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Examination of a Multi-ingredient Preworkout Supplement on Total Volume of Resistance Exercise and Subsequent Strength and Power Performance

Bergstrom, Haley C. 1 ; Byrd, M. Travis 1 ; Wallace, Brian J. 2 ; Clasey, Jody L. 1

1 Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky; and

2 Kinesiology and Athletic Training Department, University of Wisconsin Oshkosh, Oshkosh, Wisconsin

Address correspondence to Dr. Haley C. Bergstrom, [email protected] .

Bergstrom, HC, Byrd, MT, Wallace, BJ, and Clasey, JL. Examination of a multi-ingredient preworkout supplement on total volume of resistance exercise and subsequent strength and power performance. J Strength Cond Res 32(6): 1479–1490, 2018—This study examined the acute effects of a multi-ingredient preworkout supplement on (a) total-, lower-, and upper-body volume of resistance exercise and (b) the subsequent lower-body strength (isokinetic leg extension and flexion), lower-body power (vertical jump [VJ] height), upper-body power (bench throw velocity [BT v ]), and cycle ergometry performance (critical power and anaerobic work capacity). Twelve men completed baseline strength and power measures before 2 experimental visits, supplement (SUP) and placebo (PL). The experimental visits involved a fatiguing cycling protocol 30 minutes after ingestion of the SUP or PL and 15 minutes before the beginning of the resistance exercise protocol, which consisted of 4 upper-body and 4 lower-body resistance exercises performed for 4 sets to failure at 75% 1 repetition maximum. The exercise volume for the total, lower, and upper body was assessed. The VJ height and BT v were measured immediately after the resistance exercise. Postexercise isokinetic leg extension and flexion strength was measured 15 minutes after the completion of a second cycling protocol. There was a 9% increase in the total-body volume of exercise and a 14% increase in lower-body volume of exercise for the SUP compared with the PL, with no effect on exercise volume for the upper body between the SUP and PL. The increased lower-body volume for the SUP did not result in greater lower-body strength and power performance decrements after exhaustive exercise, compared with the PL. These findings suggested the potential for the SUP to increase resistance exercise volume, primarily related to an increased lower-body volume of exercise.

Introduction

The use of preworkout supplements has become increasingly popular. These supplements are used to enhance both aerobic and anaerobic performance parameters and are generally considered safe when consumed at the recommended dosages ( 29 ). There are a number of preworkout supplements available, with various combinations of active ingredients but most contain caffeine. Caffeine has been shown to have an ergogenic effect on strength, power, and endurance at dosages of 3–6 mg·kg −1 ( 18 ). The effects of caffeine have been attributed to 3 primary mechanisms, which include (a) alteration of fat metabolism ( 4 ), (b) direct effect on calcium release from the sarcoplasmic reticulum (ryanodine receptors) ( 1 ), and (c) adenosine receptor antagonism ( 15,16 ). Currently, there is conflicting evidence regarding the potential for caffeine to influence fat oxidation ( 19 ), and it is unlikely that caffeine could exert its effects on calcium release at the typical dosage contained in preworkout beverages (∼3–6 mg·kg −1 ) ( 16 ). It has been suggested that for high-intensity exercise, caffeine's effects are most likely related to its role as an adenosine receptor antagonist, which may serve to decrease the perception of fatigue ( 43 ) and increase the release of neurotransmitters ( 16 ) and motor neuron excitability ( 32,40 ). Caffeine supplementation has been shown to increase muscular strength ( 46 ), muscular endurance ( 5,36 ), and peak and mean power output during anaerobic cycling ( 5 ). There are limited data, however, regarding the effects of caffeine in combination with citrulline-malate, amino acids (beta-alanine, leucine, tyrosine), creatine, and vitamins (B-3, B-6, B-12, C, and D) on exercise performance.

Ingredients, such as citrulline-malate, leucine, and aspartic acid, contained in preworkout supplements may augment the effects of caffeine. For example, citrulline-malate has been shown to increase the number of repetitions to failure during repeated sets at 60% 1 repetition maximum (RM) for lower-body exercise ( 50 ). In addition, citrulline may have vasodilatory properties as a precursor to arginine and nitric oxide production ( 45 ), increase muscle efficiency and delay fatigue ( 17 ), and increase utilization of amino acids during exercise ( 44 ). Bioperine is considered a thermogenic ingredient, extracted from black pepper, and may increase the metabolic rate ( 33 ), whereas huperzine A has been shown to have cognitive enhancing properties ( 51 ). Branched-chain amino acids, such as leucine, have potential acute and chronic effects related to enhanced cognitive function ( 48 ), decreased muscle soreness ( 26 ), and increased muscle protein synthesis ( 2,37 ). In addition, aspartic acid may reduce the accumulation of ammonia in the blood and improve muscular endurance performance ( 3 ), whereas tyrosine, the precursor to dopamine and norepinephrine, may improve cognitive function under environmental and physical stressors ( 28 ).

The acute affects of preworkout supplementation may be augmented by longer-term (>4 weeks) dosing strategies of other ingredients, such as beta-alanine, creatine, and amino acids, contained in multi-ingredient preworkout supplements ( 30 ). Research has shown increases in total exercise volume and a reduction in the subjective feelings of fatigue after 3 weeks of supplementation with beta-alanine ( 23 ). Both beta-alanine and creatine may augment the effects of caffeine by delaying neuromuscular fatigue ( 12,42 ). The branched-chain amino acid leucine has been shown to be an important signal to stimulate maximal muscle protein synthesis ( 37 ), and a preworkout supplement containing branched-chain amino acids and creatine has been shown to result in greater increases in muscle thickness, lean mass, and strength, when compared with a placebo ( 35 ). Thus, it is possible that a combination of caffeine, citrulline-malate, amino acids (beta-alanine, leucine, tyrosine), creatine, and vitamins (B-3, B-6, B-12, C, and D) may work synergistically to enhance performance in acute and longer-term dosing strategies, beyond supplementation with each ingredient alone. No previous studies, however, have examined the potential ergogenic effects of this combination of ingredients contained in a preworkout supplement. Thus, further research is needed on the combined effects of these ingredients on total exercise volume and subsequent strength, power, and anaerobic performance. Therefore, the primary purposes of this study were to examine the acute effects of multi-ingredient preworkout supplementation in resistance-trained men on (a) total-, lower-, and upper-body volume of resistance exercise; (b) the subsequent lower-body strength (isokinetic leg extension and flexion), lower-body power (vertical jump [VJ] height), upper-body power (bench throw velocity) and cycle ergometry performance (critical power [CP] and anaerobic work capacity [AWC]).

Experimental Approach to the Problem

This was a randomized, double-blind, placebo-controlled, crossover design with 2 treatments, supplement (SUP) and placebo (PL). This study involved 5 visits to the exercise physiology and human performance laboratories. All testing procedures were performed at the same time of day for each subject. During visit 1, the subjects demographic information was recorded, and subjects completed a familiarization of the isokinetic leg flexor and extensor strength testing, VJ test, bench press throw test, and CP 3-minute all-out test cycling protocol (CP 3min ). After 24 hours, the subjects returned to the laboratory to complete visit 2, which included total-body dual-energy x-ray absorptiometry (DXA) scans for body composition assessment and baseline 1RM testing for the barbell back squat, barbell flat bench press, barbell deadlift, and barbell reverse lunge. Forty-eight to 72 hours after completing visit 2, the subjects returned to the laboratory for visit 3 to complete baseline testing for the VJ and bench press throw, followed by 1RM testing for the incline press, front squat, barbell bent-over row, and standing barbell overhead press. In addition, following the 1RM testing, the baseline values were measured for isokinetic leg flexion and extension strength. The experimental visits were completed during visits 4 and 5. Visit 4 was conducted 48–72 hours after completion of the baseline testing (visit 3), and visit 5 was completed 7–10 days after visit 4. For visit 4, the subjects were randomly assigned to ingest either the SUP or PL and ingested the crossover treatment for visit 5. Blood pressure (systolic and diastolic) and heart rate (HR) were taken at 2 time points (15 minutes after arrival and 25 minutes after ingestion). Thirty minutes after ingestion, the subjects completed the experimental protocol outlined in Figures 1 and 2 . Briefly, the subjects completed a fatiguing cycling protocol 15 minutes before the beginning of the resistance exercise protocol ( Figure 2 ). The exercise volume for the total body, lower body, and upper body was assessed. Five minutes after completion of the resistance exercise protocol, subjects completed VJ test and the bench throw test, to assess lower- and upper-body power, respectively. After the bench throw test, the subjects completed a second fatiguing cycling protocol. Isokinetic leg extension and flexion strength was measured 15 minutes after the completion of the second cycling protocol. The subjects were asked to refrain from strenuous exercise for at least 24 hours and avoid the consumption of alcohol or caffeine for at least 48 hours before each testing session. Furthermore, the subjects recorded any food and drink consumed 24 hours before, and the day of, the first experimental visit (visit 4). The subjects were asked to consume the same diet 24 hours before, and the day of, the last experimental visit (visit 5), to ensure the same total caloric (kilocalories), protein, carbohydrate, and fat intake.

Twelve men, with resistance training experience (mean ± SD : age = 22 ± 3 years [range = 19–26 years]; height = 179 ± 7 cm; body mass = 86 ± 13 kg) were recruited for this study. The subjects were involved in a whole-body resistance training program, at least 3 times per week continuously for at least 1 year. Potential subjects who were unable to maximally back squat a weight of ≥1.5 times their body mass were excluded from participation. The mean ± SD 1RM back squat for the subjects in this study was 142 ± 34 kg (1.7 ± 0.3 × body mass). All subjects were free from musculoskeletal injuries or neuromuscular diseases and did not report any medical disorders or medicinal or supplement usage that could have affected the outcome of this study. This study was approved by the University of Kentucky's Institutional Review Board for the protection of human subjects, and all subjects completed a written health history questionnaire and informed consent document before any testing.

Body Composition Assessments

A total-body DXA scan (GE Lunar Prodigy; GE Lunar, Inc., Madison, WI, USA) scan was performed to assess total-body fat percentage (%BF) and mineral-free lean model mass (in kilograms). The subjects were instructed to remove all objects, such as jewelry or eyeglasses, and wore T-shirt and shorts containing no metal during the scanning procedure. All scans were analyzed by a single trained investigator using the Lunar software version 13.10 (GE Lunar, Inc., Madison, WI, USA).

1-Repetition Maximum Testing

All of the resistance exercises were dynamic constant external resistance (DCER) barbell movements, including 4 upper-body (flat bench press, bent-over row, incline bench press, and standing shoulder press) and 4 lower-body (back squat, deadlift, front squat, and reverse lunge) lifts. A standardized warm-up was completed before each of the 1RM tests. The warm-up began with 10 repetitions at 50%, 5 repetitions at 70%, 3 repetitions at 80%, and 1 repetition at 90% of each subject's predicted 1RM body mass. One minute of rest was provided between warm-up sets, and 2 minutes of rest was provided between the final warm-up set and the first 1RM attempt. The subjects completed up to 3 attempts to determine the 1RM ( 13 ). For all 1RM DCER strength testing, progressive loads were added until the subject could not complete a repetition through the full range of motion. Additional trials were performed with lighter loads until the 1RM was determined within 2.27 kg, which was typically achieved within 3 trials. Three minutes of rest was given between 1RM attempts.

The barbell back squat was performed on a standard free-weight rack using an Olympic barbell. The barbell was positioned above the posterior deltoids at the base of the neck. The subjects' feet were positioned shoulder-width apart, with the toes pointed slightly outward. The subjects were instructed to keep their feet on the floor and maintain a flat back, keeping the torso-to-floor angle relatively constant through the range of motion. A complete repetition was considered when the subject moved from an erect position into flexion at the knee and hip until the thighs were parallel to the floor and then returned to the original position ( 49 ). The front squat was performed in a similar manner as the back squat, with the exception that the barbell was positioned across the front of the body over the anterior deltoids near the clavicle. A clean grip or cross-armed grip was used at the subject's discretion.

The barbell deadlift was performed using free weights and a standard Olympic barbell. The subjects performed a conventional style deadlift (vs. sumo), in which their feet were approximately hip width, with toes pointed slightly outward. The subjects started the lift with flexion at the knees and hips so that the back was flat and at an approximately 60° angle to the floor. The subjects were instructed to use an alternating grip. A complete repetition was considered when the subject reached full extension at the knees and hips with the barbell and returned the barbell back to the floor in a controlled manner. “Hitching” and “back lifting” (where the lifter extends their knees before, not at the same time as, their hips) was not permitted.

The barbell reverse lunge was performed in a standard squat rack with an Olympic barbell. The subjects grasped the barbell with a closed, pronated grip. The bar was positioned above the posterior deltoids at the base of the neck. The subjects stepped backward with one, keeping the torso erect and the trailing foot planted on the floor. The subject allowed the thigh and lower leg to slowly flex until the knee was 1–2 inches above the floor and the thigh was parallel with the floor (∼2 seconds). The subjects pushed off the floor with the back leg, extending the leg and thighs, brining the back foot to the starting position. After a brief pause (∼1 second), the subject completed the same movement with the opposite leg. The 1RM was considered to be achieved only if the weight could be moved through the range of motion twice (using right and left legs as the back leg 1 time).

The flat barbell bench press was performed on a standard free-weight bench with an Olympic barbell. After receiving a liftoff from the spotter, the subjects lowered the barbell to their chest just above the nipple line, paused briefly, and then pressed the bar to full extension of the forearms. This was defined as one complete repetition. The incline bench press was performed in the same manner as the flat barbell bench press, with the exception that the bench was inclined to approximately 45°. The barbell touched the chest slightly higher than during the flat barbell bench press.

The shoulder press was performed in a standard squat rack with an Olympic barbell. The subjects used a 3-handed pronated grip to secure the barbell in their hands and lifted it from the rack. The barbell was positioned across the front of the body over the anterior deltoids near the clavicle. The subjects were instructed to take one step backward with each foot, gain their balance, and push the barbell overhead to full elbow extension. One repetition was defined as raising and lowering the bar under control. Safety pins were set within the rack, so the subject could release the weight from their grip onto the pins if needed. Additionally, one spotter was placed on each side of the barbell for safety.

The barbell bent-over row was performed from the floor with an Olympic barbell, using a closed, pronated grip. The subjects positioned their feet shoulder-width apart, with slight flexion at the knees. The torso was flexed so that it is just slightly above parallel to the floor. The movement began with the forearms fully extended and the barbell 1–2 inches from the floor. The subject pulled the bar toward the torso, keeping the back flat and slight flexion at the knees. The barbell touched the lower chest or upper abdomen and was lowered back to the starting position.

Vertical Jump Test

Vertical jump height was measured using the Vertec vertical jump device (Gill Athletics, Champaign, IL, USA). Each subject was positioned directly underneath the Vertec and instructed to jump as high as possible from a standing 2-foot position, use a countermovement, and move the highest horizontal vane with a single hand ( 39 ). Each subject performed 3 VJs with 2 minutes of rest between each trial. Vertical jump height was calculated as the difference between the highest vane of the Vertec reached and the standing reach height and expressed in centimeters. The test-retest data from our laboratory for the VJ test ( n = 15) has been shown to be highly reliable (intraclass correlation [ICC] = 0.99) with no significant mean differences (mean difference = −2.36 cm; 95% confidence interval [CI] = −6.92 to 2.19 cm; p > 0.05) between test-retest values.

Isokinetic Testing

Isokinetic strength was assessed using a Biodex System 4 (Biodex Medical, Shirley, NY, USA). The subjects were positioned on the isokinetic dynamometer in a seated position. After several submaximal repetitions, the subjects completed 3 maximum effort concentric leg flexion and extension contractions on the dynamometer at 30°·sec −1 . The peak torque (N·m) was defined as the highest of the 3 trials. The isokinetic strength testing has been shown to be highly reliable (ICC = 0.98), with no significant mean differences between test-retest values ( 9 ).

Bench Throw Test

The 1RM barbell flat bench press was determined before the bench throw test. The bench throw test was performed on a Smith machine (OSSM; Life Fitness, Chicago, IL, USA), with the subject supine on a flat bench. A weight equal to 30% of the subjects' bench press 1RM was used. The subjects were instructed to begin the movement with the arms fully extended and then lower the barbell in a rapid but controlled (without pulling or allowing the barbell to bounce off the chest) manner and then immediately move the barbell as fast as possible from the chest. The bar was released and caught by the subject, with a test administrator as the spotter. Three throws were performed, and the bench throw peak velocity was recorded by a HUMAC360 potentiometer and software (CSMi, Stoughton, MA, USA). The throw that resulted in the highest velocity (centimeter·sec −1 ) was used for analysis. The bench throw test from our laboratory ( n = 10) has been shown to be highly reliable (ICC = 0.924) with no significant mean differences (mean difference = −4.0 cm·sec −1 ; 95% CI = −10.1 to 2.14 cm·sec −1 ; p > 0.05) between test-retest values.

