Publications by authors named "Matthew T Stratton"

24 Publications

  • Page 1 of 1

Cross-sectional and longitudinal associations between subcutaneous adipose tissue thickness and dual-energy X-ray absorptiometry fat mass.

Clin Physiol Funct Imaging 2021 Nov 22;41(6):514-522. Epub 2021 Sep 22.

Energy Balance and Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, Texas, USA.

The present study examined cross-sectional and longitudinal relationships between total and segmental subcutaneous tissue thicknesses from ultrasonography (US) and total and segmental fat mass (FM) estimates from dual-energy X-ray absorptiometry (DXA). Traditional US FM estimates were also examined. Twenty resistance-trained males (mean ± SD; age: 22.0 ± 2.6 years; body mass: 74.8 ± 11.5 kg; DXA fat: 17.5 ± 4.5%) completed a 6-week supervised resistance training programme while consuming a hypercaloric diet. Pre- and post-intervention body composition was assessed by DXA and B-mode US. Data were analysed using Pearson's correlation (r), Lin's correlation coefficient (CCC), paired t-tests, Wilcoxon signed-rank tests and Bland-Altman analysis, as appropriate. Cross-sectionally, correlations were observed between total DXA FM and total subcutaneous tissue thickness (r = 0.88). Longitudinally, a correlation was observed between total DXA FM changes and total subcutaneous tissue changes (r = 0.49, CCC = 0.38). Correlations of similar magnitudes were observed for the upper body and trunk estimates, but DXA FM changes were unrelated to subcutaneous tissue changes for the lower body and arms. Cross-sectionally, US 2-compartment FM and DXA FM were correlated (r = 0.91, CCC = 0.83). Longitudinally, a weaker correlation was observed (r = 0.47, CCC = 0.33). In summary, longitudinal associations between US and DXA are weaker than cross-sectional relationships; additionally, correlations between US subcutaneous tissue and whole-body DXA FM appear to be driven by the trunk region rather than appendages. Reporting raw skinfold thicknesses rather than FM estimates alone may improve the utility of techniques based on subcutaneous tissue thickness, such as US and skinfolds.
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http://dx.doi.org/10.1111/cpf.12727DOI Listing
November 2021

Tracking changes in body composition: comparison of methods and influence of pre-assessment standardisation.

Br J Nutr 2021 Jul 30:1-19. Epub 2021 Jul 30.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, USA.

The present study reports the validity of multiple assessment methods for tracking changes in body composition over time and quantifies the influence of unstandardised pre-assessment procedures. Resistance-trained males underwent 6 weeks of structured resistance training alongside a hyperenergetic diet, with four total body composition evaluations. Pre-intervention, body composition was estimated in standardised (i.e. overnight fasted and rested) and unstandardised (i.e. no control over pre-assessment activities) conditions within a single day. The same assessments were repeated post-intervention, and body composition changes were estimated from all possible combinations of pre-intervention and post-intervention data. Assessment methods included dual-energy X-ray absorptiometry (DXA), air displacement plethysmography, three-dimensional optical imaging, single- and multi-frequency bioelectrical impedance analysis, bioimpedance spectroscopy and multi-component models. Data were analysed using equivalence testing, Bland-Altman analysis, Friedman tests and validity metrics. Most methods demonstrated meaningful errors when unstandardised conditions were present pre- and/or post-intervention, resulting in blunted or exaggerated changes relative to true body composition changes. However, some methods - particularly DXA and select digital anthropometry techniques - were more robust to a lack of standardisation. In standardised conditions, methods exhibiting the highest overall agreement with the four-component model were other multi-component models, select bioimpedance technologies, DXA and select digital anthropometry techniques. Although specific methods varied, the present study broadly demonstrates the importance of controlling and documenting standardisation procedures prior to body composition assessments across distinct assessment technologies, particularly for longitudinal investigations. Additionally, there are meaningful differences in the ability of common methods to track longitudinal body composition changes.
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http://dx.doi.org/10.1017/S0007114521002579DOI Listing
July 2021

Comparison of Indirect Calorimetry and Common Prediction Equations for Evaluating Changes in Resting Metabolic Rate Induced by Resistance Training and a Hypercaloric Diet.

J Strength Cond Res 2021 Jun 22. Epub 2021 Jun 22.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, Texas.

Abstract: Rodriguez, C, Harty, PS, Stratton, MT, Siedler, MR, Smith, RW, Johnson, BA, Dellinger, JR, Williams, AD, White, SJ, Benavides, ML, and Tinsley, GM. Comparison of indirect calorimetry and common prediction equations for evaluating changes in resting metabolic rate induced by resistance training and a hypercaloric diet. J Strength Cond Res XX(X): 000-000, 2021-The ability to accurately identify resting metabolic rate (RMR) changes over time allows practitioners to prescribe appropriate adjustments to nutritional intake. However, there is a lack of data concerning the longitudinal utility of commonly used RMR prediction equations. The purpose of this study was to evaluate the validity of several commonly used prediction equations to track RMR changes during a hypercaloric nutritional intervention and supervised resistance exercise training program. Twenty resistance-trained men completed the study. The protocol lasted 6 weeks, and subjects underwent RMR assessments by indirect calorimetry (IC) preintervention and postintervention to obtain reference values. Existing RMR prediction equations based on body mass (BM) or dual-energy X-ray absorptiometry fat-free mass (FFM) were also evaluated. Equivalence testing was used to evaluate whether each prediction equation demonstrated equivalence with IC. Null hypothesis significance testing was also performed, and Bland-Altman analysis was used alongside linear regression to assess the degree of proportional bias. Body mass and FFM increased by 3.6 ± 1.7 kg and 2.4 ± 1.6 kg, respectively. Indirect calorimetry RMR increased by 165 ± 97 kcal·d-1, and RMR:FFM increased by 5.6 ± 5.2%. All prediction equations underestimated mean RMR changes relative to IC, with magnitudes ranging from 75 to 155 kcal·d-1, while also displaying unacceptable levels of negative proportional bias. In addition, no equation demonstrated equivalence with IC. Common RMR prediction equations based on BM or FFM did not fully detect the increase in RMR observed with resistance training plus a hypercaloric diet. Overall, the evaluated prediction equations are unsuitable for estimating RMR changes in the context of this study.
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http://dx.doi.org/10.1519/JSC.0000000000004077DOI Listing
June 2021

Endocrine and Body Composition Changes Across a Competitive Season in Collegiate Speed-Power Track and Field Athletes.

