Factors Influencing Running Velocity at Lactate Threshold in Male and Female Runners at Different Levels of Performance

Background

The primary aim was to examine the relationship between lactate threshold (LT) expressed as percentage of maximal oxygen uptake (VO_2max) and running velocity at LT (LT_V). A secondary aim was to investigate to what extent VO_2max, oxygen cost of running (C_R), and maximal aerobic speed (MAS) determined LT_V. A third aim was to investigate potential differences in LT and LT_V between elite, national and recreational runners, as well as possible gender differences regarding VO_2max, C_R, LT, and LT_V.

Methods

Seventy-five competitive runners (37 males and 38 females) with an average VO_2max of 63.0 ± 9.3 mL⋅kg^–1⋅min^–1, and an average LT_V of 13.6 ± 2.3 km⋅h^–1 were tested for VO_2max, LT, LT_V, MAS, and C_R.

Results

Lactate threshold did not correlate with LT_V. With an r – value of 0.95 (p < 0.001) and a standard error of estimate of 4.0%, the product of MAS and individual LT determined 90% of LT_V, outside a range of ±0.27 km⋅h^–1. LT_V increased with higher performance level. However, LT did not differ between elite, national and recreational runners. Female runners had 2.5% higher LT, 8% lower LT_V, and 21% lower VO_2max, but 9% better C_R than male runners.

Conclusion

Lactate threshold did not correlate with LT_V. The product of MAS and LT correlated strongly with LT_V. There were no differences between elite, national and recreational runners regarding LT, but female runners had higher LT than the male runners. Female runners at the same relative performance level had lower LT_V and VO_2max, but better C_R than male runners.

The Polarization-Index: A Simple Calculation to Distinguish Polarized From Non-polarized Training Intensity Distributions

The training intensity distribution (TID) of endurance athletes has retrieved substantial scientific interest since it reflects a vital component of training prescription: (i) the intensity of exercise and its distribution over time are essential components for adaptation to endurance training and (ii) the training volume (at least for most endurance disciplines) is already near or at maximum, so optimization of training procedures including TID have become paramount for success. This paper aims to elaborate the polarization-index (PI) which is calculated as log10(Zone 1/Zone 2∗Zone 3∗100), where Zones 1-3 refer to aggregated volume (time or distance) spent with low, mid, or high intensity training. PI allows to distinguish between non-polarized and polarized TID using a cut-off > 2.00 a.U. and to quantify the level of a polarized TID. Within this hypothesis paper, examples from the literature illustrating the usefulness of PI-calculation are discussed as well as its limitations. Further it is elucidated how the PI may contribute to a more precise definition of TID descriptors.