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  • Author: Adrian W. Midgley x
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Ehsan Ghahramanloo, Adrian W. Midgley and David J. Bentley

Background:

There is little information regarding the effects of concurrent training (endurance and resistance training performed in the same overall regimen) on blood lipid profile in sedentary male subjects. This study compared the effects of 3 different 8-wk training programs [endurance training (ET), strength training (ST) and concurrent training (CT)] on blood lipid profile and body composition in untrained young men.

Methods:

A total of 27 subjects were randomly allocated to an ET, ST or CT group which performed either progressive treadmill (ET), free weight (ST) or both the endurance and strength training requirements for 8 weeks.

Results:

High-density lipoprotein and low-density lipoprotein profiles significantly improved in the ET and CT groups (P < .01) but not in the ST group. Triglyceride and total cholesterol profiles significantly improved in all 3 training groups. Total fat mass significantly decreased in the ET and CT groups (P < .001) but not in the ST group, whereas fat free mass significantly increased in the ST and CT groups (P < .01) but not in the ET group.

Conclusions:

These results indicate that CT can be used to simultaneously improve both the serum lipid profile and body composition of previously untrained, apparently health young men.

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Steve Barrett, Adrian W. Midgley, Christopher Towlson, Andrew Garrett, Matt Portas and Ric Lovell

Purpose:

To assess the acute alterations in triaxial accelerometry (PlayerLoad [PLVM]) and its individual axial planes (anteroposterior PlayerLoad [PLAP], mediolateral PlayerLoad [PLML], and vertical PlayerLoad [PLV]) during a standardized 90-min soccer match-play simulation (SAFT90). Secondary aims of the study were to assess the test–retest reliability and anatomical location of the devices.

Methods:

Semiprofessional (n = 5) and university (n = 15) soccer players completed 3 trials (1 familiarization, 2 experimental) of SAFT90. PlayerLoad and its individual planes were measured continuously using micromechanical-electrical systems (MEMS) positioned at the scapulae (SCAP) and near the center of mass (COM).

Results:

There were no between-halves differences in PLVM; however, within-half increases were recorded at the COM, but only during the 1st half at the SCAP. Greater contributions to PLVM were provided by PLV and PLML when derived from the SCAP and COM, respectively. PLVM (COM 1451 ± 168, SCAP 1029 ± 113), PLAP (COM 503 ± 99, SCAP 345 ± 61), PLML (COM 712 ± 124, SCAP 348 ± 61), and PLV (COM 797 ± 184, SCAP 688 ± 124) were significantly greater at the COM than at the SCAP. Moderate and high test–retest reliability was observed for PlayerLoad and its individual planes at both locations (ICC .80–.99).

Conclusions:

PlayerLoad and its individual planes are reliable measures during SAFT90 and detected within-match changes in movement strategy when the unit was placed at the COM, which may have implications for fatigue management. Inferring alterations in lower-limb movement strategies from MEMS units positioned at the SCAP should be undertaken with caution.

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Hans Luttikholt, Lars R. McNaughton, Adrian W. Midgley and David J. Bentley

Context:

There is currently no model that predicts peak power output (PPO) thereby allowing comparison between different incremental exercise test (EXT) protocols. In this study we have used the critical power profile to develop a mathematical model for predicting PPO from the results of different EXTs.

Purpose:

The purpose of this study was to examine the level of agreement between actual PPO values and those predicted from the new model.

Methods:

Eleven male athletes (age 25 ± 5 years, VO2max 62 ± 8 mL · kg–1 · min–1) completed 3 laboratory tests on a cycle ergometer. Each test comprised an EXT consisting of 1-minute workload increments of 30 W (EXT30/1) and 3-minute (EXT25/3) and 5-minute workload increments (EXT25/5) of 25 W. The PPO determined from each test was used to predict the PPO from the remaining 2 EXTs.

Results:

The differences between actual and predicted PPO values were statistically insignificant (P > .05). The random error components of the limits of agreement of ≤30 W also indicated acceptable levels of agreement between actual and predicted PPO values.

Conclusions:

Further data collection is necessary to confirm whether the model is able to predict PPO over a wide range of EXT protocols in athletes of different aerobic and anaerobic capacities.

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S. Andy Sparks, Benjamin Dove, Craig A. Bridge, Adrian W. Midgley and Lars R. McNaughton

Power meters have traditionally been integrated into the crank set, but several manufacturers have designed new systems located elsewhere on the bike, such as inside the pedals.

