Feasibility of predicting maximal oxygen uptake by using the efficiency factor in healthy men

Conventionally, efficiency is indirectly estimated through a respiratory gas analyser (oxygen, carbon dioxide), which is a complex and rather costly calculation method that is difficult to perform in many situations. Therefore, the present study proposed a modified definition of efficiency, called the efficiency factor (EF) (i.e., the ratio of work to the corresponding exercise intensity), and evaluated the relation between the EF and maximal oxygen uptake ([Formula: see text]), as well as compared the prediction models established based on the EF. The heart rate (maximal heart rate: 186 ± 6 beats min^-1), rating of perceived exertion (19 ± 1), and [Formula: see text] (39.0 ± 7.1 mL kg^-1 min^-1) of 150 healthy men (age: 20 ± 2 years; height: 175.0 ± 6.0 cm; weight: 73.6 ± 10.7 kg; body mass index [BMI]: 24.0 ± 3.0 kg m^-2; percent body fat [PBF]: 17.0 ± 5.7%) were measured during the cardiopulmonary exercise test (CPET). Through multiple linear regression analysis, we established the BMI model using age and BMI as parameters. Additionally, we created the PBF model^HRR utilizing weight, PBF, and heart rate reserve (HRR) and developed PBF model^EF6 and PBF model^EF7 by incorporating EF6 from the exercise stage 6 and EF7 from the exercise stage 7 during the CPET, respectively. EF6 (r = 0.32, p = 0.001) and EF7 (r = 0.31, p = 0.002) were significantly related to [Formula: see text]. Among the models, the PBF model^EF6 showed the highest accuracy, which could explain 62.6% of the variance in the [Formula: see text] at with a standard error of estimate (SEE) of 4.39 mL kg^-1 min^-1 (%SEE = 11.25%, p < 0.001). These results indicated that the EF is a significant predictor of [Formula: see text], and compared to the other models, the PBF model^EF6 is the best model for estimating [Formula: see text].