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The present systematic review aimed to compare the accuracy of Bioelectrical Impedance Analysis (BIA) and Bioelectrical Impedance Vector Analysis (BIVA) vs. reference methods for the assessment of body composition in athletes. Studies were identified based on a systematic search of internationally electronic databases (PubMed and Scopus) and hand searching of the reference lists of the included studies. In total, 42 studies published between 1988 and 2021 were included. The methodological quality was assessed using the Quality Assessment Tool for Observational Cohort and Cross-sectional Studies as recommended by the National Institute of Health. Twenty-three studies had an overall good rating in terms of quality, while 13 were rated as fair and 6 as poor, resulting in a low to moderate risk of bias. Fat mass was inconsistently determined using BIA vs. the reference methods, regardless of the BIA-technology. When using the foot to hand technology with predictive equations for athletes, a good agreement between BIA and the reference methods was observed for fat-free mass, total body, intra and extra cellular water. However, an underestimation in fat-free mass and body fluids was found when using generalized predictive equations. Classic and Specific BIVA represented a valid approach for assessing body fluids (Classic BIVA) and percentage of fat mass (Specific BIVA). The present systematic review suggests that BIA and BIVA can be used for assessing body composition in athletes, provided that foot-to-hand technology, predictive equations, and BIVA references for athletes are used.

The current study determined the area-per-player during small- or large-sided games with or without goalkeeper that replicates the relative (m·min.sup.-1) total distance, high-intensity running distance, sprint distance and metabolic power covered during official matches. Time-motion analysis was performed on twenty-five elite soccer-players during 26 home-matches. A total of 2565 individual samples for SSGs using different pitch sizes and different number of players were collected and classified as SSGs with (SSG-G) or without goalkeeper (SSG-P). A between-position comparison was also performed. The area-per-player needed to replicate the official match demands was largely higher in SSG-G vs SSG-P for total distance [187±53 vs 115±35 m.sup.2, effect size (ES): 1.60 95%CI 0.94/2.21], high-intensity running distance [262±72 vs 166±39 m.sup.2, ES: 1.66(0.99/2.27)] and metabolic power [177±42 vs 94±40, ES: 1.99(1.31/2.67)], but similar for sprint distance [(316±75 vs 295±99 m.sup.2, ES: 0.24(-0.32/0.79)] with direction of larger area-per-player for sprint distance > high-intensity running > total distance [all equal to] metabolic power for both SSG-G and SSG-P. In SSG-G, forwards required higher area-per-player than central-defenders [ES: 2.96(1.07/4.35)], wide-midfielders [ES: 2.45(0.64/3.78)] and wide-defenders [ES: 3.45(1.13/4.99)]. Central-midfielders required higher area-per-player than central-defenders [ES: 1.69(0.20/2.90)] and wide-midfielders [ES: 1.35(-0.13/2.57)]. In SSG-P, central defenders need lower area-per-player (ES: -6.01/-0.92) to overall replicate the match demands compared to all other positions. The current results may be used to gain knowledge of the SSGs relative to the match demands. This imply manipulating SSGs using higher or lower ApP, the presence of the goalkeeper or design specific rules to increase or decrease the position-specific demands with respect to the desired external load outcomes.

Peripheral fatigue results from multiple electrochemical and mechanical events in the cell body and the muscle–tendon complex. Combined force and surface electromyographic signal analysis is among the most widely used approaches to describe the behaviour of a fatigued muscle. Advances in technologies and methodological procedures (e.g. laser diffraction, 31P magnetic resonance spectroscopy, shear-wave elastography, tensiomyography, myotonometry, mechanomyography, and high-density surface electromyography) have expanded our knowledge of muscle behaviour before, during, and after a fatiguing task. This review gives an update on recent developments in technologies for investigating the effects of peripheral fatigue linked to skeletal muscle contraction and on mechanistic insights into the electrochemical and mechanical aspects of fatigue. The salient points from the literature analysis are: (1) the electrochemical and mechanical events in the cell (alterations in cross-bridge formation and function and in depolarization of the tubular membrane) precede the events taking place at the muscle–tendon complex (decrease in muscle–tendon unit stiffness); (2) the changes in the fatigued muscle are not homogenous along its length and width but rather reflect a functional compartmentalisation that counteracts the decline in performance; (3) fatigue induces changes in load sharing among adjacent/synergistic muscles. A focus of future studies is to observe how these regional differences occur within single muscle fibres. To do this, a combination of different approaches may yield new insights into the mechanisms underlying muscle fatigue and how the muscle counteracts fatigue.

