authors’ knowledge, no study has investigated the effects of a placebo treatment on pacing strategy. In this study, we used a balanced placebo design to examine the placebo effects of caffeine on pacing strategy and performance over 1000-m running time trials. By using a balanced placebo design, we
Philip Hurst, Lieke Schipof-Godart, Florentina Hettinga, Bart Roelands and Chris Beedie
Ian N. Bezodis, David G. Kerwin, Stephen-Mark Cooper and Aki I.T. Salo
contacts divided by the time between them. Inertia data were taken from de Leva 18 apart from the feet, 19 with 200 g added due to the mass of the running spike. 8 Step frequency was calculated by dividing the step velocity by the step length. Comparisons against known locations on the track surface and
Francesco Campa, Hannes Gatterer, Henry Lukaski and Stefania Toselli
. Procedures The athletes performed 2 running test sessions separated by 1 week. During each session, athletes ran on a treadmill for 30 minutes at an intensity corresponding to a score of 15 (heavy work) on the Borg scale. 8 They were randomly assigned to have a cold shower or no shower during the first
Philo U. Saunders, Amanda J. Cox, Will G. Hopkins and David B. Pyne
It is unclear whether physiological measures monitored in an incremental treadmill test during a training season provide useful diagnostic information about changes in distance running performance.
To quantify the relationship between changes in physiological measures and performance (peak running speed) over a training season.
Well-trained distance runners (34 males; VO2max 64 ± 6 mL⋅kg-1⋅min-1, mean ± SD) completed four incremental treadmill tests over 17 wk. The tests provided values of peak running speed, VO2max, running economy, and lactate threshold (as speed and %VO2max). The physiological measures were included in simple and multiple linear regression models to quantify the relationship between changes in these measures and changes in peak speed.
The typical within-subject variation in peak speed from test to test was 2.5%, whereas those for physiological measures were VO2max (mL⋅min-1⋅kg-1) 3.0%, economy (m⋅kg⋅mL–1) 3.6%, lactate threshold (%VO2max) 8.7%, and body mass 1.8%. In simple models these typical changes predicted the following changes in performance: VO2max 1.4%, economy 0.8%, lactate threshold –0.3%, and body mass –0.2% (90% confidence limits ~±0.7%); the corresponding correlations with performance were 0.57, 0.33, –0.05, and –0.13 respectively (~±0.20). In a multiple linear regression model, the contribution of each physiological variable to performance changed little after adjustment for the other variables.
Change in VO2max in an incremental test during a running season is a good predictor of change in peak running speed, change in running economy is a moderate predictor, and lactate threshold and body mass provide little additional information.
Arthur H. Bossi, Guilherme G. Matta, Guillaume Y. Millet, Pedro Lima, Leonardo C. Pertence, Jorge P. de Lima and James G. Hopker
To describe pacing strategy in a 24-h running race and its interaction with sex, age group, athletes’ performance group, and race edition.
Data from 398 male and 103 female participants of 5 editions were obtained based on a minimum 19.2-h effective-running cutoff. Mean running speed from each hour was normalized to the 24-h mean speed for analyses.
Mean overall performance was 135.6 ± 33.0 km with a mean effective-running time of 22.4 ± 1.3 h. Overall data showed a reverse J-shaped pacing strategy, with a significant reduction in speed from the second-to-last to the last hour. Two-way mixed ANOVAs showed significant interactions between racing time and both athlete performance group (F = 7.01, P < .001, ηp 2 = .04) and race edition (F = 3.01, P < .001, ηp 2 = .02) but not between racing time and either sex (F = 1.57, P = .058, ηp 2 < .01) or age group (F = 1.25, P = .053, ηp 2 = .01). Pearson product–moment correlations showed an inverse moderate association between performance and normalized mean running speed in the first 2 h (r = –.58, P < .001) but not in the last 2 h (r = .03, P = .480).
While the general behavior represents a rough reverse J-shaped pattern, the fastest runners start at lower relative intensities and display a more even pacing strategy than slower runners. The “herd behavior” seems to interfere with pacing strategy across editions, but not sex or age group of runners.
The tropical climate is unique in that the seasons are dominated by the movement of the tropical rain belt, resulting in dry and wet seasons rather than the four-season pattern of changes in temperature and day length seen in other parts of the world. More than 33% of the world population lives in the humid tropics, which are characterized by consistently high monthly temperatures and rainfall that exceeds evapotranspiration for most days of the year. Both the 2014 Football World Cup (in Brazil) and the 2016 Olympic Games (in Rio de Janeiro) will take place in this climate. This review focuses on the effects of the tropical environment on human exercise performance, with a special emphasis on prolonged aerobic exercise, such as swimming, cycling, and running. Some of the data were collected in Guadeloupe, the French West Indies Island where all the French teams will be training for the 2016 Olympic Games. We will first fully define the tropical climate and its effects on performance in these sports. Then we will discuss the types of adaptation that help to enhance performance in this climate, as well as the issues concerning the prescription of adequate training loads. We will conclude with some perspectives for future research.
