{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T15:44:03Z","timestamp":1787240643666,"version":"build-2736575974"},"reference-count":40,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T00:00:00Z","timestamp":1635292800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Obesity is protective of bone health; however, abdominal obesity is associated with a higher fracture risk. Little is known about whether body composition protects or adversely affects osteoporotic fractures because of practical issues regarding assessment tools. This study aimed to evaluate the association of predicted body composition with fracture risk to determine the distinctive and differing effects of muscle or fat mass on bone health outcomes in the general population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This population\u2010based, longitudinal cohort study used 2009\u20132010 Korean National Health Insurance Service data and follow\u2010up data from 1 January 2011 to 31 December 2013, to determine the incidence of osteoporotic fracture (total, spine, and non\u2010spine) defined using the International Classification of Diseases, Tenth Revision codes. The study participants were aged \u226550\u00a0years (men, 158\u00a0426; women, 131\u00a0587). The predicted lean body mass index (pLBMI), appendicular skeletal muscle index (pASMI), and body fat mass index (pBFMI) were used to assess body composition, using anthropometric prediction equations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Over a 3\u00a0year follow\u2010up, we identified 2350 and 6175 fractures in men and women, respectively. The mean age of the participants was 60.2\u00a0\u00b1\u00a08.3 and 60.7\u00a0\u00b1\u00a08.4\u00a0years in men and women, respectively. In a multivariable\u2010adjusted Cox proportional hazards regression model, increasing pLBMI or pASMI was significantly associated with a decreased risk of total fractures in men and women. When comparing individuals in the lowest pLBMI and pASMI (reference groups), men with the highest pLBMI and pASMI had adjusted hazard ratios of 0.63 [95% confidence interval (CI) 0.47\u20130.83] and 0.62 (95% CI 0.47\u20130.82), and women with the highest pLBMI and pASMI had adjusted hazard ratios of 0.72 (95% CI 0.60\u20130.85) and 0.71 (95% CI 0.60\u20130.85), respectively, for total fractures. The pBFMI had no significant association with total fractures in men or women. Regarding sex\u2010specific or site\u2010specific differences, the protective effects of the pLBMI and pASMI on fractures were greater in men and reduced the risk of spinal fractures. An increased pBFMI was associated with an increased risk of spinal fractures in women.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>An increased pLBMI or pASMI was significantly associated with decreased total osteoporotic fracture risk; however, the pBFMI showed no statistically significant association. Muscle mass was more important than fat mass in preventing future osteoporotic fractures based on anthropometric prediction equations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcsm.12850","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T19:53:21Z","timestamp":1635364401000},"page":"2247-2258","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Body composition and osteoporotic fracture using anthropometric prediction equations to assess muscle and fat masses"],"prefix":"10.1002","volume":"12","author":[{"given":"Changbin","family":"Hong","sequence":"first","affiliation":[{"name":"Department of Family Medicine Seoul National University Hospital  Seoul Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seulggie","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences Seoul National University Graduate 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