The effects of melatonin and magnesium in a novel supplement delivery system on sleep scores, body composition and metabolism in otherwise healthy individuals with sleep disturbances.

The purpose of this study was to investigate the effects of a novel dietary supplement, including melatonin and magnesium, delivered via coffee pods on sleep quality, resting metabolic rate (RMR), and body composition in individuals with poor sleep quality disturbances. Using a double-blinded, randomized, crossover trial, we recruited 35 participants to a 4-week intervention with both supplements (1.9 mg melatonin + 200 mg elemental magnesium before sleep) and placebo conditions, considering a 7d washout period between treatments. The Pittsburgh Sleep Quality Index (PSQI) questionnaire was applied, RMR (kcal) was measured using indirect calorimetry (canopy ventilated open-circuit system) and body composition was assessed using dual-energy X-ray absorptiometry. Decreases in PSQI and anger - hostility scores, as well as in energy intake and fat mass, were observed (p < 0.05) for both conditions, from baseline to the end of each 4-week intervention. Differences between conditions were also observed for these parameters along with energy spent in activity, number of sedentary breaks, sleep efficiency, latency time, time in bed, total sleep time, awakening time, and movement index (p < 0.05) favouring the supplement condition. However, the final PSQI questionnaire scores still indicated poor sleep quality on average (PSQI > 5), in both conditions, with no changes regarding RMR. A melatonin-magnesium supplement, in a coffee pod format, showed improvements in sleep quality in otherwise healthy individuals with sleep disturbances, however PSQI questionnaire scores still indicated poor quality on average (PSQI > 5).

Methods over Materials: The Need for Sport-Specific Equations to Accurately Predict Fat Mass Using Bioimpedance Analysis or Anthropometry.

Bioelectrical impedance analysis (BIA) and anthropometry are considered alternatives to well-established reference techniques for assessing body composition. In team sports, the percentage of fat mass (FM%) is one of the most informative parameters, and a wide range of predictive equations allow for its estimation through both BIA and anthropometry. Although it is not clear which of these two techniques is more accurate for estimating FM%, the choice of the predictive equation could be a determining factor. The present study aimed to examine the validity of BIA and anthropometry in estimating FM% with different predictive equations, using dual X-ray absorptiometry (DXA) as a reference, in a group of futsal players. A total of 67 high-level male futsal players (age 23.7 ± 5.4 years) underwent BIA, anthropometric measurements, and DXA scanning. Four generalized, four athletic, and two sport-specific predictive equations were used for estimating FM% from raw bioelectric and anthropometric parameters. DXA-derived FM% was used as a reference. BIA-based generalized equations overestimated FM% (ranging from 1.13 to 2.69%, p < 0.05), whereas anthropometry-based generalized equations underestimated FM% in the futsal players (ranging from −1.72 to −2.04%, p < 0.05). Compared to DXA, no mean bias (p > 0.05) was observed using the athletic and sport-specific equations. Sport-specific equations allowed for more accurate and precise FM% estimations than did athletic predictive equations, with no trend (ranging from r = −0.217 to 0.235, p > 0.05). Regardless of the instrument, the choice of the equation determines the validity in FM% prediction. In conclusion, BIA and anthropometry can be used interchangeably, allowing for valid FM% estimations, provided that athletic and sport-specific equations are applied.

Fat-free mass estimation in male elite futsal players: Development and validation of a new bioelectrical impedance-based predictive equation.