Cycling Protocol

The subjects performed a CP 3min maximal effort protocol on mechanically braked cycle ergometer (model 894E; Monark HealthCare International, Langly, WA, USA ) with the resistance set at 4.5% of body mass (0.045 × body mass in kilograms) ( 6,10 ). Before the test, the seat height was adjusted so that the subject's legs were near full extension at the bottom of the pedal revolution. Toe cages were used to maintain pedal contact throughout the test. The subjects completed a 5-minute warm-up at 50 W at their preferred cadence (70–80 rev·min −1 ) followed by a 5-minute rest. The test began with unloaded cycling at the preferred cadence followed by 3 minutes of an all-out effort. The subjects were instructed to increase the pedaling cadence to 110 rev·min −1 in the last 5 seconds of the unloaded phase and then maintain the cadence as high as possible for 3 minutes. The cycle ergometer protocol was performed twice during each experimental visit, 30 minutes after ingestion of the SUP or PL (prefatigue) and 15 minutes after the bench throw test (postfatigue) ( Figure 1 ). The CP (expressed in Watts [W]) was defined as the mean power output over the final 30 seconds of the test, and the AWC (expressed in kilojoules [kJ]) was calculated using the equation, AWC = 150 seconds ( P 150 —CP), where P 150 equals the mean power output for the first 150 seconds ( 10 ). The power outputs were recorded using the Monark Anaerobic Test software (Monark Exercise AB, Vansbro, Sweden). The test-retest reliability for the CP and AWC parameters from our laboratory ( n = 13) indicated the ICC values were R = 0.91 and R = 0.79, respectively, with no significant mean differences between test and retest (CP mean difference = −0.23 W; 95% CI = −13.0 to 12.6 W; p > 0.05; AWC mean difference = 0.65 J; 95% CI = −0.74 to 2.03 J).

Resistance Exercise Protocol

After the rest period, the subjects completed a resistance exercise protocol consisting of 4 lower-body exercises (barbell back squat, deadlift, front squat, and reverse lunge) superset with 4 upper-body exercises (flat barbell bench press, bent-over row, incline press, and shoulder press). A description of the supersets and protocol are presented in Figure 2 . Four sets at 75% of 1RM of each exercise were completed. Each set was performed for 10 repetitions or to volitional exhaustion. Volitional exhaustion was defined as the inability of the subject to complete a repetition through the full range of motion. Completing a repetition through 50% of the range of motion was counted as a half repetition. Three minutes of rest was provided between 1 set of an exercise and the start of the next set of that same exercise. One minute was provided between the lower-body and upper-body exercise. Water was provided ad libitum during visit 4, and the total volume consumed was recorded. The subject was asked to consume the same volume of water during visit 5. The volume of exercise was calculated for the total body (all 8 exercises listed in Figure 2A ), lower body (barbell back squat, deadlift, front squat, and reverse lunge), and upper body (flat barbell bench press, bent-over row, incline press, and shoulder press), as the product of the total number of repetitions completed and the weight lifted.

Supplementation

The subjects were randomly assigned to ingest either the SUP or PL during visit 4 and ingested the crossover treatment for visit 5. The subjects consumed 1 scoop (1 serving = 20.9 g) of either the SUP or PL powder mixed with approximately 12 oz. of water. The SUP (MusclePharm, Inc., Denver, CO, USA) contained citrulline-malate (6 g), leucine (4 g), aspartic acid (3 g), creatine hydrochloride (2 g), beta-alanine (1.6 g), tyrosine (1.2 g), and caffeine anhydrous (350 mg). A complete list of the ingredients and the relative dose of each ingredient is provided in Table 1 . The PL was flavored maltodextrin, similar in color and flavor to the SUP formulation. An investigator, who was not involved in the data collection, prepared and administered both the SUP and PL beverages for all subjects, providing double blinding of both the subjects and data collection personnel.

Dietary Analyses

The subjects recorded all food and beverages consumed the day before, and the day of, the first experimental trial (visit 4). The subjects were provided a copy of the 2-day food logs and asked to consume a similar diet the day before, and the day of, the second experimental visit (visit 5). The total energy and macronutrient intake were analyzed ( www.supertracker.usda.gov ).

Statistical Analyses

Mean differences in total-, lower-, and upper-body volume of resistance exercise for the SUP and PL were examined with separate, paired samples t -tests. In addition, mean differences in total volume between the SUP and PL were examined for each exercise (back squat, deadlift, front squat, reverse lunge, flat bench press, incline press, bent-over row, and standing overhead press) using separate, paired samples t -tests. The VJ height, bench throw velocity, and isokinetic leg extension and flexion peak torque were analyzed with separate, 1-way repeated-measures analyses of variance (ANOVAs) and least significant different paired samples t -tests. The HR and systolic and diastolic blood pressure values were examined with separate 2 (time [15 minutes after arrival and 25 minutes after ingestion]) × 2 (condition [SUP, PL]) repeated-measures ANOVAs and follow-up pairwise comparisons. The CP and AWC values were analyzed with separate 2 (time [prefatigue, postfatigue]) × 2 (condition [SUP, PL]) repeated-measures ANOVAs and follow-up pairwise comparisons. In addition, the total caloric (kilocalories) and macronutrient (grams of carbohydrate, protein, and fat) intake were analyzed with separate 2 (time [24 hours before testing, day of testing]) × 2 (condition [SUP, PL]) repeated-measures ANOVAs. An alpha level of p ≤ 0.05 was considered statistically significant for all analyses. All statistical analyses were performed with Statistical Package for the Social Sciences software (v.23.0.; IBM SPSS, Inc., Chicago, IL, USA).

The descriptive characteristics of the subjects are presented in Table 2 . The HR and blood pressure analyses revealed no time × condition interactions and no main effects for time or condition for HR and systolic blood pressure. However, there was a main effect for time for diastolic blood pressure ( F = 8.99; p = 0.012, pη 2 = 0.45), which indicated an increase from 15 minutes after arrival (72 ± 8 mm Hg) and 25 minutes (79 ± 4 mm Hg) after ingestion of the PL or SUP but no main effect for condition ( Table 3 ). The results of the statistical analyses for volume of exercise indicated that the total-body (SUP = 14,908 ± 3,163 kg; PL = 13,668 ± 2,731 kg) and lower-body (SUP = 8,507 ± 2,006 kg; PL = 7,493 ± 1,552 kg) volume were significantly greater (total body: t = 3.594, p = 0.004; lower body: t = 3.105, p = 0.010) for the SUP than for the PL ( Figure 3 ). In addition, the SUP resulted in a greater total volume of exercise for 9 of the 12 subjects compared with the PL ( Figure 4 ). There was, however, no difference ( t = 1.090; p = 0.30) between the SUP (6,401 ± 1,565 kg) and PL (6,175 ± 1,565 kg) for upper-body volume of exercise ( Figure 3 ). The volume of exercise for the back squat was greater for the SUP (2,649 ± 685 kg) than for the PL (2,286 ± 693 kg), but there were no differences between SUP and PL for any of the other exercises (deadlift, front squat, reverse lunge, flat bench press, incline press, bent-over row, and standing overhead press) ( Figures 5 and 6 ).

The results of the statistical analyses for the power and strength performance parameters are provided in Table 4 . The results of the 1-way repeated-measures ANOVA indicated significant differences among the means for the VJ height ( F = 10.57; p = 0.001; pη 2 = 0.49), isokinetic leg extension peak torque ( F = 3.76; p = 0.04; pη 2 = 0.26), and bench throw velocity ( F = 3.37; p = 0.05; pη 2 = 0.24). The follow-up pairwise comparisons indicated that there were significant decreases from baseline in the VJ height and isokinetic leg extension peak torque for the SUP and PL, but there were no significant differences between conditions. In addition, the bench throw velocity decreased significantly from baseline for the PL but not for the SUP. There were, however, no significant differences among the 3 time points (baseline, PL, SUP) for the isokinetic leg flexion peak torque values ( F = 2.16; p = 0.14; pη 2 = 0.16).

The results of the 2 × 2 repeated-measures ANOVA for CP indicated no time × condition interaction ( F = 2.35; p = 0.15; pη 2 = 0.18), and there were no main effects for time ( F = 4.52; p = 0.06; pη 2 = 0.29) or condition ( F = 2.97; p = 0.11; pη 2 = 0.21) ( Table 5 ). The results of the 2 × 2 repeated-measures ANOVA for AWC indicated no time × condition interaction ( F = 2.84; p = 0.12; pη 2 = 0.21) and no main effects for condition ( F = 0.19; p = 0.68; pη 2 = 0.02); however, there was a main effect for time ( F = 9.04; p = 0.01; pη 2 = 0.45). The follow-up pairwise comparison indicated that AWC significantly decreased from prefatigue (15.6 ± 2.8 J) to postfatigue (13.9 ± 3.5 J) ( Table 5 ). There were no significant differences in total caloric intake or macronutrients consumed 24 hours before, and the day of, the experimental protocol for the SUP and PL conditions.

The primary purpose of this study was to examine the effects of a multi-ingredient preworkout supplement on the total volume of resistance exercise. The current findings indicated a 9% increase in the total-body volume of exercise and a 14% increase in lower-body volume of exercise for the SUP compared with the PL, with no effect on exercise volume for the upper body between the SUP and PL. The resistance training protocol in this study included 8 separate exercises, divided into 4 supersets of a lower-body and an upper-body exercise. When each exercise was examined separately, the volume was only greater for the SUP than for the PL for the back squat (∼16%) ( Figures 5 and 6 ). The back squat was superset with the bench press and was the first exercise performed in the resistance training protocol, 45 minutes after supplementation. A number of recent studies have examined the effects of preworkout supplements containing similar ingredients to the SUP in this study ( 22,23,27,31 ). When performed in isolation, an increase in lower-body ( 22,23 ) and upper-body ( 27 ) exercise volume has previously been reported after acute ingestion of a multi-ingredient preworkout supplement. Preworkout supplementation has also been reported to have no effect on exercise volume for the bench press or leg press preformed at 70% of the 1RM to failure ( 31 ). This study was unique in the inclusion of 4 supersets of multiple resistance exercises (4 lower body and 4 upper body), a common practice by individuals who perform whole-body resistance training programs. The increases in the volume of exercise after multi-ingredient preworkout supplementation were likely related to the acute effects caffeine and its role as an adenosine receptor antagonist ( 14,15,18,40 ). Caffeine has been shown to decrease the ratings for perceived exertion ( 14 ) and increase subjective ratings of task motivation ( 34 ), focus ( 23 ), and energy ( 23 ). The caffeine contained in the SUP in this study resulted in a mean relative dose of 4.2 ± 0.6 mg·kg −1 , which was higher than the relative dose (∼3.5 mg·kg −1 ) in preworkout supplements previously reported ( 22,23,27,31 ) to be effective for improving exercise volume or cognitive performance. The increased exercise volume observed in the present study may also be attributed to the acute ingestion of 6 g of citrulline-malate in SUP, which can increase the vasodilatory response ( 44,45 ) and improve muscular efficiency ( 17 ), whereas ingestion of amino acids, leucine and tyrosin, and huperzine A have enhanced cognitive function and focus during exercise ( 26,48,51 ). It is possible that these ingredients (caffeine, citrulline-malate, amino acids, and huperzine A) worked synergistically to increase exercise volume by increasing blood flow and the removal of metabolic by-products and improving focus and decreasing perceptions of fatigue. Thus, the current findings suggested that the multi-ingredient preworkout was most effective for increasing exercise volume within the first 45 minutes of supplementation and for exercise involving large muscle groups of the lower body.

A secondary purpose of this study was to examine the effect of the SUP on strength and power performance following a high volume resistance training session. In contrast to previous studies ( 5,36,46 ) that have shown acute increases in performance of lower-body parameters (i.e., muscular strength and power) after preworkout or caffeine supplementation, there were similar decreases in the lower-body power (VJ), quadriceps strength (isokinetic leg extension peak torque), and anaerobic cycle ergometry performance (AWC) for the SUP and PL after the resistance exercise. These findings, however, indicated that the increased lower-body volume of exercise performed for the SUP did not result in greater lower-body power and quadriceps strength performance decrements compared with the PL. Thus, although the SUP did not improve subsequent lower-body strength and power performance after an exhaustive resistance exercise protocol, it is possible the multi-ingredient preworkout supplement examined in this study could increase lower-body volume of exercise without altering subsequent performance to a greater extent than a lower volume exercise program. In addition, the upper-body power (i.e., bench throw test) was maintained for the SUP but not for the PL. These findings suggested that the upper body did not demonstrate the same level of fatigue as the lower body for the SUP. In addition, there was no decrease in leg flexor strength for either the SUP or PL, which indicated that the protocol was not fatiguing for the hamstrings muscle group. One limitation of the present study, however, was the ∼20-minute delay between the completion of the final resistance exercise and the measurement of lower-body strength. This delay may have allowed some recovery of muscular strength. Taken together, these findings suggested that the current protocol demonstrated the greatest fatigue and potential effect for the SUP for the quadriceps muscle group.

In summary, the preworkout supplement examined in this study resulted in a 9% increase in the total-body volume of exercise and a 14% increase in lower-body volume of exercise for the SUP compared with the PL, with no effect on exercise volume for the upper body between the SUP and PL. These findings suggested that the SUP was most effective for increasing exercise volume within the first 45 minutes of supplementation and for exercise involving large muscle groups of the lower body. The increased lower-body volume for the SUP did not result in greater lower-body strength and power performance decrements after exhaustive exercise, when compared with the PL. In addition, the upper-body power was maintained in the SUP after the exhaustive exercise. Taken together, these findings suggested the potential for the SUP to increase resistance exercise volume, without greater impairment in performance, when compared with a PL.

Practical Applications

The multi-ingredient preworkout supplement examined in this study was effective for increasing the total volume of resistance exercise, primarily related to increases in lower-body volume of exercise. Although volume is an important aspect of resistance training adaptations ( 38 ), the 9–14% differences in exercise volume between SUP and PL may not be large enough to elicit greater adaptions for the SUP than for the PL. It is possible that the acute increases in exercise volume for the SUP observed in this study may translate into greater strength and performance adaptations if the effects of the supplement are maintained with a chronic dosing strategy (i.e., before each training session for >4 weeks). Future studies should examine the effects of the preworkout supplement used in this study on resistance exercise volume and performance adaptations with chronic (i.e., > 4 weeks) supplementation to determine if increases in exercise volume are maintained and translate into greater adaptations. In addition, there is some evidence ( 30 ) that 4 and 8 weeks of preworkout supplementation before resistance training may improve 1RM strength and cognitive function to a greater degree, compared with a placebo. It was suggested ( 30 ) that these adaptations were the result of longer-term supplementation of ingredients such as beta-alanine and creatine nitrate contained in the preworkout supplement. Many of the ingredients in the SUP do not have acute effects, but they may have implication for strength and power performance parameters after longer-term dosing strategies (>4 weeks). For example, longer-term (∼4 weeks) dosing strategies for creatine and beta-alanine have been shown to result in increases in energy stores (i.e., phosphocreatine) ( 24 ) and intramuscular buffering capacity (i.e., increased levels of carnosine) ( 12,20,21 ), respectively. These adaptations have been shown to increase strength and power ( 8,9,11,25 ) and augment the effects of caffeine by delaying neuromuscular fatigue ( 12,41,42 ), allowing a greater number of repetitions to be completed via mechanisms other than adenosine receptor antagonism. The supplement in this study, however, contained only 2 g of creatine hydrochloride, which is reported to be less effective at increasing intramuscular phosphocreatine levels than creatine monohydrate, and the dosage was lower than typically recommended (5 g·d −1 for 30 days or 20 g·d −1 for 5–7 days) ( 7 ). In addition, the amount of beta-alanine in the SUP in this study was less than previously shown ( 47 ) to be effective at increasing intramuscular carnosine levels (3–6 g·d −1 for 2–4 weeks). Thus, it is unclear if the amount of creatine and beta-alanine contained in this study would be sufficient to increase intramuscular phosphocreatine and carnosine levels. In addition, future studies should measure intramuscular levels of phosphocreatine and carnosine after chronic supplementation to determine if the lower doses of creatine and beta-alanine (2 g and 1.6 g, respectively) result in increased energy stores and intramuscular buffering capacity, which have the potential to effect strength and performance adaptations.

Acknowledgments

The supplement examined in this study was provided by MusclePharm, Inc. (MusclePharm, Denver, CO), and the placebo was provided by True Nutrition (True Nutrition, Vista, CA).

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ergogenic aid; training volume; caffeine

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Pre- versus post-exercise protein intake has similar effects on muscular adaptations

Affiliations.

1 Department of Health Sciences, Herbert H. Lehman College, City University of New York , Bronx , NY , United States.
2 Department of Nutrition, California State University , Northridge , CA , United States.
3 Graduate School and Research, University of Mary Hardin Baylor , Belton , TX , United States.
4 Weightology , Issaquah , WA , United States.
PMID: 28070459
PMCID: PMC5214805
DOI: 10.7717/peerj.2825
Correction: Pre- versus post-exercise protein intake has similar effects on muscular adaptations. Schoenfeld BJ, Aragon AA, Wilborn C, Urbina SL, Hayward SE, Krieger J. Schoenfeld BJ, et al. PeerJ. 2017 Aug 1;5:e2825/correction-1. doi: 10.7717/peerj.2825/correction-1. eCollection 2017. PeerJ. 2017. PMID: 28785512 Free PMC article.

The purpose of this study was to test the anabolic window theory by investigating muscle strength, hypertrophy, and body composition changes in response to an equal dose of protein consumed either immediately pre- versus post-resistance training (RT) in trained men. Subjects were 21 resistance-trained men (>1 year RT experience) recruited from a university population. After baseline testing, participants were randomly assigned to 1 of 2 experimental groups: a group that consumed a supplement containing 25 g protein and 1 g carbohydrate immediately prior to exercise (PRE-SUPP) ( n = 9) or a group that consumed the same supplement immediately post-exercise (POST-SUPP) ( n = 12). The RT protocol consisted of three weekly sessions performed on non-consecutive days for 10 weeks. A total-body routine was employed with three sets of 8-12 repetitions for each exercise. Results showed that pre- and post-workout protein consumption had similar effects on all measures studied ( p > 0.05). These findings refute the contention of a narrow post-exercise anabolic window to maximize the muscular response and instead lends support to the theory that the interval for protein intake may be as wide as several hours or perhaps more after a training bout depending on when the pre-workout meal was consumed.

