James A. Betts, Javier T. Gonzalez, Louise M. Burke, Graeme L. Close, Ina Garthe, Lewis J. James, Asker E. Jeukendrup, James P. Morton, David C. Nieman, Peter Peeling, Stuart M. Phillips, Trent Stellingwerff, Luc J.C. van Loon, Clyde Williams, Kathleen Woolf, Ron Maughan and Greg Atkinson
Sabrina Skorski, Iñigo Mujika, Laurent Bosquet, Romain Meeusen, Aaron J. Coutts and Tim Meyer
Physiological and psychological demands during training and competition generate fatigue and reduce an athlete’s sport-specific performance capacity. The magnitude of this decrement depends on several characteristics of the exercise stimulus (eg, type, duration, and intensity), as well as on individual characteristics (eg, fitness, profile, and fatigue resistance). As such, the time required to fully recover is proportional to the level of fatigue, and the consequences of exercise-induced fatigue are manifold. Whatever the purpose of the ensuing exercise session (ie, training or competition), it is crucial to understand the importance of optimizing the period between exercise bouts in order to speed up the regenerative processes and facilitate recovery or set the next stimulus at the optimal time point. This implies having a fairly precise understanding of the fatigue mechanisms that contribute to the performance decrement. Failing to respect an athlete’s recovery needs may lead to an excessive accumulation of fatigue and potentially “nonfunctional overreaching” or to maladaptive training. Although research in this area recently increased, considerations regarding the specific time frames for different physiological mechanisms in relation to exercise-induced fatigue are still missing. Furthermore, recommendations on the timing and dosing of recovery based on these time frames are limited. Therefore, the aim of this article is to describe time courses of recovery in relation to the exercise type and on different physiological levels. This summary supports coaches, athletes, and scientists in their decision-making process by considering the relationship of exercise type, physiology, and recovery.
Thomas Zochowski, Elizabeth Johnson and Gordon G. Sleivert
Warm-up before athletic competition might enhance performance by affecting various physiological parameters. There are few quantitative data available on physiological responses to the warm-up, and the data that have been reported are inconclusive. Similarly, it has been suggested that varying the recovery period after a standardized warm-up might affect subsequent performance.
To determine the effects of varying post-warm-up recovery time on a subsequent 200-m swimming time trial.
Ten national-caliber swimmers (5 male, 5 female) each swam a 1500-m warm-up and performed a 200-m time trial of their specialty stroke after either 10 or 45 min of passive recovery. Subjects completed 1 time trial in each condition separated by 1 wk in a counterbalanced order. Blood lactate and heart rate were measured immediately after warm-up and 3 min before, immediately after, and 3 min after the time trial. Rating of perceived exertion was measured immediately after the warm-up and time trial.
Time-trial performance was significantly improved after 10 min as opposed to 45 min recovery (136.80 ± 20.38 s vs 138.69 ± 20.32 s, P < .05). There were no significant differences between conditions for heart rate and blood lactate after the warm-up. Pre-time-trial heart rate, however, was higher in the 10-min than in the 45-min rest condition (109 ± 14 beats/min vs 94 ± 21 beats/min, P < .05).
A post-warm-up recovery time of 10 min rather than 45 min is more beneficial to 200-m swimming time-trial performance.
Louise M. Burke and David B. Pyne
Bicarbonate loading is a popular ergogenic aid used primarily by athletes in short-duration, high-intensity sporting events and competitions. Controlled experimental trials have shown that small (worthwhile) benefits can obtained from acute doses of bicarbonate taken before exercise. Gastrointestinal problems encountered by some athletes limit the widespread use of this practice, however. The transfer of positive research findings to the competitive environment has proved problematic for some individuals. More recent applications involve serial ingestion of bicarbonate over several days before competition or during high-intensity training sessions over a few weeks. A number of research questions need to be addressed to enhance applications of bicarbonate loading in the elite sport environment. This commentary examines some of research and practical issues of bicarbonate loading used to enhance both training and competitive performance.
Conall F. Murtagh, Christopher Nulty, Jos Vanrenterghem, Andrew O’Boyle, Ryland Morgans, Barry Drust and Robert M. Erskine
Purpose: To investigate differences in neuromuscular factors between elite and nonelite players and to establish which factors underpin direction-specific unilateral jump performance. Methods: Elite (n = 23; age, 18.1 [1.0] y; body mass index, 23.1 [1.8] kg·m−2) and nonelite (n = 20; age, 22.3 [2.7] y; body mass index, 23.8 [1.8] kg·m−2) soccer players performed 3 unilateral countermovement jumps (CMJs) on a force platform in the vertical, horizontal-forward, and medial directions. Knee extension isometric maximum voluntary contraction torque was assessed using isokinetic dynamometry. Vastus lateralis fascicle length, angle of pennation, quadriceps femoris muscle volume (M vol), and physiological cross-sectional area (PCSA) were assessed using ultrasonography. Vastus lateralis activation was assessed using electromyography. Results: Elite soccer players presented greater knee extensor isometric maximum voluntary contraction torque (365.7 [66.6] vs 320.1 [62.6] N·m; P = .045), M vol (2853  vs 2429  cm3; P = .001), and PCSA (227  vs 193  cm2; P = .003) than nonelite. In both cohorts, unilateral vertical and unilateral medial CMJ performance correlated with M vol and PCSA (r ≥ .310, P ≤ .043). In elite soccer players, unilateral vertical and unilateral medial CMJ performance correlated with upward phase vastus lateralis activation and angle of pennation (r ≥ .478, P ≤ .028). Unilateral horizontal-forward CMJ peak vertical power did not correlate with any measure of muscle size or activation but correlated inversely with angle of pennation (r = −.413, P = .037). Conclusions: While larger and stronger quadriceps differentiated elite from nonelite players, relationships between neuromuscular factors and unilateral jump performance were shown to be direction-specific. These findings support a notion that improving direction-specific muscular power in soccer requires improving a distinct neuromuscular profile.