OBJECTIVES: The present study aimed to develop and cross-validate a futsal-specific bioelectrical equation for estimating fat-free mass (FFM) in male players. METHODS: A total of 66 futsal players (age 23.3 ± 5.4 years) from the Major Portuguese Futsal League "LIGA PLACARD" and from the 2nd and 3rd National Futsal Leagues were included in this cross-sectional, observational study. The participants underwent a foot-to-hand bioelectrical impedance analysis (BIA) at 50 kHz and completed a dual-energy X-ray absorptiometry (DXA) scan for reference body composition data. The sport-specific model was developed by stepwise multiple regression using bioelectrical raw parameters [resistance (R) and reactance (Xc)] as independent variables. Validation was performed using the PRESS approach, least squares regression, concordance correlation coefficient (CCC) and Bland-Altman analyses. RESULTS: A BIA-based model was developed for FFM [FFM (kg) = -8.865 + 0.437 * Body Mass (kg) + 0.186 * Xc + 0.415 * stature (cm)2/R (R2 = 0.89, standard error of estimation = 2.38 kg)]. Results showed a substantial strength of agreement (CCC = 0.953), an r2 of 0.88 with a standard error of estimation equal to 2.31 kg, no mean bias (0.04 kg, p>0.05), low limits of agreement (ranged from -4.5 to 4.6 kg), and no trend (r = -0.170, p = 0.172). CONCLUSIONS: The present equation is the first to allow for a valid, accurate, and sport-specific assessment of FFM in male futsal players.

Development and Validation of an Anthropometric Equation to Predict Fat Mass Percentage in Professional and Semi-Professional Male Futsal Players.

This study aimed to (i) characterise the body composition of professional and semi-professional male futsal players, (ii) assess the validity of commonly used equations to estimate FM%, (iii) develop and cross-validate a futsal-specific FM% prediction equation. In a cross-sectional design, 78 adult male futsal players were assessed for body mass, stature, skinfolds, and girths as per the International Society for the Advancement of Kinanthropometry protocol and completed a dual-energy X-ray absorptiometry (DXA) scan for reference body composition data. Using paired-sample t-tests, the FM% from the DXA and nine published equations were compared. New sport-specific models were developed by stepwise multiple regression. Existing equations were cross-validated using the least squares regression, concordance correlation coefficient, and the Bland−Altman analyses. New equations were further cross-validated using the PRESS approach. None of the existing equations accurately predicted the DXA-derived FM% (p < 0.001; R2 ≤ 0.76, SEE ≥ 1.59; CCC ≤ 0.83; bias = −8.2% to −1.3%, limited agreement, and varying trends). The novel Bettery® equation: −0.620 + (0.159 ∗ Σ4SKF [triceps, abdominal, iliac crest, and front thigh (mm)]) + (0.120 ∗ waist girth (cm)), demonstrated a high accuracy (R2 = 0.85, SEE = 1.32%), a moderate strength of agreement (CCC = 0.92), no bias (0.2%), good agreement (±2.5%), and no trend (r = −0.157; p = 0.170) against the DXA. The Bettery® equation is the first to allow for a valid and sport-specific assessment of FM% in male futsal players.

Association between Phase Angle from Bioelectric Impedance and Muscular Strength and Power in Physically Active Adults.

This study aimed to compare muscle strength and power indicators according to bioimpedance spectroscopy's phase angle (PhA) values, in resistance-trained (RT) men, while exploring associations between PhA and performance. Forty-four men aged 18−45 years, engaged in RT, were allocated according to PhA tertiles. Lean soft tissue (LST) and fat mass (%FM) were assessed using dual-energy x-ray absorptiometry; dynamic muscle strength using 1 repetition maximum (1RM) of bench press (BP) and back squat (BS) and muscle power using Wingate test (WT) and countermovement jump (CMJ). For WT and CMJ, the 3rd tertile was significantly higher than the 1st tertile (p = 0.027 and p = 0.018, respectively). Regarding BP 1RM, the 3rd tertile was significantly higher than the 2nd tertile (p = 0.037). LST better explained the variability in the WT, BS and BP (p =< 0.001), while %FM better accounted for jump height in CMJ (p =< 0.001). PhA was a predictor of performance in both CMJ (p = 0.040) and BP (p = 0.012), independently of LST and %FM. Participants with higher PhA also displayed superior muscle strength of the upper limbs and greater muscle power of the lower limbs. PhA displayed significant moderate associations with performance in CMJ and BP, even after controlling for body composition. Still, LST was the most important predictor of muscle strength and power.

