{
  "abstract": "Background/objective To assess whether fat-free mass (FFM) or body mass (M) is the more appropriate body size variable to predict maximum oxygen uptake (VO 2max, L⋅min−1).Methods Data (3930 cardiopulmonary exercise tests) were provided from the FRIEND registry. Our prediction equations adopted the well-known allometric/power function model VO 2max (L⋅min−1)=a·Xb, using either FFM or M as the predictor variable (X). These models can be linearised with a log-transformation, and analysis of covariance (ANCOVA) can then be used to estimate the unknown parameters.Results Initially, when predicting Ln(VO 2max) using only Ln(FFM) adjusted for age and sex, the explained variance was R2=0.718 (Akaike information criterion (AIC)=−1882.5), with the FFM exponent b=0.658. However, when predicting Ln(VO2max) using M AND bodyfat% separately, the explained variance increased to R2=0.733 (AIC=−2077.4), with the M exponent b=0.636. The difference in R2 and AICs confirmed the benefit of predicting VO2max using separate M and bodyfat% terms. The analysis identified an enlarged negative bodyfat% term that improved the prediction of VO2max, explained latterly by central adiposity (waist circumference). These final, more inclusive M and FFM exponents were estimated to be b=0.67, suggesting that VO2max should be normalised using VO2max (mL·FFM−2/3·min−1) or preferably VO2max (mL·M−2/3·min−1) rather than VO2max (mL·FFM−1·min−1). We also found that linear prediction models systematically under-estimate the VO2max of overweight and underweight individuals, but over-estimate the VO2max of average-weight individuals.Conclusion Incorporating FFM into equations to predict VO 2max 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.",
  "authors": [
    {
      "affiliations": [
        "Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK"
      ],
      "name": "Alan Nevill"
    },
    {
      "affiliations": [
        "Health Sciences, Taylor University, Upland, Indiana, USA"
      ],
      "name": "Matthew Harber"
    },
    {
      "affiliations": [
        "Sport and Physical Activity Research Centre, University of Wolverhampton Faculty of Education Health and Wellbeing, Walsall, UK",
        "National Institute of Dance Medicine and Science, Birmingham, UK"
      ],
      "name": "Matthew Wyon"
    },
    {
      "affiliations": [
        "Cardiology, VA Palo Alto Health Care System, Palo Alto, California, USA"
      ],
      "name": "Jonathan Myers"
    },
    {
      "affiliations": [
        "Department of Physical Therapy, University of Illinois Chicago, Chicago, Illinois, USA"
      ],
      "name": "Ross Arena"
    },
    {
      "affiliations": [
        "Newman University, Birmingham, West Midlands, UK"
      ],
      "name": "Tony Myers"
    },
    {
      "affiliations": [
        "Ball State University, Muncie, Indiana, USA"
      ],
      "name": "Leonard A Kaminsky"
    }
  ],
  "title": "Should we use fat-free mass or body mass and percentage body fat as separate predictors to predict maximum oxygen uptake?",
  "uid": "62528fbc-ef36-530f-adf0-c5b9afc81b2a"
}