Somatotype and Bioimpedance Vector Analysis: A New Target Zone for Male Athletes

Dominant Somatotype Development in Relation to Body Composition and Dietary Macronutrient Intake among High-Performance Athletes in Water, Cycling and Combat Sports

Relevant properties of the somatotype as important indicators can be associated with the body composition characteristics as well as both metabolic and bio-mechanical efficiency of athletes in the sport concerned. The primary aim of this single cross-sectional study was to determine the somatotype profiles in association with body composition and nutritional profiles among Lithuanian elite athletes (n = 189) involved in water, cycling and combat sports. The body composition along with the somatotype profiles and the nutritional status of athletes were evaluated using a battery of multiple frequency (5, 50, 250, 550, and 1000 kHz) bioelectrical impedance analysis (BIA) and a 3-day food record analysis. In terms of the prediction for athletes to be classified as endomorphs, mesomorphs or ectomorphs, the linear discriminant analysis was conducted to assess the grouping of samples. Both the multiple linear regression and multivariate logistic regression statistical analyses were performed to explore the associations between the independent and dependent variables. The central tendency values for the somatotype components of endomorphy, mesomorphy and ectomorphy in athletes playing water, cycling and combat sports were 4.3-4.9-3.4, 4.3-4.8-3.4 and 4.5-5.5-2.9, respectively. The central mesomorph somatotype with a trend towards endomorphy was dominant and varied according to a high muscle-to-fat ratio in elite athletes. Significant (p ≤ 0.001) positive associations between both endomorphy and mesomorphy values and higher body fat percentage as well as lower and upper limb muscle mass were identified. The lower levels of trunk muscle mass were related to athletes' endomorphy and mesomorphy, too. Furthermore, in the athletes' sample under analysis, high-level mesomorphs were prone to consume low-carbohydrate (adjusted odd ratio (AOR) 0.5, 95% confidence interval (CI) 0.2; 0.9) and high-protein diets (AOR 2.5, 95% CI 1.1; 5.5). Contrastingly, the elite athletes with a higher expression of endomorphy were on high-carbohydrate (AOR 5.4, 95% CI 1.1; 8.3) and high-fat diets (AOR 4.6, 95% CI 1.5; 7.1) along with insufficient protein diet (AOR 0.3, 95% CI 0.1; 0.9). Finally, whilst nutrition goals as a mediator can play a significant role in undergoing the maintenance of balance between the optimal body composition for athletic performance and the development of an ecto-mesomorphic somatotype, the elite athletes with higher levels of endomorphy value should be aware of lowering the body fat percentage coupled with dietary fat reduction and higher protein intakes. The findings obtained from the study may serve as an antecedent for a more targeted management of the elite athletes' training process. Somatotyping as an additional assessment method can be successfully deployed in choosing correct coaching techniques, contributing to talent recognition processes or identifying reference morphometric parameters in elite athletes competing in water, cycling and combat sports.

Athletic bioimpedance-based equations underestimate fat free mass components in male elite soccer players: development and validation of new soccer-specific predictive models

BACKGROUND

Bioelectrical impedance analysis (BIA) is a rapid and user-friendly technique for assessing body composition in sports. Currently, no sport-specific predictive equations are available, and the utilization of generalized formulas can introduce systematic bias. The objectives of this study were as follows: (i) to develop and validate new predictive models for estimating fat-free mass (FFM) components in male elite soccer players; (ii) to evaluate the accuracy of existing predictive equations.

METHODS

A total of 102 male elite soccer players (mean age 24.7 ± 5.7 years), participating in the Italian first league, underwent assessments during the first half of the in-season period and were randomly divided into development and validation groups. Bioelectrical resistance (R) and reactance (Xc), representing the bioimpedance components, were measured using a foot-to-hand BIA device at a single frequency of 50 kHz. Dual-energy X-ray absorptiometry was employed to acquire reference data for FFM, lean soft tissue (LST), and appendicular lean soft tissue (ALST). The validation of the newly developed predictive equations was conducted through regression analysis, Bland-Altman tests, and the area under the curves (AUC) of regression receiver operating characteristic (RROC) curves.