A Novel Plant-Based Protein Has Similar Effects Compared to Whey Protein on Body Composition, Strength, Power, and Aerobic Performance in Professional and Semi-Professional Futsal Players.

Introduction: The effects of dietary protein on body composition and physical performance seemingly depend on the essential amino acid profile of the given protein source, although controversy exists about whether animal protein sources may possess additional anabolic properties to plant-based protein sources. Purpose: To compare the effects of a novel plant-based protein matrix and whey protein supplementation on body composition, strength, power, and endurance performance of trained futsal players. Methods: Fifty male futsal players were followed during 8 weeks of supplementation, with 40 completing the study either with plant-based protein (N = 20) or whey protein (N = 20). The following measures were assessed: bone mineral content, lean body mass, and fat mass; muscle thickness of the rectus femoris; total body water; blood glucose, hematocrit, C-reactive protein, aspartate aminotransferase, alanine aminotransferase, creatine kinase, creatinine, and estimated glomerular filtration rate; salivary cortisol; maximal strength and 1-RM testing of the back squat and bench press exercises; muscle power and countermovement jump; VO2max and maximal aerobic speed. Subjects were asked to maintain regular dietary habits and record dietary intake every 4 weeks through 3-day food records. Results: No differences in any variable were observed between groups at baseline or pre- to post-intervention. Moreover, no time*group interaction was observed in any of the studied variables, and a time effect was only observed regarding fat mass reduction. Conclusions: Supplementing with either a novel plant-based protein matrix or whey protein did not affect any of the variables assessed in high-level futsal players over 8 wks. These results suggest that whey protein does not possess any unique anabolic properties over and above those of plant-based proteins when equated to an essential amino acid profile in the population studied. Furthermore, when consuming a daily protein intake >1.6 g/kg BW.day-1, additional protein supplementation does not affect body composition or performance in trained futsal players, regardless of protein type/source.

Comparison of generalized and athletic bioimpedance-based predictive equations for estimating fat-free mass in resistance-trained exercisers.

OBJECTIVES: This study aimed to test whether athlete-specific, bioelectrical, impedance-based equations to estimate fat-free mass (FFM) could be more accurate than generalized equations when testing resistance-trained exercisers. METHODS: A total of 50 resistance-trained men (age 30.9 ± 7.4 y; body mass index: 25.3 ± 2.2 kg/m2) and 20 men from the general population (age 29.9 ± 9.1 y; body mass index: 22.8 ± 2.4 kg/m2) underwent bioelectrical impedance and dual-energy x-ray absorptiometry (DXA) evaluations. FFM was derived by one bioelectrical impedance-based equation specific for athletes and three generalized equations, all developed with foot-to-hand bioimpedance technologies at a 50 kHz frequency. DXA was the reference method for the FFM assessment. RESULTS: Compared with DXA, when assessing the resistance-trained participants, the athletic-specific equation had neither mean (-0.89 kg; P = 0.789) or proportional bias (r = -0.104; P = 0.474) with a coefficient of determination equal to R2 = 0.91. In contrast, the three generalized predictive equations overestimated FFM (range, 4.11-5.37 kg; P < 0.05) with R2 ranging from 0.84 to 0.90. The athletic-specific equation underestimated FFM in the general population participants (-2.93 kg; P < 0.05). CONCLUSIONS: When assessing body composition in resistance-trained exercisers, specific equations for athletes should be preferred to generalized ones to avoid an overestimation in FFM. Furthermore, athlete-specific and generalized formulas cannot be used interchangeably, even when assessing body composition in the general population.

Editorial: New Training Strategies and Evaluation Methods for Improving Health and Physical Performance.

Physical activity is among the most effective methods for improving health, body composition, and physical function, and its practice is suitable for every population [...].

Bioelectrical Impedance Vector Analysis Discriminates Aerobic Power in Futsal Players: The Role of Body Composition.