J Strength Cond Res 2021 Aug;35(8):2067-2074

Exercise Science and Sport Management, Kennesaw State University, Kennesaw, Georgia; and.

Abstract: Mangine, GT, Eggerth, A, Gough, J, Stratton, MT, Feito, Y, and VanDusseldorp, TA. Endocrine and body composition changes across a competitive season in collegiate speed-power track and field athletes. J Strength Cond Res 35(8): 2067-2074, 2021-Maintaining lean mass is important for track and field (TF) athletes who compete in speed-power events, but little is known about how lean mass and related hormones might change over an 8- to 10-month collegiate season. Therefore, to monitor changes in free testosterone (T), cortisol (C), and body composition in TF athletes across their entire competitive season, 9 female (20.3 ± 1.2 years, 169 ± 5 cm, and 67.6 ± 8.5 kg) and 7 male (21.1 ± 2.0 years, 181 ± 9 cm, and 77.3 ± 5.9 kg) Division I TF athletes provided resting and fasted blood samples at the onset of their indoor season (baseline), before and on returning from the indoor conference championships (ICCs), at the beginning and end of a heavy midseason training week (HVY), and before leaving for the National Collegiate Athletic Association (NCAA) Championships. Body composition was also assessed at each of these periods using a 4-compartment model. Except for a 20% reduction (p = 0.030) from ICCs to the onset of HVY in men only, linear mixed models with repeated measures did not reveal any changes in hormone concentrations. Compared with baseline, an overall increase in fat-free mass was observed at HVY (∼2.74%, p = 0.023) before it reduced by 3.81% before the NCAA Championships (p = 0.022). Despite variations in training and competition, resting concentrations of hormones indicative of anabolic status remained relatively consistent over the course of an entire season in speed-power TF athletes. Coaches and athletes may consider monitoring these variables to assess the athlete's response to the changing demands of a competitive season.
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http://dx.doi.org/10.1519/JSC.0000000000004069DOI Listing
August 2021

Predicting Adaptations to Resistance Training Plus Overfeeding Using Bayesian Regression: A Preliminary Investigation.

J Funct Morphol Kinesiol 2021 Apr 21;6(2). Epub 2021 Apr 21.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX 79409, USA.

Relatively few investigations have reported purposeful overfeeding in resistance-trained adults. This preliminary study examined potential predictors of resistance training (RT) adaptations during a period of purposeful overfeeding and RT. Resistance-trained males ( = 28; = 21 completers) were assigned to 6 weeks of supervised RT and daily consumption of a high-calorie protein/carbohydrate supplement with a target body mass (BM) gain of ≥0.45 kg·wk. At baseline and post-intervention, body composition was evaluated via 4-component (4C) model and ultrasonography. Additional assessments of resting metabolism and muscular performance were performed. Accelerometry and automated dietary interviews estimated physical activity levels and nutrient intake before and during the intervention. Bayesian regression methods were employed to examine potential predictors of changes in body composition, muscular performance, and metabolism. A simplified regression model with only rate of BM gain as a predictor was also developed. Increases in 4C whole-body fat-free mass (FFM; (mean ± SD) 4.8 ± 2.6%), muscle thickness (4.5 ± 5.9% for elbow flexors; 7.4 ± 8.4% for knee extensors), and muscular performance were observed in nearly all individuals. However, changes in outcome variables could generally not be predicted with precision. Bayes R values for the models ranged from 0.18 to 0.40, and other metrics also indicated relatively poor predictive performance. On average, a BM gain of ~0.55%/week corresponded with a body composition score ((∆FFM/∆BM)*100) of 100, indicative of all BM gained as FFM. However, meaningful variability around this estimate was observed. This study offers insight regarding the complex interactions between the RT stimulus, overfeeding, and putative predictors of RT adaptations.
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http://dx.doi.org/10.3390/jfmk6020036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167794PMC
April 2021

Longitudinal agreement of four bioimpedance analyzers for detecting changes in raw bioimpedance during purposeful weight gain with resistance training.

Eur J Clin Nutr 2021 07 16;75(7):1060-1068. Epub 2021 Mar 16.

Energy Balance & Body Composition Laboratory; Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, USA.

Background: Due to inherent errors involved in the transformation of raw bioelectrical variables to body fluids or composition estimates, the sole use of resistance (R), reactance (Xc), and phase angle (φ) has been advocated when quantifying longitudinal changes. The aim of this investigation was to assess the ability of four bioimpedance analyzers to detect raw bioimpedance changes induced by purposeful weight gain with resistance training.

Methods: Twenty-one resistance trained males completed a 6-week lifestyle intervention with the aim of purposeful weight gain. Bioimpedance analysis was performed before and after the intervention using four different analyzers (MFBIA: InBody 770; MFBIA: Seca mBCA 515/514; BIS: ImpediMed SFB7; SFBIA: RJL Quantum V) for the quantification of R, Xc, and φ at the 50-kHz frequency. Repeated measures ANOVA and follow up tests were performed.

Results: Analysis revealed main effects of time and method for R, Xc, and φ (p ≤ 0.02), without significant time x method interactions (p ≥ 0.07). Follow up for time main effects indicated that, on average, R decreased by 4.5-5.8%, Xc decreased by 2.3-4.0%, and φ increased by 1.8-2.6% across time for all analyzers combined. However, varying levels of disagreement in absolute values were observed for each bioelectrical variable.

Conclusions: The differences in absolute bioelectrical values suggests that analyzers should not be used interchangeably, which holds particular importance when reference values are utilized. Despite absolute differences, analyzers with varying characteristics demonstrated similar abilities to detect changes in R, Xc, and φ over time.
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http://dx.doi.org/10.1038/s41430-020-00811-3DOI Listing
July 2021

Agreement of bioelectrical resistance, reactance, and phase angle values from supine and standing bioimpedance analyzers.

Physiol Meas 2021 Feb 16. Epub 2021 Feb 16.

Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, Texas, UNITED STATES.

Objective: Bioimpedance devices are commonly used to assess health parameters and track changes in body composition. However, the cross-sectional agreement between different devices has not been conclusively established. Thus, the objective of this investigation was to examine the agreement between raw bioelectrical variables (resistance, reactance, and phase angle at the 50-kHz frequency) obtained from three bioimpedance analyzers.

Approach: Healthy male (n=76, Mean±SD; 33.8±14.5 years; 83.9±15.1 kg; 179.4±6.9 cm) and female (n=103, Mean±SD; 33.4±15.9 years; 65.6±12.1 kg; 164.9±6.4 cm) participants completed assessments using three bioimpedance devices: supine bioimpedance spectroscopy (BIS), supine single-frequency bioelectrical impedance analysis (SFBIA), and standing multi-frequency bioelectrical impedance analysis (MFBIA). Differences in raw bioelectrical variables between the devices were quantified via one-way analysis of variance for the total sample and for each sex. Equivalence testing was used to determine equivalence between methods.

Main Results: Significant differences in all bioelectrical variables were observed between the three devices when examining the total sample and males only. The devices appeared to exhibit slightly better agreement when analyzing female participants only. Equivalence testing using the total sample as well as males and females separately revealed that resistance and phase angle were equivalent between the supine devices (BIS, SFBIA), but not with the standing analyzer (MFBIA).

Significance: The present study demonstrated disagreement between different bioimpedance analyzers for quantifying raw bioelectrical variables, with the poorest agreement between devices that employed different body positions during testing. These results suggest that researchers and clinicians should employ device-specific reference values to classify participants based on raw bioelectrical variables, such as phase angle. If reference values are needed but are unavailable for a particular bioimpedance analyzer, the set of reference values produced using the most similar analyzer and reference population should be selected.
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http://dx.doi.org/10.1088/1361-6579/abe6faDOI Listing
February 2021

Correction to: Effects of Bang® Keto Coffee Energy Drink on Metabolism and Exercise Performance in Resistance-Trained Adults: A Randomized, Double-blind, Placebo-controlled, Crossover Study.

J Int Soc Sports Nutr 2020 09 15;17(1):48. Epub 2020 Sep 15.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, 79424, USA.

An amendment to this paper has been published and can be accessed via the original article.
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http://dx.doi.org/10.1186/s12970-020-00378-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491167PMC
September 2020

Fat-free mass characteristics vary based on sex, race, and weight status in US adults.

Nutr Res 2020 09 12;81:58-70. Epub 2020 Jul 12.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University. 3204 Main St, Lubbock, TX 79409, USA.

Common body composition estimation techniques necessitate assumptions of uniform fat-free mass (FFM) characteristics, although variation due to sex, race, and body characteristics may occur. National Health and Nutrition Examination Survey data from 1999 to 2004, during which paired dual-energy x-ray absorptiometry (DXA) and bioimpedance spectroscopy assessments were performed, were used to estimate FFM characteristics in a sample of 4619 US adults. Calculated FFM characteristics included the density and water, bone mineral, and residual content of FFM. A rapid 4-component model was also produced using DXA and bioimpedance spectroscopy data. Study variables were compared across sex, race/ethnicity, body mass index (BMI), and age categories using multiple pairwise comparisons. A general linear model was used to estimate body composition after controlling for other variables. Statistical analyses accounted for 6-year sampling weights and complex sampling design of the National Health and Nutrition Examination Survey and were based on 5 multiply imputed datasets. Differences in FFM characteristics across sex, race, and BMI were observed, with notable dissimilarities between men and women for all outcome variables. In racial/ethnic comparisons, non-Hispanic blacks most commonly presented distinct FFM characteristics relative to other groups, including greater FFM density and proportion of bone mineral. Body composition errors between DXA and the 4-component model were significantly influenced by sex, age, race, and BMI. In conclusion, FFM characteristics, which are often assumed in body composition estimation methods, vary due to sex, race/ethnicity, and weight status. The variation of FFM characteristics in diverse populations should be considered when body composition is evaluated.
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http://dx.doi.org/10.1016/j.nutres.2020.07.002DOI Listing
September 2020

Effects of Bang® Keto Coffee Energy Drink on Metabolism and Exercise Performance in Resistance-Trained Adults: A Randomized, Double-blind, Placebo-controlled, Crossover Study.

J Int Soc Sports Nutr 2020 08 24;17(1):45. Epub 2020 Aug 24.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, 79424, USA.

Background: Energy drinks are often consumed by the general population, as well as by active individuals seeking to enhance exercise performance and augment training adaptations. However, limited information is available regarding the efficacy of these products. Thus, the purpose of this study was to determine the effects of a commercially available caffeine- and protein-containing energy drink on metabolism and muscular performance.

Methods: Sixteen resistance-trained males (n = 8; mean ± SD; age: 22.4 ± 4.9 years; body mass: 78.8 ± 14.0 kg; body fat: 15.3 ± 6.4%) and females (n = 8; age: 24.5 ± 4.8 years; body mass: 67.5 ± 11.9 kg; body fat: 26.6 ± 7.1%) participated in this randomized, double-blind, placebo-controlled, crossover study. Following a familiarization visit, participants completed two identical visits to the laboratory separated by 5-10 days, each of which consisted of indirect calorimetry energy expenditure (EE) assessments before and after consumption of the beverage (Bang® Keto Coffee; 130 kcal, 300 mg caffeine, 20 g protein) or placebo (30 kcal, 11 mg caffeine, 1 g protein) as well as after exercise testing. In addition, participants' subjective feelings of energy, fatigue, and focus as well as muscular performance (leg press one-repetition maximum and repetitions to fatigue, maximal isometric and isokinetic squat testing) were assessed. Multiple repeated measures ANOVAs with Tukey post-hoc tests were used to analyze data. Estimates of effect size were quantified via partial eta squared (η) and Hedge's g.

Results: A significant interaction effect was identified for EE (p < 0.001, η = 0.52) but not respiratory exchange ratio (p = 0.17, η = 0.11). Following consumption of the beverage, EE was 0.18 [corrected]  kcal·min greater than placebo at the post-beverage time point (p < 0.001) and 0.08 [corrected]  kcal·min greater than placebo at the post-exercise time point (p = 0.011). However, no between-condition differences were detected for any subjective or muscular performance outcomes.

Conclusions: The results of this study suggest that consumption of the energy drink had minimal effects on lower-body muscular performance and subjective factors in the context of a laboratory setting. However, the beverage was found to significantly increase energy expenditure compared to placebo immediately following ingestion as well as during the recovery period after an exercise bout, suggesting that active individuals may improve acute metabolic outcomes via consumption of a caffeine- and protein-containing energy drink.

Trial Registration: This trial was prospectively registered at ClinicalTrials.gov (Identifier: NCT04180787 ; Registered 29 November 2019).
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http://dx.doi.org/10.1186/s12970-020-00374-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446127PMC
August 2020

A Field-based Three-Compartment Model Derived from Ultrasonography and Bioimpedance for Estimating Body Composition Changes.

Med Sci Sports Exerc 2021 03;53(3):658-667

Energy Balance and Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, TX.

Purpose: The purpose of this study was to assess the agreement between a field-based three-compartment (3CFIELD) model and a laboratory-based three-compartment (3CLAB) model for tracking body composition changes over time.

Methods: Resistance-trained males completed a supervised nutrition and resistance training intervention. Before and after the intervention, assessments were performed via air displacement plethysmography (ADP), bioimpedance spectroscopy (BIS), portable ultrasonography (US), and bioelectrical impedance analysis (BIA). ADP body density and BIS body water were used within the reference 3CLAB model, whereas US-derived body density and BIA body water were used within the 3CFIELD model. Two-compartment model body composition estimates provided by US and BIA were also examined. Changes in fat-free mass and fat mass were analyzed using repeated-measures ANOVA, equivalence testing, Bland-Altman analysis, linear regression, and related validity analyses.

Results: Significant increases in fat-free mass (3CLAB, 4.0 ± 4.5 kg; 3CFIELD, 3.9 ± 4.2 kg; US, 3.2 ± 4.3 kg; BIA, 3.9 ± 4.2 kg) and fat mass (3CLAB, 1.3 ± 2.2 kg; 3CFIELD, 1.4 ± 2.2 kg; US, 2.1 ± 2.6 kg; BIA, 1.4 ± 2.9 kg) were detected by all methods. However, only the 3CFIELD model demonstrated equivalence with the 3CLAB model. In addition, the 3CFIELD model exhibited superior performance to US and BIA individually, as indicated by the total error (3CFIELD, 1.0 kg; US, 1.8 kg; BIA, 1.6 kg), 95% limits of agreement (3CFIELD, ±2.1 kg; US, ±3.3 kg; BIA, ±3.1 kg), correlation coefficients (3CFIELD, 0.79-0.82; US, 0.49-0.55; BIA, 0.61-0.72), and additional metrics.

Conclusions: The present study demonstrated the potential usefulness of a 3CFIELD model incorporating US and BIA data for tracking body composition changes over time, as well as its superiority to US or BIA individually. As such, this accessible multicompartment model may be suitable for implementation in field or limited-resource settings.
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http://dx.doi.org/10.1249/MSS.0000000000002491DOI Listing
March 2021

Sit-to-Stand Kinetics and Correlates of Performance in Young and Older Males.

Arch Gerontol Geriatr 2020 Jul 30;91:104215. Epub 2020 Jul 30.

Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, 30144, United States.

Purpose: To compare sit-to-stand (STS) kinetics in young (YM) and older (OM) males and determine correlates of STS performance.

Methods: YM (n = 15, age = 20.7 ± 2.2 yrs) and OM (n = 15, age = 71.6 ± 3.9 yrs) performed a single STS task as quickly as possible on a force plate and the vertical ground reaction force (VGRF) signal was analyzed. Peak VGRF, as well as peak (100 ms rolling average), early (minimum VGRF to 50% peak VGRF), late (50% peak VGRF to peak VGRF), and overall (minimum VGRF to peak VGRF) rate of force development (RFD) were calculated. Power (absolute and relative) and velocity parameters as well as rate of electromyography rise (RER) were also obtained.

Results: STS time, average power, early RFD, and lower limb lean mass were similar between groups (p > 0.05). All other power, velocity, RFD, and RER measures were lower in OM (p < 0.05; d = 0.41-2.19). Peak VGRF and all RFD measures, except late RFD, were strongly correlated with STS performance in OM, while peak VGRF and peak RFD were only moderately correlated with performance in YM.

Conclusions: Most kinetic variables, except absolute average power, were diminished in OM, and there was a preferential decrease in late RFD compared to early RFD. Peak VGRF and RFD exhibited stronger correlations with STS time and power in OM compared to YM, and early RFD appears to be more influential for STS performance than late RFD. These findings may be useful for practitioners/clinicians involved in designing interventions aimed at optimizing STS performance in older adults.
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http://dx.doi.org/10.1016/j.archger.2020.104215DOI Listing
July 2020

Impact of Varying Dosages of Fish Oil on Recovery and Soreness Following Eccentric Exercise.

Nutrients 2020 Jul 27;12(8). Epub 2020 Jul 27.

Department of Health, Exercise and Sports Sciences, University of New Mexico, Albuquerque, NM 87131, USA.

Fish oils (FOs) are rich in omega-3 long-chain polyunsaturated fatty acids, which have been purported to enhance recovery of muscular performance and reduce soreness post-exercise. However, the most effective FO dose for optimizing recovery remains unclear. The purpose of this investigation was to examine the effect of FO supplementation dosing on the recovery of measures of muscular performance, perceived soreness, and markers of muscle damage following a rigorous bout of eccentric exercise. Thirty-two college-aged resistance-trained males (~23.6 years, 71.6 kg, 172.1 cm) were supplemented with 2, 4, 6 g/day (G) FO or placebo (PL) for ~7.5 weeks. Following 7 weeks of supplementation, pre-exercise (PRE) performance assessments of vertical jump (VJ), knee extensor strength, 40-yard sprint, T-test agility, and perceived soreness were completed prior to a bout of muscle-damaging exercise and were repeated immediately post (IP), 1-, 2-, 4-, 24-, 48-, and 72-h (H) post-exercise. Repeated measures analysis of variance indicated a treatment × time interaction ( < 0.001) for VJ and perceived soreness, but no group differences were observed at any time point. VJ returned to PRE (54.8 ± 7.9 cm) by 1H (51.8 ± 6.5 cm, = 0.112) for 6G, while no other groups returned to baseline until 48H. Lower soreness scores were observed in 6G compared to PL at 2H (mean difference [MD] = 2.74, = 0.046), at 24H (MD: 3.45, < 0.001), at 48H (MD = 4.45, < 0.001), and at 72H (MD = 3.00, = 0.003). Supplementation with 6G of FO optimized the recovery of jump performance and muscle soreness following a damaging bout of exercise.
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http://dx.doi.org/10.3390/nu12082246DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468920PMC
July 2020

Comparison of whole egg . egg white ingestion during 12 weeks of resistance training on skeletal muscle regulatory markers in resistance-trained men.

Br J Nutr 2020 11 24;124(10):1035-1043. Epub 2020 Jun 24.

Department of Health and Human Performance, Marymount University, Arlington, TX22207, USA.

Eggs are considered a high-quality protein source for their complete amino acid profile and digestibility. Therefore, this study aimed to compare the effects of whole egg (WE) v. egg white (EW) ingestion during 12 weeks of resistance training (RT) on the skeletal muscle regulatory markers and body composition in resistance-trained men. Thirty resistance-trained men (mean age 24·6 (sd 2·7) years) were randomly assigned into the WE + RT (WER, n 15) or EW + RT (EWR, n 15) group. The WER group ingested three WE, while the EWR group ingested an isonitrogenous quantity of six EW per d immediately after the RT session. Serum concentrations of regulatory markers and body composition were measured at baseline and after 12 weeks. Significant main effects of time were observed for body weight (WER 1·7, EWR 1·8 kg), skeletal muscle mass (WER 2·9, EWR 2·7 kg), fibroblast growth factor-2 (WER 116·1, EWR 83·2 pg/ml) and follistatin (WER 0·05, EWR 0·04 ng/ml), which significantly increased (P < 0·05), and for fat mass (WER -1·9, EWR -1·1 kg), transforming growth factor-β1 (WER -0·5, EWR -0·1 ng/ml), activin A (WER -6·2, EWR -4·5 pg/ml) and myostatin (WER -0·1, EWR -0·06 ng/ml), which significantly decreased (P < 0·05) in both WER and EWR groups. The consumption of eggs absent of yolk during chronic RT resulted in similar body composition and functional outcomes as WE of equal protein value. EW or WE may be used interchangeably for the dietary support of RT-induced muscular hypertrophy when protein intake is maintained.
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http://dx.doi.org/10.1017/S0007114520002238DOI Listing
November 2020

Explaining Discrepancies Between Total and Segmental DXA and BIA Body Composition Estimates Using Bayesian Regression.

J Clin Densitom 2021 Apr-Jun;24(2):294-307. Epub 2020 May 19.

Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, USA; School of Physical Therapy, Texas Woman's University, Denton, TX, USA.

Introduction/background: Few investigations have sought to explain discrepancies between dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) body composition estimates. The purpose of this analysis was to explore physiological and anthropometric predictors of discrepancies between DXA and BIA total and segmental body composition estimates.

Methodology: Assessments via DXA (GE Lunar Prodigy) and single-frequency BIA (RJL Systems Quantum V) were performed in 179 adults (103 F, 76 M, age: 33.6 ± 15.3 yr; BMI: 24.9 ± 4.3 kg/m). Potential predictor variables for differences between DXA and BIA total and segmental fat mass (FM) and lean soft tissue (LST) estimates were obtained from demographics and laboratory techniques, including DXA, BIA, bioimpedance spectroscopy, air displacement plethysmography, and 3-dimensional optical scanning. To determine meaningful predictors, Bayesian robust regression models were fit using a t-distribution and regularized hierarchical shrinkage "horseshoe" prior. Standardized model coefficients (β) were generated, and leave-one-out cross validation was used to assess model predictive performance.

Results: LST hydration (i.e., total body water:LST) was a predictor of discrepancies in all FM and LST variables (|β|: 0.20-0.82). Additionally, extracellular fluid percentage was a predictor for nearly all outcomes (|β|: 0.19-0.40). Height influenced the agreement between whole-body estimates (|β|: 0.74-0.77), while the mass, length, and composition of body segments were predictors for segmental LST estimates (|β|: 0.23-3.04). Predictors of segmental FM errors were less consistent. Select sex-, race-, or age-based differences between methods were observed. The accuracy of whole-body models was superior to segmental models (leave-one-out cross-validation-adjusted R of 0.83-0.85 for FM and LST vs. 0.20-0.76 for segmental estimates). For segmental models, predictive performance decreased in the order of: appendicular lean soft tissue, LST, LST and FM, FM, FM, and LST.

Conclusions: These findings indicate the importance of LST hydration, extracellular fluid content, and height for explaining discrepancies between DXA and BIA body composition estimates. These general findings and quantitative interpretation based on the presented data allow for a better understanding of sources of error between 2 popular segmental body composition techniques and facilitate interpretation of estimates from these technologies.
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http://dx.doi.org/10.1016/j.jocd.2020.05.003DOI Listing
May 2020

Early and late rapid torque characteristics and select physiological correlates in middle-aged and older males.

PLoS One 2020 23;15(4):e0231907. Epub 2020 Apr 23.

Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, Georgia, United States of America.

Purpose: The purpose of this study was to compare early and late rapid torque parameters of the plantar flexors (PFs) in middle-aged (MM) and older (OM) males, and determine the effect of normalization to peak torque (PT) and muscle cross-sectional area (CSA).

Methods: Twenty-nine healthy, MM (n = 14; 45 ± 2 yrs) and OM (n = 15; 65 ± 3 yrs) performed rapid, maximal isometric contractions of the PFs. PT, as well as rate of torque development and impulse during the early (0-50 ms; RTD0-50, IMP0-50) and late (100-200 ms; RTD100-200, IMP100-200) contraction phases were calculated. Torque at 50 (TQ50), 100 (TQ100), and 200 (TQ200) ms was also obtained. CSA and echo-intensity (EI) of the gastrocnemii were acquired via ultrasonography. Torque variables were normalized to PT and CSA. Rate of EMG rise (RER) for the medial gastrocnemius was calculated at 30, 50 and 75 ms.

Results: TQ100 (MM = 69.71 ± 16.85 vs. OM = 55.99 ± 18.54 Nm; p = 0.046), TQ200 (MM = 114.76 ± 26.79 vs. OM = 91.56 ± 28.10 Nm; p = 0.031), and IMP100-200 (MM = 4.79 ± 1.11 vs. OM = 3.83 ± 1.17 Nm·s; p = 0.032) were lower in OM. PT, TQ50, RTD0-50, IMP0-50, RTD100-200, RER, CSA, and EI were similar between groups (p > 0.05). No differences were found for normalized torque variables (p > 0.05). EI was moderately associated with normalized torque parameters only (r = -0.38 --0.45). RER, at 75 ms, was moderately correlated with early, absolute torque measures and rapid torque variables made relative to PT and CSA (r = 0.41 --0.64).

Conclusion: Late rapid torque parameters of the PFs were preferentially impaired in OM compared to MM, and PT as well as CSA appeared to mediate this result.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231907PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179893PMC
July 2020

Four Weeks of Time-Restricted Feeding Combined with Resistance Training Does Not Differentially Influence Measures of Body Composition, Muscle Performance, Resting Energy Expenditure, and Blood Biomarkers.

Nutrients 2020 Apr 17;12(4). Epub 2020 Apr 17.

Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA 30144, USA.

Recently, interest in time-restricted feeding (TRF) has increased from reports highlighting improvements in body composition and muscular performance measures. Twenty-six recreationally active males were randomly assigned to either TRF ( = 13; ~22.9 years; 82.0 kg; 178.1 cm; 8 h eating window, 25% caloric deficit, 1.8 g/kg/day protein) or normal diet (ND; = 13; ~22.5 years; 83.3 kg; 177.5 cm; normal meal pattern; 25% caloric deficit, 1.8 g/kg/day protein) groups. Participants underwent 4-weeks of supervised full body resistance training. Changes in body composition (fat mass (FM), fat free mass (FFM), and body fat percentage (BF%)), skeletal muscle cross sectional area (CSA) and muscle thickness (MT) of the vastus lateralis (VL), rectus femoris, (RF), and biceps brachii (BB) muscles, resting energy expenditure (REE), muscular performance, blood biomarkers, and psychometric parameters were assessed. Significant ( < 0.05) decreases were noted in BM, FM, BF%, testosterone, adiponectin, and REE, along with significant increases in BP, LP, VJ, VJ, VL, BB, and BB in both groups. Plasma cortisol levels were significantly elevated at post ( = 0.018) only in ND. Additionally, FFM was maintained equally between groups. Thus, a TRF style of eating does not enhance reductions in FM over caloric restriction alone during a 4-week hypocaloric diet.
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http://dx.doi.org/10.3390/nu12041126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231047PMC
April 2020

Physiological differences between advanced CrossFit athletes, recreational CrossFit participants, and physically-active adults.

PLoS One 2020 7;15(4):e0223548. Epub 2020 Apr 7.

Exercise Science and Sport Management, Kennesaw State University, Kennesaw, Georgia.

This investigation examined anthropometric, hormonal, and physiological differences between advanced (ADV; n = 8, 27.8 ± 4.2 years, 170 ± 11 cm, 79.8 ± 13.3 kg) and recreational (REC; n = 8, 33.5 ± 8.1 years, 172 ± 14 cm, 76.3 ± 19.5 kg) CrossFit (CF) trained participants in comparison to physically-active controls (CON; n = 7, 27.5 ± 6.7 years, 171 ± 14 cm, 74.5 ± 14.3 kg). ADV and REC were distinguished by their past competitive success. REC and CON were resistance-trained (>2 years) and exercised on 3-5 days·wk-1 for the past year, but CON utilized traditional resistance and cardiovascular exercise. All participants provided a fasted, resting blood sample and completed assessments of resting metabolic rate, body composition, muscle morphology, isometric mid-thigh pull strength, peak aerobic capacity, and a 3-minute maximal cycle ergometer sprint across two separate occasions (separated by 3-7 days). Blood samples were analyzed for testosterone, cortisol, and insulin-like growth factor-1. Compared to both REC and CON, one-way analysis of variance revealed ADV to possess lower body fat percentage (6.7-8.3%, p = 0.007), greater bone and non-bone lean mass (12.5-26.8%, p ≤ 0.028), muscle morphology characteristics (14.2-59.9%, p < 0.05), isometric strength characteristics (15.4-41.8%, p < 0.05), peak aerobic capacity (18.8-19.1%, p = 0.002), and 3-minute cycling performance (15.4-51.1%, p ≤ 0.023). No differences were seen between REC and CON, or between all groups for resting metabolic rate or hormone concentrations. These data suggest ADV possess several physiological advantages over REC and CON, whereas similar physiological characteristics were present in individuals who have been regularly participating in either CF or resistance and cardiovascular training for the past year.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223548PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138313PMC
June 2020

Novel body fat estimation using machine learning and 3-dimensional optical imaging.

Eur J Clin Nutr 2020 05 16;74(5):842-845. Epub 2020 Mar 16.

Energy Balance & Body Composition Laboratory; Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, USA.

Estimates of body composition have been derived using 3-dimensional optical imaging (3DO), but no equations to date have been calibrated using a 4-component (4C) model criterion. This investigation reports the development of a novel body fat prediction formula using anthropometric data from 3DO imaging and a 4C model. Anthropometric characteristics and body composition of 179 participants were measured via 3DO (Size Stream SS20) and a 4C model. Machine learning was used to identify significant anthropometric predictors of body fat (BF%), and stepwise/lasso regression analyses were employed to develop new 3DO-derived BF% prediction equations. The combined equation was externally cross-validated using paired 3DO and DXA assessments (n = 158), producing a R value of 0.78 and a constant error of (X ± SD) 0.8 ± 4.5%. 3DO BF% estimates demonstrated equivalence with DXA based on equivalence testing with no proportional bias in the Bland-Altman analysis. Machine learning methods may hold potential for enhancing 3DO-derived BF% estimates.
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http://dx.doi.org/10.1038/s41430-020-0603-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220828PMC
May 2020

Safety of Short-Term Supplementation with Methylliberine (Dynamine) Alone and in Combination with TeaCrine in Young Adults.

Nutrients 2020 Feb 28;12(3). Epub 2020 Feb 28.

Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA 30144, USA.

Methylliberine (Dynamine; DYM) and theacrine (Teacrine; TCR) are purine alkaloids purported to have similar neuro-energetic effects as caffeine. There are no published human safety data on DYM, and research on TCR is limited. The purpose of this study was to examine the effect of four weeks of DYM supplementation with and without TCR on cardiovascular function and blood biomarkers. One-hundred twenty-five men and women (mean age 23.0 yrs, height 169.7 cm, body mass 72.1 kg; = 25/group) were randomly assigned to one of five groups: low-dose DYM (100 mg), high-dose DYM (150 mg), low-dose DYM with TCR (100 mg + 50 mg), high-dose DYM with TCR (150 mg + 25 mg) , and placebo. Regardless of group and sex, significant main effects for time were noted for heart rate, systolic blood pressure, and QTc ( < 0.001), high-density lipoproteins ( = 0.002), mean corpuscular hemoglobin ( = 0.018), basophils ( = 0.006), absolute eosinophils ( = 0.010), creatinine ( = 0.004), estimated glomerular filtration rate ( = 0.037), chloride ( = 0.030), carbon dioxide ( = 0.023), bilirubin ( = 0.027), and alanine aminotransferase ( = 0.043), among others. While small changes were found in some cardiovascular and blood biomarkers, no clinically significant changes occurred. This suggests that DYM alone or in combination with TCR consumed at the dosages used in this study does not appear to negatively affect markers of health over four weeks of continuous use.
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http://dx.doi.org/10.3390/nu12030654DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146520PMC
February 2020

Supplements and Nutritional Interventions to Augment High-Intensity Interval Training Physiological and Performance Adaptations-A Narrative Review.

Nutrients 2020 Jan 31;12(2). Epub 2020 Jan 31.

School of Health and Exercise Sciences, University of British Columbia, Okanagan Campus, Kelowna, BC V1V1V7, Canada.

High-intensity interval training (HIIT) involves short bursts of intense activity interspersed by periods of low-intensity exercise or rest. HIIT is a viable alternative to traditional continuous moderate-intensity endurance training to enhance maximal oxygen uptake and endurance performance. Combining nutritional strategies with HIIT may result in more favorable outcomes. The purpose of this narrative review is to highlight key dietary interventions that may augment adaptations to HIIT, including creatine monohydrate, caffeine, nitrate, sodium bicarbonate, beta-alanine, protein, and essential amino acids, as well as manipulating carbohydrate availability. Nutrient timing and potential sex differences are also discussed. Overall, sodium bicarbonate and nitrates show promise for enhancing HIIT adaptations and performance. Beta-alanine has the potential to increase training volume and intensity and improve HIIT adaptations. Caffeine and creatine have potential benefits, however, longer-term studies are lacking. Presently, there is a lack of evidence supporting high protein diets to augment HIIT. Low carbohydrate training enhances the upregulation of mitochondrial enzymes, however, there does not seem to be a performance advantage, and a periodized approach may be warranted. Lastly, potential sex differences suggest the need for future research to examine sex-specific nutritional strategies in response to HIIT.
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http://dx.doi.org/10.3390/nu12020390DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071320PMC
January 2020

Rate of Force Development as a Predictor of Mobility in Community-dwelling Older Adults.

