{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["11(3)"],"submitter":["Kong L"],"pubmed_abstract":["<h4>Objectives</h4>To assess the prevalence of frailty and identify predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes.<h4>Design</h4>A cross-sectional design.<h4>Setting</h4>Two community health centres in central China.<h4>Participants</h4>291 community-dwelling older adults aged ≥65 years with type 2 diabetes.<h4>Main outcome measures</h4>Data were collected via face-to-face interviews, anthropometric measurements, laboratory tests and community health files. The main outcome measure was frailty, as assessed by the frailty phenotype criteria. The multivariate logistic regression model was used to identify the predictors of frailty.<h4>Results</h4>The prevalence of prefrailty and frailty were 51.5% and 19.2%, respectively. The significant predictors "],"journal":["BMJ open"],"pagination":["e041578"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7934736"],"repository":["biostudies-literature"],"pubmed_title":["Predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes: a cross-sectional survey."],"pmcid":["PMC7934736"],"pubmed_authors":["Kong L","Li J","Wang Q","Fan J","Bai J","Zhao H","Mao J"],"additional_accession":[]},"is_claimable":false,"name":"Predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes: a cross-sectional survey.","description":"<h4>Objectives</h4>To assess the prevalence of frailty and identify predictors of frailty among Chinese community-dwelling older adults with type 2 diabetes.<h4>Design</h4>A cross-sectional design.<h4>Setting</h4>Two community health centres in central China.<h4>Participants</h4>291 community-dwelling older adults aged ≥65 years with type 2 diabetes.<h4>Main outcome measures</h4>Data were collected via face-to-face interviews, anthropometric measurements, laboratory tests and community health files. The main outcome measure was frailty, as assessed by the frailty phenotype criteria. The multivariate logistic regression model was used to identify the predictors of frailty.<h4>Results</h4>The prevalence of prefrailty and frailty were 51.5% and 19.2%, respectively. The significant predictors ","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Mar","modification":"2025-04-22T10:44:55.259Z","creation":"2025-04-05T23:42:02.118Z"},"accession":"S-EPMC7934736","cross_references":{"pubmed":["33664069"],"doi":["10.1136/bmjopen-2020-041578"]}}