Scaling or normalising maximum oxygen uptake to predict 1-mile run time in boys.

  • Nevill A
  • Rowland T
  • Goff D
 et al. 
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There is still considerable debate and some confusion as to the most appropriate method of scaling or normalizing maximum oxygen uptake (VO2max) for differences in body mass (m) in both adults and children. Previous studies on adult populations have demonstrated that although the traditional ratio standard VO2max (ml kg(-1) min(-1)) fails to render VO2max independent of body mass, the ratio standard is still the best predictor of running performance. However, no such evidence exists in children. Hence, the purpose of the present study was to investigate whether the ratio standard is still the most appropriate method of normalising VO2max to predict 1-mile run speed in a group of 12-year-old children (n=36). Using a power function model and log-linear regression, the best predictor of 1-mile run speed was given by: speed (m s(-1))=55.1 VO2max(0.986) m(-0.96). With both the VO2max and body mass exponents being close to unity but with opposite signs, the model suggest the best predictor of 1-mile run speed is almost exactly the traditional ratio standard recorded in the units (ml kg(-1) min(-1)). Clearly, reporting the traditional ratio standard VO2max, recorded in the units (ml kg(-1) min(-1)), still has an important place in publishing the results of studies investigating cardiovascular fitness of both children and adults.

Author-supplied keywords

  • Algorithms
  • Anthropometry
  • Anthropometry: methods
  • Biological
  • Body Mass Index
  • Child
  • Humans
  • Male
  • Models
  • Oxygen
  • Oxygen Consumption
  • Oxygen Consumption: physiology
  • Oxygen: metabolism
  • Physical Examination
  • Physical Examination: methods
  • Physical Examination: standards
  • Reproducibility of Results
  • Running
  • Running: physiology
  • Sensitivity and Specificity
  • Statistical
  • Task Performance and Analysis
  • United States

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  • Alan Nevill

  • Thomas Rowland

  • Donna Goff

  • Leslie Martel

  • Lisa Ferrone

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