Keywords: Anabolic window; Nutrient timing; Protein supplementation; Protein timing; Resistance training.

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Conflict of interest statement

James Krieger is an employee of Weightology.

Figure 1. Self-reported kcal intake in pre-exercise…

Figure 1. Self-reported kcal intake in pre-exercise supplementation (PRE-SUPP) and post-exercise supplementation (POST-SUPP) groups.

Figure 2. Self-reported macronutrient intake in pre-exercise…

Figure 2. Self-reported macronutrient intake in pre-exercise supplementation (PRE-SUPP) and post-exercise supplementation (POST-SUPP) groups.

Figure 3. Biceps thickness.

Individual changes in…

Individual changes in biceps thickness for PRE and POST. Values in…

Figure 4. Medial quadriceps thickness.

Individual changes…

Individual changes in medial quadriceps thickness for PRE and POST.…

Figure 5. Lateral quadriceps thickness.

Individual changes in lateral quadriceps thickness for PRE and POST.…

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Research article
Open access
Published: 15 February 2010

The effects of a pre-workout supplement containing caffeine, creatine, and amino acids during three weeks of high-intensity exercise on aerobic and anaerobic performance

Abbie E Smith 1 ,
David H Fukuda 1 ,
Kristina L Kendall 1 &
Jeffrey R Stout 1

Journal of the International Society of Sports Nutrition volume 7 , Article number: 10 ( 2010 ) Cite this article

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A randomized, single-blinded, placebo-controlled, parallel design study was used to examine the effects of a pre-workout supplement combined with three weeks of high-intensity interval training (HIIT) on aerobic and anaerobic running performance, training volume, and body composition.

Twenty-four moderately-trained recreational athletes (mean ± SD age = 21.1 ± 1.9 yrs; stature = 172.2 ± 8.7 cm; body mass = 66.2 ± 11.8 kg, VO 2 max = 3.21 ± 0.85 l·min -1 , percent body fat = 19.0 ± 7.1%) were assigned to either the active supplement (GT, n = 13) or placebo (PL, n = 11) group. The active supplement (Game Time ® , Corr-Jensen Laboratories Inc., Aurora, CO) was 18 g of powder, 40 kcals, and consisted of a proprietary blend including whey protein, cordyceps sinensis, creatine, citrulline, ginseng, and caffeine. The PL was also 18 g of powder, 40 kcals, and consisted of only maltodextrin, natural and artificial flavors and colors. Thirty minutes prior to all testing and training sessions, participants consumed their respective supplements mixed with 8-10 oz of water. Both groups participated in a three-week HIIT program three days per week, and testing was conducted before and after the training. Cardiovascular fitness (VO 2 max) was assessed using open circuit spirometry (Parvo-Medics TrueOne ® 2400 Metabolic Measurement System, Sandy, UT) during graded exercise tests on a treadmill (Woodway, Pro Series, Waukesha, WI). Also, four high-speed runs to exhaustion were conducted at 110, 105, 100, and 90% of the treadmill velocity recorded during VO 2 max, and the distances achieved were plotted over the times-to-exhaustion. Linear regression was used to determine the slopes (critical velocity, CV) and y-intercepts (anaerobic running capacity, ARC) of these relationships to assess aerobic and anaerobic performances, respectively. Training volumes were tracked by summing the distances achieved during each training session for each subject. Percent body fat (%BF) and lean body mass (LBM) were assessed with air-displacement plethysmography (BOD POD ® , Life Measurement, Inc., Concord, CA).

Both GT and PL groups demonstrated a significant (p = 0.028) increase in VO 2 max from pre- to post-training resulting in a 10.3% and 2.9% improvement, respectively. CV increased (p = 0.036) for the GT group by 2.9%, while the PL group did not change (p = 0.256; 1.7% increase). ARC increased for the PL group by 22.9% and for the GT group by 10.6%. Training volume was 11.6% higher for the GT versus PL group (p = 0.041). %BF decreased from 19.3% to 16.1% for the GT group and decreased from 18.0% to 16.8% in the PL group (p = 0.178). LBM increased from 54.2 kg to 55.4 kg (p = 0.035) for the GT group and decreased from 52.9 kg to 52.4 kg in the PL group (p = 0.694).

These results demonstrated improvements in VO 2 max, CV, and LBM when GT is combined with HIIT. Three weeks of HIIT alone also augmented anaerobic running performance, VO 2 max and body composition.

The study of nutrient timing has become an important and popular aspect of sports nutrition, exercise training, performance, and recovery [ 1 ]. The idea of nutrient timing was initiated by post-workout supplementation and has further spread to research on the timing of pre-exercise nutritional strategies [ 1 ]. Traditional nutritional interventions prior to training have focused on carbohydrate administration, while more current literature has supported a combination of amino acids, protein, creatine and caffeine as effective supplements for improving performance [ 2 – 6 ]. While the ergogenic effects from these individual ingredients are generally supported, the practical importance of product-specific research has become an area of increasing demand. Paradoxically, product-specific research often tests a blend of ingredients that provides a direct application of the research findings for consumers, but is unable to pinpoint the effects of individual ingredients. Furthermore, integrating nutritional supplements into research designs that use realistic exercise training protocols allows for impactful sport-specific practical applications. Since many team sports, such as football, basketball, hockey and soccer utilize repeated bouts of short sprints separated by active recovery periods, interval running may be applicable to many sports and sensitive to nutritional supplements that are designed to delay high-intensity, exercise-induced fatigue. In fact, evidence exists to support the use of high-intensity interval training (HIIT) strategies to improve performance [ 7 ], however, only a few studies have examined HIIT combined with nutritional supplementation [ 8 – 13 ].

The physiological demand of HIIT elicits rapid metabolic and cardiovascular adaptations, including increased exercise performance, muscle buffering capacity, aerobic capacity (VO 2 peak) and fat oxidation [ 8 , 14 – 17 ]. Furthermore, HIIT results in diminished stores of adenosine tri-phosphate (ATP), phosphocreatine (PCr) and glycogenic substrates as well as the accumulation of metabolites adenosine di-phosphate (ADP), inorganic phosphate (P i ), and hydrogen ions (H + ) [ 18 ]. Therefore, HIIT may cause several physiological adaptations within a relatively brief training period, making it a practical time-efficient tool to examine training- and supplement-induced changes in performance. Although the work to rest ratio of HIIT protocols vary, the current study and others utilizing a 2:1 work:rest strategy have been effective for improving VO 2 max, time to exhaustion [ 9 , 11 , 19 ], muscle buffering capacity, and lactate threshold [ 8 ]. Additionally, the same HIIT strategy that is used in the present study has been employed to evaluate the effects of creatine [ 9 , 10 ], beta-alanine [ 11 ], and sodium bicarbonate [ 8 ] supplementation on measures of performance. Therefore, it is possible that the training outcomes measured after a period of HIIT may be sensitive to nutritional supplements that are designed to prolong the acute factors associated with fatigue. More so, the active ingredients in the current pre-workout supplement have potential to improve performance. Caffeine or caffeine containing supplements acting as a central nervous system stimulant [ 20 ] have been suggested to augment catecholamine concentrations promoting fat utilization sparing intramuscular glycogen resulting in an improvement in performance [ 21 , 22 ]. PCr, a major component of biological buffering has been reported to be significantly increased with Cr supplementation [ 23 , 24 ]. Increasing total Cr stores can result in greater pre-exercise PCr availability, improved muscle buffer capacity and an acceleration of PCr resynthesis during recovery [ 25 , 26 ]. Additionally, branched chain amino acids (BCAA's; leucine, isoleucine, and valine) are suggested to be the primary amino acids oxidized during intense exercise [ 27 ]. When supplementing with BCAAs prior to exercise, research suggests an improvement in protein synthesis, reduction in protein degradation, ultimately improving recovery [ 27 – 29 ].

Interval training is generally used to elicit both anaerobic and aerobic training adaptations due to the large physiological spectrum of demands [ 30 ]. The critical power test (CP), originally proposed by Monod and Scherrer [ 31 ], characterizes both anaerobic work capacity (AWC) and aerobic parameters (CP). The CP test has been shown to be reliable in measuring aerobic and anaerobic parameters as well as changes with high-intensity training [ 10 , 32 – 34 ]. Hughson et al. [ 35 ] applied the concept of CP to running, which characterized the term critical velocity (CV) as the running-based analogue of CP. Thus, CV is defined as the maximal running velocity that can be maintained for an extended period of time using only aerobic energy stores. In contrast, the anaerobic running capacity (ARC) is the distance that can be run at a maximal velocity using only anaerobic energy sources. As described by Housh et al. [ 36 ], the CV test involves a series of runs to exhaustion at various supramaximal running velocities to determine the relationship between time to exhaustion and velocity. The hyperbolic relationship between velocity and time to exhaustion can then be used to calculate total distance (total distance = velocity × time). Plotting total distance as a function of time for each velocity results in a mathematical model to quantify CV (slope of the line) and ARC (y-intercept), which defines the indirect method of evaluating both aerobic and anaerobic capabilities, respectively [ 35 , 37 ].

Recent evidence has shown that interval training with two-minute work bouts, similar to the HIIT in the present study, exerts a significant influence on aerobic abilities (CV), rather than the anaerobic improvements (AWC) demonstrated by the CP test [ 32 , 38 ]. Training at intensities of 100% and 105% of VO 2 peak on a cycle ergometer elicited a 15% [ 32 ] and 13% [ 38 ] increase in aerobic capacity, respectively. Training at higher intensities for shorter durations (i.e. 60 sec) may be more advantageous for anaerobic improvements [ 33 ], although this hypothesis has not been evaluated using the CV test. Likewise, the efficacy of single-ingredient supplements has been assessed using the CP model. For example, creatine supplementation has been shown to improve AWC, which is primarily limited by the amount of energy available from stored ATP and phosphocreatine (PCr) [ 39 ]. However, less conclusive evidence is available on the effects of creatine on CP [ 10 , 40 , 41 ]. It is possible that combining the use of a multi-ingredient, pre-workout supplement with HIIT may further delineate the anaerobic and aerobic demands of training as measured by CV and ARC using the running-based CV test. Therefore, the purpose of the present study was to examine the effects of a pre-workout supplement combined with three weeks of HIIT on aerobic and anaerobic running performance, training volume, and body composition. To date, no one has examined the combined effects of high-intensity interval running with a pre-workout nutritional supplement.

Twenty-four moderately-trained men (mean ± SD age = 20.8 ± 2.0 yrs; stature = 175.7 ± 8.3 cm; body mass = 70.9 ± 13.5 kg, VO 2 max = 3.71 ± 0.73 l·min -1 , percent body fat = 14.0 ± 4.6%) and women (mean ± SD age = 21.5 ± 1.8 yrs; stature = 168.0 ± 7.5 cm; body mass = 60.7 ± 6.5 kg, VO 2 max = 2.57 ± 0.48 l·min -1 , percent body fat = 24.9 ± 4.4%) volunteered for this study. Table 1 shows the groups-specific demographics. All participants completed a health history questionnaire and signed a written informed consent prior to testing to screen for training habits and prior caffeine and supplement use. All procedures were approved by the University's Institutional Review Board for the protection of human subjects.

Research Design

This study used a randomized, single-blinded, placebo-controlled parallel design. Each subject visited the laboratory on 18 separate occasions, where visits 1-3 were familiarization sessions, visits 4-6 and 16-18 were baseline and post-testing sessions, respectively. All testing sessions were separated by 24-48 hours. Visits 7-15 took place over a three-week period, with three days of training per week. Figure 1 illustrates the timeline for testing and training.

Study Timeline .

All participants completed a familiarization week of testing, including a maximal graded exercise test (GXT) for the determination of aerobic capacity (VO 2 max) followed by two separate days of runs to exhaustion to determine CV and ARC. These familiarization sessions were implemented to minimize any potential learning effects. After familiarization, participants were randomly assigned to a supplementation group: (a) an active pre-workout supplement (Game Time ® , GT, n = 13) or (b) placebo (PL, n = 11). The same GXT, CV, and ARC testing that took place during the familiarization sessions were performed at baseline (pre-training) and post-training (Figure 1 ).

All participants were instructed to maintain their current dietary habits throughout the duration of the study. Furthermore, participants were asked to refrain from caffeine and any vigorous activity for 24 hours prior to any testing session.

Body Composition Assessments

Air displacement plethysmography (ADP; BOD POD ® , Life was Measurement, Inc., Concord, CA) was used to estimate body volume after an eight-hour fast at baseline and post-testing. Prior to each test, the BOD POD was calibrated according to the manufacturer's instructions with the chamber empty and using a cylinder of known volume (49.55 L). The participant, wearing only Spandex shorts or tight-fitting bathing suit and swimming cap, entered and sat in the fiberglass chamber. The BOD POD was sealed and the participant breathed normally for 20 seconds while BV was measured. The subjects' weight and body volume were measured and used to determine percent body fat (%BF), fat mass (FM, kg), and lean body mass (LBM, kg) using the revised formula of Brozek et al.[ 42 ]. Previous test-retest reliability data for ADP from our laboratory indicated that, for 14 young adults (24 ± 3 yrs) measured on separate days, the ICC was 0.99 with a SEM of 0.47% fat.

Supplementation

The caloric values and nutrient compositions of the GT and PL supplements are listed in Table 2 . On each of the testing and training days the participants ingested the GT or PL in the laboratory 30 minutes prior to testing on an empty stomach (subjects were instructed not to eat within 4 hours prior to their laboratory visits). Since the GT and PL supplements were in powder form, the investigators mixed the contents of the GT or PL packets with 8-12 oz of cold tap water in a white cup prior to the participant's arrival. After the mixture was consumed, a stopwatch was used to precisely allow 30 minutes after consumption prior to the initiation of the testing or training. The participants did not consume the GT or PL drinks on the rest days; therefore, supplementation only occurred prior to the in-laboratory testing or training visits.

Determination of VO 2 max

All participants performed a GXT to volitional exhaustion on a treadmill (Woodway, Pro Series, Waukesha, WI) to determine VO 2 max. Based on the protocol of Peake et al.[ 43 ], the initial GXT velocity was set at 10 km/h at a 0% grade and increased 2 km·h -1 every two minutes up to 16 km·h -1 , followed by 1 km·h -1 increments per minute up to 18 km·h -1 . The gradient was then increased by 2% each minute until VO 2 max was achieved. Open-circuit spirometry was used to estimate VO 2 max (l·min -1 ) with a metabolic cart (True One 2400 ® Metabolic Measurement System, Parvo-Medics Inc., Sandy, UT) by sampling and analyzing the breath-by-breath expired gases. The metabolic cart software calculated VO 2 and determined the VO 2 max value for each GXT.

Critical Velocity

To determine CV and ARC, the linear Total Distance (TD) model described and evaluated by Florence and Weir et al [ 44 ] was used:

Where the total distance achieved during each run to exhaustion (TD; y axis) was plotted over the time-to-exhaustion (t; x axis), and linear regression was used to calculate the y-intercept (ARC) and the slope (CV).

Four treadmill runs to exhaustion were performed to establish the distance-time relationships for the TD model for each subject. Each participant ran at 90%, 100%, 105%, and 110% of the treadmill velocity (km·h -1 ) that corresponded with their VO 2 max score. The time-to-exhaustion (s) and distance achieved (km) was recorded for each run.

High-intensity interval training

After baseline testing, participants completed three weeks of high-intensity interval training (HIIT) for three days per week using a fractal periodization scheme to adjust the training velocities. Each training session consisted of five sets of two-minute running bouts with one minute of rest between each bout. The total running duration (s) and velocity (km·h -1 ) during each training session was recorded and used to calculate total training volume (km). Training was performed on the same treadmill used for the GXTs (Woodway, Pro Series, Waukesha, WI). Figure 1 shows the relative treadmill velocities used during the training period. The training intensity began at 90% of the velocity achieved during the baseline VO 2 max test and progressed in an undulating manner, reaching a maximum of 110% by the end of the three-week training period.

Statistical Analyses

Five separate two-way, mixed factorial ANOVA models (2 × 2; time [pre- vs. post-training] × group [GT vs. PL]) were used to analyze the raw CV, ARC, VO 2 max, %BF, FM, and LBM data. For significant interactions, independent- or dependent-samples t-tests were used as post-hoc tests. For training volume, the sum of training distances for all nine training visits was calculated for each subject, and an independent-sample t-test was used to examine the means of the total training volume values (km). In addition, independent-sample t-tests were used to determine group mean differences (GT vs. PL) during the pre-training testing sessions.

Except for training volume, percent change scores were calculated for each participant from pre- to post-training for CV, ARC, VO 2 max, %BF, FM, and LBM. These percent changes scores were averaged separately for the GT and PL groups and 95% confidence intervals were constructed around the mean percent change scores (Figure 2 ). When the 95% confidence interval includes zero, the mean percent change score is no different from zero, which can be interpreted as no statistical change (p > 0.05). However, if the 95% confidence interval does not include zero, the mean percent change for that variable can be considered statistically significant (p ≤ 0.05). In addition, individual response graphs were created and plotted to illustrate how each subject responded from pre- to post-training (Figure 3 ).

Mean percent change scores ± 95% confidence intervals for (A) critical velocity, (B) anaerobic running capacity, (C) aerobic capacity, (D) percent body fat, (E) lean body mass, and (F) fat mass . Black circles = GT group; White circles = PL group. * indicates a significant difference when 0 is outside of the 95% confidence interval.

Percent change scores from pre- to post-training for each individual participant for (A) critical velocity, (B) anaerobic running capacity, (C) aerobic capacity, (D) percent body fat, (E) fat mass and (F) lean body mass . Black circles = GT group; White circles = PL group.