Aims: The present study aimed to assess the ability of bioelectrical impedance vector analysis (BIVA) in discriminating fitness levels in futsal players, exploring the association of body composition and bioelectrical parameters with aerobic power. Methods: Forty-eight professional futsal players (age 23.8 ± 5.3 years) were involved in a cross-sectional study during their pre-season phase. Fat mass (FM) and muscle mass were determined by dual-energy X-ray absorptiometry. VO2max was obtained by indirect calorimetry through a graded exercise test performed on a treadmill. Bioelectrical resistance (R), reactance (Xc), and phase angle (PhA) were directly measured using a foot-to-hand bioimpedance technology at a 50 kHz frequency. Bioelectric R and Xc were standardized for the participants' height and used to plot the bioimpedance vector in the R-Xc graph according to the BIVA approach. Results: The participants divided into groups of VO2max limited by tertiles showed significant differences in mean vector position in the R-Xc graph (p < 0.001), where a higher VO2max resulted in a longer vector and upper positioning. FM, muscle mass, and PhA differed (p < 0.01) among the athletes grouped by tertiles of VO2max, where athletes with a greater aerobic power showed a lower percentage of FM and a higher percentage of muscle mass and PhA. FM and PhA were associated with VO2max (FM: r = −0.658, p < 0.001; PhA: r = 0.493, p < 0.001). These relationships remained significant after adjusting for age and body mass (FM: ß = −0.335, p = 0.046; PhA: ß = 0.351, p = 0.003). Conclusions: Bioelectrical impedance vectors positioned on the lower pole of the R-Xc graph identified futsal players with a lower VO2max, while longer vectors corresponded to a greater aerobic power. Additionally, PhA, that describes the vector direction, was positively associated with VO2max, while a higher FM negatively affected VO2max in the futsal players. BIVA and PhA evaluation may represent a valid support for screening the aerobic fitness level in professional futsal players, when more sophisticated assessment methods are not available.

The effects of phosphatidic acid on performance and body composition - a scoping review.

Phosphatidic acid (PA) is a lipid mediator proposed to increase muscle protein synthesis via direct stimulation of the mammalian target of rapamycin (mTOR) and may act as an anabolic supplemental aid. Evidence on the effectiveness of PA as an anabolic supplement is equivocal. We aimed to systematically assess the effect of PA on performance and body composition. Due to the small number of studies, this is a scoping review. A comprehensive search was performed in Pubmed, SPORTDiscus and Web of Science, from the 1 January 2010 to the 31 August 2020. Our search retrieved 2009 articles, which when filtered, resulted in six studies, published between 2012 and 2019, which were analysed further. Five studies were performed in adult male populations and one in an elderly male population. From these, three studies suggested no effect of PA on lean body mass , while the remaining showed a possible positive effect (body composition and performance improvements). In one of these, the supplement included other potentially anabolic substances, precluding an isolated effect of PA. After a thorough analysis of the studies included, the evidence does not support the supplementation with PA to increase performance or improve body composition in young or elderly men.

Effectiveness of a lifestyle weight-loss intervention targeting inactive former elite athletes: the Champ4Life randomised controlled trial.

