Regional Bioelectrical Phase Angle Is More Informative than Whole-Body Phase Angle for Monitoring Neuromuscular Performance: A Pilot Study in Elite Young Soccer Players

Phase Angle and Body Composition as Predictors of Fitness and Athletic Performance in Adolescent Boxers

BACKGROUND

Phase angle (PhA) is an indicator of cellular health, function, and integrity. PhA has been considered an indicator of nutritional and health status, but it is uncertain whether it could be used as a fitness or athletic performance indicator.

OBJECTIVE

To analyze the relationship between PhA and the fitness and athletic performance of adolescent boxers and to know whether this association is independent of body composition.

METHODS

Thirty-seven trained youth boxers (15-18 y old) participated in the study. Participants underwent anthropometry and bioelectrical impedance assessments. The following tests were conducted: Fitness-Gram battery; speed, agility, and quickness; ball throws; punch impact force; bench press maximal strength; and vertical and horizontal jumps. Linear regression models were estimated and adjusted by covariates.

RESULTS

The PhA was related to upper-limb strength. Nevertheless, in linear regression models, after adjusting models by body composition, only PhA remained as a predictor of relative maximal strength. The PhA was not a predictor of speed, agility, and quickness; cardiorespiratory fitness; or lower-limb power, in which adiposity was the main predictor of fitness.

CONCLUSIONS

In adolescent boxers, PhA can predict upper-limb maximal strength independently of bioelectrical impedance analysis premises. However, compared with mucle mass, PhA is not a better predictor of upper-limb maximal strength.

Analysis of Hydration Habits Before and During a Specific Training Session in Male Padel Athletes Aged over 65: Physiological and Psychological Implications

(1) Background: Since older adults are more susceptible to dehydration and there is a lack of information on older athletes, this study observed a group of 12 male padel players in this age group (70.42 ± 3.50 years) to characterize their hydration habits, physiological demands, and psychological responses before and during a 90 min padel training (PT). (2) Methods: After approval from the Ethics Committee (CE/FCDEF-UC/00022023) and the provision of signed informed consent, participants' body mass, height, waist and hip circumferences, body mass index, waist-to-hip ratio, and waist-to-height ratio were measured. Habitual fluid intake was monitored by diary from the evening until before the PT; the subjects completed a Profile of Mood States questionnaire (POMS) and a satiety scale (SLIM). To assess hydration levels at different moments, we used a portable osmometer and an eight-point urine color chart and weighed the participants immediately before and after the PT. During the PT, heart rate (HR) and hydration were monitored. After the PT, subjects completed another POMS and SLIM. (3) Results: Subjects trained at 73.2 ± 12.3% of their maximum HR, with brief peaks at the anaerobic threshold or higher (130.00 ± 18.78 bpm). The mean urine osmolality indicated normal hydration or minimal dehydration. However, the urine color values indicated dehydration after the training. Subjects drank 438 mL of liquids at night, 333 mL before PT, and 900 mL during the PT, with a good repartition of the liquids. POMS and SLIM were not affected by the training. (4) Conclusions: Older male padel athletes achieved challenging yet safe training, staying within healthy intensity zones; their hydration patterns nearly met the recommendations for exercise and should be slightly increased.

Fat-free mass mediates the association between body mass and jump height in healthy young adults

BACKGROUND

The countermovement jump (CMJ) is a reliable and valid test of lower-extremity (LE) muscle power and neuromuscular performance. Body mass is positively associated with CMJ performance in young adults, warranting the examination of the influence of body composition on jump height (JH). This study examined the mediation effects of body composition on CMJ performance in young adults. The hypothesis was that fat-free mass and percent fat mass would significantly mediate the association between body mass with JH in young adults.

METHODS

Healthy young adults (N.=81; 47 female; mean age 25.1±3.4) completed this study and underwent body composition assessment using a bioelectrical impedance analysis device. Participants performed three CMJ trials to measure average JH using an electronic jump mat. Mediation analysis models were performed to examine the hypothesis of this study.

RESULTS

The mediation analyses indicated that the indirect effects of fat-free mass on the association between body mass with JH were significant (indirect effect [IE]=-0.23, 95% CI -0.315, 0.767; IE=0.76, 95% CI 0.334, 1.272; respectively), after controlling for sex and percent fat mass.

CONCLUSIONS

The association between body mass with JH in young adults with normal BMI was mediated by fat-free mass. Clinicians, trainers, and coaches should potentially target increasing fat-free mass when improving LE power and neuromuscular performance in rehabilitation and sports settings in this population, but further studies are needed.

The Effect of Passive Dehydration on Phase Angle and Body Composition: A Bioelectrical Impedance Analysis

Bioelectrical impedance analysis (BIA) is a method used to estimate body composition, and it relies mainly on the body's water content. Insufficient body water can introduce bias to body composition scores.

PURPOSE

To determine the effect of body weight loss elicited by passive dehydration on body composition scores, including phase angle (PhA).