A type I error rate that was less than or equal to 5% was considered statistically significant for all analyses. ANOVA models and t-tests were computed using SPSS (Version 14.0, SPSS Inc., Chicago, Ill), and the 95% confidence intervals and individual response graphs were calculated and created in Microsoft Excel (Version 2007, Microsoft Corporation; The Microsoft Network, LLC, Richmond, WA).

Table 3 contains the means and standard errors for each of the dependent variables (CV, ARC, VO 2 max, %BF, FM, and LBM). In addition, there were no significant differences (p > 0.05) between the GT and PL groups at the pre-training testing session.

ANOVA Models

For CV, there was no time × group interaction (p = 0.256) and no main effect for time (p = 0.507), but there was a main effect for group (p = 0.036). CV for the GT group was greater than the PL group at the pre- and post-training testing sessions.

For ARC, there was no time × group interaction (p = 0.183) and no main effects for time (p = 0.093) or group (p = 0.053).

For VO 2 max, there was no time × group interaction (p = 0.391) and no main effect for group (p = 0.258), but there was a main effect for time (p = 0.028). VO 2 max increased from pre- to post-training for the GT and PL groups.

For %BF, there was no time × group interaction (p = 0.481) and no main effects for time (p = 0.178) or group (p = 0.864).

For FM, there was no time × group interaction (p = 0.335) and no main effects for time (p = 0.305) or group (p = 0.583).

For LBM, there was no time × group interaction (p = 0.386) and no main effects for time (p = 0.694) or group (p = 0.615).

Total training volume for the GT group was greater than (p = 0.041) the PL group. (Figure 4 ).

Training volume for the GT and PL groups across the nine day training session .

95% Confidence Intervals

CV increased from pre- to post-training for the GT group (2.9% increase), but did not change for the PL group (1.7% increase) (Figure 2-A ). However, Figure 2-B shows that ARC did not change from pre- to post-training for the GT group (10.6% increase), but did increase for the PL group (22.9% increase). VO 2 max did not change from pre- to post-training for either the GT (10.3% increase) or PL (3.3% increase) groups (Figure 2-C ). For body composition, %BF did not change for either the GT (6.7% decrease) or PL (9.4% decrease) groups (Figure 2-D ), LBM did not change for either the GT (2.8% increase) or PL (1.3% decrease) groups (Figure 2-E ), and FM did not change for either the GT (4.1% decrease) or PL (11.6% decrease) groups (Figure 2-F ) from pre- to post-training.

Individual Responses

For CV, 10 out of 13 (77%) subjects increased in the GT group, whereas only 7 of 11 (64%) increased in the PL group (Figure 3A ). Eight subjects increased in the GT (62%) and PL (73%) groups for ARC (Figure 3B ). For VO 2 max, 10 increased in the GT group (77%), and 8 increased in the PL group (73%) (Figure 3C ).

Nine subjects in the GT group (69%) and 8 subjects in the PL group (73%) decreased in %BF from pre- to post-training (Figure 3D ). Similarly, 8 subjects in both groups (62% for GT and 73% for PL) showed a decrease in FM (Figure 3E ). LBM increased for 9 subjects in the GT group (69%), while only 6 subjects increased in the PL group (55%) (Figure 3F ).

The results of the present study indicated that acute ingestion of the current pre-exercise drink (GT) containing a combination of cordyceps sinensis, caffeine, creatine (Kre-Alkalyn ® ), whey protein, branched chain amino acids, arginine AKG, citrulline AKG, rhodiola, and vitamin B6 and B12 may improve running performance over a 3-week training period. When combined with HIIT, GT ingestion improved CV, VO 2 max, lean body mass, and total training volume when compared to the PL and HIIT group. In addition, although not significant, the fact that LBM changes were positive for the GT group and negative for the PL group (Figure 2-E ) suggests that GT may aid in maintaining LBM during the course of HIIT for three weeks.

While this may be the first study to examine a pre-workout supplement in combination with HIIT, previous research has examined the efficacy of similar, separate ingredients on exercise training and performance. However, since most previous studies examine blended supplements that often include various ingredients and dose combinations, it is difficult to directly compare many previous studies. One primary ingredient in the GT supplement, caffeine, has been used as an effective ergogenic aid by acting as a stimulant, reducing feelings of fatigue, and increasing times to exhaustion [ 22 , 45 – 47 ]. Caffeine has been shown to primarily influence longer-duration endurance exercise by 20-50% [ 48 ] and resting metabolic rate [ 45 , 49 – 51 ]. The benefits of caffeine supplementation for higher-intensity exercise, similar to those in the current study (90%-115% VO 2 max), are less conclusive [ 52 , 53 ]. For example, assessing anaerobic power using a Wingate test after a range of caffeine doses (3.2-7 mg/lb) resulted in no improvements [ 52 , 53 ] while Anselme et al. demonstrated a 7% increase in anaerobic power after 6 mg/kg of caffeine consumption [ 54 ]. In addition, a recent report by Wiles et al. demonstrated improvements in performance during a bout of short-duration, high-intensity cycling and mean power output following 5 mg/kg of caffeine [ 55 ]. The results of the present study indicated that the pre-exercise GT drink improved aerobic performance (CV) and training volume, but did not alter the ARC. It is possible that the caffeine in GT may be partly responsible for the increases in CV and training volume. However, the independent effects of caffeine cannot be directly assessed in the present study.

Previous studies have suggested that the ergogenic effects of caffeine may be proportional to the amount of caffeine administered [ 56 – 58 ]. Most studies have utilized 3-9 mg/kg of caffeine when demonstrating improvements in performance [ 48 ], while one study showed that as little 2 mg/kg increased cycling performance [ 58 ]. Yet another study demonstrated that 201 mg of caffeine was not sufficient for increasing run time to exhaustion [ 59 ]. In the present study, the pre-exercise GT supplement contained only 100 mg of caffeine in one serving. Since the range of body mass values for the participants in the present study was 46.1 kg to 108.9 kg, the relative caffeine doses were 1.0 - 2.2 mg/kg, which is lower than the previously suggested ergogenic doses. Therefore, although caffeine may have contributed to improvements in aerobic performance and training volume in the present study, it is possible that there were synergistic effects from other GT ingredients.

One concern about the ergogenic doses of caffeine is that relatively high levels of urinary caffeine concentrations are banned by both the National Collegiate Athletics Association (NCAA) and the International Olympic Committee (IOC). The NCAA and IOC limits for urinary caffeine concentrations are 15 μg/ml and 12 μg/ml, respectively. In a well-controlled study [ 60 ] the average urinary concentration of caffeine was 14 μg/ml after the ingestion of 9 mg/kg. In an earlier study, Pasman et al. (1995) demonstrated that 9 and 13 mg/kg of caffeine consumption resulted in urinary caffeine concentrations that exceeded the International Olympic Committee's (IOC's) limit of 12 μg/ml in some subjects. However, 5 mg/kg of caffeine did not exceed or even approach 12 μg/ml in any subject [ 61 ]. Since the relative caffeine dose range for the GT supplement in the present study was 1.0 - 2.2 mg/kg for an absolute dose of 100 mg of caffeine per serving, it is highly unlikely that the caffeine in GT would cause urinary concentrations anywhere near the limits set forth by the NCAA or IOC. Therefore, although not tested specifically in this study, the GT supplement may be safe for consumption by NCAA and IOC athletes as it pertains to caffeine concentrations.

A large amount of literature exists demonstrating that short-term high-dose (20 g/day for 5-7 days) creatine supplementation is effective for increasing total muscle phosphocreatine stores [ 23 , 24 ] and improving maximal intermittent exercise [ 23 , 25 , 62 – 64 ] and lean body mass [ 64 – 68 ]. However, the data on short-term low-dose creatine supplementation is less supported, with a minimum of 3 g/day for at least 28 days necessary to elicit increases in muscle creatine stores [ 69 ]. The current pre-workout GT drink provided 1.5 g/day of creatine on testing and training days only for a total of 15 days, which was below the minimum recommended dose. A similar study by Thompson and colleagues used a comparable combination of training (swimming) and 2 g of creatine daily for six weeks and demonstrated no effects of the creatine supplementation or training on muscle creatine concentration, anaerobic performance, or aerobic indices [ 70 ]. Thus, although the creatine content of the GT supplement may not fully explain the improvements in CV and training volume, the combination with the other GT ingredients may have been influential for intermittent recovery between sprint bouts as well as helping to maintain LBM.

The BCAAs in GT may have also played a role in improving CV and training volume as well as maintaining LBM. BCAAs may be the primary amino acids oxidized during intense exercise [ 27 ] and have been suggested as fundamental for protein synthesis [ 27 – 29 ]. Studies have demonstrated that the ingestion of BCAA supplements prior to exercise has augmented protein synthesis and reduced protein degradation, which may ultimately enhance recovery time [ 27 , 29 ]. Furthermore, BCAAs may conceivably enhance performance in all-out running, similar to the current study by improving mental focus allowing participants to run harder and longer [ 71 , 72 ]. Again, however, the GT supplement contained approximately 1 g of BCAAs which is lower than other effective dosing protocols (7.5-12 g). There was also approximately 9 g of whey protein concentrate in the GT supplement. Although whey protein has not been directly shown to improve running performance when consumed a priori, the fact that whey protein also contains relatively high concentrations of the BCAAs may indirectly suggest that the BCAAs in combination with whey protein may influence performance by enhancing recovery between training bouts and maintaining LBM [ 73 – 76 ].

Cordyceps sinensis (or simply cordyceps ) is commonly used in traditional Chinese medicine, and it is derived from a fungus that grows on several species of caterpillars at relatively high altitudes[ 77 ]. It has been suggested that cordyceps may be an anti-oxidant during intense exercise [ 78 ] and may also improve VO 2 max [ 79 ]. In two reviews by Zhu et al. [ 77 , 80 ], it was suggested that cordyceps sinensis may act through the autonomic nervous system to improve respiration, blood flow, and tissue oxygenation. One study has demonstrated improvements in VO 2 max in sedentary men [ 79 ] with relatively high doses (4.5 g/d for 6 weeks) of cordyceps. However, with lower doses (2.5 g) similar to what is found in GT in the present study, there were no ergogenic effects of cordyceps reported in previous studies on VO 2 max [ 81 – 83 ] in healthy, active men. Thus, given the conflicting evidence, cordyceps may be another ingredient in GT that acted synergistically to improve CV and training volume in the present study.

The role that the remaining ingredients in the GT supplement (ex. Citrulline and rhodiola) may play is not completely evident. Citrulline is a non-essential amino acid that may increase lactate absorption, enhance ATP resynthesis, and delay fatigue during intense exercise [ 84 , 85 ]. While evidence is limited in humans, citrulline may have influenced ATP/PCr resynthesis during HIIT bouts thereby enhancing the training volume. Furthermore, rhodiola may act as a stimulant to optimize serotonin and dopamine levels [ 86 ]. Acute supplementation (i.e., 2 days) has been shown to increase time to exhaustion and VO 2 peak by acting as an antioxidant and reducing the perception of fatigue [ 87 – 90 ]. Together these ingredients may have positively influenced CV and training volume, however, this speculation cannot be proven in the current study.

In conclusion, the results of this study indicate that the acute ingestion of the pre-exercise GT supplement containing 100 mg of caffeine, 1.5 g creatine, 1 g BCAAs, 9 g whey protein, 2.5 g of cordyceps sinensis and a combined 0.75 g of citrulline and rhodiola, taken prior to HIIT for three weeks can significantly improve CV and total training volume when compared to HIIT and PL. Furthermore, the maintenance of and trend toward an improvement in LBM suggests that GT may be helpful in maintaining lean mass during intense training periods. Although there was not a single ingredient in GT that could solely account for the improvements, it is likely that the combination of relatively low doses of several ingredients (caffeine, creatine, BCAAs, whey protein, and cordyceps) may be responsible for the increases in aerobic performance, training volume, and the maintenance of lean mass.

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Smith, A.E., Fukuda, D.H., Kendall, K.L. et al. The effects of a pre-workout supplement containing caffeine, creatine, and amino acids during three weeks of high-intensity exercise on aerobic and anaerobic performance. J Int Soc Sports Nutr 7 , 10 (2010). https://doi.org/10.1186/1550-2783-7-10

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DOI : https://doi.org/10.1186/1550-2783-7-10

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Published: 12 September 2024

Frailty as a sequela of burn injury: a post hoc analysis of the “RE-ENERGIZE” multicenter randomized-controlled trial and the National Health Interview Survey

Adriana C. Panayi ORCID: orcid.org/0000-0003-4053-9855 1 ,
Daren K. Heyland 2 ,
Christian Stoppe 3 , 4 ,
Marc G. Jeschke 5 ,
Samuel Knoedler 6 ,
Christian Tapking 1 ,
Oliver Didzun 1 ,
Valentin Haug 7 ,
Amir K. Bigdeli 1 ,
Ulrich Kneser 1 ,
Dennis P. Orgill 6 &
Gabriel Hundeshagen 1

Military Medical Research volume 11 , Article number: 63 ( 2024 ) Cite this article

Metrics details

With advancements in burn treatment and intensive care leading to decreased mortality rates, a growing cohort of burn survivors is emerging. These individuals may be susceptible to frailty, characterized by reduced physiological reserve and increased vulnerability to stressors commonly associated with aging, which significantly complicates their recovery process. To date, no study has investigated burns as a potential risk factor for frailty. This study aimed to determine the short-term prevalence of frailty among burn survivors’ months after injury and compare it with that of the general population.

A post hoc analysis was conducted on the Randomized Trial of Enteral Glutamine to Minimize the Effects of Burn Injury (RE-ENERGIZE) trial, an international randomized-controlled trial involving 1200 burn injury patients with partial- or full-thickness burns. Participants who did not complete the 36-Item Short Form Health Survey (SF-36) questionnaire were excluded. Data for the general population were obtained from the 2022 National Health Interview Survey (NHIS). Frailty was assessed using the FRAIL (Fatigue, Resistance, Ambulation, Illness, Loss of weight) scale. Due to lack of data on loss of weight, for the purposes of this study, malnutrition was used as the fifth variable. Illness and malnutrition were based on admission data, while fatigue, resistance, and ambulation were determined from post-discharge responses to the SF-36. The burn cohort and general population groups were matched using propensity score matching and compared in terms of frailty status. Within the burn group, patients were divided into different subgroups based on their frailty status, and the differences in their (instrumental) activities of daily living (iADL and ADL) were compared. A multivariable analysis was performed within the burn cohort to identify factors predisposing to frailty as well as compromised iADL and ADL.

Out of the 1200 burn patients involved in the study, 600 completed the required questionnaires [follow-up time: (5.5 ± 2.3) months] and were matched to 1200 adults from the general population in the U.S. In comparison to the general population, burn patients exhibited a significantly higher likelihood of being pre-frail (42.3% vs. 19.8%, P < 0.0001), or frail (13.0% vs. 1.0%, P < 0.0001). When focusing on specific components, burn patients were more prone to experiencing fatigue (25.8% vs. 13.5%, P < 0.0001), limited resistance (34.0% vs. 2.7%, P < 0.0001), and restricted ambulation (41.8% vs. 3.8%, P < 0.0001). Conversely, the incidence rate of illness was observed to be higher in the general population (1.2% vs. 2.8%, P = 0.03), while no significant difference was detected regarding malnutrition (2.3% vs. 2.6%, P = 0.75). Furthermore, in comparison with robust burn patients, it was significantly more likely for pre-frail and frail patients to disclose compromise in ADL and iADL. The frail cohort reported the most pronounced limitation.

Conclusions

Our findings suggest a higher incidence of post-discharge frailty among burn survivors in the short-term following injury. Burn survivors experience compromised fatigue, resistance, and ambulation, while rates of illness and malnutrition were lower or unchanged, respectively. These results underscore the critical need for early identification of frailty after a burn injury, with timely and comprehensive involvement of a multidisciplinary team including burn and pain specialists, community physicians, physiotherapists, nutritionists, and social workers. This collaborative effort can ensure holistic care to address and mitigate frailty in this patient population.

It is estimated that up to 33,000 people each day—7 to 12 million people per year—sustain a burn injury that requires medical care and can lead to limitations in quality of life or result in death [ 1 ]. Given the backdrop of an aging population, there has been a burgeoning interest in evaluating post-burn outcomes among older adults. The assessment of the impact of “aging” on post-burn outcomes requires analysis through the lens of frailty, whereby frailty denotes an augmented susceptibility to stressors due to decreased physiological reserve and diminished capacity to maintain homeostasis [ 2 ].

A systematic review conducted in 2023 synthesized all published research on frailty and burns, identifying 18 studies dating back to 2013, with one-third of the studies published in 2022 [ 3 ]. All studies explored frailty as a risk factor for adverse outcomes of acute burns, yet the reverse hypothesis—that burn injury itself is a risk factor for long-term frailty—remains entirely unexplored. This gap in research is significant, considering that the long-term consequences of burns align with the criteria of most frailty indices [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. Despite this, a history of burns is not included in such assessments.

The hypothesis proposed here is that individuals with a history of burns may exhibit a higher prevalence of frailty compared to the general population, and these differences become apparent a few months post-discharge, which is typically when burn survivors are reintegrating into their normal lives. By highlighting the severity of this issue and outlining its impact on quality of life, we aim to identify potential opportunities and pathways for informing clinical practice, future research, and policymaking efforts.