PurposeWe investigated the effects of 12 weeks of passive static stretching training (PST) on force-generating capacity, passive stiffness, muscle architecture of plantarflexor muscles.MethodsThirty healthy adults participated in the study. Fifteen participants (STR, 6 women, 9 men) underwent 12-week plantarflexor muscles PST [(5 × 45 s-on/15 s-off) × 2exercises] × 5times/week (duration: 2250 s/week), while 15 participants (CTRL, 6 women, 9 men) served as control (no PST). Range of motion (ROM), maximum passive resistive torque (PRTmax), triceps surae architecture [fascicle length, fascicle angle, and thickness], passive stiffness [muscle–tendon complex (MTC) and muscle stiffness], and plantarflexors maximun force-generating capacity variables (maximum voluntary contraction, maximum muscle activation, rate of torque development, electromechanical delay) were calculated Pre, at the 6th (Wk6), and the 12th week (Wk12) of the protocol in both groups.ResultsCompared to Pre, STR ROM increased (P < 0.05) at Wk6 (8%) and Wk12 (23%). PRTmax increased at Wk12 (30%, P < 0.05), while MTC stiffness decreased (16%, P < 0.05). Muscle stiffness decreased (P < 0.05) at Wk6 (11%) and Wk12 (16%). No changes in triceps surae architecture and plantarflexors maximum force-generating capacity variables were found in STR (P > 0.05). Percentage changes in ROM correlated with percentage changes in PRTmax (ρ = 0.62, P = 0.01) and MTC stiffness (ρ = − 0.78, P = 0.001). In CTRL, no changes (P > 0.05) occurred in any variables at any time point.ConclusionThe expected long-term PST-induced changes in ROM were associated with modifications in the whole passive mechanical properties of the ankle joint, while maximum force-generating capacity characteristics were preserved. 12 weeks of PST do not seem a sufficient stimulus to induce triceps surae architectural changes.

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject’s age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject’s characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature. Registration code in PROSPERO : CRD42023467894.

The present review summarizes the effects of manipulating different resistance exercise variables on jumps, sprints, and changes of direction (CODs) in soccer. Regarding jumps, moderate-to-high loads, full range of movement (ROM), non-failure sets, and a moderate training volume are recommended. Different external resistances like constant-load, flywheel, or elastic bands, as well as various movement velocities and select exercises, are equally effective. As for sprints, moderate-to-high loads, constant load or flywheel but not elastic resistances, movements performed at full ROM, non-failure sets, and moderate-to-high training volume might be more effective, while numerous movement velocities and exercises could be chosen. As for CODs, moderate-to-high loads, flywheel more than constant-load resistance, and a moderate-to-high total number of repetitions are recommended, while several movement velocities and exercises could be selected, though ROM needs investigation. The effectiveness of concentric-only vs. eccentric-only training on jumps, sprints, and CODs has not been investigated, while an external focus and inter-set rest > 2 min are theoretically preferable, albeit not proven. Importantly, high movement velocity is not a prerogative of effectiveness, and limited ROM is not associated with sport-specific patterns such as jumps. Practitioners in soccer may manipulate resistance exercise variables depending on the purpose.

This study examined the most demanding passages of match play (MDP) and the effects of playing formation, ball-in-play (BiP) time and ball possession on the 1-min peak (1-min ) demand in elite soccer. During 18 official matches, 305 individual samples from 223 Italian Serie A soccer players were collected. MDP and 1-min were calculated across playing position (central defenders, wide defenders, central midfielders, wide midfielders, wide forwards and forwards). Maximum relative (m·min ) total distance (TD), high-speed running (HSR), very high-speed running (VHSR), sprint (SPR), acceleration/deceleration (Acc/Dec), estimated metabolic power (P ) and high-metabolic load (HML) distance were calculated across different durations (1-5, 10, 90 min) using a rolling method. Additionally, 1-min demand was compared across playing formation (3-4-1-2, 3-4-2-1, 3-5-2, 4-3-3, 4-4-2), BiP and ball/no-ball possession cycles. MDP showed large to verylarge [effect-size (ES): 1.20/4.06] differences between 1-min vs all durations for each parameter. In 1-min , central midfielders and wide midfielders achieved greater TD and HSR (ES:0.43/1.13) while wide midfielders and wide forwards showed greater SPR and Acc/Dec (ES:0.30/1.15) than other positions. For VHSR, SPR and Acc/Dec 1-min showed fourfold higher locomotor requirements than 90-min. 1-min for Acc/Dec was highest in 4-3-3 for forwards, central and wide midfielders. 1-min was lower during peak BiP (BiP ) for HSR, VHSR and Acc/Dec (ES: -2.57/-1.42). Comparing with vs without ball possession, BiP was greater (ES: 0.06/1.48) in forwards and wide forwards and lower (ES: -2.12/-0.07) in central defenders and wide defenders. Positional differences in MDP, 1-min and BiP were observed. Soccer-specific drills should account for positional differences when conditioning players for the peak demands. This may help practitioners to bridge the training/match gap.

