Improved VO[sub.2max] Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method

Maximal oxygen consumption (VO[sub.2max]) is an important health indicator that is often estimated using a multiple regression model (MRM) or linear extrapolation method (LEM) with the heart rate (HR) during a step test. Nonetheless, both methods have inherent problems. This study investigated a VO[sub.2max] estimation method that mitigates the weaknesses of these two methods. A total of 128 adults completed anthropometric measurements, a physical activity questionnaire, a step test with HR measurements, and a VO[sub.2max] treadmill test. The MRM included step-test HR, age, sex, body mass index, and questionnaire scores, whereas the LEM included step-test HR, predetermined constant VO[sub.2] values, and age-predicted maximal HR. Systematic differences between estimated and measured VO[sub.2max] values were detected using Bland-Altman plots. The standard errors of the estimates of the MRM and LEM were 4.15 and 5.08 mL·kg[sup.−1]·min[sup.−1], respectively. The range of 95% limits of agreement for the LEM was wider than that for the MRM. Fixed biases were not significant for both methods, and a significant proportional bias was observed only in the MRM. MRM bias was eliminated using the LEM application when the MRM-estimated VO[sub.2max] was ≥45 mL·kg[sup.−1]·min[sup.−1]. In conclusion, substantial proportional bias in the MRM may be mitigated using the LEM within a limited range.