{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T10:57:01Z","timestamp":1791197821480,"version":"4.1.0"},"reference-count":31,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aspenjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Parenter Enteral Nutr"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The Global Leadership Initiative on Malnutrition criteria has recommended using bioelectrical impedance analysis\u2010derived fat\u2010free mass index as a practical screening tool for low muscle mass. In the present study we evaluated the correlation between this index and dual\u2010energy X\u2010ray absorptiometry\u2010derived appendicular skeletal muscle mass index, and developed sex\u2010specific predictive nomograms according to the 2019 Asian Working Group for Sarcopenia criteria.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This cross\u2010sectional analysis included 369 community\u2010dwelling adults from the Hallym Aging Study. Body composition was assessed by bioelectrical impedance analysis and dual\u2010energy X\u2010ray absorptiometry. Low appendicular skeletal muscle mass index was defined as &lt;7.0\u2009kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      for men and &lt;5.4\u2009kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      for women. Receiver operating characteristic analysis identified optimal cutoffs. Multivariable logistic regression and sex\u2010specific nomograms were developed, adjusting for age, albumin, creatinine, hypertension, diabetes, and dyslipidemia. Models were internally validated using 1000 bootstrap resamples.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      This index moderately correlated with appendicular skeletal muscle mass index (\n                      <jats:italic>\u03c1<\/jats:italic>\n                      \u2009=\u20090.65 in males,\n                      <jats:italic>\u03c1<\/jats:italic>\n                      \u2009=\u20090.36 in females;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001). Optimal cutoffs were 17.7\u2009kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      for males (area under the curve, 0.84) and 16.1\u2009kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      for females (0.73). This index remained independently associated with low appendicular skeletal muscle mass index after multivariable adjustment. Nomograms showed good discrimination (\n                      <jats:italic>C<\/jats:italic>\n                      \u2010statistics\u2009=\u20090.78 in males, 0.73\u2009=\u2009in females) and calibration. In females, metabolic disorders, particularly hypertension and diabetes, significantly increased this risk.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Fat\u2010free mass index is a practical marker for low muscle mass screening. However, its accuracy varies by sex and metabolic health, requiring sex\u2010and disease\u2010specific calibration to improve malnutrition diagnosis and sarcopenia screening.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jpen.70136","type":"journal-article","created":{"date-parts":[[2026,8,16]],"date-time":"2026-08-16T05:45:38Z","timestamp":1786859138000},"page":"1031-1039","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sex\u2010specific screening of low appendicular skeletal muscle mass index in community dwelling adults: A descriptive cross\u2010sectional study"],"prefix":"10.1002","volume":"50","author":[{"given":"Na Young","family":"Yeo","sequence":"first","affiliation":[{"name":"Department of Medical Big\u2010Data Convergence Kangwon National University Chuncheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soo\u2010Young","family":"Seo","sequence":"additional","affiliation":[{"name":"Institute of New Frontier Research Team Hallym University College of Medicine Chuncheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7249-7941","authenticated-orcid":false,"given":"Heeji","family":"Choi","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center Hallym University Sacred Heart Hospital Chuncheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong\u2010Hyun","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Social and preventive Medicine Hallym University College of Medicine Chuncheon Republic of Korea"},{"name":"Hallym Research Institute of Clinical Epidemiology Hallym University College of Medicine Chuncheon Republic of 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