Salivary hormonal values from high-speed resistive exercise workouts.

Our study purpose examined salivary hormonal responses to high-speed resistive exercise. Healthy subjects (n = 45) performed 2 elbow flexor workouts on a novel (inertial kinetic exercise; Oconomowoc, WI, USA) strength training device. Our methods included saliva sample collection at both preexercise and immediately postexercise; workouts entailed two 60-second sets separated by a 90-second rest period. The samples were analyzed in duplicate for their testosterone and cortisol concentrations ([T], [C]). Average and maximum elbow flexor torque were measured from each exercise bout; they were later analyzed with a 2(gender) × 2(workout) analysis of variance (ANOVA) with repeated measures for workout. The [T] and [C] each underwent a 2(gender) × 2(time) ANOVA with repeated measures for time. A within-subject design was used to limit error variance. Average and maximum torque each had gender (men > women; p < 0.05) effects. The [T] elicited a 2-way interaction (p < 0.05), as men incurred a significant 14% increase over time, but women's values were unchanged. Yet multivariate regression revealed that 3 predictor variables (body mass and average and maximum torques) did not account for a significant amount of variance associated with the rise in male [T]. Changes in [C] were not significant. In conclusion, changes in [T] concur with the results from other studies that showed significant elevations in male [T], despite the brevity of current workouts and the rather modest volume of muscle mass engaged. Practical applications imply that salivary assays may be a viable alternative to blood draws from athletes, yet coaches and others who may administer this treatment should know that our results may have produced greater pre-post hormonal changes if postexercise sample collection had occurred at a later time point.

Net energy expenditure of gravity-independent high-speed resistive exercise done by women.

INTRODUCTION: Elevated metabolism is common to spaceflight while exercise in microgravity exacerbates energy costs. Thus in-flight exercise countermeasures must be devised that minimize energy costs as they are performed on hardware operable in microgravity. METHODS: Female subjects (N = 28), subdivided into athletic and sedentary groups, each performed two workouts on a resistive exercise device (Impulse Training Systems; Newnan, GA). Comprised exclusively of either tonic or phasic repetitions, each exercise bout entailed two 1 -min sets interspersed by a 90-s rest from which the work volume was determined. Oxygen consumption was measured before, during, and after workouts until gas uptake returned to pre-exercise levels. Net oxygen consumption was converted to net energy expenditures via indirect calorimetry. Mean net energy expenditure and work volume values were each compared with 2 (athletes, sedentaries) x 2 (tonic, phasic) ANOVAs, with repeated measures for workout. In addition, multivariate regression employed three predictor (body mass, body fat percentage, work volume) variables to account for the net energy expenditure variance. RESULTS: Workouts yielded a metabolic cost of approximately 14 kcal, yet the data produced no significant intergroup or workout differences. However, work volume analysis yielded a significant (tonic > phasic) effect. The multivariate analysis explained small yet significant amounts of net energy expenditure variance. DISCUSSION: Current results: 1) are partly attributable to higher series elastic element activity seen with Impulse repetitions; and 2) offer new information with respect to in-flight exercise protocols for female astronauts.

Front squat data reproducibility collected with a triple-axis accelerometer.

The purpose of our study was to assess data reproducibility from 2 consecutive front squat workouts, spaced 1 week apart, performed by American college football players (n = 18) as they prepared for their competitive season. For each workout, our methods entailed the performance of 3-6 front squat repetitions per set at 55, 65, and 75% of subject's 1 repetition maximum (1RM) load. In addition, a fourth set was done at a heavier load, with a resistance equal to 80 and 83% of their 1RM values, for the first and second workouts, respectively. A triple-axis accelerometer was affixed to a barbell to quantify exercise performance. Per load, the accelerometer measures peak values for the following indices: force, velocity, and power. To assess data reproducibility, inter-workout comparisons were made for 12 performance indices with 4 statistical test-retest measures: intraclass correlation coefficients, coefficients of variation (CVs), and the SEM expressed in both absolute and relative terms. Current results show that the majority of performance indices exceeded intraclass correlation (0.75-0.80) and CV (10-15%) values previously deemed as acceptable levels of data reproducibility. The 2 indices with the greatest variability were power and velocity values obtained at 55% of the 1RM load; thus, it was concluded that higher movement rates at the lightest load were the most difficult aspect of front squat performance to repeat successfully over time. Our practical applications imply lighter loads, with inherently higher rates of barbell movement, yield lower data reproducibility values.

