Dataset Information

A Plyometric Warm-Up Protocol Improves Running Economy in Recreational Endurance Athletes.

ABSTRACT: This study explored the impact of two differing warm-up protocols (involving either resistance exercises or plyometric exercises) on running economy (RE) in healthy recreationally active participants. Twelve healthy university students [three males, nine females, age 20 ± 2 years, maximal oxygen uptake (38.4 ± 6.4 ml min-1 kg-1)] who performed less than 5 h per week of endurance exercise volunteered to participant in this study. All participants completed three different warm-up protocols (control, plyometric, and resistance warm-up) in a counterbalanced crossover design with trials separated by 48 h, using a Latin-square arrangement. Dependent variables measured in this study were RE at four running velocities (7, 8, 9, and 10 km h-1), maximal oxygen uptake; heart rate; respiratory exchange rate; expired ventilation; perceived race readiness; rating of perceived exertion, time to exhaustion and leg stiffness. The primary finding of this study was that the plyometric warm-up improved RE compared to the control warm-up (6.2% at 7 km h-1, ES = 0.355, 9.1% at 8 km h-1, ES = 0.513, 4.5% at 9 km h-1, ES = 0.346, and 4.4% at 10 km h-1, ES = 0.463). There was no statistically significant difference in VO2 between control and resistance warm-up conditions at any velocity. There were also no statistically significant differences between conditions in other metabolic and pulmonary gas exchange variables; time to exhaustion; perceived race readiness and maximal oxygen uptake. However, leg stiffness increased by 20% (P = 0.039, ES = 0.90) following the plyometric warm-up and was correlated with the improved RE at a velocity of 8 km h-1 (r = 0.475, P = 0.041). No significant differences in RE were found between the control and resistance warm-up protocols. In comparison with the control warm-up protocol, an acute plyometric warm-up protocol can improve RE in healthy adults.

SUBMITTER: Wei C

PROVIDER: S-EPMC7080849 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Plyometric Warm-Up Protocol Improves Running Economy in Recreational Endurance Athletes.

Wei ChenGuang C Yu Liang L Duncan Benedict B Renfree Andrew A

Frontiers in physiology 20200312

This study explored the impact of two differing warm-up protocols (involving either resistance exercises or plyometric exercises) on running economy (RE) in healthy recreationally active participants. Twelve healthy university students [three males, nine females, age 20 ± 2 years, maximal oxygen uptake (38.4 ± 6.4 ml min<sup>-1</sup> kg<sup>-1</sup>)] who performed less than 5 h per week of endurance exercise volunteered to participant in this study. All participants completed three different wa ...[more]

PMID: 32226393

Similar Datasets

Project description:Background: Properly performed training is a matter of importance for endurance athletes (EA). It allows for achieving better results and safer participation. Recently, the development of machine learning methods has been observed in sports diagnostics. Velocity at anaerobic threshold (VAT), respiratory compensation point (VRCP), and maximal velocity (Vmax) are the variables closely corresponding to endurance performance. The primary aims of this study were to find the strongest predictors of VAT, VRCP, Vmax, to derive and internally validate prediction models for males (1) and females (2) under TRIPOD guidelines, and to assess their machine learning accuracy. Materials and Methods: A total of 4001 EA (nmales = 3300, nfemales = 671; age = 35.56 ± 8.12 years; BMI = 23.66 ± 2.58 kg·m−2; VO2max = 53.20 ± 7.17 mL·min−1·kg−1) underwent treadmill cardiopulmonary exercise testing (CPET) and bioimpedance body composition analysis. XGBoost was used to select running performance predictors. Multivariable linear regression was applied to build prediction models. Ten-fold cross-validation was incorporated for accuracy evaluation during internal validation. Results: Oxygen uptake, blood lactate, pulmonary ventilation, and somatic parameters (BMI, age, and body fat percentage) showed the highest impact on velocity. For VAT R2 = 0.57 (1) and 0.62 (2), derivation RMSE = 0.909 (1); 0.828 (2), validation RMSE = 0.913 (1); 0.838 (2), derivation MAE = 0.708 (1); 0.657 (2), and validation MAE = 0.710 (1); 0.665 (2). For VRCP R2 = 0.62 (1) and 0.67 (2), derivation RMSE = 1.066 (1) and 0.964 (2), validation RMSE = 1.070 (1) and 0.978 (2), derivation MAE = 0.832 (1) and 0.752 (2), validation MAE = 0.060 (1) and 0.763 (2). For Vmax R2 = 0.57 (1) and 0.65 (2), derivation RMSE = 1.202 (1) and 1.095 (2), validation RMSE = 1.205 (1) and 1.111 (2), derivation MAE = 0.943 (1) and 0.861 (2), and validation MAE = 0.944 (1) and 0.881 (2). Conclusions: The use of machine-learning methods allows for the precise determination of predictors of both submaximal and maximal running performance. Prediction models based on selected variables are characterized by high precision and high repeatability. The results can be used to personalize training and adjust the optimal therapeutic protocol in clinical settings, with a target population of EA.

