Does Concurrent Training Intensity Distribution Matter?

2017 ◽  
Vol 31 (1) ◽  
pp. 181-195 ◽  
Author(s):  
Adrián Varela-Sanz ◽  
José L. Tuimil ◽  
Laurinda Abreu ◽  
Daniel A. Boullosa
Keyword(s):  
Intensity Distribution ◽  
Concurrent Training ◽  
Training Intensity

Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists

2013 ◽  
Vol 114 (4) ◽  
pp. 461-471 ◽  
Author(s):  
Craig M. Neal ◽  
Angus M. Hunter ◽  
Lorraine Brennan ◽  
Aifric O'Sullivan ◽  
D. Lee Hamilton ◽  
...  
Keyword(s):  
Exercise Capacity ◽  
Intensity Distribution ◽  
High Intensity ◽  
Threshold Model ◽  
Endurance Performance ◽  
High Intensity Exercise ◽  
Metabolic Adaptation ◽  
Mitochondrial Enzyme ◽  
Training Intensity ◽  
Metabolomics Analysis

This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.

Heart-Rate Variability and Training-Intensity Distribution in Elite Rowers

2014 ◽  
Vol 9 (6) ◽  
pp. 1026-1032 ◽  
Author(s):  
Daniel J. Plews ◽  
Paul B. Laursen ◽  
Andrew E. Kilding ◽  
Martin Buchheit
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensity Distribution ◽  
Lactate Threshold ◽  
Training Intensity ◽  
Training Time ◽  
Low Intensity ◽  
Elite Rowers ◽  
And Training ◽  
Intensity Training

Purpose:Elite endurance athletes may train in a polarized fashion, such that their training-intensity distribution preserves autonomic balance. However, field data supporting this are limited.Methods:The authors examined the relationship between heart-rate variability and training-intensity distribution in 9 elite rowers during the 26-wk build-up to the 2012 Olympic Games (2 won gold and 2 won bronze medals). Weekly averaged log-transformed square root of the mean sum of the squared differences between R-R intervals (Ln rMSSD) was examined, with respect to changes in total training time (TTT) and training time below the first lactate threshold (>LT1), above the second lactate threshold (LT2), and between LT1 and LT2 (LT1–LT2).Results:After substantial increases in training time in a particular training zone or load, standardized changes in Ln rMSSD were +0.13 (unclear) for TTT, +0.20 (51% chance increase) for time >LT1, –0.02 (trivial) for time LT1–LT2, and –0.20 (53% chance decrease) for time >LT2. Correlations (±90% confidence limits) for Ln rMSSD were small vs TTT (r = .37 ± .80), moderate vs time >LT1 (r = .43 ± .10), unclear vs LT1–LT2 (r = .01 ± .17), and small vs >LT2 (r = –.22 ± .50).Conclusion:These data provide supportive rationale for the polarized model of training, showing that training phases with increased time spent at high intensity suppress parasympathetic activity, while low-intensity training preserves and increases it. As such, periodized low-intensity training may be beneficial for optimal training programming.

Training intensity distribution in young tennis players

2016 ◽  
Vol 11 (6) ◽  
pp. 880-886 ◽  
Author(s):  
Alexandre Moreira ◽  
Rodrigo V Gomes ◽  
Caroline D Capitani ◽  
Charles R Lopes ◽  
Audrei R Santos ◽  
...  
Keyword(s):  
Heart Rate ◽  
Intensity Distribution ◽  
Perceived Exertion ◽  
Rating Of Perceived Exertion ◽  
Moderate Intensity ◽  
Training Intensity ◽  
Match Play ◽  
Training Time ◽  
Tennis Players ◽  
Professional Tennis

The aim of this study was to describe the training intensity distribution of elite young tennis players, based on the session rating of perceived exertion and heart rate methods. Twelve professional tennis players participated in this study. Heart rate and session rating of perceived exertion were collected in 384 tennis training sessions, 23 simulated matches, and 17 official matches. The total training time spent in the heart rate zone-1 (52.00%) and zone-2 (37.10%) was greater than the time spent in zone-3 (10.90%) during the 5-week training period ( p < 0.05). Similarly, the total training time spent in the session rating of perceived exertion zone-1 (42.00%) and zone-2 (47.50%) was also greater than the time in zone-3 (10.50%) ( p < 0.05). The data of the present study suggest that the majority of the training sessions of these young tennis players were performed at low-to-moderate intensity zone and, therefore, under the intensity performed during actual tennis match play.

Analysis of top kayakers’ training-intensity distribution and physiological adaptation based on structural modelling

2020 ◽  
Vol 289 (2) ◽  
pp. 195-210 ◽  
Author(s):  
Ruta Dadeliene ◽  
Stanislav Dadelo ◽  
Natalija Pozniak ◽  
Leonidas Sakalauskas
Keyword(s):  
Intensity Distribution ◽  
Physiological Adaptation ◽  
Structural Modelling ◽  
Training Intensity

scholarly journals Effects of Different Training Intensity Distribution in Recreational Runners

2020 ◽  
Vol 1 ◽  
Author(s):  
Luca Festa ◽  
Cantor Tarperi ◽  
Kristina Skroce ◽  
Antonio La Torre ◽  
Federico Schena
Keyword(s):  
Intensity Distribution ◽  
Training Intensity ◽  
Recreational Runners

IMPACT OF TRAINING INTENSITY DISTRIBUTION ON PERFORMANCE IN ENDURANCE ATHLETES

2007 ◽  
Vol 21 (3) ◽  
pp. 943-949 ◽  
Author(s):  
JONATHAN ESTEVE-LANAO ◽  
CARL FOSTER ◽  
STEPHEN SEILER ◽  
ALEJANDRO LUCIA
Keyword(s):  
Intensity Distribution ◽  
Endurance Athletes ◽  
Training Intensity

Withdrawal: Plews and Laursen (2017)

2018 ◽  
Vol 13 (3) ◽  
pp. 399
Keyword(s):  
Intensity Distribution ◽  
Editorial Office ◽  
Training Intensity ◽  
Link Type ◽  
Contractual Obligations ◽  
And Performance ◽  
Sports Physiology

We, the Editors and Publishers of the International Journal of Sports Physiology and Performance, have withdrawn the following article in whole: Plews, DJ, Laursen, PB. Training intensity distribution over a four-year cycle in Olympic champion rowers: different roads lead to Rio [version of record published online ahead of print September 27, 2017]. Int J Sports Physiol Perform. doi: 10.1123/ijspp.2017-0343. The Editorial Office was contacted with the request to withdraw this article informing the Editor-in-Chief that the data in this article were not permissible to use due to undisclosed contractual obligations.

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