Lee N. Burkett

A Meta-analysis to Determine the Dose Response for Strength Development

PURPOSE The identification of a quantifiable dose-response relationship for strength training is important to the prescription of proper training programs. Although much research has been performed examining strength increases with training, taken individually, they provide little insight into the magnitude of strength gains along the continuum of training intensities, frequencies, and volumes. A meta-analysis of 140 studies with a total of 1433 effect sizes (ES) was carried out to identify the dose-response relationship. METHODS Studies employing a strength-training intervention and containing data necessary to calculate ES were included in the analysis. RESULTS ES demonstrated different responses based on the training status of the participants. Training with a mean intensity of 60% of one repetition maximum elicits maximal gains in untrained individuals, whereas 80% is most effective in those who are trained. Untrained participants experience maximal gains by training each muscle group 3 d.wk and trained individuals 2 d.wk. Four sets per muscle group elicited maximal gains in both trained and untrained individuals. CONCLUSION The dose-response trends identified in this analysis support the theory of progression in resistance program design and can be useful in the development of training programs designed to optimize the effort to benefit ratio.

A comparison of 3 different rest intervals on the exercise volume completed during a workout.

The purpose of this research was to compare differences between 3 different rest intervals on the squat and bench press volume completed during a workout. Fifteen college-aged men volunteered to participate in this study (age 20.73 ± 2.60 years; body mass 80.73 ± 10.80 kg). All subjects performed 3 testing sessions, during which 4 sets of the squat and bench press were performed with an 8 repetition maximum (8RM) load. During each testing session, the squat and bench press were performed with a 1, 2, or 5-minute rest interval between sets. Volume was defined as the total number of repetitions completed over 4 sets for each rest condition. Statistical analysis was conducted separately for the squat and bench press. One-way repeated analyses of variance with Bonferroni post hocs demonstrated significant differences between each rest condition for both exercises tested (p < 0.05). The 5-minute rest condition resulted in the highest volume completed, followed in descending order by the 2- and 1-minute rest conditions. The ability to perform a higher volume of training with a given load may stimulate greater strength adaptations.

Non-exercise VO2max estimation for physically active college students.

This study sought to develop a maximal oxygen consumption (VO2max) regression model derived strictly from self-reported non-exercise (N-EX) predictor variables. The VO2max (mean +/- SD; 44.05 +/- 6.6 ml.kg-1.min-1) of 100 physically active college students (50 females, 50 males), aged 18 to 29 yr, was measured using a treadmill protocol and open circuit calorimetry. Questionnaire-based predictor variables used in the N-EX regression model included (a) the subjects perceived functional ability (PFA) to walk, jog, or run given distances, (b) habitual physical activity (PA-R) data, (c) body mass index (BMI), and (d) gender. BMI (kg.m-2) was computed from self-reported body weight in pounds and self-reported body height in feet and inches. The questionnaire-based N-EX regression model (R = 0.85, SEE = 3.44 ml.kg-1.min-1) developed in this study exceeded the accuracy of previously developed N-EX regression models and is comparable to many exercise-based regression models in the literature. Cross-validation using PRESS (predicted residual sum of squares) statistics demonstrated minimal shrinkage (R = 0.84, SEE = 3.60 ml.kg-1.min-1) of the present regression model. The PFA data were useful in explaining observed VO2max variance (squared partial r2 = 0.155, P < 0.0001) and enhanced the ability of the N-EX regression model to accurately predict criterion VO2max. These results suggest that a questionnaire-based N-EX regression model provides a valid and convenient method for predicting VO2max in physically active college students.

The effect of rest interval length on bench press performance with heavy vs. light loads.