METHODS

Twenty-five euhydrated apparently healthy and physically active men's (age = 22.6 ± 3.3 yr.; body mass = 76.7 ± 15.9 kg; height = 172.0 ± 6.3 cm) body composition variables and PhA were measured before and after sitting quietly for 5 h in a controlled environment (26.6 ± 1.7 °C, 72 ± 4.9%RH).

RESULTS

It was found that five hours of passive dehydration caused a loss in body weight (Δ = 0.76 ± 0.34 kg, p < 0.05) and a decrease in body fat estimation (Δ = 0.90 ± 0.87 kg, p < 0.001). Additionally, an increase in ECW (Δ = 0.12 ± 0.30 L, p < 0.021) and PhA (Δ = 0.10 ± 0.15°, p < 0.005) was observed.

CONCLUSION

Body weight loss due to passive dehydration decreased BIA-derived fat mass, and increased extracellular water and PhA in physically active and apparently healthy men. Nonetheless, these changes had a negligible effect on the accuracy of the equipment, rendering them clinically insignificant.

Maximal Running Speed and Critical Speed Are Positively Related to Phase Angle in Healthy Young Adults

Phase Angle (PhA), derived from bioelectrical impedance analysis, is a measurement of cellular resistance to electrical current and a non-invasive tool to monitor neuromuscular performance. The relationship between PhA and components of athletic performance is not fully understood. The purpose of this study was to determine if maximal running speed, critical speed (CS), and/or D prime (D') derived from a 3-minute all-out-test (3MAOT) correlates to PhA, reactance (Xc), or resistance (R). Sixty-one (male n=35, female n=26) healthy young adults (23.4±3.9 years) completed bioelectrical impedance analysis (Inbody770) and a 3MAOT. The correlations between PhA, Xc, and R and 3MAOT results were evaluated using correlations. Simple and multiple linear-regressions were used to test if results from the 3MAOT (maximum running speed, CS, D') could predict PhA. Linear regression analysis indicated that maximum running speed and CS alone explained 32% and 9% of the variance in PhA, respectively (R2=0.32, p<0.05; R2=0.09, p<0.05). Multiple linear regression indicated that maximum running speed, CS, and D' explained 35% of the variance in PhA (R2=0.35; p<0.05). Only maximum running speed remained a significant predictor of PhA after controlling for age (β=0.45; p<0.05), but not after controlling for both age and sex (β=0.14; p>0.05). Since maximum running speed was a stronger predictor of PhA compared to CS (proxy for endurance performance), practitioners should use discernment when using PhA as a readiness tool to monitor endurance performance.

Limb-specific isometric and isokinetic strength in adults: The potential role of regional bioelectrical impedance analysis-derived phase angle

BACKGROUND & AIMS

It is not yet known whether regional bioelectrical impedance (BIA) phase angle (PhA) may be informative of different types of strength performed by the lower and upper limbs, independently of lean soft tissue mass (LSTM). Using a sample of healthy adults, we aimed to examine the association and relevance of regional PhA relative to isometric and isokinetic strength of each limb.

METHODS

A total of 57 participants (32.7 ± 12.9 years; 24.7 ± 3.5 kg/m2) were included in the present investigation. Regional raw BIA variables were determined using a phase-sensitive BIA device. Dual-energy X-ray absorptiometry was used to evaluate LSTM. Absolute isometric and isokinetic (i.e., 60°/s and 180°/s) strength of each limb (extension and flexion) was assessed using an isokinetic dynamometer and used to calculate relative strength.

RESULTS

In absolute strength, only dominant leg PhA was associated with isometric extension strength (β = 0.283) and isokinetic 180°/s flexion strength (β = 0.354), regardless of LSTM (p < 0.05). In relative strength, a significant association of regional PhA was found for dominant arm flexion isometric strength (β = 0.336), and non-dominant arm and dominant leg extension isometric strength (β = 0.377, β = 0.565, respectively; p < 0.05), independently of LSTM. Similarly, for isokinetic 180°/s strength, regional PhA significantly explained the variance in the relative strength of both arms and dominant leg (β = 0.350 to 0.506), regardless of LSTM (p < 0.05). Relative isokinetic 60°/s strength was not consistently associated with regional PhA (p ≥ 0.05).

CONCLUSIONS

Regional PhA significantly explained relative (isometric and 180°/s isokinetic strength of both arms and dominant leg), but not absolute muscle strength, independently of regional LSTM. Thus, after accounting for body size, regional PhA seems to have its own characteristics that explain relative strength independently of LSTM.

