AUTHOR=Du Zonghao , Lu Wei , Lang Diandong 

TITLE=Comparison between 2,000 m and 3,000 m time trials to estimate the maximal aerobic speed for collegiate runners

JOURNAL=Frontiers in Physiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.1005259

DOI=10.3389/fphys.2022.1005259

ISSN=1664-042X

ABSTRACT= Considered to be less resource burden, 2000 m and 3000 m time trials (TTs) have been recognized as alternatives to accurately estimate the maximal aerobic speed (MAS) derived from laboratory-graded exercising testing (GXT). Previous studies have commonly used ordinary least squares linear regression, and the Bland–Altman method to compare the agreement between MAS and TTs performance. The agreement analysis aimed to identify the systematic bias between the results of the two methods, rather than identify similarities. Model II regression technique (ordinary least product regression) is increasingly favored by researchers in the field of physiology. Thus, we aimed to 1) use the ordinary least product (OLP) and Bootstrap methods to determine the agreement between the average speed of 2000 m TT (S2000) and the average speed of 3000 m TT(S3000), and 2) determine whether S2000 or S3000 can accurately approximate GXT-derived MAS. It is used as an alternative to estimate the MAS and prescribe the training intensity. Thirty-five Beijing Sport University recreational male runners completed a MAS test in the laboratory settings, followed by 2000 m and 3000 m TTs randomly, with a 7-day interval. OLP regression was used to analyze the agreement between GXT-derived MAS and S2000, S3000. The bootstrap method was used to calibrate the equations. Differences between GXT-derived MAS and S2000 and S3000 were compared using a one-way repeated measure analysis of variance (ANOVA) and a post hoc analysis (Bonferroni). The significance level was p ＜ 0.05. The results showed that before calibration, the 95%CI of the OLP regression intercept and slope between GXT-derived MAS and S2000 and S3000 did not include 0 and 1.00, respectively. These values, after calibration, included 0 and 1.00, respectively. Post hoc analysis revealed that S3000 closely approximated GXT-derived MAS and underestimated 0.46% (0.06 km.h–1, p ＞ 0.05 ), S2000 overestimated 5.49% (0.81 km.h–1, p ＜ 0.05) by MAS. It concluded that 3000 m TT performance approximated GXT-derived MAS compared to 2000 m TT performance. There exist fixed bias and proportional bias between GXT-derived MAS and TT performance. More attention should be applied to calibration when using the TT performance to estimate MAS.