OBJECTIVES: Many athletes struggle in managing the end of their career, often gaining weight and adopting unhealthy lifestyles. Lifestyle programmes targeting former athletes who have gained substantial fat mass (FM) postsports career are lacking. We studied the effects of the Champ4Life programme on body composition and other health-related outcomes in former elite athletes with overweight or obesity. METHODS: Ninety-four former athletes(42.4±7.3 y, 34.0% female) were recruited and randomly assigned to either an intervention group (IG; n=49) or a control group (CG; n=45). The IG attended 12 educational sessions addressing physical activity, weight management and nutrition. They also had a nutrition appointment aimed to prescribe a moderate caloric deficit(~300-500 kcal/day). Dual-energy X-ray absorptiometry was used to assess body composition. The Short-Form Health Survey-36 questionnaire was used to measure general health-related quality of life. Blood samples were collected to assess cardiometabolic health parameters. RESULTS: At 12 months, the IG lost more weight (estimated difference (ED)=-5.3 kg; -6.9 to -3.8), total FM (ED=-4.1 kg; -5.4 to -2.8) and abdominal FM (ED=-0.49 kg; -0.64 to -0.33) than did the CG (p's<0.001). Cardiometabolic health markers also improved significantly (p<0.05) more in the IG at 12 months (insulin (ED=-4.9 µU/mL;-8.0 to -1.8); homoeostatic model assessment (ED=-1.2; -2.1 to -0.4); total cholesterol (ED=-21.8 mg/dL; -35.4 to -8.2); low-density lipoprotein (ED=18.2 mg/dL;-29.2 to -7.1)), as did quality-of-life dimensions (physical functioning (ED=11.7; 6.5 to 16.9); physical role (ED=17.6; 2.1 to 33.0); general health (ED=19.4; 11.4 to 27.4); vitality (ED=13.3; 5.3 to 21.3) and mental health (ED=12.3; 4.1 to 20.6)). CONCLUSIONS: The Champ4Life programme was effective in substantially reducing total and abdominal FM while preserving fat-free mass and improving health-related markers. These findings will enable evidence-based decisions when implementing lifestyle interventions targeting retired elite athletes. TRIAL REGISTERATION NUMBER: NCT03031951.

Adaptive thermogenesis after moderate weight loss: magnitude and methodological issues.

PURPOSE: The aim of this study was (1) to assess AT through 13 different mathematical approaches and to compare their results; and (2) to understand if AT occurs after moderate WL. METHODS: Ninety-four participants [mean (SD); BMI, 31.1 (4.3) kg/m2; age, 43.0 (9.4) years; 34% females] underwent a 1-year lifestyle intervention (clinicaltrials.gov ID: NCT03031951) and were randomized to intervention (IG, n = 49) or control groups (CG, n = 45), and all measurements were made at baseline and after 4 months. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. AT was assessed through 13 different approaches, varying in how REE was predicted and/or how AT was assessed. RESULTS: IG underwent a mean negative energy balance (EB) of 270 (289) kcal/day, p < 0.001), resulting in a WL of - 4.8 (4.9)% and an FM loss of - 11.3 (10.8)%. Regardless of approach, AT occurred in the IG, ranging from ~ - 65 to ~ - 230 kcal/day and three approaches showed significant AT in the CG. CONCLUSIONS: Regardless of approach, AT occurred after moderate WL in the IG. AT assessment should be standardized and comparisons among studies with different methodologies to assess AT must be avoided.

Generalized bioelectric impedance-based equations underestimate body fluids in athletes.

The current study aimed: (i) to external validate total body water (TBW) and extracellular water (ECW) derived from athlete and non-athlete predictive equations using radioisotope dilution techniques as a reference criterion in male and female athletes; (ii) in a larger sample, to determine the agreement between specific and generalized equations when estimating body fluids in male and female athletes practicing different sports. A total of 1371 athletes (men: n = 921, age 23.9 ± 1.4 y; women: n = 450, age 27.3 ± 6.8 y) participated in this study. All athletes underwent bioelectrical impedance analyses, while TBW and ECW were assessed with dilution techniques in a subgroup of 185 participants (men: n = 132, age 21.7 ± 5.1 y; women: n = 53, age 20.3 ± 4.5 y). Two specific and eight generalized predictive equations were tested. Compared to the criterion methods, no mean bias was observed using the athlete-specific equations for TBW and ECW (-0.32 to 0.05, p > 0.05) and the coefficient of determination ranged from R2  = 0.83 to 0.94. The majority of the generalized predictive equations underestimated TBW and ECW (p < 0.05); R2 ranged from 0.66 to 0.89. In the larger sample, all the generalized equations showed lower TBW and ECW values (ranging from -6.58 to -0.19, p < 0.05) than specific predictive equations; except for TBW in female power/velocity (one equation) athletes and team sport (two equations). The use of generalized BIA-based equations leads to an underestimation of TBW, and ECW compared to athlete-specific predictive equations. Additionally, the larger sample indicates that generalized equations overall provided lower TBW and ECW compared to the athlete-specific equations.