RESULTS

Developed models were: FFM = - 7.729 + (body mass × 0.686) + (stature2/R × 0.227) + (Xc × 0.086) + (age × 0.058), R2 = 0.97, Standard error of estimation (SEE) = 1.0 kg; LST = - 8.929 + (body mass × 0.635) + (stature2/R × 0.244) + (Xc × 0.093) + (age × 0.048), R2 = 0.96, SEE = 0.9 kg; ALST = - 24.068 + (body mass × 0.347) + (stature2/R × 0.308) + (Xc × 0.152), R2 = 0.88, SEE = 1.4 kg. Train-test validation, performed on the validation group, revealed that generalized formulas for athletes underestimated all the predicted FFM components (p < 0.01), while the new predictive models showed no mean bias (p > 0.05), with R2 values ranging from 0.83 to 0.91, and no trend (p > 0.05). The AUC scores of the RROC curves indicated an accuracy of 0.92, 0.92, and 0.74 for FFM, LST, and ALST, respectively.

CONCLUSIONS

The utilization of generalized predictive equations leads to an underestimation of FFM and ALST in elite soccer players. The newly developed soccer-specific formulas enable valid estimations of body composition while preserving the portability of a field-based method.

Body fat of competitive volleyball players: a systematic review with meta-analysis

BACKGROUND

Reference values of body fat for competitive volleyball players are lacking, making it difficult to interpret measurement results. This review systematically summarized published data on the relative body fat of volleyball players and calculated potential differences between sex, measurement method, and competitive level.

METHODS

The protocol followed the Preferred Reported Items for Systematic Reviews and Meta-Analysis guidelines. The literature search was conducted using five electronic databases to retrieve all relevant publications from January 1, 2010, to July 1, 2021. The 63 studies including 2607 players that met the inclusion criteria were analyzed using random-effects models. Data were reported as pooled mean body fat with 95% confidence intervals.

RESULTS

Body fat for males and females was 12.8% (11.9-13.8%) and 22.8% (21.9-23.7%), respectively. Body fat was 18.3% (16.3-20.4%) measured via skinfolds, 18.4% (15.6-21.2%) via bioelectrical impedance analysis, 24.2% (20.4-28.0%) via dual-energy x-ray absorptiometry and 21.6% (17.4-25.8%) via densitometry. Regional, national, and international-level players had body fat values of 19.5% (17.8-21.2%), 20.3% (18.6-22.0%), and 17.9% (15.7-20.4%), respectively. When the meta-regression was adjusted for the variables sex, measurement method, and competitive level, a significant difference between sex (p < 0.001), dual-energy x-ray absorptiometry and skinfolds (p = 0.02), and national and international-level players (p = 0.02) was found. However, sensitivity analysis revealed that findings regarding measurement method and competitive level were not robust and should, therefore, be interpreted with caution.

CONCLUSIONS

Despite the limitations of published data, this meta-analysis provided pooled values for body fat of male and female volleyball players for different competitive levels and measurement methods.

New bioelectrical impedance vector references and phase angle centile curves in 4,367 adults: The need for an urgent update after 30 years

BACKGROUND & AIMS

The bioelectrical impedance vector analysis (BIVA) represents a qualitative analysis of body composition. The vector, defined by resistance (R) and reactance (Xc) standardized by stature, can be evaluated compared to the 50%,75%, and 95% tolerance ellipses representative of the reference populations. The tolerance ellipses for healthy adults have been provided in 1995 and were developed by mixing underage, adult, and elderly subjects, possibly misrepresenting the actual adult population. The current multicentric, cross-sectional study aimed to provide new tolerance ellipses specific for the general adult population and as a secondary aim to present centile curves for the bioelectrical phase angle.

