{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T13:35:35Z","timestamp":1792503335489,"version":"4.5.0"},"reference-count":40,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T00:00:00Z","timestamp":1677542400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81703304"],"award-info":[{"award-number":["81703304"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81973130"],"award-info":[{"award-number":["81973130"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The associations of multimorbidity patterns with transitions between frailty states remain unclear in older individuals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used data from the National Health and Aging Trends Study 2011\u20132019. Frailty was measured annually using the Fried frailty phenotype. Multimorbidity patterns at baseline were identified using latent class analysis based on 14 chronic conditions. We used the semi\u2010Markov multi\u2010state model to investigate the influences of multimorbidity characterized by condition counts and patterns on subsequent frailty transitions over follow\u2010ups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 9450 participants aged \u226565\u00a0years at baseline, 34.8% were non\u2010frail, 48.1% were pre\u2010frail and 17.0% were frail. Over a median follow\u2010up of 4.0\u00a0years, 16\u00a0880 frailty transitions were observed, with 10\u00a0527 worsening and 6353 improving. For 7675 participants with multimorbidity, four multimorbidity patterns were identified: osteoarticular pattern (62.4%), neuropsychiatric\u2013sensory pattern (17.2%), cardiometabolic pattern (10.3%) and complex multimorbidity pattern (10.1%). Compared with no disease, multimorbidity was significantly associated with an increased risk of worsening transitions, including from non\u2010frail to pre\u2010frail (hazard ratio [HR]\u00a0=\u00a01.35; 95% confidence interval [CI]\u00a0=\u00a01.21\u20131.52), from non\u2010frail to frail (HR\u00a0=\u00a01.68; 95% CI\u00a0=\u00a01.04\u20132.73), from pre\u2010frail to frail (HR\u00a0=\u00a02.19; 95% CI\u00a0=\u00a01.66\u20132.90) and from pre\u2010frail to death (HR\u00a0=\u00a01.64; 95% CI\u00a0=\u00a01.11\u20132.41). Compared with the osteoarticular pattern, neuropsychiatric\u2013sensory, cardiometabolic and complex multimorbidity patterns had a significantly higher risk of worsening frailty (all\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&lt;\u00a00.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Multimorbidity was associated with dynamic transitions between frailty states and death among older American adults, and the associations varied across multimorbidity patterns. The findings could offer significant implications for public health policymakers in planning interventions and healthcare resources. They also might inform clinicians regarding providing targeted clinical treatment and health management based on multimorbidity patterns of older people.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcsm.13197","type":"journal-article","created":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T04:54:39Z","timestamp":1677560079000},"page":"1075-1082","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Associations between multimorbidity and frailty transitions among older Americans"],"prefix":"10.1002","volume":"14","author":[{"given":"Yan","family":"Luo","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuming","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaipeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Graduate School of Social Work University of Denver  Denver CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carson M.","family":"De Fries","sequence":"additional","affiliation":[{"name":"Graduate School of Social Work University of Denver  Denver CO USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziting","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiwen","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhou","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yonghua","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beibei","family":"Xu","sequence":"additional","affiliation":[{"name":"Medical Informatics Center Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,2,28]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)62167-9"},{"key":"e_1_2_9_3_1","unstructured":"The Academy of Medical Sciences.Multimorbidity: a priority for global health research. 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