Ricardo J.S. Costa, Robert Walters, James L.J. Bilzon and Neil P. Walsh
The purpose of the study was to determine the effects of carbohydrate (CHO) intake, with and without protein (PRO), immediately after prolonged strenuous exercise on circulating bacterially stimulated neutrophil degranulation. Twelve male runners completed 3 feeding interventions, 1 week apart, in randomized order after 2 hr of running at 75% VO2max. The feeding interventions included a placebo solution, a CHO solution equal to 1.2 g CHO~/kg body mass (BM), and a CHO-PRO solution equal to 1.2 g CHO/kg BM and 0.4 g PRO/kg BM (CHO+PRO) immediately postexercise. All solutions were flavor and water-volume equivalent (12 ml/kg BM). Circulating leukocyte counts, bacterially stimulated neutrophil degranulation, plasma insulin, and cortisol were determined from blood samples collected preexercise, immediately postexercise, and every 30 min until 180 min postexercise. The immediate postexercise circulating leukocytosis, neutrophilia, and lymphocytosis (p < .01 vs. preexercise) and the delayed lymphopenia (90 min postexercise, p < .05 vs. preexercise) were similar on all trials. Bacterially stimulated neutrophil degranulation decreased during recovery in control (23% at 180 min, p < .01 vs. preexercise) but remained above preexercise levels with CHO and CHO+PRO. In conclusion, CHO ingestion, with or without PRO, immediately after prolonged strenuous exercise prevented the decrease in bacterially stimulated neutrophil degranulation during recovery.
Ryu Nagahara, Alberto Botter, Enrico Rejc, Masaaki Koido, Takeshi Shimizu, Pierre Samozino and Jean-Benoit Morin
To test the concurrent validity of data from 2 different global positioning system (GPS) units for obtaining mechanical properties during sprint acceleration using a field method recently validated by Samozino et al.
Thirty-two athletes performed maximal straight-line sprints, and their running speed was simultaneously measured by GPS units (sampling rate: 20 or 5 Hz) and either a radar or laser device (devices taken as references). Lower-limb mechanical properties of sprint acceleration (theoretical maximal force, theoretical maximal speed, maximal power) were derived from a modeling of the speed–time curves using an exponential function in both measurements. Comparisons of mechanical properties from 20- and 5-Hz GPS units with those from reference devices were performed for 80 and 62 trials, respectively.
The percentage bias showed a wide range of overestimation or underestimation for both systems (-7.9% to 9.7% and -5.1% to 2.9% for 20- and 5-Hz GPS), while the ranges of its 90% confidence limits for 20-Hz GPS were markedly smaller than those for 5-Hz GPS. These results were supported by the correlation analyses.
Overall, the concurrent validity for all variables derived from 20-Hz GPS measurements was better than that obtained from the 5-Hz GPS units. However, in the current state of GPS devices’ accuracy for speed–time measurements over a maximal sprint acceleration, it is recommended that radar, laser devices, and timing gates remain the reference methods for implementing the computations of Samozino et al.
Mark E. Kasmer, Xue-cheng Liu, Kyle G. Roberts and Jason M. Valadao
To determine prevalence of heel strike in a midsize city marathon, if there is an association between foot-strike classification and race performance, and if there is an association between foot-strike classification and gender.
Foot-strike classification (forefoot, midfoot, heel, or split strike), gender, and rank (position in race) were recorded at the 8.1-km mark for 2112 runners at the 2011 Milwaukee Lakefront Marathon.
1991 runners were classified by foot-strike pattern, revealing a heel-strike prevalence of 93.67% (n = 1865). A significant difference between foot-strike classification and performance was found using a Kruskal-Wallis test (P < .0001), with more elite performers being less likely to heel strike. No significant difference between foot-strike classification and gender was found using a Fisher exact test. In addition, subgroup analysis of the 126 non-heel strikers found no significant difference between shoe wear and performance using a Kruskal-Wallis test.
The high prevalence of heel striking observed in this study reflects the foot-strike pattern of most mid-distance to long-distance runners and, more important, may predict their injury profile based on the biomechanics of a heel-strike running pattern. This knowledge can help clinicians appropriately diagnose, manage, and train modifications of injured runners.
Ned Brophy-Williams, Matthew W. Driller, Cecilia M. Kitic, James W. Fell and Shona L. Halson
To determine the effect of wearing compression socks between repeated running bouts on perceptual, physiological, and performance-based parameters.
Twelve well-trained male runners (mean ± SD 5-km time 19:24 ± 1:19 [min:s]) recorded their perceptions of the efficacy of compression socks for recovery before completion of 2 experimental sessions. Each session consisted of two 5-km running time trials (TT1 and TT2) on a treadmill, with a 1-h recovery period between. In a randomized crossover design, 1 session required participants to wear compression socks during the recovery period, and no compression socks were worn between TTs in the other session (control).
Running performance between TT1 and TT2 for runners wearing compression socks was similar between TTs (mean Δ 5.3 ± 20.7 s, d = 0.07, P = .20), whereas for control runners, performance significantly decreased in the second TT (mean Δ 15.9 ± 13.3 s, d = 0.19, P < .01). When grouped by perception of efficacy for compression socks, participants with strong beliefs (n = 7) experienced improved subsequent running performance with compression socks (mean Δ –3.6 ± 19.2 s, d = 0.05, P = .32) compared with those with neutral or negative perceptions (n = 5; mean Δ 17.9 ± 17.0 s, d = 0.19, P = .04). Cross-sectional area of the calf and muscle soreness were significantly reduced during the recovery period with the use of compression socks (P < .01), whereas ratings of fatigue showed no difference between conditions.
Wearing compression socks between repeated running bouts can aid recovery and subsequent performance. Furthermore, subsequent exercise performance may be even further enhanced when athletes believe in the efficacy of compression socks to assist in recovery between exercise bouts.