How Do Football Playing Positions Differ in Body Composition? A First Insight into White Italian Serie A and Serie B Players

The present study aimed to investigate how playing positions differ in specific body composition variables in professional soccer players with respect to specific field zones and tactical lines. Five hundred and six Serie A and B professional soccer players were included in the study and analyzed according to their playing positions: goalkeepers (GKs), central backs (CBs), fullbacks (FBs), central midfielders (MIDs), wide midfielders (WMs), attacking midfielders (AMs), second strikers (SSs), external strikers (ESs), and central forwards (CFs), as well as their field zones (central and external) and tactical lines (defensive, middle, and offensive). Anthropometrics (stature and body mass) of each player were recorded. Then, body composition was obtained by means of bioelectric impedance analysis (BIA). GKs and CFs were the tallest and heaviest players, with no differences from each other. Likewise, GKs and CFs, along with CBs, were apparently more muscular (for both upper and lower limbs) and fatter at the same time compared with the other roles. Overall, players of the defensive line (CBs and FBs), along with those playing in central field zones (CBs, MIDs, AMs, SSs, and CFs), were significantly (p < 0.05) superior in almost all anthropometric and body composition variables than those of middle and offensive line and external zones, respectively.

Relationship between Bioelectrical Impedance Phase Angle and Upper and Lower Limb Muscle Strength in Athletes from Several Sports: A Systematic Review with Meta-Analysis

The phase angle (PhA) of bioelectrical impedance is determined by primary factors such as age, body mass index and sex. The researchers' interest in applying PhA to better understand the skeletal muscle property and ability has grown, but the results are still heterogeneous. This systematic review with a meta-analysis aimed to examine the existence of the relationship between PhA and muscle strength in athletes. The data sources used were PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science and the study eligibility criteria were based on the PECOS. The searches identified 846 titles. From those, thirteen articles were eligible. Results showed a positive correlation between PhA and lower limb strength (r = 0.691 [95% CI 0.249 to 0.895]; p = 0.005), while no meta-analysis was possible for the relationships between PhA and lower limb strength. Furthermore, GRADE shows very low certainty of evidence. In conclusion, it was found that most studies showed a positive correlation between PhA and vertical jump or handgrip strength. The meta-analysis showed the relationship between PhA and vertical jump, however, little is known for the upper limbs as was not possible to perform a meta-analysis, and for the lower limbs we performed it with four studies and only with vertical jump.

Bioimpedance basics and phase angle fundamentals

Measurement of phase angle using bioimpedance analysis (BIA) has become popular as an index of so-called "cellular health". What precisely is meant by this term is not always clear but strong relationships have been found between cellular water status (the relative amounts of extra- and intracellular water), cell membrane integrity and cellular mass. Much of the current research is empirical observation and frequently pays little regard to the underlying biophysical models that underpin the BIA technique or attempts to provide mechanistic explanations for the observations. This brief review seeks to provide a basic understanding of the electrical models frequently used to describe the passive electrical properties of tissues with particular focus on phase angle. In addition, it draws attention to some practical concerns in the measurement of phase angle and notes the additional understanding that can be gained when phase angle are obtained with bioimpedance spectroscopy (BIS) rather than single frequency BIA (SFBIA) along with the potential for simulation modelling.

Evaluation of raw segmental bioelectrical impedance variables throughout anterior cruciate ligament reconstruction rehabilitation

Background.Raw bioelectrical impedance analysis (BIA) variables are related to physical function in healthy and diseased populations. Therefore, BIA may be an insightful, noninvasive method of assessment to track following anterior cruciate ligament reconstruction (ACLR).Objectives.Evaluate phase angle, reactance and impedance at 50 kHz (PhA₅₀, Xc₅₀, andZ₅₀, respectively) in the operative (OP) and non-operative (NOP) limbs during ACLR rehabilitation.Approach.Seventeen patient (12 M, 5 F; 18.8 ± 4.8 years) clinic reports were evaluated prior to ACLR (PRE), two- (2 W), six- (6 W), and twelve-weeks (12 W) post-ACLR and at return to sport testing (RTS).Setting.All observations occurred during the participant's physical therapy visits.Measurements.A multi-frequency BIA device measured segmental PhA, Xc, andZ. Linear mixed effects models were used to assess any leg and time interaction and changes over leg and time, independently. Any interactions or main effects were considered significant atp< 0.05.Main results.Significant legxtime interactions were observed for each variable. PhA₅₀and Xc₅₀of NOP were higher (p< 0.001) than OP at each time point by an average of by 0.9° and 4.9 Ω, respectively. In OP, PhA₅₀and Xc₅₀decreased from PRE to 2 W and increased from 6 to 12 W and 12 W to RTS (p< 0.01, for all). At RTS, PhA₅₀and Xc₅₀were similar to PRE in OP (p> 0.05). ForZ₅₀, the OP leg did not change over time (p> 0.05).Z₅₀was greater in NOP at 2 and 6 W (p< 0.01, for both). There were differences in PhA₅₀in NOP between PRE and 6 W and from 6 W to RTS (p< 0.05 for both). Xc₅₀did not change (p> 0.05), andZ₅₀PRE was lower than at 2 W (p< 0.05).Significance.A multi-frequency BIA device can detect changes in segmental BIA variables following ACLR.