Purpose:

This study aimed to determine the validity and reliability of the Keo power pedals during several laboratory cycling tasks.

Methods:

Ten active male participants (mean ± SD age 34.0 ± 10.6 y, height 1.77 ± 0.04 m, body mass 76.5 ± 10.7 kg) familiar with laboratory cycling protocols completed this study. Each participant was required to complete 2 laboratory cycling trials on an SRM ergometer (SRM, Germany) that was also fitted with the Keo power pedals (Look, France). The trials consisted of an incremental test to exhaustion followed by 10 min rest and then three 10-s sprint tests separated by 3 min of cycling at 100 W.

Results:

Over power ranges of 75 to 1147 W, the Keo power-pedal system produced typical error values of 0.40, 0.21, and 0.21 for the incremental, sprint, and combined trials, respectively, compared with the SRM. Mean differences of 21.0 and 18.6 W were observed between trials 1 and 2 with the Keo system in the incremental and combined protocols, respectively. In contrast, the SRM produced differences of 1.3 and 0.6 W for the same protocols.

Conclusions:

The power data from the Keo power pedals should be treated with some caution given the presence of mean differences between them and the SRM. Furthermore, this is exacerbated by poorer reliability than that of the SRM power meter.

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Lars R. McNaughton, Steve Kenney, Jason Siegler, Adrian W. Midgley, Ric J. Lovell and David J. Bentley

Context:

Recently, superoxygenated-water beverages have emerged as a new purported ergogenic substance.

Purpose:

This study aimed to determine the effects of superoxygenated water on submaximal endurance performance.

Methods:

Eleven active male subjects, VO2max 52.6 ± 4.8 mL · kg−1 · min−1, height 180.0 ± 2.0 cm, weight 76.0 ± 7.0 kg, age 24 ± 1.0 y (mean ± SD), completed a 45-min cycle-ergometry exercise test at 70% of their previously predicted maximal power output with a 10-min rest period, followed by a 15-min time trial (TT). Thirty minutes before the exercise test subjects consumed 15 mL of either superoxygenated water (E) or placebo (P; water mixed with low-chlorine solution). Subjects then completed the test again a week later for the other condition (double-blind, randomized). The physiological variables measured during exercise were VO2, VCO2, respiratory-exchange ratio (RER), VE, PO2, PCO2, blood lactate (bLa–), and heart rate (HR). Mean distance covered and the average power output for the 15-min TT were also measured as performance indicators.

Results:

There were no significant differences in VO2, VCO2, RER, VE, bLa, PO2, and HR (P > .05) during the exercise tests. Neither were there any significant improvements in the total distance covered (P 9.01 ± 0.74 km vs E 8.96 ± 0.68 km, P > .05) or the average power output (P 186.7 ± 35.8 W vs E 179.0 ± 25.9 W, P > .05) during the 15-min TT.

Conclusion:

Based on these results the authors conclude that consuming 15 mL of superoxygenated water does not enhance submaximal or maximal TT cycling performance.

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Laura J.S. Moore, Adrian W. Midgley, Gemma Thomas, Shane Thurlow and Lars R. McNaughton

Purpose:

The aim of this work was to determine whether the consumption of pre-exercise high– or low–glycemic index (GI) meals has a beneficial effect on time trial performance.

Methods:

Eight male cyclists were provided with either a high-GI or low-GI meal, providing 1 g·kg−1 body mass of carbohydrate, 45 min before performing a 40-km time trial on a Velotron cyclePro.

Results:

Time trial performance was significantly improved in the low-GI trial (92.5 ± 5.2 min) compared with the high-GI trial (95.6 ± 6.0 min) (P = .009). Blood glucose concentrations at the point of exhaustion were significantly higher in the low-GI trial (5.2± 0.6 mmol·L−1) compared with the high-GI trial (4.7 ± 0.7 mmol·L−1) (P = .001). There was no significant difference in estimated carbohydrate oxidation data between the low-GI (2.51 ± 1.74 g·min−1) and high-GI (2.18 ± 1.53 g·min−1) meals (P = .195). No significant difference in estimated fat oxidation was observed between the low-GI (0.15 ± 0.15 g·min−1) and high-GI (0.29 ± 0.18 g·min−1) diets (P = .83).

Conclusions:

The improvement in time trial performance for the low-GI trial may be associated with an increased availability of glucose to the working muscles, contributing additional carbohydrate for oxidation and possibly sparing limited muscle and liver glycogen stores.