Predicting VO2peak from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway

• Published in: PloS one 2016-01, Vol.11 (1), p.e0144873-e0144873
• Main Authors: Loe, Henrik, Nes, Bjarne M, Wisløff, Ulrik
• Format: Article
• Language: English
• Subjects: Adult; Bicycling; Biology and Life Sciences; Body Weight; Cardiovascular disease; Cardiovascular diseases; Exercise; Exercise Test; Female; Fitness equipment; Health care; Health risks; Heart Rate; Humans; Linear Models; Male; Mathematical models; Medical imaging; Medicine; Medicine and Health Sciences; Men; Mens health; Metabolism; Middle Aged; Model accuracy; Models, Biological; Mortality; Multiple regression analysis; Norway; Oxygen; Oxygen Consumption - physiology; Oxygen uptake; Physical fitness; Physical Sciences; Population; Prediction models; Regression analysis; Reproducibility of Results; Research and Analysis Methods; Running; Splitting; Velocity; Walking; Womens health; Workloads
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0144873

Peak oxygen uptake (VO2peak) is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO2peak prediction models for men and women based on directly measured VO2peak from a large healthy population. VO2peak prediction models based on submaximal- and peak performance treadmill work were derived from multiple regression analysis. 4637 healthy men and women aged 20-90 years were included. Data splitting was used to generate validation and cross-validation samples. The accuracy for the peak performance models were 10.5% (SEE = 4.63 mL⋅kg(-1)⋅min(-1)) and 11.5% (SEE = 4.11 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 75% and 72% of the variance explained. For the submaximal performance models accuracy were 14.1% (SEE = 6.24 mL⋅kg(-1)⋅min(-1)) and 14.4% (SEE = 5.17 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 55% and 56% of the variance explained. The validation and cross-validation samples displayed SEE and variance explained in agreement with the total sample. Cross-classification between measured and predicted VO2peak accurately classified 91% of the participants within the correct or nearest quintile of measured VO2peak. Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO2peak, which may be beneficial for risk stratification in health care settings.