Source of data for burn patients

The burn population was identified from the previously published Randomized Trial of Enteral Glutamine to Minimize the Effects of Burn Injury (RE-ENERGIZE). RE-ENERGIZE was an international, multicenter, double-blinded, randomized-controlled trial that investigated the effects of enteral glutamine supplementation (0.5 g/kg) in severe burn patients. Severe burns were defined as those of partial- or full-thickness that would necessitate surgery [ 12 ]. The data collection period for RE-ENERGIZE spanned 10 years (2011–2021), and the findings were published by Heyland et al. [ 12 ] in 2022. In summary, a total of 1209 patients from 54 burn units across 14 countries were enrolled. The eligible total body surface area (TBSA) burned criteria was: > 20% for individuals aged 18 to 39 years, > 15% within concomitant inhalation injury, > 15% for individuals aged 40 to 59 years, and > 10% for those over age 60. Therefore, patients admitted with severe burns covering an average TBSA burn of 33% underwent randomization. A total of 1200 individuals were included in the final analysis, of which 596 belonged to the glutamine group while 604 were in the placebo group. Since no beneficial effect was observed from glutamine in the original trial, both groups were combined for our burn cohort analysis. The relevant data collected encompassed details about burn centers (such as geographic regions), patient demographics [including sex, age, race/ethnicity, body mass index (BMI), substance use like alcohol or smoking], and injury specifics [such as cause and extent of burn (TBSA)], as well as outcomes [comprising length of stay in the intensive care unit (ICU), length of hospital stay (LOHS), and discharge destination].

Source of normative data

The 2022 National Health Interview Survey (NHIS) served as the primary data source for the general population. Administered by the National Center for Health Statistics through telephone or face-to-face (household) interviews, NHIS collects annual cross-sectional data on the health status of the U.S. population. The dataset employs a multistage probability study design to ensure that the data are representative of both household and non-institutionalized civilian populations in the U.S. Additionally, there is an oversampling of Black, Asian, and Hispanic populations [ 13 ]. Eligible participants include residents living in households or non-institutional settings, including rooming houses, group homes, and homeless shelters.

Data availability and ethical approval

This study is a post hoc analysis of the RE-ENERGIZE (NCT00985205) trial, in which the analyzed data of the burn cohort have been previously published [ 12 ]. The complete dataset is not publicly accessible due to its inclusion of sensitive information that could potentially compromise the privacy of research participants. The RE-ENERGIZE trial protocol was approved by the Research Ethics Committees at Queen’s University, Kingston, Ontario, Canada (Approval No. NCT00985205; https://clinicaltrials.gov/study/NCT00985205 ), and all participating centers and the informed consent form underwent review and approved by the Research Ethics Board (REB approval NO. 6013407). Before randomization, each patient or their designated surrogate provided written informed consent. All documentation regarding the ethical approval can be found in the published protocol [ 14 ]. Data concerning the normative population are openly accessible from the Centers for Disease Control and Prevention National Health Center for Health Statistics at https://www.cdc.gov/nchs/nhis/data-questionnaires-documentation.htm , 2022 NHIS document.

FRAIL (Fatigue, Resistance, Ambulation, Illness, Loss of weight) scale

The FRAIL scale consists of 5 components: fatigue, resistance, ambulation, illness, and loss of weight [ 15 ]. This is a widely used and extensively studied tool with previous research supporting its validity in frailty assessment in various populations, although not specifically in a burn injury cohort [ 16 , 17 , 18 , 19 , 20 ]. On average, 3 to 6 months after hospital discharge, the patients were contacted to complete the 36-Item Short Form Health Survey (SF-36) questionnaire. Fatigue, resistance, and ambulation were determined from responses to the SF-36 or NHIS questionnaires and are indicative of the post-discharge status. Illness indicated the presence of more than 5 of the following conditions: hypertension, diabetes, cancer other than minor skin cancer, chronic lung disease, myocardial infarction, congestive heart failure or coronary artery disease, angina, asthma, arthritis, and stroke. Kidney disease was excluded from the analysis because of missing data in the NHIS. Due to insufficient data in both burn injury and control cohorts, the concept of “loss of weight” was substituted with “malnutrition”, using recognized definitions from the World Health Organization and the European Society for Clinical Nutrition and Metabolism [ 21 ]. Therefore, in terms of time point, the onset of illness and loss of weight occurred at the time of hospital admission, while fatigue, resistance, and ambulation were assessed at 3–6 months after hospital discharge. A score of 0 on the FRAIL scale indicates robustness, a score of 1–2 indicates pre-frailty, and a score of 3–5 indicates frailty. Figure 1 provides an overview of the questions and scoring methodology [ 21 ]. The relationship between TBSA and frailty was investigated by comparing the distribution of TBSA among three groups: robustness ( n = 268), pre-frailty ( n = 254), and frailty ( n = 78).

Components of the FRAIL scale. FRAIL scale is an acronym for fatigue, resistance, ambulation, illness, and loss of weight. Respondents were asked to report their level of tiredness over the past 4 weeks. Those who felt “all of the time” or “most of the time” scored 1 point on the fatigue component. Similarly, respondents were asked to query about any difficulty walking up 10 steps alone without resting or aids. Those answering “Yes” scored 1 point on the resistance component. Additionally, respondents were asked if they had any difficulty walking several hundred yards alone without aids. A positive response also scored 1 point on the ambulation component. Finally, individuals reporting 5 or more out of 11 specified illnesses (hypertension, diabetes, cancer other than minor skin cancer, COPD/chronic lung disease, myocardial infarction, congestive heart failure or coronary artery disease, angina, asthma, arthritis, stroke, and kidney disease), scored 1 point on the illness component. Kidney disease is excluded because of missing data in the NHIS. Due to insufficient data on weight change in both the Randomized Trial of Enteral Glutamine to Minimize the Effects of Burn Injury (RE-ENERGIZE) and National Health Interview Survey (NHIS) cohorts, loss of weight was replaced by malnutrition. Using accepted definitions of malnutrition from the World Health Organization and the European Society for Clinical Nutrition and Metabolism [ 21 ], individuals with a body mass index (BMI) lower than 18.5 kg/m 2 , those aged between 65–70 years with BMI < 20 kg/m 2 , and those aged over 70 years with BMI < 22 kg/m 2 were assigned a score of 1 point on the malnutrition component. Finally, each component on the FRAIL scale contributes 1 point to overall scores ranging from 0–5, where a score of 0 indicates robustness, while scores between 1–2 indicate pre-frailty and scores between 3–5 indicate frailty

The post-discharge independence of burn patients was evaluated through the assessment of their responses to the Katz index of activities of daily living (ADL) [ 22 ] and the Lawton index of instrumental activities of daily living (iADL) [ 23 ] questionnaires, as previously described [ 19 ]. ADL and iADL are two commonly assessed domains on self-reported questionnaires for measuring functional disability [ 24 ], both considered significant predictors of long-term care service use [ 25 ]. ADL includes 4 components (toileting, transferring, continence, and feeding), while iADL comprises 8 components (ability to use a telephone, shopping, food preparation, housekeeping, laundry, mode of transportation, responsibility for own medications, and ability to handle finances). Any response indicating less than complete independence was classified as an ADL limitation. The utilization of both the Katz index for assessing ADL independence and the Lawton index for evaluating iADL has been prevalent in prior research due to its comprehensive insight into an individual’s functional abilities [ 26 , 27 , 28 , 29 , 30 , 31 ]. While, ADL to self-care tasks essential for basic survival and well-being, such as toileting, bathing, eating, and dressing, iADL involves more complex tasks supporting daily life within the home and community. Examples include tasks such as household management, financial administration, telephone usage, grocery procurement, and medication compliance [ 32 ]. The combined iADL and ADL scores were calculated and plotted against the follow-up period. For example, when computing the iADL score, each component was assigned a point score which was then summed to yield an overall score. For instance, the component “Ability to use the telephone” was scored as follows: “Operates telephone on own initiative, looks up and dials numbers” scored 0, “Dials a few well-known numbers” scored 1, “Answers telephone, but does not dial” scored 2, and “Does not use the phone at all” scored 3. Consequently, higher scores indicate greater dependence. ADL and iADL assessments were conducted 2 to 15 months post-hospital discharge.

Statistical analysis

All data from both databases were collected and matched in Microsoft Excel ® 2024 (Microsoft, Redmond, WA, USA). Propensity score matching was performed in R software (version 4.1.2) using the Matchlt package. Each treated unit “burn patient” was paired with two controls “general population” through a nearest-neighbor one-to-two matching technique to enhance study precision as previously described [ 33 ]. Matching variables included age, sex, race/ethnicity, BMI, history of alcohol misuse, and current smoking status. The quality of the matching was visualized with histograms and jitter plots (Additional file 1 : Figs. S1, S2). The resulting matched cohorts were subsequently utilized for assessing frailty by comparing all 5 components of the FRAIL scale. Continuous data (age, BMI) were presented as means and standard deviations (SD) and compared using a Student’s t -test, while categorical data were presented as absolute n (%) and compared using a χ 2 or Fishers exact test, as appropriate. Finally, a multivariable linear regression analysis was performed on the burns cohort to identify factors associated with frailty, compromised ADL, and iADL. Included variables were age, alcohol misuse, smoking, type of burn (scald, chemical, other), BMI, TBSA, LOHS, glutamine administration, sex, and race. All statistical analysis was conducted in GraphPad Prism (version 9) and the data were visualized in GraphPad Prism and Adobe Illustrator. All P -values less than 0.05 were considered significant.

Cohort demographics and characteristics

In the RE-ENERGIZE trial, there were a total of 1200 participants, of whom 600 completed the necessary questionnaires to meet the eligibility criteria for this post-hoc study. The patient recruitment process is detailed in Fig. 2 . Average follow-up time was (5.5 ± 2.3) months post-burn. A total of 1200 adults from the general population were included matched (Table 1 ). The burn population was well-matched to the general population, with both cohorts consisting predominantly of males (> 70.0%) and individuals of White ethnicity (> 70%). The cohorts were similar in terms of age [(48.7 ± 17.1) years vs. (48.3 ± 17.8) years, P = 0.65] and BMI [(28.3 ± 6.0) kg/m 2 vs. (28.0 ± 7.6) kg/m 2 , P = 0.50]. The burn cohort had a higher percentage of Native American subjects (3.0% vs. 1.0%, P = 0.002), while the normative cohort had a higher percentage of Black or African American subjects (6.3% vs. 10.8%, P = 0.002; Table 1 ).

Patient recruitment process. ADL activities of daily living, iADL instrumental activities of daily living, NHIS National Health Interview Survey

Prevalence of frailty

Out of 600 burn patients, there were 268 classified as robustness, while 254 were categorized as pre-frailty, and another 78 as frailty individuals within this cohort group. Additionally, burn patients exhibited a notably lower likelihood of being classified as robustness compared to their counterparts in normative populations (44.7% vs. 79.2%, P < 0.0001), but showed a substantially higher probability of being categorized as pre-frail (42.3% vs. 19.8%, P < 0.0001), or frail individuals (13.0% vs. 1.0%, P < 0.0001; Table 1 ). Furthermore, when examining specific components of the FRAIL scale among these patients with burns, it became evident that they had an increased tendency towards experiencing fatigue (25.8% vs. 13.5%, P < 0.0001), increased resistance (34.0% vs. 2.7%, P < 0.0001), and restricted ambulation (41.8% vs. 3.8%, P < 0.0001). Moreover, the incidence of illness appeared higher in the general population compared to that observed among those with burns (1.2% vs. 2.8%, P = 0.03). However, malnutrition rates did not display significant differences between these two groups (2.3% vs. 2.6%, P = 0.75; Table 1 ). Lastly, an analysis focusing on various comorbidities encompassed within the illness component revealed that individuals from general populations demonstrated a notably greater likelihood of having conditions such as asthma, arthritis, congestive heart failure (CHF) or coronary heart disease (CHD), chronic obstructive pulmonary disease (COPD)/chronic lung disease, hypertension and myocardial infarction ( P < 0.05) whereas those from the burn patient group displayed a markedly elevated probability for cancer other than minor skin cancer and diabetes ( P < 0.01).

TBSA and frailty in the burn population

When examining the relationship between TBSA and frailty, we observed that the majority of robust patients (score 0) had a TBSA ranging from 20 to 29% (102/268; accounting for 38.1% of all robust patients), followed by a TBSA range of 10 to 19% (60/268; representing 22.4% of all robust patients). The overall TBSA range for robust patients was from 10 to 76%. Similarly, most pre-frail patients (score 1–2) exhibited a TBSA between 20 and 29% (87/254; constituting 34.3% of all pre-frail patients), followed by a TBSA between 30 and 39% (58/254; representing 22.8% of all pre-frail patients). The total TBSA range for pre-frail patients was from 10 to 93%. Finally, the majority of frail patients (score 3–5) had a TBSA between 20 and 29% (24/78; accounting for 30.8% of all frail patients), followed by a TBSA ranging from 10 to 19% (17/78; constituting 21.8% of all frail patients). The total TBSA range for frail patients was from 10 to 85% (Fig. 3 a). When considering the entire cohort, most patients exhibited robust and had a TBSA of 20–29% (102/600; 17.0% of all patients), followed by pre-frail patients with a TBSA of 20–29% (87/600; 14.5% of all patients), and then robust patients with a TBSA of 10–19% (60/600; 10.0% of all patients; Fig. 3 b).

Association between TBSA and frailty. a The distribution of TBSA percentages across frailty score groups indicates that the majority of robust, pre-frail, and frail patients had a TBSA between 20 and 29%. As TBSA increases, there is a corresponding increase in the percentage of pre-frail and frail patients. b The distribution of TBSA among the patient cohort is visualized as a percentage. The majority of patients demonstrated robustness with a TBSA of 20–29% (102/600; 17.0% of all patients), followed by pre-frail patients within the same TBSA range (87/600; 14.5% of all patients)

ADL in the burn population

In comparison to robust burn patients, pre-frail burn patients exhibited a significantly higher likelihood of requiring assistance in toileting (11.4% vs. 2.6%, P < 0.0001), transferring (10.6% vs. 0.7%, P < 0.0001), continence (9.1% vs. 1.1%, P < 0.0001), and feeding (6.7% vs. 1.1%, P < 0.0001). Similarly, frail burn patients were notably more likely than robust patients to necessitate assistance in toileting (30.8% vs. 2.6%, P < 0.0001), transferring (28.2% vs. 0.7%, P < 0.0001), continence (20.5% vs. 1.1%, P < 0.0001), and feeding (17.9% vs. 1.1%, P = 0.001; Table 2 ). The distribution of ADL score over follow-up time is depicted in Additional file 1 : Fig. S3.

iADL in the burn population

Compared to robust patients, pre-frail burn patients demonstrated significantly lower levels of independently in using the telephone (87.0% vs. 95.5%, P = 0.002), shopping (48.4% vs. 81.7%, P < 0.0001), meal preparation (53.9% vs. 81.3%, P < 0.0001), housekeeping (37.0% vs. 72.4%, P < 0.0001), laundry (60.6% vs. 81.3%, P < 0.0001), travel (55.1% vs. 82.1%, P < 0.0001), managing their medication (73.2% vs. 92.9%, P < 0.0001), and financial management (69.3% vs. 88.4%, P < 0.0001; Table 2 ).

In comparison to robust patients, frail burn patients showed significantly lower levels of independence in using the telephone (80.8% vs. 95.5%, P < 0.0001), shopping (21.8% vs. 81.7%, P < 0.0001), preparing meals (26.9% vs. 81.3%, P < 0.0001), housekeeping (14.1% vs. 72.4%, P < 0.0001), laundry (33.3% vs. 81.3%, P < 0.0001), travel (34.6% vs. 82.1%, P < 0.0001), managing their medication (51.3% vs. 92.9%, P < 0.0001), and financial management (48.7% vs. 88.4%, P < 0.0001; Table 2 ). The distribution of iADL score against follow-up time is shown in Additional file 1 : Fig. S3.

Factors associated with frailty and limitations in ADL or iADL in the burn cohort

The entire burn cohort was utilized to conduct a multivariable linear regression analysis aimed at identifying risk factors for frailty, as well as limitations in ADL and iADL. The results revealed that age ( P < 0.0001) and smoking ( P = 0.04) were independent risk factors for frailty. Furthermore, the chemical burn was identified as an independent risk factor for ADL limitations ( P = 0.0003), while both chemical burn ( P = 0.01) and scald burn ( P = 0.04) were identified as independent risk factors for iADL limitations. Additionally, individuals of Asian or Pacific Islander race were found to have a protective effect against iADL limitations ( P = 0.01, Table 3 ).

Advancements in both burn care and intensive care have led to decreased mortality rates, with reports showing a survival rate of 96.7% among individuals treated at burn centers across the U.S. [ 1 ]. There has been a notable increase in post-burn morbidity within the expanding community of burn survivors [ 34 , 35 ]. Put differently, as these survivors live longer lives, they are increasingly confronted with enduring consequences from their injuries. Frailty, characterized by diminished physiological reserve and increased susceptibility to stressors, can significantly complicate efforts to manage and rehabilitate these individuals (Additional file 1 : Fig. S4) [ 11 , 36 ]. This underscores the necessity for an enhanced comprehension regarding long-term susceptibility to frailty in this patient population. In the discussion, we leverage findings from this study to propose diverse strategies aimed at mitigating and limiting frailty among burn survivors.

Early recognition and assessment

Our analysis indicates a higher prevalence of frailty in the burn population, approximately 5 months after injury (Fig. 4 ). The components of fatigue, resistance, and ambulation were all significantly more restricted in the burn survivors, while the variables of frailty assessed on hospital admission, that is, illness and malnutrition, were higher or did not differ in the normative population, respectively. This provides evidence that although the patients were not frail upon admission to the hospital, they experienced a significant increase in frailty shortly after discharge. This emphasizes the importance of early recognition and assessment of frailty following a burn injury as a critical component of comprehensive burn care. Importantly, the RE-ENERGIZE data did not include information on the pre-burn frail status of patients. Therefore, an exact inference about which patients became frail after the injury cannot be made.