Project description:BackgroundThe percentage of sustained maximal oxygen uptake and the running economy are important factors that determine the running success of endurance athletes. Running economy is defined as the oxygen uptake required to run at a given speed and depends on metabolic, cardiorespiratory, biomechanical, neuromuscular, and anthropometric factors. With regard to anthropometric characteristics, total body mass seems to be a crucial factor for the running economy. Moreover, neuromuscular components, especially knee muscular strength and the strength balance ratio, also seem to be critical for the running economy. In addition to knee muscle strength, hip muscle strength is also an important contributor to running performance on level or hilly ground. However, the relationship between running economy and the hip muscles is unknown. Thus the aim of the present study was to verify whether hip flexor and extensor isokinetic peak torque, the isokinetic strength balance ratio, total body mass and fat free mass were associated with running economy in both sexes and to compare sex differences in physical fitness and isokinetic strength characteristics.MethodsA total of 24 male (31.0 ± 7.7 years, 176.2 ± 7.3 cm, and 70.4 ± 8.4 kg) and 15 female (31.3 ± 6.7 years, 162.9 ± 3.9 cm, and 56.0 ± 5.3 kg) recreationally-trained endurance runners were recruited. Maximal oxygen uptake, running economy, conventional (concentric flexors-to-concentric extensors) and functional (concentric flexors-to-eccentric extensors) hip isokinetic strength balance ratios, peak torque of the hip flexor and extensor muscles, total body mass, and fat-free mass were measured. Running economy was assessed on two separate days by means of the energy running cost (Ec) using a motorized treadmill at 10.0 and 12.0 km h-1 (3% gradient) and 11.0 and 14.0 km h-1 (1% gradient).ResultsThe functional balance ratio was significantly and negatively associated with Ec at 11.0 (r = - 0.43, P = 0.04) and 12.0 km h-1 (r = - 0.65, P = 0.04) when using a 3% gradient in male runners. Considering muscular strength, male runners only showed a significant relationship between Ec (assessed at 12 km h-1 and a 3% gradient) and peak torque for extensor muscle eccentric action (r = 0.72, P = 0.04). For female runners, only peak torque relative to total body mass for extensor muscles (180° s-1) was positively associated with Ec when assessed at 10 km h-1 using a 3% gradient (r = 0.59, P = 0.03). No significant relationships were found between Ec and total body mass or fat-free mass.DiscussionGiven that the functional balance ratio was associated with a better Ec, coaches and athletes should consider implementing a specific strengthening program for hip flexor muscles to increase the functional ratio.

Project description:BackgroundMaximal aerobic speed (MAS) is a useful parameter to assess aerobic capacity and estimate training intensity in middle- and long-distance runners. However, whether middle- and long-distance runners reach different levels of MAS compared to other endurance athletes with similar V̇O2max has not been previously studied. Therefore, we aimed to compare V̇O2max, MAS and spatiotemporal parameters between sub-elite middle- and long-distance runners (n = 6) and endurance non-runners (n = 6). In addition, we aimed to compare the maximal blood lactate concentration [BLa] experienced by participants after conducting these tests.MethodsTelemetric portable respiratory gas analysis, contact and flight time, and stride length and rate were measured using a 5-m contact platform during an incremental test at a synthetic athletics track. V̇O2, heart rate, respiratory quotient values in any 15 s average period during the test were measured. [BLa] was analyzed after the test . Running spatiotemporal parameters were recorded at the last two steps of each 400 m lap. A coefficient of variation (%CV) was calculated for each spatiotemporal variable in each participant from 8 km h-1 onwards.ResultsWhereas runners reported faster MAS (21.0 vs. 18.2 km h-1) than non-runners (p = 0.0001, ES = 3.0), no differences were found for V̇O2max and maximum blood lactate concentration during the running tests (p > 0.05). While significant increases in flight time and stride length and frequency (p < 0.001, 0.52 ≤ ηp2 ≤ 0.8) were observed throughout the tests, decreases in contact time (p < 0.001, ηp2=0.9 ) were reported. Runners displayed a greater %CV (p = 0.015) in stride length than non-runners. We conclude that middle- and long-distance runners can achieve a faster MAS compared to non-running endurance athletes despite exhibiting a similar V̇O2max. This superior performance may be associated to a greater mechanical efficiency. Overall, runners displayed a greater ability to modify stride length to achieve fast speeds, which may be related to a more mechanically efficient pattern of spatiotemporal parameters than non-runners.

Dataset Information

A Plyometric Warm-Up Protocol Improves Running Economy in Recreational Endurance Athletes.

Publications

A Plyometric Warm-Up Protocol Improves Running Economy in Recreational Endurance Athletes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets