{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T15:53:11Z","timestamp":1787500391801,"version":"build-2736575974"},"reference-count":24,"publisher":"BMJ","issue":"1","license":[{"start":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:00:00Z","timestamp":1773273600000},"content-version":"unspecified","delay-in-days":70,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open Sport Exerc Med"],"accepted":{"date-parts":[[2026,2,15]]},"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background\/objective<\/jats:title>\n                    <jats:p>\n                      To assess whether fat-free mass (FFM) or body mass (M) is the more appropriate body size variable to predict maximum oxygen uptake (VO\n                      <jats:sub>2max<\/jats:sub>\n                      , L\u22c5min\n                      <jats:sup>\u22121<\/jats:sup>\n                      ).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data (3930 cardiopulmonary exercise tests) were provided from the FRIEND registry. Our prediction equations adopted the well-known allometric\/power function model VO\n                      <jats:sub>2max<\/jats:sub>\n                      (L\u22c5min\n                      <jats:sup>\u22121<\/jats:sup>\n                      )=\n                      <jats:italic>a<\/jats:italic>\n                      \u00b7\n                      <jats:italic>X<\/jats:italic>\n                      <jats:sup>\n                        <jats:italic>b<\/jats:italic>\n                      <\/jats:sup>\n                      , using either FFM or M as the predictor variable (\n                      <jats:italic>X<\/jats:italic>\n                      ). These models can be linearised with a log-transformation, and analysis of covariance (ANCOVA) can then be used to estimate the unknown parameters.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Initially, when predicting Ln(VO\n                      <jats:sub>2max<\/jats:sub>\n                      ) using only Ln(FFM) adjusted for age and sex, the explained variance was R\n                      <jats:sup>2<\/jats:sup>\n                      =0.718 (Akaike information criterion (AIC)=\u22121882.5), with the FFM exponent b=0.658. However, when predicting Ln(VO\n                      <jats:sub>2max<\/jats:sub>\n                      ) using M AND bodyfat% separately, the explained variance increased to R\n                      <jats:sup>2<\/jats:sup>\n                      =0.733 (AIC=\u22122077.4), with the M exponent b=0.636. The difference in R\n                      <jats:sup>2<\/jats:sup>\n                      and AICs confirmed the benefit of predicting VO\n                      <jats:sub>2max<\/jats:sub>\n                      using separate M and bodyfat% terms. The analysis identified an enlarged negative bodyfat% term that improved the prediction of VO\n                      <jats:sub>2max<\/jats:sub>\n                      , explained latterly by central adiposity (waist circumference). These final, more inclusive M and FFM exponents were estimated to be b=0.67, suggesting that VO\n                      <jats:sub>2max<\/jats:sub>\n                      should be normalised using VO\n                      <jats:sub>2max<\/jats:sub>\n                      (mL\u00b7FFM\n                      <jats:sup>\u22122\/3<\/jats:sup>\n                      \u00b7min\n                      <jats:sup>\u22121<\/jats:sup>\n                      ) or\n                      <jats:italic>preferably<\/jats:italic>\n                      VO\n                      <jats:sub>2max<\/jats:sub>\n                      (mL\u00b7M\n                      <jats:sup>\u22122\/3<\/jats:sup>\n                      \u00b7min\n                      <jats:sup>\u22121<\/jats:sup>\n                      ) rather than VO\n                      <jats:sub>2max<\/jats:sub>\n                      (mL\u00b7FFM\n                      <jats:sup>\u22121<\/jats:sup>\n                      \u00b7min\n                      <jats:sup>\u22121<\/jats:sup>\n                      ). We also found that linear prediction models systematically\n                      <jats:italic>under-estimate<\/jats:italic>\n                      the VO\n                      <jats:sub>2max<\/jats:sub>\n                      of overweight and underweight individuals, but\n                      <jats:italic>over-estimate<\/jats:italic>\n                      the VO\n                      <jats:sub>2max<\/jats:sub>\n                      of average-weight individuals.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Incorporating FFM into equations to predict VO\n                      <jats:sub>2max<\/jats:sub>\n                      fails to explain the negative effect of central adiposity. However, by incorporating M and percentage body fat (BF%) separately into the allometric models, a greater\/enlarged negative BF% term explains this apparent omission\/absence.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjsem-2025-003029","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:55:14Z","timestamp":1773327314000},"page":"e003029","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Should we use fat-free mass or body mass and percentage body fat as separate predictors to predict maximum oxygen uptake?"],"prefix":"10.1136","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0506-3652","authenticated-orcid":false,"given":"Alan","family":"Nevill","sequence":"first","affiliation":[{"name":"Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Harber","sequence":"additional","affiliation":[{"name":"Health Sciences, Taylor University, Upland, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0942-2333","authenticated-orcid":false,"given":"Matthew","family":"Wyon","sequence":"additional","affiliation":[{"name":"Sport and Physical Activity Research Centre, University of Wolverhampton Faculty of Education Health and Wellbeing, Walsall, UK"},{"name":"National Institute of Dance Medicine and Science, Birmingham, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2592-136X","authenticated-orcid":false,"given":"Jonathan","family":"Myers","sequence":"additional","affiliation":[{"name":"Cardiology, VA Palo Alto Health Care System, Palo Alto, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ross","family":"Arena","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy, University of Illinois Chicago, Chicago, Illinois, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tony","family":"Myers","sequence":"additional","affiliation":[{"name":"Newman University, Birmingham, West Midlands, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonard A","family":"Kaminsky","sequence":"additional","affiliation":[{"name":"Ball State University, Muncie, Indiana, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,3,12]]},"reference":[{"key":"2026031207550504000_12.1.e003029.1","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1007\/BF00705066","article-title":"Scaling physiological measurements for individuals of different body size","volume":"65","author":"Nevill","year":"1992","journal-title":"Europ J Appl Physiol"},{"key":"2026031207550504000_12.1.e003029.2","unstructured":"Astrand P , Rodahl K . 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