The purpose of the current study was to compare the effect of 3 different rest intervals on multiple sets of the bench press exercise performed with heavy vs. light loads. Sixteen resistance-trained men performed 2 testing sessions each week for 3 weeks. During the first testing session each week, 5 consecutive sets of the bench press were performed with 80% of 1 repetition maximum (1RM) and with a 1-, 2-, or 3-minute rest interval between sets. During the second testing session each week the same procedures were repeated with 50% of 1RM. The total repetitions completed and the sustainability of repetitions were compared between rest conditions and between loads. For each load, resting 3 minutes between sets resulted in significantly greater total repetitions vs. resting 2 minutes (p = 0.000) or 1 minute (p = 0.000) between sets. However, the sustainability of repetitions was not significantly different between loads (p = 0.849). These results can be applied to weekly bench press workouts that undulate between heavy (i.e., 80% 1RM) and light (i.e., 50% 1RM) intensities. When the training goal is maximal strength development, 3 minutes of rest should be taken between sets to avoid significant declines in repetitions. The ability to sustain repetitions while keeping the intensity constant may result in a higher training volume and consequently greater gains in muscular strength.

The Effect of Rest Interval Length on the Sustainability of Squat and Bench Press Repetitions

The purpose of this study was to compare the effect of 3 different rest intervals on the sustainability of squat and bench press repetitions over 5 consecutive sets performed with a 15 repetition maximum (RM)–load. Fifteen college-age men with previous resistance training experience were tested weekly over a period of 3 weeks. During each testing session, 5 consecutive sets of the squat and the bench press were performed with a 30-second, 1-minute, or 2-minute rest interval between sets. For each exercise, significant declines in repetitions occurred between the first and the fifth sets (p = 0.000). For the squat, a significant difference in the ability to sustain repetitions occurred between the 30-second and 2-minute rest condition (p = 0.003). However, differences were not significant between the 30-second and 1-minute rest conditions (p = 0.986) and between the 1-minute and 2-minute rest conditions (p = 0.042). For the bench press, significant differences in the ability to sustain repetitions occurred between the 30-second and 2-minute rest conditions (p = 0.000) and between the 1-minute and 2-minute rest conditions (p = 0.000). However, differences were not significant between the 30-second and 1-minute rest conditions (p = 0.019). For each exercise, the number of repetitions completed on the first set was not sustained over subsequent sets, irrespective of the rest condition. These results suggest that when short rest intervals are used to develop muscular endurance, the intensity should be lowered over subsequent sets to sustain repetitions within the range conducive to this training goal.

The best warm-up for the vertical jump in college-age athletic men.

The purpose of this study was to determine the effectiveness of specific and nonspecific warm-ups on the vertical jump test performed by athletic men. Twenty-nine men (18–23 years) in athletics (speed positions in football) performed vertical jump tests on 4 separate days after completing 4 different warm-up protocols. The 4 warm-up protocols were (a) submaximal jump warm-up, (b) weighted jump warm-up, (c) stretching warm-up, and (d) no warm-up. The weighted jump warm-up protocol required 5 countermovement jumps onto a box, with the athletes holding dumbbells equaling 10% of their body weight. The submaximal jump warm-up protocol required the athletes to perform 5 counter-movement jumps at 75% intensity of their past maximum vertical jump score. The stretching warm-up protocol required the athletes to perform 14 different stretches, each held for 20 seconds. The no warm-up protocol required the athletes to perform no activity prior to being tested. Three vertical jumps were measured following each warm-up; the score for analysis was the best jump. The data were analyzed with a repeated measures analysis of variance and Bonferroni post hoc tests. The Bonferroni post hoc tests showed a significant difference (p < 0.001) between the weighted jump warm-up and all other warm-ups. The effect size was 0.380 and the power was 1.00 for the statistical analyses. We concluded that utilizing a weighted resistance warm-up would produce the greatest benefit when performing the vertical jump test.