METHODS

R, Xc, and phase angle were measured in 2137 and 2230 males and females using phase-sensitive foot-to-hand analyzers at 50 kHz. A minimum of 35 subjects were included for each sex and age category from 18 to 65 years.

RESULTS

The new mean vectors showed a leftward shift on the R-Xc graph with respect to the former reference values (males: F = 75.3; p < 0.001; females: F = 36.6, p < 0.001). The results provided new 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentile curves for phase angle, identifying time point phases of decrement (males: -0.03° per year at 33.0-51.0 years and -0.05° per year after 51 years; females: -0.03° per year from 37.2 to 57.9 years).

CONCLUSIONS

Compared to the original references, the new data are characterized by a different distribution within the R-Xc graph with a higher phase angle. Thirty years after the BIVA invention, the current study presents new tolerance ellipses and phase angle reference values for the adult population.

New Predictive Resting Metabolic Rate Equations for High-Level Athletes: A Cross-Validation Study

PURPOSE

The present study aims a) to assess the agreement between the measured resting metabolic rate (RMR) using indirect calorimetry and different predictive equations (predicted RMR), and b) to propose and cross-validate two new predictive equations for estimating the RMR in high-level athletes.

METHODS

The RMR of 102 athletes (44 women) was assessed using indirect calorimetry, whereas the body composition was assessed using skinfolds. Comparisons between measured and predicted RMR values were performed using one-way ANOVA. Mean difference, root mean square error (RMSE), simple linear regression, and Bland-Altman plots were used to evaluate the agreement between measured and predicted RMR. The accuracy of predictive equations was analyzed using narrower and wider accuracy limits (±5% and ±10%, respectively) of measured RMR. Multiple linear regression models were employed to develop the new predictive equations based on traditional predictors (equation 1) and the stepwise method (equation 2).

RESULTS

The new equations 1 and 2 presented good agreement based on the mean difference (3 and -15 kcal·d -1 ), RMSE (200 and 192 kcal·d -1 ), and R2 (0.71 and 0.74), respectively, and accuracy (61% of subjects between the limit of ±10% of measured RMR). Cunningham's equation provided the best performance for males and females among the existing equations, whereas Jagim's equation showed the worst performance for males (mean difference = -335 kcal·d -1 ; RMSE = 386 kcal·d -1 ). Compared with measured RMR, most predictive equations showed heteroscedastic distribution (linear regression's intercept and slope significantly different from zero; P ≤ 0.05), mainly in males.

CONCLUSIONS

The new proposed equations can estimate the RMR in high-level athletes accurately. Cunningham's equation is a good option from existing equations, and Jagim's equation should not be used in high-level male athletes.

The Correlation between Psychological Characteristics and Psychomotor Abilities of Junior Handball Players

The general development of the sports world has guided researchers in sports science to study excellence in sports performance, namely, the study of the characteristics and requirements specific to each sport. However, in order to meet these requirements, each individual must have a set of specific characteristics similar to those of the group to which he/she belongs. The variables in the study are related to the psychomotor abilities and psychological aspects that could influence the overall performance of junior III handball players. The main work instruments are related to field testing and psychological characteristics measurement. For psychomotor abilities, we used means such as the TReactionCo software (eye-hand coordination), Just Jump platform (dynamic balance), Tractronix system (general dynamic coordination), and Illinois test (spatial-temporal orientation), and for the psychological characteristics, we used the Motivational Persistence Questionnaire. In addition, the result of the study is represented by new software that we created in order to better observe the level of development of these characteristics in junior handball players. From a statistical point of view, we calculated the correlations between psychomotor abilities and psychological characteristics using ANOVA in order to see field position differences and performed linear regression for the variables of this study.