J Geriatr Phys Ther 2021 Apr-Jun 01;44(2):74-81

Cobb Senior Services, Marietta, Georgia.

Background And Purpose: Rate of force development (RFD) is influential, and possibly more influential than other muscular performance parameters, for mobility in older adults. However, only a few studies have investigated this matter, and this has not been examined for the plantar flexors (PFs). The purpose of this study was to examine the contribution of PF RFD and other common tests of muscular performance to Up-and-Go (UG) performance and walking speed (WS) in older adults.

Methods: Twenty-six (19 females) healthy, community-dwelling older adults (73.7 ± 4.9 years) were recruited from a senior citizen center for this observational study. Handgrip strength, UG performance, as well as preferred and maximal WS were obtained. Time taken to complete 5-chair rises and the number of chair rises completed in 30 seconds were recorded. Rate of force development of the PFs was obtained during a rapid, bilateral calf raise performed on a force plate. Hierarchical multiple linear regression was used to identify significant predictors, after adjusting for physical activity level and body mass index, of mobility (ie, UG, preferred and maximal WS).

Results And Discussion: No muscular performance variables correlated with preferred WS. Rate of force development (adjusted R2 = 0.356; P = .008) and handgrip strength (adjusted R2 = 0.293; P = .026) were the only predictors of maximal WS and accounted for a 21.7% and 16.1% change in R2, respectively, after accounting for physical activity level and body mass index. Rate of force development was the only predictor of UG performance (adjusted R2 = 0.212; P = .006) and accounted for a 29.2% change in R2 after adjustment variables were applied.

Conclusions: Compared to common assessments of muscular performance, such as handgrip strength and chair rise performance, PF RFD was a greater predictor of mobility in older adults. These findings, in conjunction with recent reports, indicate that the assessment of RFD likely complements strength testing, thereby enabling a more robust assessment of functional decline in older adults.
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http://dx.doi.org/10.1519/JPT.0000000000000258DOI Listing
July 2021

Neuromuscular function of the plantar flexors and predictors of peak power in middle-aged and older males.

Exp Gerontol 2019 10 30;125:110677. Epub 2019 Jul 30.

Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA 30144, United States of America. Electronic address:

Little evidence exists regarding the contribution of torque and velocity to the age-related decrease in peak power (PP) for the plantar flexors (PFs). A comprehensive assessment of PF neuromuscular function is necessary to elucidate age-related changes, especially between middle-aged and older adults, in order to identify early, age-related decrements. Thus, the purpose of this study was to examine neuromuscular function of the PFs in middle-aged and older males, and identify predictors of PP. Twenty-eight healthy, middle-aged (n = 13; 45.1 ± 2.7 yrs) and older (n = 15; 65.3 ± 3.2 yrs) males performed concentric isotonic PF contractions ranging in intensity from 20% to 70% isometric strength using a dynamometer. PP in addition to velocity and torque at the moment in time PP occurred, as well as the rate of velocity, torque (RTD), and power (RPD) development were recorded. The rate of electromyography rise (RER) was derived from the linear slope of the normalized electromyography signal. Isometric and concentric dynamic strength were assessed, as well as cross-sectional area and muscle quality (i.e., echo intensity) of the PFs via panoramic ultrasonography. The relationship between serum c-terminal agrin levels and select variables was examined to explore the potential role of neuromuscular junction deterioration. Appendicular lean mass and physical activity level were similar between groups (p > 0.05), and only PP (p = 0.046; d = 0.79), RPD (p = 0.026; d = 0.90), RTD (p = 0.022; d = 0.91), and RER (p = 0.010; d = 1.04) were lower in older males. When groups were collapsed, RTD was the only significant predictor of PP, while c-terminal agrin levels were not associated with any variables. Our findings indicate that PP and time-dependent parameters of muscle activation and contractile function of the PFs are dramatically diminished in older adults compared to middle-aged adults. PP is produced at the same velocity and relative intensity in middle-aged and older males, and RTD is most influential for PP. The inability of the PFs to be rapidly activated appeared to be influential for the age-related impairment in PP and time-dependent contractile parameters.
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http://dx.doi.org/10.1016/j.exger.2019.110677DOI Listing
October 2019

Effect of Branched-Chain Amino Acid Supplementation on Recovery Following Acute Eccentric Exercise.

Nutrients 2018 Oct 1;10(10). Epub 2018 Oct 1.

Department of Health, Exercise and Sports Science, University of New Mexico, Albuquerque, NM 87131, USA.

This study investigated the effect of branched-chain amino acid (BCAA) supplementation on recovery from eccentric exercise. Twenty males ingested either a BCAA supplement or placebo (PLCB) prior to and following eccentric exercise. Creatine kinase (CK), vertical jump (VJ), maximal voluntary isometric contraction (MVIC), jump squat (JS) and perceived soreness were assessed. No significant ( > 0.05) group by time interaction effects were observed for CK, soreness, MVIC, VJ, or JS. CK concentrations were elevated above baseline ( < 0.001) in both groups at 4, 24, 48 and 72 hr, while CK was lower ( = 0.02) in the BCAA group at 48 hr compared to PLCB. Soreness increased significantly from baseline ( < 0.01) in both groups at all time-points; however, BCAA supplemented individuals reported less soreness ( < 0.01) at the 48 and 72 hr time-points. MVIC force output returned to baseline levels ( > 0.05) at 24, 48 and 72 hr for BCAA individuals. No significant difference between groups ( > 0.05) was detected for VJ or JS. BCAA supplementation may mitigate muscle soreness following muscle-damaging exercise. However, when consumed with a diet consisting of ~1.2 g/kg/day protein, the attenuation of muscular performance decrements or corresponding plasma CK levels are likely negligible.
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http://dx.doi.org/10.3390/nu10101389DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6212987PMC
October 2018
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