Single versus Multiple Sets for Strength: A Meta-Analysis to Address the Controversy

Weight training can be used as a stressor to overload the neuromuscular system and develop strength. A number of weight training variables can be manipulated to overload this system. The main variables include volume, intensity, and the amount of rest allowed between sets or workouts. Of these variables, volume has received much interest among researchers and professionals, and considerable debate has arisen (Byrd, 1999) regarding an increased strength benefit of multiple-set programs. The debate over the amount of volume needed to elicit maximal strength gains has continued in recent years with several narrative reviews (Carpinelli & Otto, 1999; Feigenbaum & Pollock, 1999) ofresearch literature comparing single and multiple sets of training. These reviews have determined that single-set training programs elicit similar strength increases or health benefits (especially in untrained individuals) compared to multiple-set programs due to the inability of most of these studies to identify a statistical difference at the .05IeveI. The reliance on probability values (p) places considerable importance on statistical power. If statistical power is low, the possibility of committing a Type II error (failing to reject the Null hypothesis despite a true difference existing) is increased. With this in mind, a

Effects of shoes and foot orthotics on VO2 and selected frontal plane knee kinematics.

The objective of this study was to investigate the effects of shoes and foot orthotics on running economy and selected frontal plane knee kinematics during the support phase of running. Twenty-one male runners who had been fitted with orthotics served as subjects. Subjects participated in three submaximal runs on a treadmill under the following conditions: barefoot, shoes, and shoes plus orthotics. A run consisted of 1 min at 161 m . min-1, 2 min at 180 m . min-1, and 4 min at 201 m . min-1. VO2 was calculated for the last 3 min of each test. Frontal plane motion was filmed during the sixth min of each submaximal run, and linear and angular displacement of the knee were then calculated from film data. Results from the mechanical aspect of this study indicate that there were no significant differences among the means for linear displacement of the knee. Angular displacement of the knee during barefoot running was significantly (P less than 0.05) less than shoe and shoe-plus-orthotic conditions. There was no difference, however, between shoes and shoes plus orthotics. The economy results revealed that the aerobic cost of running increased as the amount of mass added to the foot increased. In absolute terms (1 . min-1), running in shoes plus orthotics was significantly (P less than 0.05) more costly than running barefoot. It appears that if orthotics do, in fact, improve running economy by improving running mechanics, the amount of improvement is negated by the additional cost of running associated with the mass of the orthotics.

Exercise capacity of untrained spinal cord injured individuals and the relationship of peak oxygen uptake to level of injury.

Twenty spinal cord injured individuals were tested for maximal oxygen uptake ([Vdot ]O2 peak using a hysteresis brake wheelchair ergometer. The subjects were divided into 4 groups as follows: (a) quadriplegics (4 subjects); (b) untrained female paraplegics (5 subjects); (c) untrained male paraplegics (7 subjects); and (d) trained male paraplegics (4 subjects). The [Vdot ]O2 peak were analysed by a one way ANOVA and Fishers LSD multiple comparisons. The F-ratio (50-93) was significant (p = < 0.000l). Fishers LSD post hoc multiple comparisons found the following differences: (a) quadriplegics were significantly lower than the untrained paraplegic females, untrained paraplegic males and trained paraplegic males; (b) untrained females were significantly lower than the untrained male paraplegics, and trained paraplegic males; (c) untrained paraplegic males were significantly lower than the trained male paraplegics. A Spearman Rho correlation was calculated using injury level and [Vdot ]O2 max for all the untrained SCI individuals. The correlation was 0.68 and had a significance level of 0.0019. The present study combined with the known research literature gives strong evidence that [Vdot ]O2 peak in the untrained SCI is highly related to level of injury.

Following Steve Scott: Physiological Changes Accompanying Training

In brief: American mile record holder Steve Scott was tested for maximal aerobic capacity and running economy on three occasions over nine months, a period that included off-season, preseason, the indoor season, and the early part of the outdoor season. The laboratory results demonstrated that Scotts training raised his maximal aerobic capacity approximately 8% and improved his running economy 5%. In comparing Scotts data with that of former American record holder Jim Ryun, it appears that Scotts better economy, which allowed him to perform at a lower percentage of his maximal aerobic capacity, was the essential difference between the two runners.