{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:48:20Z","timestamp":1787014100737,"version":"build-2736575974"},"reference-count":45,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:00:00Z","timestamp":1760572800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:00:00Z","timestamp":1760572800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2026,1]]},"abstract":"Abstract<\/jats:title>\n \n Aim<\/jats:title>\n \n Body mass index (\n BMI<\/jats:styled-content>\n ) might fail to distinguish between fat and muscle mass. The fat\u2010to\u2010muscle mass ratio (\n FMR<\/jats:styled-content>\n ) and cardiorespiratory fitness (\n CRF<\/jats:styled-content>\n ) may provide complementary insights into the risk of type 2 diabetes mellitus (\n T2DM<\/jats:styled-content>\n ). This study aimed to investigate the independent and joint associations of\n FMR<\/jats:styled-content>\n and\n CRF<\/jats:styled-content>\n with incident\n T2DM<\/jats:styled-content>\n .\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n This prospective analysis included 60\u2009837 adults from the\n UK<\/jats:styled-content>\n Biobank without diabetes at baseline.\n FMR<\/jats:styled-content>\n was assessed via bioelectrical impedance analysis, and\n CRF<\/jats:styled-content>\n was estimated from a submaximal cycle test. Cox proportional hazards models evaluated associations with\n T2DM<\/jats:styled-content>\n incidence. Additive and multiplicative interaction effects were further estimated. Predictive performance was evaluated using time\u2010dependent\n ROC<\/jats:styled-content>\n analysis.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Over a median 14.49\u2010year follow\u2010up, 2439 participants developed\n T2DM<\/jats:styled-content>\n . Higher\n FMR<\/jats:styled-content>\n (per 1\u2010\n SD<\/jats:styled-content>\n ) was independently associated with higher\n T2DM<\/jats:styled-content>\n risk in women (\n HR<\/jats:styled-content>\n \u2009=\u20091.17, 95%\n CI<\/jats:styled-content>\n : 1.07\u20131.27) and men (\n HR<\/jats:styled-content>\n \u2009=\u20091.32, 95%\n CI<\/jats:styled-content>\n : 1.23\u20131.42). Higher\n CRF<\/jats:styled-content>\n (per 1\u2010\n MET<\/jats:styled-content>\n increment) was associated with lower risk in women (\n HR<\/jats:styled-content>\n \u2009=\u20090.84, 95%\n CI<\/jats:styled-content>\n : 0.80\u20130.89) and men (\n HR<\/jats:styled-content>\n \u2009=\u20090.82, 95%\n CI<\/jats:styled-content>\n : 0.79\u20130.86). Participants with both high\n FMR<\/jats:styled-content>\n and low\n CRF<\/jats:styled-content>\n had the highest risk (\n HR<\/jats:styled-content>\n \u2009=\u20091.81, 95%\n CI<\/jats:styled-content>\n : 1.59\u20132.07). This association was strongest in adults <60\u2009years. Adding\n FMR<\/jats:styled-content>\n and\n CRF<\/jats:styled-content>\n to the Cambridge Diabetes Risk Score significantly improved predictive accuracy at 3, 5 and 10\u2009years.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n FMR<\/jats:styled-content>\n and\n CRF<\/jats:styled-content>\n were independent predictors of\n T2DM<\/jats:styled-content>\n , with their combination identifying the highest\u2010risk phenotype. Integrating\n FMR<\/jats:styled-content>\n and\n CRF<\/jats:styled-content>\n assessment enhances\n T2DM<\/jats:styled-content>\n risk stratification and identifies high\u2010risk individuals who may benefit from lifestyle interventions focusing on improving body composition and fitness.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1111\/dom.70217","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T04:30:40Z","timestamp":1760675440000},"page":"463-471","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Independent and joint association of fat\u2010to\u2010muscle mass ratio and cardiorespiratory fitness with type 2 diabetes mellitus incidence: A prospective cohort study"],"prefix":"10.1111","volume":"28","author":[{"given":"Haofeng","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"},{"name":"Graduate School Peking Union Medical College, Chinese Academy of Medical Science Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yutong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"},{"name":"Graduate School Peking Union Medical College, Chinese Academy of Medical Science Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyang","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"},{"name":"Graduate School, Medical College Beijing University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxi","family":"Xia","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"},{"name":"Graduate School, Medical College Beijing University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sixian","family":"Weng","sequence":"additional","affiliation":[{"name":"Arrhythmia Center, Department of Cardiology Beijing Anzhen Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junsong","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6674-5537","authenticated-orcid":false,"given":"Fang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Cardiology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences Beijing China"},{"name":"Graduate School Peking Union Medical College, Chinese Academy of Medical Science Beijing China"},{"name":"Graduate School, Medical College Beijing University Beijing China"},{"name":"Beijing Key Laboratory of Geriatrics\u2010Based and Al\u2010Driven Pharmaceutical and Medical Device Evaluation and Translation Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,10,16]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140\u20106736(23)01301\u20106"},{"key":"e_1_2_10_3_1","unstructured":"IDF diabetes atlas|global diabetes data & statistics.https:\/\/diabetesatlas.org\/. 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