Improved VO(2max) Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method

Maximal oxygen consumption (VO(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(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(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(2) values, and age-predicted maximal HR. Systematic differences between estimated and measured VO(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(−1)·min(−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(2max) was ≥45 mL·kg(−1)·min(−1). In conclusion, substantial proportional bias in the MRM may be mitigated using the LEM within a limited range.