Phase Angle Is a Marker of Muscle Quantity and Strength in Overweight/Obese Former Athletes.

BACKGROUND: An increasing body of evidence indicates that the phase angle (PhA) can be applied as a marker of nutritional status, disease prognosis, and mortality probability. Still, it is not known whether PhA can be used as an indicator of muscular quantity and strength and maximal aerobic capacity in overweight/obese former highly active individuals, an understudied population. This study aimed to analyze the association between PhA with skeletal muscle mass, maximal isometric strength, and maximal aerobic capacity through VO2max, in overweight/obese and inactive former athletes. METHODS: Cross-sectional information of 94 (62 males) former adult athletes (age: 43.1 ± 9.4 years old; body mass index: 31.4 ± 4.8 kg/m2) taking part in a weight-loss clinical trial was analyzed. Total fat and fat-free mass were determined by dual-energy X-ray absorptiometry, while skeletal muscle mass was predicted from appendicular lean soft tissue. Values for upper- and lower-body maximal isometric strength were assessed by handgrip and leg press dynamometry. VO2max was determined by indirect calorimetry through a graded exercise test performed on a treadmill. RESULTS: PhA was associated with skeletal muscle mass (r = 0.564, p < 0.001), upper-body strength (r = 0.556, p < 0.001), lower-body strength (r = 0.422, p < 0.001), and VO2max (r = 0.328, p = 0.013). These relationships remained significant for skeletal muscle mass (ß = 2.158, p = 0.001), maximal isometric strength (upper-body: ß = 2.846, p = 0.012; low-er-body: ß = 24.209, p = 0.041) after adjusting for age, sex, and fat mass but not for VO2max (ß = -0.163, p = 0.098). CONCLUSION: Our findings indicated that former athletes with higher values of PhA exhibited greater muscle mass and strength, despite sex, age, and body composition, which suggests that this simple raw BI parameter can be utilized as an indicator of muscle quantity and functionality in overweight/obese former athletes.

Fat-free Mass Bioelectrical Impedance Analysis Predictive Equation for Athletes using a 4-Compartment Model.

Bioelectrical impedance analysis equations for fat-free mass prediction in healthy populations exist, nevertheless none accounts for the inter-athlete differences of the chemical composition of the fat-free mass. We aimed to develop a bioimpedance-based model for fat-free mass prediction based on the four-compartment model in a sample of national level athletes; and to cross-validate the new models in a separate cohort of athletes using a 4-compartment model as a criterion. There were 142 highly trained athletes (22.9±5.0 years) evaluated during their respective competitive seasons. Athletes were randomly split into development (n=95) and validation groups (n=47). The criterion method for fat-free mass was the 4-compartment model. Resistance and reactance were obtained with a phase-sensitive 50 kHz bioimpedance device. Athletic impedance-based models were developed (fat-free mass=- 2.261+0.327*Stature2/Resistance+0.525*Weight+5.462*Sex, where stature is in cm, Resistance is in Ω, Weight is in kg, and sex is 0 if female or 1 if male). Cross validation revealed R2 of 0.94, limits of agreement around 10% variability and no trend, as well as a high concordance correlation coefficient. The new equation can be considered valid thus affording practical means to quantify fat-free mass in elite adult athletes.

Prediction of Somatotype from Bioimpedance Analysis in Elite Youth Soccer Players.