Long-term trajectory of frailty among burn patients is influenced by targeted intervention. Following burn injuries in the short term, patients may face compromised resistance and ambulation while concurrently experiencing fatigue stemming from various factors such as inadequate pain management leading to disrupted sleep patterns or heightened anxiety and depression related to trauma-induced sequelae. Collectively impacting patient independence including (instrumental) activities of daily living, these challenges encompass essential tasks, such as shopping and cooking, cleaning and managing medications, as well as finances. In the long run, this could result in malnutrition, an increase in chronic illnesses, and a notable elevation across all 5 components measured by the FRAIL score. Hypothetically, prompt long-standing engagement with a multidisciplinary team comprising rehabilitation services, community physicians, nutritionists, pain and mental health specialists, as well as social support, holds promise for mitigating fatigue, resistance compromises, and averting prolonged illness and malnutrition

Interestingly, our multivariable analysis of predisposing factors did not reveal TBSA to have a significant impact on the development of frailty, while age was a predictable predictor. Although there was a slight trend suggesting that patients with higher TBSA were also more likely to have higher FRAIL scores (Fig. 3 ), the multivariate analysis showed no significant correlation between TBSA and frailty. TBSA is one of the most powerful indicators of burn trauma severity and strongly correlates with adverse outcomes and short- and long-term morbidity [ 37 , 38 ]. This finding highlights the multifactorial nature of frailty in general and certainly emphasizes the need for more advanced screening methods that go beyond mere burn size [ 39 , 40 , 41 ].

Multidisciplinary approach

The management of severe burn injuries in general, and frailty in severely burned patients in particular, requires a multidisciplinary team approach involving burn specialists, community physicians, geriatricians, pain management experts, physiotherapists, occupational therapists, mental health professionals, nutritionists, and social workers (Fig. 4 ).

The long-term trajectory of burn survivors is characterized by low resistance and low ambulation which limits patients’ independence, predisposing to illness. At the same time increased fatigue and malnutrition also predispose to illness. A multidisciplinary collaborative effort ensures comprehensive care for addressing the diverse needs of frail patients, including rehabilitation to minimize the loss of ambulation and resistance, medical management to promptly identify and treat illnesses such as cardiovascular compromise and diabetes, nutritional support to prevent malnutrition and thus limit illness, and psychosocial interventions [ 42 ]. By maintaining ambulation and resistance, independence is maximized which in turn limits malnutrition, illness and fatigue. For example, occupational therapy can promote well-being through occupation by enabling burn survivors to engage in meaningful activities of everyday life. Occupational therapy achieves this by collaborating with patients and their community to enhance the survivors’ ability to engage in their chosen or necessary occupation or by modifying their occupation or environment to better support their engagement [ 43 ].

We have identified significant limitations in iADL and ADL among frail burn survivors, which compromise their independence and predispose these patients to further frailty. Approximately 25% of frail burn survivors report being unable to dispense their medication, compared to 1% of robust survivors. This notable limitation may have multiple contributing factors (e.g., disability due to a hand burn, presence of compression garments, and the type and shape of medication bottles), presenting a multidisciplinary challenge for resolution. The inability to adhere to medications could result in untreated illness and consequently increase frailty [ 44 , 45 ]. Addressing this issue may require modified medication bottles, adaptive aids promoting independence, as well as specialized situational training through physiotherapy and occupational therapy. Additionally, social support can enhance adherence and overall well-being. The retrospective nature of this post hoc analysis limited our ability to consider certain variables that may influence our results, such as the body location of the burn injury (e.g., extremities or face), depth of the burn (e.g., second or third degree), setting of the injury (e.g., work-related or home-related), post-discharge care options (e.g., inpatient physiotherapy, outpatient physiotherapy or occupational therapy, treatment by mental health or pain specialists), as well as the socioeconomic status of the patients.

Optimizing nutrition and rehabilitation

Frailty often leads to impaired nutritional status and decreased muscle mass [ 46 , 47 ], which can impede wound healing and functional recovery in burn patients [ 48 , 49 ]. Our multivariable analysis revealed no association between glutamine administration and the extent of frailty, ADL, and iADL. Similarly, previous literature on amino acid supplementation in the treatment of sarcopenia and frailty has yielded conflicting results [ 50 , 51 , 52 ]. Although hydroxyl-methyl butyrate has been reported to enhance muscle protein synthesis when combined with arginine and glutamine, glutamine alone has not been shown to prevent muscle deterioration [ 53 ]. Following a burn injury, the body’s energy and nutrient demand increase dramatically to support tissue repair and wound healing [ 5 ]. During the acute phase, adequate nutrition, including sufficient calories, protein, vitamins, and minerals, is crucial for facilitating the regeneration of damaged tissues, while minimizing complications such as infections, and promoting faster wound closure [ 54 ]. Preventing malnutrition during this high-demand period can reduce the risk of long-term frailty associated with prolonged healing and impaired tissue integrity [ 55 ]. In the medium- and long-term, severe burn injuries result in muscle wasting and loss of lean body mass due to increased protein breakdown and decreased protein synthesis [ 56 ].

In turn, a significant reduction in muscle mass and strength can severely impact the activity and energy levels of burn survivors. They often experience chronic fatigue, decreased stamina, and overall weakness, making it challenging to perform even basic ADLs such as dressing and bathing [ 57 ]. Our findings indicated that frailer burn survivors are more likely to require assistance with feeding, rely on parenteral feeding, and need help with shopping. More than 40% of frail burn survivors required their meals to be prepared and served compared to only 3% of robust survivors. Furthermore, diminished energy and physical capacity compromise the ability to participate in social and recreational activities, further affecting the quality of life [ 58 ]. As a result, survivors may increasingly depend on caregivers or adaptive aids, impacting their sense of independence and self-esteem. Additionally, the combination of physical limitations and increased dependency can contribute to a cycle of reduced physical activity, further exacerbating muscle wasting and frailty. Optimal nutrition, particularly high-quality protein intake, is crucial for preserving muscle mass, strength, and function, which are essential for mobility, independence, and overall resilience against frailty (Additional file 1 : Fig. S4) [ 59 ]. Adequate nutrition is essential for providing the energy required for daily activities, rehabilitation, and physical therapy. It plays a crucial role in maintaining muscle strength, endurance, and functional independence. These factors are fundamental prerequisites for implementing a comprehensive rehabilitation program that includes nutritional support, physical therapy, and occupational therapy to help mitigate these effects [ 58 ]. Such programs aim to restore muscle mass, improve energy levels, and enhance the individual’s ability to participate in ADL, ultimately promoting greater independence and quality of life.

Long-term follow-up and care

Burn patients are at increased risk of experiencing long-term complications, such as chronic pain, functional impairment, and recurrent hospitalizations, which have been shown to contribute to frailty (Additional file 1 : Fig. S4) [ 8 , 35 , 39 ]. In a recent post hoc analysis of the same burn cohort, our research team identified a strong correlation between chronic pain, anxiety, and depression in these patients [ 60 ]. Previous research has also established a significant link between poor mental health and long-term frailty [ 61 ]. This highlights the necessity for comprehensive care that integrates both mental health support and physical rehabilitation to optimize the long-term outcomes of burn survivors. Establishing structured long-term follow-up programs is essential for monitoring progress, addressing ongoing needs, and preventing future frailty-related events. Losing track of burn patients during follow-up poses a significant concern both clinically and scientifically: comparison of the burn patients who were “lost to follow-up” with those included as responders revealed notable differences in baseline characteristics. Non-responders were on average younger, more likely to be smokers, less likely to be Hispanic but more likely to be African American. They were also more likely to have had inhalation injury or been transferred to another hospital ward with shorter hospital and ICU stays. This inherent limitation present in all prospective research regarding short- and long-term burn survivors emphasizes the importance of standardized 6-month follow-ups that extend beyond evaluating the need for secondary reconstructive procedures.

Although early detection of frailty and ADL deficiencies has been established, little information exists regarding their longitudinal progression. It is essential to collect outcome measures over time [ 62 , 63 ], and implement extended, standardized, and interdisciplinary long-term protocols. A recent meta-analysis found that follow-up for burn patients seldom extends 5 years post-injury, which is considered long term [ 39 ]. Currently, all specialized follow-up care for burn survivors is exclusively provided by surgical institutions involved in secondary reconstruction. After achieving satisfactory reconstruction and reaching an acceptable level of scarring control, pain management effectiveness, and functional capability improvement, patient monitoring becomes sporadic or ceases altogether. There remains a lack of comprehensive protocols for diagnosing and treating long-term organ damage across disciplines while assessing their respective contributions to complex phenomena such as frailty. It is essential to identify long-term complications that may appear unrelated but are linked with an increased risk of developing diabetes and cardiovascular disease over decades. The establishment of a standardized interdisciplinary system for monitoring burn patients in the long term is crucial. This system could involve lifelong, follow-up appointments every 5 years similar to those offered for cancer patients after hospital discharge. To validate our preliminary findings comprehensively and ensure their applicability across different contexts, independent studies or datasets should confirm them. Conducting a prospective study comparing frailty levels upon admission with those at early (within months) and long-term (after years) post-discharge intervals, while examining diverse post-discharge care options like physiotherapy or occupational therapy would significantly enhance our understanding of chronic burn injury effects.

Limitations

The response data are based on self-reporting, which is inherently susceptible to inaccuracies. Due to differences in the questionnaire protocols of the two databases (RE-ENERGIZE and NHIS), certain questions and response options were adjusted to achieve consensus. Although the RE-ENERGIZE data spans 6 years (2016–2021), we chose to utilize only the 2022 NHIS data as it provided all the necessary frailty assessment information due to its rotating design. The use of a general population database and propensity score matching helps to minimize this limitation. Another limitation of our study is that while the NHIS data is US-centric, the RE-ENERGIZE data collection was international, with the majority of patients based in North America. Given that only a limited subset of both populations was sampled, generalizability poses a concern. The extent to which our results can be applied to other populations and settings, particularly low- and middle-income countries, remains uncertain. Baseline differences in co-morbidities were observed between the two groups. The existing literature on illness present on admission following an acute burn is limited and inconclusive [ 64 , 65 ]. Therefore, further research is necessary to determine whether there are genuine disparities in the baseline health of acute burn injury patients compared to the general population. The specific body location is particularly relevant, as injuries to the head and neck, as well as upper and lower extremities, are associated with higher levels of disability and would consequently be linked with elevated FRAIL scores [ 66 ]. Although data on the exact depth of the burns were not provided, all eligible patients for the trial had partial- or full-thickness burns requiring surgery. Generalizability may also pose a concern since only a restricted subset of both populations was sampled. The burn cohort analyzed in this study was defined post hoc and had not been considered in the original power calculation of the sample size. Therefore, it has been previously proposed that statistical hypotheses from post hoc analyses are inherently regarded as exploratory only [ 67 ]. Finally, due to the cross-sectional design of the study, making causal inferences is precluded.

In this study, we conducted an analysis of one of the largest multicenter cohorts of patients with extensive burns to determine the prevalence of frailty in such patients’ months after injury, comparing it to a non-burned general population. Patients with a history of burns exhibit a higher prevalence of frailty compared to the general population group, and these differences are apparent a few months post-discharge, which is typically when burn survivors return to their normal lives. Additionally, we investigated the interrelationship between the presence of frailty and compromise in (instrumental) ADL. By establishing the severity of the issue and describing its impact on quality of life, we aim to identify potential opportunities and avenues for guiding clinical practice, future research, and policymaking efforts.

Data availability

Datasets generated and analyzed to provide the findings in this study are available from the corresponding author upon reasonable request.

Abbreviations

Activities of daily living

Body mass index

Congestive heart failure/coronary heart disease

Chronic obstructive pulmonary disease

Fatigue, Resistance, Ambulation, Illness, Loss of weight

Instrumental activities of daily living

Intensive care unit

Length of hospital stay

National Health Interview Survey

Randomized Trial of Enteral Glutamine to Minimize the Effects of Burn Injury

36-Item Short Form Health Survey questionnaire

Total body surface area

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Acknowledgements

This work was supported by the U.S. Department of Defense (W81XWH-09-2-0194 for the pilot phase), and the Canadian Institutes of Health Research (MCT-94834 for the pilot phase and 14238 for the definitive phase).

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ACP was involved in the conceptualization of the study, data collection, methodology, statistical analysis, data visualization, and writing of the original draft. DKH, CS, and MGJ were involved in the data collection and the review and editing of the manuscript. SK was involved in the methodology, statistical analysis, and the review and editing of the manuscript. CT was involved in the writing of the original draft. OD, VH, AKB, and UK were involved in the review and editing of the manuscript. DPO was involved in the methodology and the review and editing of the manuscript. GH was involved in the conceptualization of the study, data collection, methodology, and writing of the original draft.

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Correspondence to Gabriel Hundeshagen .

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The protocol for the RE-ENERGIZE trial was approved by the Ethics Committees at Queen’s University, Kingston, Ontario, Canada (Approval number: NCT00985205; https://clinicaltrials.gov/study/NCT00985205 ) and at all other participating centers. The entities that provided support, financial or product, had no role in the protocol design, conduct of the trial, or data analysis. The also did not have access to the data or manuscript prior to publication. Written informed consent was obtained from each subject or a designated surrogate prior to randomization.

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Additional file 1: fig. s1.

Quality of matching visualized as a histogram. Fig. S2 Quality of matching visualized as a jitter plot. Fig. S3 ADL and iADL scores assessed over the follow-up period in months. Fig. S4 Theoretic schematic depicting the potential impact of frailty on patients with a history of burn injury.

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Panayi, A.C., Heyland, D.K., Stoppe, C. et al. Frailty as a sequela of burn injury: a post hoc analysis of the “RE-ENERGIZE” multicenter randomized-controlled trial and the National Health Interview Survey. Military Med Res 11 , 63 (2024). https://doi.org/10.1186/s40779-024-00568-x

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Pre- versus post-exercise protein intake has similar effects on muscular adaptations

Brad jon schoenfeld.

1 Department of Health Sciences, Herbert H. Lehman College, City University of New York, Bronx, NY, United States

Alan Aragon

2 Department of Nutrition, California State University, Northridge, CA, United States

Colin Wilborn

3 Graduate School and Research, University of Mary Hardin Baylor, Belton, TX, United States

Stacie L. Urbina

Sara e. hayward, james krieger.

4 Weightology, Issaquah, WA, United States

Associated Data

The following information was supplied regarding data availability:

The raw data has been supplied as Supplementary File .

The purpose of this study was to test the anabolic window theory by investigating muscle strength, hypertrophy, and body composition changes in response to an equal dose of protein consumed either immediately pre- versus post-resistance training (RT) in trained men. Subjects were 21 resistance-trained men (>1 year RT experience) recruited from a university population. After baseline testing, participants were randomly assigned to 1 of 2 experimental groups: a group that consumed a supplement containing 25 g protein and 1 g carbohydrate immediately prior to exercise (PRE-SUPP) ( n = 9) or a group that consumed the same supplement immediately post-exercise (POST-SUPP) ( n = 12). The RT protocol consisted of three weekly sessions performed on non-consecutive days for 10 weeks. A total-body routine was employed with three sets of 8–12 repetitions for each exercise. Results showed that pre- and post-workout protein consumption had similar effects on all measures studied ( p > 0.05). These findings refute the contention of a narrow post-exercise anabolic window to maximize the muscular response and instead lends support to the theory that the interval for protein intake may be as wide as several hours or perhaps more after a training bout depending on when the pre-workout meal was consumed.

Introduction

Nutrient timing, operationally defined as the consumption of nutrients in and/or around an exercise bout, has been advocated as a strategy to optimize a myriad of performance- and muscular-related adaptations. Several researchers have put forth the notion that the timing of nutrient consumption is even more important to these adaptations than the quantity of food and macronutrient ratio of the diet ( Candow & Chilibeck, 2008 ). Perhaps the most heralded aspect of nutrient timing involves consuming protein immediately after exercise. The purported beneficial effects (i.e., increased muscle protein synthetic response) of protein timing are based on the hypothesis that a limited “anabolic window of opportunity” exists for post-workout anabolism ( Lemon, Berardi & Noreen, 2002 ). To take advantage of this window of opportunity, common thought is that protein must be consumed within approximately 45 min to 1 h of completion of exercise to maximize post-workout muscle protein synthesis (MPS) ( Ivy & Ferguson-Stegall, 2013 ). It has been postulated that the anabolic response to a resistance training bout is blunted if protein is ingested after this narrow window, thereby impairing muscular gains ( Ivy & Ferguson-Stegall, 2013 ).

A review of literature determined that while compelling evidence exists showing muscle is sensitized to protein ingestion following a workout, the anabolic window does not appear to be as narrow as what was once thought ( Aragon & Schoenfeld, 2013 ). Rather, the authors proposed that the interval for consumption may be as wide as 5–6 h after exercise depending on the timing of the pre-workout meal; the closer a meal is consumed prior to exercise, the larger the post-workout anabolic window of opportunity.