Teun van Erp, Dajo Sanders and Jos J. de Koning
Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen’s d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men’s training (d = 0.44–1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men’s and women’s training (d = 0.07–0.12). However, load values expressed per kilometer were moderately (d = 0.67–0.76) higher in women compared with men’s training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.
Ildus I. Ahmetov, Olga L. Vinogradova and Alun G. Williams
The ability to perform aerobic or anaerobic exercise varies widely among individuals, partially depending on their muscle-fiber composition. Variability in the proportion of skeletal-muscle fiber types may also explain marked differences in aspects of certain chronic disease states including obesity, insulin resistance, and hypertension. In untrained individuals, the proportion of slow-twitch (Type I) fibers in the vastus lateralis muscle is typically around 50% (range 5–90%), and it is unusual for them to undergo conversion to fast-twitch fibers. It has been suggested that the genetic component for the observed variability in the proportion of Type I fibers in human muscles is on the order of 40–50%, indicating that muscle fiber-type composition is determined by both genotype and environment. This article briefly reviews current progress in the understanding of genetic determinism of fiber-type proportion in human skeletal muscle. Several polymorphisms of genes involved in the calcineurin–NFAT pathway, mitochondrial biogenesis, glucose and lipid metabolism, cytoskeletal function, hypoxia and angiogenesis, and circulatory homeostasis have been associated with fiber-type composition. As muscle is a major contributor to metabolism and physical strength and can readily adapt, it is not surprising that many of these gene variants have been associated with physical performance and athlete status, as well as metabolic and cardiovascular diseases. Genetic variants associated with fiber-type proportions have important implications for our understanding of muscle function in both health and disease.
Thomas Sawczuk, Ben Jones, Sean Scantlebury and Kevin Till
Purpose: To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes. Methods: Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day’s training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS). Results: There was no relationship between CMJ and training (r = −.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = −.05; ±.06). The PRS was correlated with training (r = −.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = −0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = −0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate. Conclusions: The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete’s overall well-being. The CMJ was not associated with the training or sleep response in this population.
Paulo Farinatti, Silvio Rodrigues Marques Neto, Ingrid Dias, Felipe A. Cunha, Eliete Bouskela and Luiz G. Kraemer-Aguiar
Cardiac autonomic dysfunction (CADysf) in children is often associated to obesity and may be attenuated by physical activity. In this study, we investigated the effects of resistance training (RT) upon CADysf assessed by heart rate variability (HRV) in obese adolescents.
Volunteers were assigned into groups according to standard deviation scores for body mass index (z-BMI) and percentile for age and sex: obese (OB; z-BMI from 2 to 3 and ≥ 95th percentile, n = 24) and normal weight controls (CG; z-BMI from -2–1 and < 85th percentile, n = 20). OB performed isolated RT during 12 weeks [3 sets of 6–10reps with 70–85% 10RM]. Waist circumference, systolic/diastolic blood pressures (SBP/DBP), lipids, and HRV were assessed at baseline. Only OB underwent postintervention assessments.
At baseline, SBP (122.4 ± 9.1 vs. 109.7 ± 11.5 mmHg, p < .001) and DBP (76.1 ± 7.1 vs. 65.3 ± 5.9 mmHg, p < .001) were higher, while parasympathetic HRV indexes were lower (p < .05) in OB compared with CG. After RT, waist circumference (3%, p < .001) and SBP (10%, p < .001) reduced in OB. Parasympathetic indexes of HRV increased in OB (SDNN: 25%, p = .03; rMSSD: 48%, p = .0006; pNN50: 67%, p = .001; total power: 54%, p = .01; HF: 101%, p = .001) and baseline differences between groups for sympathetic and parasympathetic activities were no longer observed after RT.
RT attenuated CAdyfs and BP in obese adolescents, by increasing parasympathetic activity and decreasing sympatho-vagal balance.
Stephen B. Draper, Dan M. Wood, Jo Corbett, David V.B. James and Christopher R. Potter
We tested the hypothesis that prior heavy-intensity exercise reduces the difference between asymptotic oxygen uptake (VO2) and maximum oxygen uptake (VO2max) during exhaustive severe-intensity running lasting ≍2 minutes. Ten trained runners each performed 2 ramp tests to determine peak VO2 (VO2peak) and speed at venti-latory threshold. They performed exhaustive square-wave runs lasting ≍2 minutes, preceded by either 6 minutes of moderate-intensity running and 6 minutes rest (SEVMOD) or 6 minutes of heavy-intensity running and 6 minutes rest (SEVHEAVY). Two transitions were completed in each condition. VO2 was determined breath by breath and averaged across the 2 repeats of each test; for the square-wave test, the averaged VO2 response was then modeled using a monoexponential function. The amplitude of the VO2 response to severe-intensity running was not different in the 2 conditions (SEVMOD vs SEVHEAVY; 3925 ± 442 vs 3997 ± 430 mL/min, P = .237), nor was the speed of the response (τ; 9.2 ± 2.1 vs 10.0 ± 2.1 seconds, P = .177). VO2peak from the square-wave tests was below that achieved in the ramp tests (91.0% ± 3.2% and 92.0% ± 3.9% VO2peak, P < .001). There was no difference in time to exhaustion between conditions (110.2 ± 9.7 vs 111.0 ± 15.2 seconds, P = .813). The results show that the primary VO2 response is unaffected by prior heavy exercise in running performed at intensities at which exhaustion will occur before a slow component emerges.