Anthropometry as a predictor of vertical jump heights derived from an instrumented platform.

The current study purpose examined the vertical height-anthropometry relationship with jump data obtained from an instrumented platform. Our methods required college-aged (n = 177) subjects to make 3 visits to our laboratory to measure the following anthropometric variables: height, body mass, upper arm length (UAL), lower arm length, upper leg length, and lower leg length. Per jump, maximum height was measured in 3 ways: from the subjects' takeoff, hang times, and as they landed on the platform. Standard multivariate regression assessed how well anthropometry predicted the criterion variance per gender (men, women, pooled) and jump height method (takeoff, hang time, landing) combination. Z-scores indicated that small amounts of the total data were outliers. The results showed that the majority of outliers were from jump heights calculated as women landed on the platform. With the genders pooled, anthropometry predicted a significant (p < 0.05) amount of variance from jump heights calculated from both takeoff and hang time. The anthropometry-vertical jump relationship was not significant from heights calculated as subjects landed on the platform, likely due to the female outliers. Yet anthropometric data of men did predict a significant amount of variance from heights calculated when they landed on the platform; univariate correlations of men's data revealed that UAL was the best predictor. It was concluded that the large sample of men's data led to greater data heterogeneity and a higher univariate correlation. Because of our sample size and data heterogeneity, practical applications suggest that coaches may find our results best predict performance for a variety of college-aged athletes and vertical jump enthusiasts.

Anthropometry as a predictor of bench press performance done at different loads.

The purpose of our study was to examine the ability of anthropometric variables (body mass, total arm length, biacromial width) to predict bench press performance at both maximal and submaximal loads. Our methods required 36 men to visit our laboratory and submit to anthropometric measurements, followed by lifting as much weight as possible in good form one time (1 repetition maximum, 1RM) in the exercise. They made 3 more visits in which they performed 4 sets of bench presses to volitional failure at 1 of 3 (40, 55, or 75% 1RM) submaximal loads. An accelerometer (Myotest Inc., Royal Oak MI) measured peak force, velocity, and power after each submaximal load set. With stepwise multivariate regression, our 3 anthropometric variables attempted to explain significant amounts of variance for 13 bench press performance indices. For criterion measures that reached significance, separate Pearson product moment correlation coefficients further assessed if the strength of association each anthropometric variable had with the criterion was also significant. Our analyses showed that anthropometry explained significant amounts (p < 0.05) of variance for 8 criterion measures. It was concluded that body mass had strong univariate correlations with 1RM and force-related measures, total arm length was moderately associated with 1RM and criterion variables at the lightest load, whereas biacromial width had an inverse relationship with the peak number of repetitions performed per set at the 2 lighter loads. Practical applications suggest results may help coaches and practitioners identify anthropometric features that may best predict various measures of bench press prowess in athletes.

Prediction of resultant testosterone concentrations from flywheel-based resistive exercise.

INTRODUCTION: Numerous variables impact resultant testosterone concentrations (TC) that foretell the efficacy of workouts. Identifying variables may aid the development of in-flight exercise prescription. METHODS: To identify variables that predict the variance in TC from flywheel ergometer exercise, 17 subjects did 3 workouts in a randomized order. Comprised of 10-repetition leg press sets, workouts entailed either: 1) 3 sets of both concentric and eccentric muscle actions (CE3), and concentric-only actions done for 2) three (CO3), or 3) six (CO6) sets. Venous plasma TC were collected before and at 1 and 30 min postexercise. The last two collection points served as criterion measures. Body mass, delta blood lactate levels, peak angular velocity, average power, and total work from workouts were used to predict the variance in TC. RESULTS: Predictor variables accounted for significant levels of variance at both 1 and 30 min post-exercise for both the CE3 and the concentric-only (CO3 and CO6 bouts combined) workouts using multivariate regression. Inclusion of eccentric variables (only collected from the CE3 bout; r2 = 0.90) predicted nearly twice the variance than the concentric-only (r2 = 0.54) workouts. CONCLUSIONS: Body mass and average power indices were the best predictors of the variance in post-workout TC. Since a flywheel-based device is used to abate in-flight muscle atrophy and strength losses, exercise prescriptions may wish to monitor these indices as they impacted post-workout TC to the greatest extent. Future research should assess why eccentric variables increased the amount of explained variance from flywheel ergometer workouts.