Prediction of Maximum Oxygen Uptake Using Both Exercise and Non-Exercise Data

Abstract

This study sought to develop a regression model to predict maximal oxygen uptake (VO2max) based on submaximal treadmill exercise (EX) and non-exercise (N-EX) data involving 116 participants, ages 18–65 years. The EX data included the participants' self-selected treadmill speed (at a level grade) when exercise heart rate first reached at least 70% of predicted maximum heart rate (HRmax; 220 – age) by the end of any one of three 4-min consecutive stages involving walking (3.0–4.0 mph; Stage 1), jogging (4.1–6.0 mph; Stage 2), and running (> 6.0 mph; Stage 3). The N-EX data included various demographic (age, gender), biometric (body mass), and questionnaire (participants' perceived functional ability [PFA] to walk, jog, or run given distances, and their self-reported level of physical activity [PA-R]) information. All participants (n = 100) who completed the study requirements and successfully achieved a maximal level of exertion during a graded exercise test (GXT) to assess VO2max (mean ± SD; 41.39 ± 9.15 ml · kg−1 · min−1) were included in the data analysis. Stepwise regression was used to generate the following prediction equation (R = .94, SEE = 3.09 ml · kg−1 · min−1): VO2max (ml · kg−1 · min−1) = 30.04 + (6.37 × gender; females = 0, males = 1) – (0.243 × age) – (0.122 × body mass) + (3.263 × ending self-selected treadmill speed; mph) + (0.391 × PFA) + (0.669 × PA-R). Each of the predictor variables were statistically significant (p < .001) and cross-validation procedures using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .92 and SEE p = 3.29 ml · kg−1 · min−1). In summary, this submaximal treadmill test and accompanying regression model yields relatively accurate VO2max estimates in healthy men and women (ages 18–65 years) using both EX and N-EX data.