Research examining the existence of a narrow post-workout window is equivocal. In a study of healthy young and middle-aged subjects, Levenhagen et al. (2001) reported that protein synthesis of the legs and whole body, as determined by dilution and enrichment of phenylalanine, was increased threefold when an oral supplement containing 10 g protein, 8 g carbohydrate and 3 g fat was consumed immediately following exercise compared to just a 12% increase when the supplement was ingested 3-hours post-workout. It should be noted that the training protocol involved moderate intensity, long duration aerobic exercise, raising the possibility that results reflected mitochondrial and/or sarcoplasmic protein fractions, as opposed to synthesis of contractile elements ( Kumar et al., 2009 ). Conversely, Rasmussen et al. (2000) found no significant difference in leg net amino acid balance when 6 g essential amino acids (EAA) were co-ingested with 35 g carbohydrate either 1 h or 3 h after resistance training. Given that the training protocol involved 18 sets of lower body resistance exercise, it can be inferred that findings were indicative of myofibrillar protein synthesis ( Donges et al., 2012 ). Moreover, the amount of EAA was markedly higher in Rasmussen et al. versus Levenhagen et al., potentially confounding results between studies. It should be noted that while these studies provide an interesting snapshot of the transient post-exercise responses to protein timing, there is evidence that acute measures of MPS do not necessarily correlate with long-term increases in muscle growth ( Adams & Bamman, 2012 ).

Longitudinal studies on the topic of protein timing are conflicting. A number of studies have shown beneficial effects of post-workout protein timing on muscle strength and size ( Esmarck et al., 2001 ; Cribb & Hayes, 2006 ; Willoughby, Stout & Wilborn, 2007 ) while others have not ( Hoffman et al., 2009 ; Candow et al., 2006 ; Verdijk et al., 2009 ). A recent meta-analysis by Schoenfeld, Aragon & Krieger (2013) found that consuming protein within 1 h post-resistance exercise had a small but significant effect on increasing muscle hypertrophy compared to delaying consumption by at least 2 h. However, sub-analysis of these results revealed the effect all but disappeared after controlling for the total intake of protein, indicating that favorable effects were due to unequal protein intake between the experimental and control groups (∼1.7 g/kg versus 1.3 g/kg, respectively) as opposed to temporal aspects of feeding. The authors noted that inherent limitations of the studies obscure the ability to draw definitive, evidence-based conclusions on the efficacy of protein timing. Specifically, only three studies in the meta-analysis met inclusion criteria for matched protein intake between experimental and control groups. Of these studies, one showed a significant benefit to protein timing while two showed no differences between groups. Compounding matters, only two of the matched studies investigated the effects of protein timing on well-trained subjects. Cribb & Hayes (2006) randomized a cohort of young recreational male bodybuilders to consume 1 g/kg of a supplement containing 40 g whey isolate, 43 g glucose, and 7 g creatine monohydrate either immediately before and after exercise versus in the early morning and late evening in young recreational male bodybuilders. After 10 weeks of progressive resistance exercise, significant increases in lean body mass and hypertrophy of type II fibers were seen when the supplement was timed around the exercise bout as compared to delaying consumption. On the other hand, Hoffman et al. (2009) showed no significant differences in total body mass or lean body mass when resistance-trained men with an average of 5.9 years lifting experience consumed a supplement containing 42 g protein and 2 g carbohydrate immediately before and after resistance exercise versus in the early morning and late evening over a 10-week period.

Therefore, the purpose of this study was to investigate muscular adaptations in response to an equal dose of protein consumed either immediately pre- versus post-resistance exercise in well-trained men. It was hypothesized that consuming protein prior to resistance training would negate the need to consume protein immediately post-workout for maximizing muscular adaptations.

Experimental approach to the problem

To determine the effects of pre- versus post-exercise protein consumption on muscular adaptations, resistance trained subjects were pair-matched according to baseline strength in the squat and bench press exercises and then randomly assigned to one of two experimental groups: a group that consumed a supplement containing 25 g protein and 1 g carbohydrate immediately prior to exercise (PRE-SUPP) or immediately after the exercise bout (POST-SUPP). Subjects in the PRE-SUPP group were instructed to refrain from eating for at least 3 h after the exercise bout while those in the POST-SUPP group were instructed to refrain from eating for at least 3 h prior to the exercise bout. All subjects performed a hypertrophy-type resistance training protocol consisting of three weekly sessions carried out on non-consecutive days for 10 weeks. A total-body routine was employed with three sets of 8–12 repetitions performed for each exercise. Subjects were tested prior to the initial training session (T1), at the mid-point of the study (T2), and after the final training session (T3) for measures of body composition, muscle thickness, and maximal strength.

Participants

Twenty-one male volunteers were recruited from a university population (age = 22.9 ± 3.0 years; height = 175.5 ± 5.9 cms; body mass = 82.9 ± 13.6 kgs). Subjects had no existing musculoskeletal disorders, were self-reported to be free from the use of anabolic steroids or any other illegal agents known to increase muscle size for the previous year, and were considered experienced lifters, defined as consistently lifting weights at least three times per week for a minimum of one year and regularly performing the bench press and squat exercises. Approval for the study was obtained from the University of Mary Hardin-Baylor Institutional Review Board (IRB). Informed consent was obtained from all participants.

Supplementation procedures

After baseline testing, participants were pair-matched according to baseline strength in the squat and bench press exercises and then randomly assigned to one of two experimental groups: a group that consumed a supplement containing 25 g protein and 1g carbohydrate (Iso100 Hydrolyzed Whey Protein Isolate, Dymatize Nutrition, Dallas, TX) immediately prior to exercise (PRE-SUPP) ( n = 9) or immediately after the exercise bout (POST-SUPP) ( n = 12). The chosen supplement was based on research showing that consumption of 20–25 g of whey protein maximizes the MPS response in young resistance trained men ( Atherton & Smith, 2012 ; Breen & Phillips, 2012 ). All subjects consumed the supplement in the presence of a research assistant to ensure compliance. Subjects in the PRE-SUPP group were instructed to refrain from eating for at least 3 h after the exercise bout to ensure that consumption of a post-workout meal did not confound results. Similarly, those in the POST-SUPP group were instructed to refrain from eating for at least 3 h prior to the exercise bout to ensure that consumption of a pre-workout meal did not confound results.

Resistance training procedures

The resistance training protocol consisted of nine exercises per session. These exercises targeted the anterior torso muscles (flat barbell bench press, barbell military press), the posterior muscles of the torso (wide grip lat pulldown, seated cable row), the thigh musculature (barbell back squat, machine leg press, and machine leg extension), and upper extremities (dumbbell biceps curl, triceps pushdown). Subjects were instructed to refrain from performing any additional resistance-type training and to avoid additional aerobic-type exercise other than what was part of normal daily activities for the 10-week study period.

Training consisted of three weekly sessions performed on non-consecutive days for 10 weeks. All routines were directly supervised by research staff trained to ensure proper performance of all exercises. Intensity of load was approximately 75% of 1 repetition maximum (RM)—generally considered to equate to a 10RM ( Baechle & Earle, 2008 )—so that a target repetition range of 8–12 repetitions is achieved on each set. Prior to training, participants underwent 10RM testing to determine individual initial loads for each exercise. Repetition maximum testing was consistent with recognized guidelines as established by the National Strength and Conditioning Association ( Baechle & Earle, 2008 ). Subjects performed three sets of each exercise. Sets were carried out to the point of momentary concentric muscular failure—the inability to perform another concentric repetition while maintaining proper form. Cadence of repetitions was carried out with a controlled concentric contraction and an approximately 2 s eccentric contraction as determined by the supervising member of the research team. Subjects were afforded 90 s rest between sets. The load was adjusted for each exercise as needed on successive sets to ensure that subjects achieved failure in the target repetition range. Attempts were made to progressively increase the loads lifted each week within the confines of maintaining the target repetition range.

Dietary intervention

To help ensure a maximal anabolic response, each subject was given a dietary plan (protein equating to 1.8 g/kg of body mass, fat equating to 25–30% of total energy intake, and the remaining calories in carbohydrate) designed to create an energy surplus of 500 kcal/day. Dietary adherence was assessed by self-reported food records using MyFitnessPal.com ( http://www.myfitnesspal.com ), which were collected and analyzed during each week of the study. Subjects were instructed on how to properly complete the logs and record all food items and their respective portion sizes that were consumed for the designated period of interest. Each item of food was individually entered into the program, and the program provided relevant information as to total energy consumption, as well as amount of energy derived from proteins, fats, and carbohydrates over the length of the study. Diet logs were recorded every day during the study. When calculating total calories, protein, carbohydrate, and fat, values were derived from the three days prior to each testing session (T1, T2, T3) and averaged. Subjects received ongoing counseling from the research staff at each session on the importance of maintaining the prescribed dietary regimen.

Measurements

Testing was conducted prior to the initial training session (T1), at the mid-point of the study (T2), and after the final training session (T3). Subjects were instructed to refrain from any strenuous exercise for at least 48 h prior to each testing session. Subjects were instructed to avoid taking any supplements that would enhance muscle-building. The following outcomes were assessed:

Muscle Thickness : Ultrasound imaging was used to obtain measurements of muscle thickness (MT). The reliability and validity of ultrasound in determining hypertrophic measures is reported to be very high (correlation coefficients of 0.998 and 0.999, respectively) when compared to the “gold standard” magnetic resonance imaging ( Reeves, Maganaris & Narici, 2004 ). Moreover, ultrasound has a remarkable safety record with no known harmful effects associated with its proper use in adults ( Nelson et al., 2009 ). Testing was carried out using a B-mode ultrasound imaging unit (Sonoscape S8 Expert; All Imaging Systems, Irvine, CA, USA). The technician, who was not blinded, applied a water-soluble transmission gel (Aquasonic 100 Ultrasound Transmission gel; Parker Laboratories Inc., Fairfield, NJ, USA) to each measurement site and a 5 MHz ultrasound probe was placed perpendicular to the tissue interface without depressing the skin. When the quality of the image was deemed to be satisfactory, the technician saved the image to the hard drive and obtained MT dimensions by measuring the distance from the subcutaneous adipose tissue-muscle interface to the muscle-bone interface as detailed in previous research ( Schoenfeld et al., 2015a ; Schoenfeld et al., 2015b ). Measurements were taken on the right side of the body at four sites: biceps brachii, triceps brachii, medial quadriceps femoris, and lateral quadriceps femoris. For the anterior and posterior upper arm, measurements were taken 60% distal between the lateral epicondyle of the humerus and the acromion process of the scapula; for the quadriceps femoris, measurements were taken 50% between the lateral condyle of the femur and greater trochanter for both the medial (rectus femoris) and lateral (vastus lateralis) aspects of the thigh. Ultrasound has been validated as a good predictor of muscle volume in these muscles ( Miyatani et al., 2004 ; Walton, Roberts & Whitehouse, 1997 ) and has been used in numerous studies to evaluate hypertrophic changes ( Abe et al., 2000 ; Hakkinen et al., 1998 ; Nogueira et al., 2009 ; Young et al., 1983 ; Ogasawara et al., 2012 ). In an effort to help ensure that swelling in the muscles from training did not obscure results, images were obtained 48–72 h before commencement of the study and after the final training session. This is consistent with research showing that acute increases in muscle thickness return to baseline within 48 h following a resistance training session ( Ogasawara et al., 2012 ). To further ensure accuracy of measurements, at least two images were obtained for each site. If measurements were within 10% of one another the figures were averaged to obtain a final value. If measurements were more than 10% of one another, a third image was obtained and the closest of the measures were then averaged.

Body Composition : Measures of body composition were determined by dual x-ray absorptiometry (DXA) imaging. Lean mass (total fat-free mass), fat mass, and percent body fat was assessed using a Hologic™ Discovery dual energy x-ray absorptiometer (DXA; Bedford, MA, USA). Subjects were instructed to refrain from exercise for 48 h and fast for 12-hours prior to each testing session. Upon arrival, participants had their height recorded using a SECA 242 instrument (242, SECA, Hanover, MD, USA) and weight recorded using TANITA electronic scale (Model TBF-310, TANITA, Arlington Heights, IL, USA). Prior to testing, all participants were instructed to remove any traces of metal that were present (cellphone, keys, jewelry, etc.). Participants then laid supine position dressed in either shorts or a gown, and were aligned on the table by a trained research assistant. Once a centered alignment was achieved, the participants were then instructed to lay still for approximately 7 min while a low dose of radiation scanned their entire body. For DXA measurements, previous test–retest reliability in our lab are as follows: Fat Mass: ICC = 0.998; Lean Mass: ICC = 1.00; percent body fat: ICC = 0.998. All DXA scans were conducted by the same technician, analyzed with the image compare mode for serial exam software feature, and followed strict manufacturer guidelines for calibration and testing procedures as per previously published work ( Wilborn et al., 2013 ).

Maximal Strength : Upper and lower body strength was assessed by 1RM testing of the bench press (1RMBP) exercises followed by the parallel back squat (1RMBS). Subjects reported to the lab having refrained from any exercise other than activities of daily living for at least 48 h prior to baseline testing and at least 48 h prior to testing at the conclusion of the study. Repetition maximum testing was consistent with recognized guidelines as established by the National Strength and Conditioning Association ( Baechle & Earle, 2008 ). In brief, subjects performed a general warm-up prior to testing consisting of light cardiovascular exercise lasting approximately 5–10 min. A specific warm-up set of the given exercise of five repetitions was performed at ∼50% of the subject’s estimated 1RM followed by one to two sets of 2–3 repetitions at a load corresponding to ∼60–80% of estimated 1RM. Subjects then performed sets of 1 repetition of increasing weight for 1RM determination. Three to 5 min rest was provided between each successive attempt. All 1RM determinations were made within five attempts. Subjects were required to reach parallel in the 1RMBS, defined as the point at which the femur is parallel to the floor, for the attempt to be considered successful as determined by the trainer. Successful 1RMBP was achieved if the subject displayed a five-point body contact position (head, upper back and buttocks firmly on the bench with both feet flat on the floor) and executed a full lock-out. 1RMBS testing was conducted prior to 1RMBP with a 5 min rest period separating tests. All strength testing took place using free weights. Recording of foot and hand placement was made during baseline 1RM testing and then used for post-study performance. All testing sessions were supervised by two fitness professionals to achieve a consensus for success on each attempt.

Statistical analysis

Data were analyzed using a linear mixed model for repeated measures, estimated by a restricted maximum likelihood algorithm. Treatment was included as the between-subject factor, time was included as the repeated within-subjects factor, time × treatment was included as the interaction, and subject was included as a random effect. Repeated covariance structures were specified as either Hyunh-Feldt or compound symmetry, depending on which structure resulted in the best model fit as determined by Hurvich and Tsai’s Akaike’s information corrected criterion ( Hurvich & Tsai, 1989 ). As only significant main effects of time were observed, post-hoc analyses on main effects for time were done using multiple t -tests, with adjusted p -values from the simulated distribution of the maximum or maximum absolute value of a multivariate t random vector ( Edwards & Berry, 1987 ). Effect sizes were calculated as the mean pre-post change divided by the pooled pretest standard deviation ( Morris, 2008 ). Cohen’s D classification of small (0.2), medium (0.5), and large (0.8) were used to denote the magnitude of effects ( Cohen, 1988 ). All analyses were performed using SAS Version 9.2 (Cary, NC, USA). Effects were considered significant at P ≤ 0.05. Data are reported as x ¯ ± SD unless otherwise specified.

The total number of subjects initially enrolled was 59. During the course of the study, 38 subjects dropped out for the following reasons: Eight failed to follow up; 11 failed to comply with the study requirements; 10 did not have time in schedule to participate; four sustained an injury that disabled them from completing the testing protocol; three passed the deadline for study completion so their participation was suspended; and two moved away and thus were unavailable for testing sessions. Thus, 21 subjects ultimately completed the study. Attendance for those completing the study was 97.3%. All results are presented in Table 1 .

Study outcomes.