Bioelectrical Impedance Vector Analysis of Young Elite Team Handball Players

Team handball is a highly dynamic sport where physical demands differ between categories and roles. Thus, physical characteristics are fundamental for the final performance. This study aims to (a) characterize a sample of young male and female elite team handball players with a non-athletic reference population; (b) to generate their 50%, 75%, and 95% percentiles of the bioelectrical variables. The study included 55 young elite team handball players (Males, n = 37, age = 17.0 ± 1.2 yrs, height = 185.8 ± 7.3 cm, weight = 82.0 ± 11.0 kg, body mass index (BMI) = 23.7 ± 2.5; Females, n = 18, age = 17.8 ± 0.9 yrs, height = 171.2 ± 6.4 cm, weight = 67.4 ± 7.2 kg, BMI = 23.0 ± 2.0). Height and bioelectrical variables were assessed in a state of euhydration and standard conditions. Bioelectrical impedance vector analysis (BIVA) was used to characterize the bioelectrical vector (BIA vector) distribution pattern for each group. Compared to the reference values, BIA vector showed statistically significant differences in males U17 (n = 19, T2 = 51.0, p < 0.0001), males U19 (n = 18, T2 = 82.0, p < 0.0001) and females U19 (n = 18, T2 = 85.8, p < 0.0001). Male groups were also bioelectrically different (T2 = 13.7, p = 0.0036). BIVA showed specific bioelectrical characteristics in young male and female elite handball players. This study provides an original data set of bioelectrical impedance reference values of young male and female elite team handball players. Our result might help to interpret individual bioimpedance vectors and define target regions for young handball players.

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.

Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis

Body composition is acknowledged as a determinant of athletic health and performance. Its assessment is crucial in evaluating the efficiency of a diet or aspects related to the nutritional status of the athlete. Despite the methods traditionally used to assess body composition, bioelectric impedance analysis (BIA) and bioelectric impedance vector analysis (BIVA) have recently gained attention in sports, as well as in a research context. Only until recently have specific regression equations and reference tolerance ellipses for athletes become available, while specific recommendations for measurement procedures still remain scarce. Therefore, the present narrative review summarizes the current literature regarding body composition analysis, with a special focus on BIA and BIVA. The use of specific technologies and sampling frequencies is described, and recommendations for the assessment of body composition in athletes are provided. Additionally, the estimation of body composition parameters (i.e., quantitative analysis) and the interpretation of the raw bioelectrical data (i.e., qualitative analysis) are examined, highlighting the innovations now available in athletes. Lastly, it should be noted that, up until 2020, the use of BIA and BIVA in athletes failed to provide accurate results due to unspecific equations and references; however, new perspectives are now unfolding for researchers and practitioners. In light of this, BIA and especially BIVA can be utilized to monitor the nutritional status and the seasonal changes in body composition in athletes, as well as provide accurate within- and between-athlete comparisons.

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.

Body Fat Assessment in International Elite Soccer Referees

Soccer referees are a specific group in the sports population that are receiving increasing attention from sports scientists. A lower fat mass percentage (FM%) is a useful parameter to monitor fitness status and aerobic performance, while being able to evaluate it with a simple and quick field-based method can allow a regular assessment. The aim of this study was to provide a specific profile for referees based on morphological and body composition features while comparing the accuracy of different skinfold-based equations in estimating FM% in a cohort of soccer referees. Forty-three elite international soccer referees (age 38.8 ± 3.6 years), who participated in the 2018 Russian World Cup, underwent body composition assessments with skinfold thickness and dual-energy X-ray absorptiometry (DXA). Six equations used to derive FM% from skinfold thickness were compared with DXA measurements. The percentage of body fat estimated using DXA was 18.2 ± 4.1%, whereas skinfold-based FM% assessed from the six formulas ranged between 11.0% ± 1.7% to 15.6% ± 2.4%. Among the six equations considered, the Faulkner's formula showed the highest correlation with FM% estimated by DXA (r = 0.77; R² = 0.59 p < 0.001). Additionally, a new skinfold-based equation was developed: FM% = 8.386 + (0.478 × iliac crest skinfold) + (0.395 × abdominal skinfold, r = 0.78; R² = 0.61; standard error of the estimate (SEE) = 2.62 %; p < 0.001). Due to these findings, national and international federations will now be able to perform regular body composition assessments using skinfold measurements.