16.248Z"},"accession":"S-EPMC10679990","cross_references":{"pubmed":["38000823"],"doi":["10.1136/bmjopen-2023-075088"]}}