	PRE T1	PRE T2	PRE T3	POST T1	POST T2	POST T3	value for group	value for time	value for group by time interaction	PRE effect size T1–T3	POST effect size T1–T3
Body weight (kg)	86.3 ± 17.8	85.4 ± 15.5	84.7 ± 15.9	80.3 ± 9.3	79.4 ± 9.1	79.6 ± 8.4	0.31	0.07	0.65	−0.12	−0.05
BM (DEXA) (kg)	79.9 ± 17.3	79.1 ± 14.8	78.4 ± 15.3	74.1 ± 9.0	73.0 ± 8.8	73.4 ± 8.1	0.32	0.09	0.52	−0.11	−0.05
Left arm TM (kg)	5.3 ± 1.0	5.2 ± 0.9	5.2 ± 1.2	4.6 ± 0.6	4.6 ± 0.6	4.6 ± 0.5	0.08	0.57	0.97	−0.08	−0.05
Right arm TM (kg)	5.4 ± 1.0	5.3 ± 0.7	5.4 ± 1.0	5.0 ± 0.7	4.8 ± 0.6	5.1 ± 0.7	0.20	0.18	0.53	−0.01	0.10
Left leg TM (kg)	14.4 ± 3.4	14.3 ± 2.8	14.1 ± 3.1	13.4 ± 1.9	13.3 ± 1.9	13.2 ± 1.8	0.39	0.45	0.96	−0.08	−0.08
Right leg TM (kg)	14.8 ± 3.5	14.9 ± 3.1	14.7 ± 3.3	13.7 ± 2.0	13.8 ± 2.1	13.6 ± 1.9	0.34	0.67	0.93	−0.01	−0.06
Total FM (DEXA) (kg)	12.2 ± 9.0	11.8 ± 9.3	10.9 ± 7.9	8.9 ± 3.5	8.1 ± 2.8	7.9 ± 2.4	0.24	0.001	0.58	−0.20	−0.16
BF% (DEXA)	14.1 ± 6.4	13.8 ± 7.4	12.9 ± 5.9	12.0 ± 4.5	11.1 ± 3.7	10.8 ± 3.2	0.34	0.002	0.66	−0.23	−0.24
Left arm FM (kg)	0.6 ± 0.3	0.5 ± 0.3	0.5 ± 0.4	0.5 ± 0.2	0.4 ± 0.1	0.4 ± 0.1	0.26	0.008	0.80	−0.15	−0.23
Right arm FM (kg)	0.5 ± 0.3	0.5 ± 0.3	0.5 ± 0.3	0.5 ± 0.2	0.4 ± 0.1	0.4 ± 0.1	0.25	0.09	0.52	−0.16	−0.19
Left leg FM (kg)	2.4 ± 1.8	2.2 ± 1.6	2.1 ± 1.5	1.6 ± 0.7	1.5 ± 0.5	1.4 ± 0.5	0.17	0.0005	0.42	−0.23	−0.12
Right leg FM (kg)	2.5 ± 1.8	2.4 ± 1.8	2.3 ± 1.7	1.7 ± 0.6	1.6 ± 0.6	1.6 ± 0.4	0.16	0.02	0.85	−0.15	−0.11
Total LM (DEXA) (kg)	64.5 ± 8.9	64.6 ± 5.5	64.8 ± 7.4	62.6 ± 8.3	65.1 ± 12.2	63.0 ± 7.4	0.76	0.58	0.58	0.04	0.05
Left arm LM (kg)	4.5 ± 0.7	4.4 ± 0.7	4.5 ± 0.8	4.0 ± 0.6	3.9 ± 0.6	4.0 ± 0.5	0.09	0.74	0.93	−0.05	0.02
Right arm LM (kg)	4.6 ± 0.8	4.6 ± 0.5	4.6 ± 0.7	4.3 ± 0.6	4.2 ± 0.6	4.4 ± 0.6	0.25	0.09	0.55	0.03	0.19
Left leg LM (kg)	11.3 ± 1.5	11.5 ± 1.1	11.4 ± 1.4	11.2 ± 1.8	11.2 ± 1.9	11.2 ± 1.7	0.78	0.91	0.81	0.04	−0.04
Right leg LM (kg)	11.7 ± 1.6	11.9 ± 1.3	11.8 ± 1.5	11.4 ± 1.9	11.6 ± 1.9	11.4 ± 1.7	0.67	0.57	0.84	0.09	−0.02
Biceps T	41.5 ± 4.9	40.9 ± 6.0	42.1 ± 6.3	36.3 ± 4.1	36.7 ± 4.1	39.2 ± 5.9	0.06	0.09	0.48	0.12	0.57
Triceps T	51.5 ± 9.3	50.8 ± 9.3	51.9 ± 8.8	53.5 ± 7.5	50.2 ± 8.9	54.0 ± 6.5	0.74	0.23	0.61	0.05	0.06
Lateral quad T	56.6 ± 4.7	55.0 ± 5.2	54.1 ± 4.7	54.9 ± 7.2	56.0 ± 7.3	53.5 ± 6.1	0.76	0.19	0.69	−0.40	−0.23
Medial quad T	65.4 ± 6.7	66.9 ± 8.1	64.5 ± 11.8	67.6 ± 7.6	67.9 ± 8.1	68.6 ± 7.0	0.47	0.77	0.52	−0.13	0.14
Squat 1-RM	159 ± 22	164 ± 23	165 ± 23	146 ± 28	150 ± 25	154 ± 21	0.23	0.003	0.73	0.24	0.30
Bench 1-RM	124 ± 16	126 ± 20	126 ± 18	117 ± 23	118 ± 23	121 ± 22	0.48	0.07	0.50	0.15	0.20

Figures 1 and and2 2 graphically illustrate the energy and macronutrient intake of the subjects, respectively. There was no significant group by time interaction ( P = 0.18) or group effect ( P = 0.30) for self-reported calorie intake. There was a significant effect of time ( P = 0.02), with calorie intake at T2 being significantly lower than T1 (adjusted P = 0.02). There were no significant interactions or main effects for self-reported protein or carbohydrate intake ( P = 0.22–0.78). For self-reported fat intake, there was no significant group by time interaction ( P = 0.43) or group effect ( P = 0.35), but there was a significant effect of time ( P = 0.0008), with fat intake being significantly lower at T2 and T3 compared to T1 (adjusted P = 0.001–0.02).

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T1, Baseline; T2, Midpoint; T3, Endpoint. Data are presented as means ± SD. ∗ , significantly different from T1 ( P < 0.05).

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T1, Baseline; T2, Midpoint; T3, Endpoint. Data are presented as means ±SD. ∗ , significantly different from T1 ( P < 0.05).

For body weight and DXA-determined total mass, probability approached significance for an effect of time ( P = 0.07–0.09), with a tendency for weight and DXA-determined total mass to decrease from baseline to week 10 in both groups. For left-arm total mass, probability approached significance for an effect of group ( P = 0.08), with group PRE-SUPP having a tendency for greater left arm total mass compared to group POST-SUPP. There were no other significant effects or interactions for body mass or segmental total mass. Effect sizes were small for both groups.

There was a significant effect of time for left arm fat mass ( P = 0.008). Post-hoc analysis revealed significantly lower left arm fat mass at T2 and T3 compared to T1 (adjusted P = 0.01–0.02). Probability approached significance for right arm fat mass to decrease from baseline to week 10 ( P = 0.09). For left leg fat mass, there was a significant effect of time ( P = 0.0005). Post-hoc analysis revealed significantly lower left leg fat mass at T2 and T3 compared to T1 (adjusted P = 0.0004–0.01). Right leg fat mass also showed a significant effect of time ( P = 0.02), with right leg fat mass being lower at T3 compared to T1 (adjusted P = 0.02). For overall fat mass, there was a significant effect of time ( P = 0.001), with fat mass at T3 being significantly lower than T1 (adjusted P = 0.0004). Total DXA-determined body fat percentage showed a significant effect of time ( P = 0.002), with T3 being significantly lower than T1 (adjusted P = 0.001). Effect sizes were small for both groups. Overall the findings show a modest reduction in body fat for both groups over the course of the study.

For left arm lean mass, probability approached significance for an effect of group ( P = 0.09), with group PRE-SUPP having a tendency for greater left arm lean mass compared to group POST-SUPP. For right arm lean mass, probability approached significance for an effect of time ( P = 0.09), with a tendency for right arm lean mass to increase from baseline to week 10. There were no other significant effects or interactions for total lean mass or segmental lean mass. Effect sizes were small for both groups. Overall the findings show little change in lean mass across groups.

Muscle thickness

For biceps thickness, probability approached significance for an effect of group ( P = 0.06), with group POST-SUPP tending to be greater than group PRE-SUPP. In addition, probability approached significance for an effect of time ( P = 0.09), with a tendency for biceps thickness to increase from baseline to week 10. There were no other significant effects or interactions for measures of muscle thickness. Effect sizes were small for both groups, with the exception of biceps thickness, which showed a moderate effect size in POST-SUPP. Overall the findings show a modest advantage for POST-SUPP on increases in biceps thickness, with minimal changes in other hypertrophic measures. Individual changes in muscle thickness are displayed in Figs. 3 – 5 .

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Individual changes in biceps thickness for PRE and POST. Values in mms. T1, Baseline; T3, Endpoint.

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Individual changes in lateral quadriceps thickness for PRE and POST. Values in mms. T1, Baseline; T3, Endpoint.

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Individual changes in medial quadriceps thickness for PRE and POST. Values in mms. T1, Baseline; T3, Endpoint.

Maximal strength

There was a significant effect of time for 1RM squat ( P = 0.003), with T3 being significantly greater than T1 (adjusted P = 0.002). For 1RM bench, probability approached significance for an effect of time ( P = 0.07), with a tendency for an increase from baseline to week 10. Effect sizes were small for both groups.

To the authors’ knowledge, this is the first study to directly investigate muscular adaptations when consuming protein either immediately before or after resistance exercise in a cohort of trained young men. The primary and novel finding of this study was that, consistent with the research hypothesis, the timing of protein consumption had no significant effect on any of the measures studied over a 10-week period. Given that the PRE-SUPP group did not consume protein for at least 3 h post-workout, these findings refute the contention that a narrow post-exercise anabolic window of opportunity exists to maximize the muscular response and instead lends support to the theory that the interval for protein intake may be as wide as several hours or perhaps more after a training bout depending on when the pre-workout meal was consumed.

Both PRE-SUPP and POST-SUPP groups significantly increased maximal squat strength by 3.7% and 4.9%, respectively. Moreover, probability approached significance for greater changes in maximal bench press strength for PRE-SUPP and POST-SUPP, with increases of 2.4% and 3.3%, respectively. There were no significant differences in either of these measures between groups. Our findings are consistent with those of Candow et al. (2006) , who found that consumption of a 0.3 g/kg protein dose either before or after resistance training produced similar increases in 1RM leg press and bench press in a cohort of untrained elderly men over 12 weeks. Conversely, the findings are somewhat in contrast with those of Esmarck et al. (2001) , who found that consuming an oral liquid protein dose immediately after exercise produced markedly greater absolute increases in dynamic strength compared to delaying consumption for 2 h post-workout (46% versus 36%, respectively), although the values did not reach statistical significance. The reasons for discrepancies between studies is not clear at this time.

Neither group demonstrated significant gains in lean mass of the arms or legs over the course of the study. With respect to direct measures of muscle growth, probability approached significance for an increase in biceps brachii thickness ( p = 0.06) while no significant changes were noted in the triceps brachii and quadriceps femoris. No interactions were found between groups for any of these outcomes. Results are again consistent with those of Candow et al. (2006) , who found similar increases in muscle thickness of the extremities regardless of whether protein was consumed before or after training. Alternatively, our findings are in sharp contrast to those of Esmarck et al. (2001) , who reported a 6.3% increase in muscle cross sectional area in a cohort of elderly men who received protein immediately after resistance training while those delaying consumption for 2 h displayed no hypertrophic changes. The findings of Esmarck et al. (2001) are curious given that numerous studies show marked hypertrophy in an elderly population where no specific dietary restrictions were provided ( Frontera et al., 1988 ; Tracy et al., 1999 ; Ivey et al., 2000 ; Roth et al., 2001 ); it therefore seems illogical that delaying protein consumption for just 2 h post-exercise would completely eliminate any increases in muscle protein accretion. Moreover, subjects in Esmarck et al. (2001) study who consumed protein immediately post-workout experienced gains similar to that shown in other research studies that did not provide a timed protein dose ( Verdijk et al., 2009 ; Frontera et al., 1988 ; Godard, Williamson & Trappe, 2002 ). Thus, there did not appear to be a potentiating effect of post-exercise supplementation in Esmarck et al. (2001) study. Considering the very small sample size of the non-timed group ( n = 6), this calls into question the validity of results and raises the possibility that findings were due to a statistical anomaly.

Acute studies attempting to determine an “anabolic window” relative to the resistance training bout have failed to yield consistent results. In a similar way that temporal comparisons of nutrient administration in the post-exercise period have been equivocal ( Levenhagen et al., 2001 ; Rasmussen et al., 2000 ), comparisons of whether protein/amino acid administration is more effective pre- or post-exercise have also been conflicting. Tipton et al. (2001) reported that 6 g essential amino acids (EAA) co-ingested with 35 g sucrose immediately pre-exercise resulted in a significantly greater and more sustained MPS response compared to immediate post-exercise ingestion of the same treatment. A subsequent investigation by Tipton et al. (2007) reported no difference in net muscle protein balance between 20 g whey protein ingested immediately pre- versus immediately post-exercise. Although it is tempting to assume that there is an inherent difference in whole protein versus free amino acids, Fujita et al. (2009) reported similar increases in post-exercise MPS when healthy, young subjects consumed a solution of EAA (0.35 g/kg/FFM) −1 and carbohydrate (0.5 g/kg/FFM) −1 versus being fasted prior to a bout of high-intensity lower body resistance training. Collectively, the acute data do not indicate conclusive evidence of a specific temporal dosing bracket where intact protein or amino acid administration enhances resistance training adaptations.

A caveat to our findings is that despite extensive counseling efforts to ensure that subjects maintained a consistent caloric surplus, both groups substantially reduced their energy intake from baseline. The reason for this discrepancy is not clear, but it can be speculated that subjects may have considered the supervised study an opportunity to lose body fat while gaining muscle, and thus taken it upon themselves to adjust energy intake accordingly. The reduction in calories over the study period resulted in a significant reduction in body fat, with losses of 1.3 and 1.0 kg for PRE-SUPP and POST-SUPP, respectively. It is well-documented that maintaining a caloric deficit is suboptimal for building muscle. In the absence of regimented exercise, there is generally a loss of lean body mass; for every pound of weight lost, approximately 25% comes from FFM ( Varady, 2011 ). Adoption of a higher protein diet and regular resistance training can attenuate these losses and even promote slight increases in muscle mass depending on factors including training status, initial body fat levels, and the extent of caloric restriction ( Garthe et al., 2011 ; Stiegler & Cunliffe, 2006 ). That said, to achieve robust hypertrophic gains requires a sustained non-negative energy balance ( Garthe et al., 2013 ). Taken in this context, our findings indicate that PRE-SUPP and POST-SUPP strategies are similarly effective in enhancing muscle development during calorically-restricted fat loss and cannot necessarily be extrapolated to a mass-building program that incorporates an energy surplus.

The study had several notable limitations. First, the sample size was fairly small, increasing the possibility of null findings due to type II errors. Second, subjects trained using a 3-day-a-week resistance training program. Given that subjects were resistance-trained men with ample lifting experience, it is possible that a higher volume routine might have produced different results. Third, the free-living nature of the study prevented close monitoring of activity levels outside of the research setting, and it remains possible that this may have impacted results. Fourth, the study did not have a wash-out period; thus, differences between the study protocol from the subject’s pre-training routine may have influenced results from a novelty standpoint. Fifth, we did not monitor energy expenditure outside of training sessions as well as during sleep; it is unclear whether the timing would have affected such outcomes. Sixth, self-report dietary records are known to have a high degree of variance from actual nutritional intake ( Mertz et al., 1991 ); thus, caution must be used in the interpretation of food-consumption data. Seventh, the study employed a 3 day-per-week total body RT routine. Although this routine has been shown to produce significant hypertrophic increases in the target population ( Schoenfeld et al., 2015a ; Schoenfeld et al., 2015b ; Schoenfeld et al., 2016 ), it remains possible that results may have differed if subjects trained with a split-body routine that allowed for a greater total weekly training. Eighth, DXA has been shown to be prone to potential confounding by changes in hydration status ( Nana et al., 2012 ). Although we attempted to minimize these changes by instructing subjects to refrain from physical activity and food consumption prior to testing, it remains possible that body composition changes were influenced by alterations in hydration. Finally, muscle thickness was measured only at the middle portion of the muscle. Although this region is generally considered to be indicative of whole muscle growth, we cannot rule out the possibility that greater changes in proximal or distal muscle thickness occurred in one protocol versus the other.

It has been hypothesized that protein ingestion in the immediate post-exercise period is the most critical nutrient timing strategy for stimulating MPS, and on a chronic basis, optimizing muscular adaptations. In the face of this common presumption, the comparison of protein timed immediately pre- versus post-exercise has both theoretical and practical importance due to individual variations in the availability and/or convenience of protein dosing relative to training. In the present study, the presence of a narrow “anabolic window of opportunity” was not demonstrated as reflected by the fact that PRE-SUPP group showed similar changes in body composition and strength to those who consumed protein immediately post-exercise. Across the range of measures, there were no meaningful results consistently attributable to pre- versus post-exercise protein ingestion. The implications of these findings are that the trainee is free to choose, based on individual factors (i.e., preference, tolerance, convenience, and availability), whether to consume protein immediately pre- or post-exercise.

Nevertheless, the conditions of the present study warrant consideration. Despite specific instruction to maintain a caloric surplus, subjects fell into hypocaloric balance (objectively indicated by bodyweight and fat mass reductions). This raises the possibility that the results might be limited to scenarios where there is a sustained energy deficit. Previous work recommends covering the bases by ingesting protein at 0.4–0.5 g/kg of lean body mass in both the pre- and post-exercise periods ( Aragon & Schoenfeld, 2013 ). This seems to be a prudent approach in the face of uncertainty regarding the optimization of nutrient timing factors for the objectives of muscle hypertrophy and strength.

Supplemental Information

Acknowledgments.

We would like to extend our gratitude to Dymatize Nutrition for providing the protein supplements used in this study.

Funding Statement

The authors received no funding for this work.

Additional Information and Declarations

James Krieger is an employee of Weightology.

Brad Jon Schoenfeld conceived and designed the experiments, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Alan Aragon wrote the paper, reviewed drafts of the paper.

Colin Wilborn performed the experiments, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Stacie L. Urbina and Sara E. Hayward performed the experiments, wrote the paper, reviewed drafts of the paper.

James Krieger wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers):

University of Mary Hardin-Baylor Institutional Review Board.

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Examination of a Multi-ingredient Preworkout Supplement on Total Volume of Resistance Exercise and Subsequent Strength and Power Performance

Introduction

Experimental Approach to the Problem

Body Composition Assessments

1-Repetition Maximum Testing

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Isokinetic Testing

Bench Throw Test

Cycling Protocol

Resistance Exercise Protocol

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Pre- versus post-exercise protein intake has similar effects on muscular adaptations

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The effects of a pre-workout supplement containing caffeine, creatine, and amino acids during three weeks of high-intensity exercise on aerobic and anaerobic performance

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Frailty as a sequela of burn injury: a post hoc analysis of the “RE-ENERGIZE” multicenter randomized-controlled trial and the National Health Interview Survey

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FRAIL (Fatigue, Resistance, Ambulation, Illness, Loss of weight) scale

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TBSA and frailty in the burn population

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Pre- versus post-exercise protein intake has similar effects on muscular adaptations

Alan Aragon

Colin Wilborn

Stacie L. Urbina