Perspectives and Determinants for Training-Intensity Distribution in Elite Endurance Athletes

Abstract

Training-intensity distribution (TID), or the intensity of training and its distribution over time, has been considered an important determinant of the outcome of a training program in elite endurance athletes. The polarized and pyramidal TID, both characterized by a high amount of low-intensity training (below the first lactate or ventilatory threshold), but with different contributions of threshold training (between the first and second lactate or ventilatory threshold) and high-intensity training (above the second lactate or ventilatory threshold), have been reported most frequently in elite endurance athletes. However, the choice between these 2 TIDs is not straightforward. This article describes the historical, evolutionary, and physiological perspectives of the success of the polarized and pyramidal TID and proposes determinants that should be taken into account when choosing the most appropriate TID.

Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription?

“…distribution; Seiler and Kjerland, 2006;Stöggl and Sperlich, 2015;Bourgois et al, 2019) this may offer a new perspective, based on systemic autonomic regulation, to determine exercise and training zones for endurance-type sports guided by DFA-alpha1. An intensity distribution limited to the region around the aerobic threshold could be implemented on the basis of DFA-alpha1 values between a self-similar (fractal) HR time series with high complexity (DFA-alpha1: 1.0) and a completely random regulation dynamic in the HR time series with low complexity (DFA-alpha1: 0.5), thus defining a zone 1 threshold of ∼0.75.…”

“…Studies by Casties et al ( 2006 ), Platisa et al ( 2008 ), Blasco-Lafarga et al ( 2017 ), and Gronwald et al ( 2019a ) all indicate a clear decline in interbeat correlation properties with high work rates with values resembling white noise behavior at VO 2 levels historically in the realm between aerobic threshold (LT1, VT1) and anaerobic threshold (LT2, VT2). Within the context of different training models (e.g., polarized, pyramidal, or threshold training-intensity distribution; Seiler and Kjerland, 2006 ; Stöggl and Sperlich, 2015 ; Bourgois et al, 2019 ) this may offer a new perspective, based on systemic autonomic regulation, to determine exercise and training zones for endurance-type sports guided by DFA-alpha1. An intensity distribution limited to the region around the aerobic threshold could be implemented on the basis of DFA-alpha1 values between a self-similar (fractal) HR time series with high complexity (DFA-alpha1: 1.0) and a completely random regulation dynamic in the HR time series with low complexity (DFA-alpha1: 0.5), thus defining a zone 1 threshold of ~0.75.…”

“…These efforts are typically separated into 3 intensity zones based on certain physiologic thresholds. The first to second intensity zone boundary is generally defined by the first lactate (LT1) or ventilatory threshold (VT1) as an aerobic threshold (Meyer et al, 2005 ; Beneke et al, 2011 ; Hofmann and Tschakert, 2017 ; Bourgois et al, 2019 ). The second to third intensity zone transition is felt to be related to the second lactate threshold (LT2), maximum lactate steady state (MLSS), second ventilatory threshold (VT2), or respiratory compensation point (RCP) as an anaerobic threshold (Bourgois et al, 2019 ).…”

“…The first to second intensity zone boundary is generally defined by the first lactate (LT1) or ventilatory threshold (VT1) as an aerobic threshold (Meyer et al, 2005 ; Beneke et al, 2011 ; Hofmann and Tschakert, 2017 ; Bourgois et al, 2019 ). The second to third intensity zone transition is felt to be related to the second lactate threshold (LT2), maximum lactate steady state (MLSS), second ventilatory threshold (VT2), or respiratory compensation point (RCP) as an anaerobic threshold (Bourgois et al, 2019 ). Accurate and easy determinations of these thresholds would therefore be essential to set up and compare the various training-intensity distribution strategies for fitness optimization and performance enhancement as well as for mathematical modeling of zone training time or distance parameters (Seiler and Kjerland, 2006 ; Treff et al, 2019 ).…”

“…Both high intensity training (Wen et al, 2019 ) as well as combining low and high intensity training (Laursen, 2010 ; Pugliese et al, 2018 ) have been shown to be advantageous to different aspects of exercise performance. For the accurate quantification of training-intensity distributions, various models have been employed, such as polarized, threshold, or pyramidal training-intensity distribution (Seiler and Kjerland, 2006 ; Esteve-Lanao et al, 2007 ; Stöggl and Sperlich, 2015 , 2019 ; Bourgois et al, 2019 ). Although incremental exercise tests with measurement of lactate concentration and/or gas exchange are commonly done to define thresholds, the different approaches may not agree, leading to inaccurate delineation of zone boundaries (Chicharro et al, 1997 ; Hopker et al, 2011 ; Pallarés et al, 2016 ).…”