The accurate body composition assessment comprises several variables, causing it to be a time consuming evaluation as well as requiring different and sometimes costly measurement instruments. The aim of this study was to develop new equations for the somatotype prediction, reducing the number of normal measurements required by the Heath and Carter approach. A group of 173 male soccer players (age, 13.6 ± 2.2 years, mean ± standard deviation; body mass index, BMI, 19.9 ± 2.5 kg/m2), members of the academy of a professional Italian soccer team participating in the first division (Serie A), participated in this study. Bioelectrical impedance analysis (BIA) was performed using the single frequency of 50 kHz and fat-free mass (FFM) was calculated using a BIA specific, impedance based equation. Somatotype components were estimated according to the Heath-Carter method. The participants were randomly split into development (n = 117) and validation groups (n = 56). New anthropometric and BIA based models were developed (endomorphy = -1.953 - 0.011 × stature2/resistance + 0.135 × BMI + 0.232 × triceps skinfold, R2 = 0.86, SEE = 0.28; mesomorphy = 6.848 + 0.138 × phase angle + 0.232 × contracted arm circumference + 0.166 × calf circumference - 0.093 × stature, R2 = 0.87, SEE = 0.40; ectomorphy = -5.592 - 38.237 × FFM/stature + 0.123 × stature, R2 = 0.86, SEE = 0.37). Cross validation revealed R2 of 0.84, 0.80, and 0.87 for endomorphy, mesomorphy, and ectomorphy, respectively. The new proposed equations allow for the integration of the somatotype assessment into BIA, reducing the number of collected measurements, the instruments used, and the time normally required to obtain a complete body composition analysis.

A New Strategy to Integrate Heath-Carter Somatotype Assessment with Bioelectrical Impedance Analysis in Elite Soccer Player.

Easy-to-apply and quick methods for evaluate body composition are often preferred when assessing soccer teams. This study aimed to develop new equations for the somatotype quantification that would reduce the anthropometric measurements required by the Heath and Carter method, integrating the somatotype assessment to the bioelectrical impedance analysis (BIA). One hundred and seventy-six male elite soccer players (age 26.9 ± 4.5 years), registered in the Italian first division (Serie A), underwent anthropometric measurements and BIA. Endomorphy, mesomorphy, and ectomorphy were obtained according to the Heath and Carter method, while fat mass (FM) and fat free mass (FFM) estimated using a BIA-derived equation specific for athletes. The participants were randomly split into development (n = 117) and validation groups (n = 59, 1/3 of sample). The developed models including resistance2/stature, FM%, FFM, contracted arm and calf circumference, triceps, and supraspinal skinfolds had high predictive ability for endomorphy (R2 = 0.83, Standard Error of Estimate (SEE) = 0.16) mesomorphy (R2 = 0.80, SEE = 0.36), and ectomorphy (endomorphy (R2 = 0.87, SEE = 0.22). Cross validation revealed R2 of 0.80, 0.84, 0.87 for endomorphy, mesomorphy, and ectomorphy, respectively. The proposed strategy allows the integration of somatotype assessment to BIA in soccer players, reducing the number of instruments and measurements required by the Heath and Carter approach.

Body Water Content and Morphological Characteristics Modify Bioimpedance Vector Patterns in Volleyball, Soccer, and Rugby Players.

Background: Bioimpedance vector analysis (BIVA) is a widely used method based on the interpretation of raw bioimpedance parameters to evaluate body composition and cellular health in athletes. However, several variables contribute to influencing BIVA patterns by militating against an optimal interpretation of the data. This study aims to explore the association of morphological characteristics with bioelectrical properties in volleyball, soccer, and rugby players. Methods: 164 athletes belonging to professional teams (age 26.2 ± 4.4 yrs; body mass index (BMI) 25.4 ± 2.4 kg/m2) underwent bioimpedance and anthropometric measurements. Bioelectric resistance (R) and reactance (Xc) were standardized for the athlete's height and used to plot the vector in the R-Xc graph according to the BIVA approach. Total body water (TBW), phase angle (PhA), and somatotype were determined from bioelectrical and anthropometric data. Results: No significant difference (p > 0.05) for age and for age at the start of competition among the athletes was found. Athletes divided into groups of TBW limited by quartiles showed significant differences in the mean vector position in the R-Xc graph (p < 0.001), where a higher content of body fluids resulted in a shorter vector and lower positioning in the graph. Furthermore, six categories of somatotypes were identified, and the results of bivariate and partial correlation analysis highlighted a direct association between PhA and mesomorphy (r = 0.401, p < 0.001) while showing an inverse correlation with ectomorphy (r = -0.416, p < 0.001), even adjusted for age. On the contrary, no association was observed between PhA and endomorphy (r = 0.100, p = 0.471). Conclusions: Body fluid content affects the vector length in the R-Xc graph. In addition, the lateral displacement of the vector, which determines the PhA, can be modified by the morphological characteristics of the athlete. In particular, higher PhA values are observed in subjects with a high mesomorphic component, whereas lower values are found when ectomorphy is dominant.

