Search Results

To assess original research addressing the effect of the application of compression clothing on sport performance and recovery after exercise, a computer-based literature research was performed in July 2011 using the electronic databases PubMed, MEDLINE, SPORTDiscus, and Web of Science. Studies examining the effect of compression clothing on endurance, strength and power, motor control, and physiological, psychological, and biomechanical parameters during or after exercise were included, and means and measures of variability of the outcome measures were recorded to estimate the effect size (Hedges g) and associated 95% confidence intervals for comparisons of experimental (compression) and control trials (noncompression). The characteristics of the compression clothing, participants, and study design were also extracted. The original research from peer-reviewed journals was examined using the Physiotherapy Evidence Database (PEDro) Scale. Results indicated small effect sizes for the application of compression clothing during exercise for shortduration sprints (10–60 m), vertical-jump height, extending time to exhaustion (such as running at VO_2max or during incremental tests), and time-trial performance (3–60 min). When compression clothing was applied for recovery purposes after exercise, small to moderate effect sizes were observed in recovery of maximal strength and power, especially vertical-jump exercise; reductions in muscle swelling and perceived muscle pain; blood lactate removal; and increases in body temperature. These results suggest that the application of compression clothing may assist athletic performance and recovery in given situations with consideration of the effects magnitude and practical relevance.

Purpose: To investigate performance progression from early-junior to peak performance age and compare variety in race distances and swimming strokes between swimmers of various performance levels. Methods: Using a longitudinal data analysis and between-groups comparisons 306,165 annual best times of male swimmers (N = 3897) were used to establish a ranking based on annual best times at peak performance age. Individual performance trajectories were retrospectively analyzed to compare distance and stroke variety. Performances of world-class finalists and international- and national-class swimmers (swimming points: 886 [30], 793 [28], and 698 [28], respectively) were compared across 5 age groups—13–14, 15–16, 17–18, 19–20, and 21+ years—using a 2-way analysis of variance with repeated measures. Results: World-class finalists are not significantly faster than international-class swimmers up to the 17- to 18-year age group (F _2|774 = 65, P < .001, ${\eta }_p^2=.14$ ) but specialize in short- or long-distance races at a younger age. World-class breaststroke finalists show faster breaststroke times compared to their performance in other swimming strokes from an early age (P < .05), while world-class freestyle and individual medley finalists show less significant differences to their performance in other swimming strokes. Conclusions: While federation officials should aim for late talent selection, that is, not before the 17- to 18-year age group, coaches should aim to identify swimmers’ preferred race distances early on. However, the required stroke variety seems to be specific for each swimming stroke. Breaststroke swimmers could aim for early and strong specialization, while freestyle and individual medley swimmers could maintain large and very large stroke variety, respectively.

Purpose: To examine the relationship between cardiorespiratory and accelerometer-derived measures of exercise during trail running and determine the influence of accelerometer location. Methods: Eight trail runners (7 males and 1 female; age 26 [5] y; maximal oxygen consumption [ $\dot{\mathrm{V}}{\mathrm{O}}_2$ ] 70 [6] mL·kg⁻¹·min⁻¹) completed a 7-km trail run (elevation gain: 486 m), with concurrent measurements of $\dot{\mathrm{V}}{\mathrm{O}}_2$ , heart rate, and accelerations recorded from 3 triaxial accelerometers attached at the upper spine, lower spine, and pelvis. External exercise intensity was quantified from the accelerometers using PlayerLoad™ per minute and accelerometry-derived average net force. External exercise volume was calculated using accumulated PlayerLoad and the product of average net force and duration (impulse). Internal intensity was calculated using heart rate and $\dot{\mathrm{V}}{\mathrm{O}}_2$ -metrics; internal volume was calculated from total energy expenditure (work). All metrics were analyzed during both uphill (UH) and downhill (DH) sections of the trail run. Results: PlayerLoad and average net force were greater during DH compared with UH for all sensor locations (P ≤ .004). For all accelerometer metrics, there was a sensor position × gradient interaction (F _2,1429.003; P <.001). The upper spine was lower compared with both pelvis (P ≤ .003) and lower spine (P ≤ .002) for all accelerometer metrics during both UH and DH running. Relationships between accelerometer and cardiorespiratory measures during UH running ranged from moderate negative to moderate positive (r = −.31 to .41). Relationships were stronger during DH running where there was a nearly perfect correlation between work and impulse (r = .91; P < .001). Conclusions: Simultaneous monitoring of cardiorespiratory and accelerometer-derived measures during trail running is suggested because of the disparity between internal and external intensities during changes in gradient. Sensor positioning close to the center of mass is recommended.