{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T11:00:24Z","timestamp":1793876424043,"version":"4.7.0"},"reference-count":37,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2022YFC2009600"],"award-info":[{"award-number":["2022YFC2009600"]}],"id":[{"id":"10.13039\/501100012166","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":[[2025,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Body mass index (BMI) has well\u2010recognized limitations, particularly in the context of the \u2018obesity paradox\u2019, where higher BMI does not consistently evaluate adverse outcomes. These limitations underscore the need for alternative approaches. This study aimed to redefine obesity using anthropometric indicators and to assess their prognostic value for mortality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The original cohort included participants from the US National Health and Nutrition Examination Survey (NHANES) from 1999 to 2006. Additional dual\u2010energy X\u2010ray absorptiometry (DXA) data on fat distribution were sourced from NHANES 1999\u20132006 and 2011\u20132018. Ten fat distribution indicators were adopted to assess the fat distribution in the target population, including five centripetal obesity indicators, three global obesity indicators and two limb obesity indicators. All\u2010cause, cardiovascular\u2010specific and cancer\u2010specific mortality outcomes were examined using weighted Cox proportional hazards models. Logistic regression was employed to evaluate associations between fat distribution indicators and the prevalence of specific diseases.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>This study included 14\u2009936 participants (weighted 152\u2009823\u2009236 participants, mean age: 45.56\u2009\u00b1\u200917.60\u2009years) and two DXA\u2010assessed cohorts. Fat distribution indicators were correlated with various DXA\u2010defined fat components. All 10 indicators demonstrated significant associations with mortality. Notably, the relationship between centripetal obesity indicators and all\u2010cause mortality was approximately linear in both sexes. Centripetal obesity was also strongly associated with cardiovascular and cancer\u2010specific mortality (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). Although fat distribution indicators were significantly linked to the prevalence of cardiovascular disease (CVD), they showed no clear association with cancer incidence. Individuals with obesity but without centripetal fat accumulation exhibited a similar or slightly higher mortality risk compared with those with normal BMI and no centripetal obesity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Centripetal obesity indicators emerged as the strongest independent evaluators of mortality, regardless of BMI classification. These findings highlight the clinical value of incorporating fat distribution metrics alongside BMI to more accurately assess obesity\u2010related mortality risk.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jcsm.70013","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T08:54:53Z","timestamp":1752569693000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["The Combination of Fat Distribution and BMI Redefines Obesity: Result From NHANES"],"prefix":"10.1002","volume":"16","author":[{"given":"Liuqing","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Clinical Nutrition Beijing Shijitan Hospital, Capital Medical University  Beijing China"},{"name":"Key Laboratory of Cancer FSMP for State Market Regulation  Beijing China"},{"name":"Laboratory for Clinical Medicine Capital Medical University  Beijing 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Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of General Surgery\/Center for Cancer Nutrition and Metabolism Beijing Shijitan Hospital, Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Clinical Nutrition Beijing Shijitan Hospital, Capital Medical University  Beijing China"},{"name":"Key Laboratory of Cancer FSMP for State Market Regulation  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4514-8693","authenticated-orcid":false,"given":"Hanping","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cancer FSMP for State Market Regulation  Beijing China"},{"name":"Laboratory for Clinical Medicine Capital Medical University  Beijing 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