The present study investigated the activation of gluteal, thigh, and lower back muscles in different squat variations. Ten male competitive bodybuilders perform back-squat at full (full-BS) or parallel (parallel-BS) depth, using large feet-stance (sumo-BS), and enhancing the feet external rotation (external-rotated-sumo-BS) and front-squat (FS) at 80% 1-RM. The normalized surface electromyographic root-mean-square (sEMG RMS) amplitude of gluteus maximus, gluteus medius, rectus femoris, vastus lateralis, vastus medialis, adductor longus, longissimus, and iliocostalis was recorded during both the ascending and descending phase of each exercise. During the descending phase, greater sEMG RMS amplitude of gluteus maximus and gluteus medius was found in FS vs. all other exercises (p < 0.05). Additionally, FS elicited iliocostalis more than all other exercises. During the ascending phase, both sumo-BS and external-rotated-sumo-BS showed greater vastus lateralis and adductor longus activation compared to all other exercises (p < 0.05). Moreover, rectus femoris activation was greater in FS compared to full-BS (p < 0.05). No between-exercise difference was found in vastus medialis and longissimus showed no between-exercise difference. FS needs more backward stabilization during the descending phase. Larger feet-stance increases thigh muscles activity, possibly because of their longer length. These findings show how bodybuilders uniquely recruit muscles when performing different squat variations.

Direct assessment of skinfold thickness and waist and hip girths provides information about body fat and its distribution, avoiding estimation errors due to predictive equations. The present study aimed to provide new centile curves for the sum of eight skinfold thicknesses (Σ8SKF) and waist-to-hip ratio (WHR) in adult population, and to identify breakpoints during adulthood. The present investigation was conceived as a multicenter, cross-sectional study. Stature, body mass, eight skinfold thicknesses (i.e., triceps, biceps, subscapular, iliac crest, supraspinal, abdominal, thigh, and calf) and waist and hip girths were measured according to the International Society for the Advancement of Kinanthropometry protocol in 1,313 men and 1,194 women aged 18-65 years. Smoothed age- and sex-specific percentile curves were generated using the Lambda Mu and Sigma method. For both sexes, simple linear regressions of the dependent variable (Σ8SKF and WHR) versus the explanatory variable (age) were performed to investigate changes in the response variable's slope and to test for potential breakpoints. Reference percentile curves (3rd, 10th, 25th, 50th, 75th, 90th, and 97th) for Σ8SKF and WHR were provided. In men, Σ8SKF increased by 1.0 mm/year between the ages of 21 and 59, while in women, it increased by 3.8 mm/year between the ages of 38.5 and 47. In men, WHR showed a progressive increase of 0.004/year until the age of 28.4, followed by a slower increase of 0.003/year throughout the lifespan. In women, WHR increased by 0.003/year from the age of 20-65. Σ8SKF and WHR appear sex- and age-specific. Scientists and practitioners are provided with reference values for the adult population.

The current investigation compared the metabolic power and energetic characteristics in team sports with respect to positional lines and halves of match-play. Global positioning system (GPS) technology data were collected from 22 elite competitive hurling matches over a 3-season period. A total of 250 complete match-files were recorded with players split into positional groups of full-back; half-back; midfield; half-forward; full-forward. Raw GPS data were exported into a customized spreadsheet that provided estimations of metabolic power and speed variables across match-play events (average metabolic power [Pmet], high metabolic load distance [HMLD], total distance, relative distance, high-speed distance, maximal speed, accelerations, and deceleration). Pmet, HMLD, total, relative and high-speed distance were 8.9 ± 1.6 W·kg-1, 1457 ± 349 m, 7506 ± 1364 m, 107 ± 20 m·min-1 and 1169 ± 260 m respectively. Half-backs, midfielders and half-forwards outperformed full-backs (Effect Size [ES] = 1.03, 1.22 and 2.07 respectively), and full-forwards in Pmet (Effect Size [ES] = 1.70, 2.07 and 1.28 respectively), and HMLD (full-backs: ES = -1.23, -1.37 and -0.84 respectively, and full-forwards: ES = -1.77, -2.00 and -1.38 respectively). Half-backs (ES = -0.60), midfielders (ES = -0.81), and half-forwards (ES = -0.74) experienced a second-half temporal decrement in HMLD. The current investigation demonstrates that metabolic power may increase our understanding of the match-play demands placed on elite hurling players. Coaches may utilize these findings to construct training drills that replicate match-play demands.