Bioimpedance Vector Patterns Changes in Response to Swimming Training: An Ecological Approach.

BACKGROUND AND AIM: Monitoring bioelectric phase angle (PhA) provides important information on the health and the condition of the athlete. Together with the vector length, PhA constitutes the bioimpedance vector analysis (BIVA) patterns, and their joint interpretation exceeds the limits of the evaluation of the PhA alone. The present investigation aimed to monitor changes in the BIVA patterns during a training macrocycle in swimmers, trying to ascertain if these parameters are sensitive to training load changes across a 13-week training period. METHODS: Twelve national and international level swimmers (four females; eight males; 20.9 ± 1.9 years; with a competitive swimming background of 11.3 ± 1.8 years; undertaking 16-20 h of pool training and 4-5 h of dry-land training per week and 822.0 ± 59.0 International Swimming Federation (FINA) points) were evaluated for resistance (R) and reactance (Xc) using a single frequency phase sensitive bioimpedance device at the beginning of the macrocycle (M1), just before the beginning of the taper period (M2), and just before the main competition of the macrocycle (M3). At the three-time assessment points, swimmers also performed a 50 m all-out first stroke sprint with track start (T50 m) while time was recorded. RESULTS: The results of the Hotelling T2 test showed a significant vector displacement due to simultaneous R and Xc changes (p < 0.001), where shifting from top to bottom along the major axis of the R-Xc graph from M1 to M2 was observed. From M2 to M3, a vector displacement up and left along the minor axis of the tolerance ellipses resulted in an increase in PhA (p < 0.01). The results suggest a gain in fluid with a decrease in cellular density from M1 to M2 due to decrements in R and Xc. Nevertheless, the reduced training load characterizing taper seemed to allow for an increase in PhA and, most importantly, an increase of Xc, thus demonstrating improved cellular health and physical condition, which was concomitant with a significant increase in the T50 m performance (p < 0.01). CONCLUSIONS: PhA, obtained by bioelectrical R and Xc, can be useful in monitoring the condition of swimmers preparing for competition. Monitoring BIVA patterns allows for an ecological approach to the swimmers' health and condition assessment without resorting to equations to predict the related body composition variables.

Phase Angle as a Marker of Muscular Strength in Breast Cancer Survivors.

BACKGROUND: accurate prognostic tools are relevant for decision-making in cancer care. Objective measures, such as bioelectrical impedance (BI), have the potential to improve prognostic accuracy for these patients. This cross-sectional study aimed to investigate whether phase angle (PhA) derived from the electrical properties of the body tissues is a predictor of muscular strength in breast cancer survivors (BCS). METHODS: a total of 41 BCS (age 54.6 ± 9.2 years) were evaluated. PhA, obtained at frequency 50 kHz, was assessed with BI spectroscopy, and muscular strength with a handgrip dynamometer. Moderate-to-vigorous physical activity (MVPA) was assessed using the International Physical Activity Questionnaire (IPAQ). Measurements were performed in the morning after an overnight fast. RESULTS: linear regression analysis showed that PhA accounted for 22% (r2 = 0.22) of muscular strength variance. PhA remained a borderline predictor of muscular strength variance independently of age and MVPA. CONCLUSIONS: the findings of this study suggest that PhA is a significant predictor of maximal forearm isometric strength and a potential indicator of disease-related functionality in BCS.