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Medicina dello Sport 2017 March;70(1):20-35

DOI: 10.23736/S0025-7826.16.02911-2


language: English, Italian

Predicting maximal oxygen uptake in a generalized population

Irma LORENZO 1, Dalton M. PESSÔA FILHO 2, 3, Ana B. PEINADO 2, Pedro J. BENITO PEINADO 2, Francisco J. CALDERÓN 2

1 Camilo José Cela University, Villanueva de la Cañada, Madrid, Spain; 2 Department of Health and Human Performance, Technical University of Madrid, Madrid, Spain; 3 School of Sciences, São Paulo State University (UNESP), São Paulo, Brazil


BACKGROUND: The assessment of cardiorespiratory fitness using a gold-standard protocol, or group-specific estimates, cannot feasibly be managed by health and physical training professionals when dealing with different exercise disciplines and individual needs. Thus, the aim was to describe the parameters which offer a better explanation of the variance in maximal oxygen uptake (V̇O2max) in a large mixed population.
METHODS: A sample of 784 subjects (practitioners from different sport disciplines, composed of 656 men: 24±8 years, 69±10 kg and 175±8 cm; and 128 women: 21±7 years, 57±9 kg and 164±8 cm) performed a progressive test to assess V̇O2max on a cycle-ergometer or treadmill, as freely chosen by the participants. Two multiple linear stepwise-regression models were applied to the V̇O2max estimation in a sorted exploratory sample (70%): with anthropometrics plus maximal heart rate (HRmax) for model 1 (MOD1); and including maximal workload (WLmax) for model 2 (MOD2). Both models were evaluated in the validatory sample (30%) by the constant error (CE), Pearson coefficient (r), standard error of estimate (SEE), total error (TE), and adjusted r2.
RESULTS: The MOD2 equation [V̇O2max=522.475 – 8.280 (WLmax) - 368.135 (sex) + 12.872 (bw) + 5.879 (HRmax)] proved to be statistically more robust than the MOD1 equation (SEE: 8.4 and 10.1%; CE: 1.0 and 6.0%; TE: 9.0 and 17.2%; and adjusted r2: 0.87 and 0.54, respectively).
CONCLUSIONS: A highly accurate model was provided for predicting V̇O2max in a mixed-population, when including maximal workload together with HRmax, body weight, age and gender data in the estimate.

KEY WORDS: Work capacity evaluation - Oxygen consumption - Sports - Population groups - Regression analysis

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