Body composition can be estimated using anthropometric-based regression models, which are population-specific and should not be used interchangeably. However, the widespread availability of predictive equations in the literature makes selecting the most valid equations challenging. This systematic review compiles anthropometric-based predictive equations for estimating body mass components, focusing on those developed specifically for athletes using multicomponent models (i.e. separation of body mass into ≥ 3 components). Twenty-nine studies published between 2000 and 2024 were identified through a systematic search of international electronic databases (PubMed and Scopus). Studies using substandard procedures or developing predictive equations for non-athletic populations were excluded. A total of 40 equations were identified from the 29 studies. Of these, 36 were applicable to males and 17 to females. Twenty-six equations were developed to estimate fat mass, 10 for fat-free mass, three for appendicular lean soft tissue, and one for skeletal muscle mass. Thirteen equations were designed for mixed athletes, while others focused on specific contexts: soccer (n = 8); handball and rugby (n = 3 each); jockeys, swimming, and Gaelic football (n = 2 each); and futsal, padel, basketball, volleyball, American football, karate, and wheelchair athletes (n = 1 each). This review presented high-standards anthropometric-based predictive equations for assessing body composition in athletes and encourages the development of new equations for underrepresented sports in the current literature.

Objectives: CrossFit® is a high-intensity sport characterized by various workouts that require strength, speed, endurance, or agility, impacting participants' body composition. This observational study aimed to determine the morphological (anthropometrical and bioelectrical) profile of CrossFit® athletes and to compare them with other athletic populations. Methods: Anthropometrical measurements and bioelectrical vector analysis (classic and specific approaches) were performed on 145 CrossFit® practitioners (107 men aged 30.7 ± 8.4 years and 38 women aged 28.1 ± 6.7 years). Each participant's relative somatotype was calculated and compared between sexes and with a Spanish CrossFit® athletes' group. Resistance-reactance graphs and Hotelling's T2 test were applied to characterize the sample, compare them with an athletes' reference population, and identify differences between somatotype groups. Results: The most represented somatotype in both groups was the balanced mesomorph (male 3.5–5.2 - 1.7 and female 4.4–4.5 - 1.8). Compared with Spanish CrossFit® athletes, significant differences were denoted for men but not women (SAD = 2.3). The bioelectrical graphs indicated that the distribution of CrossFit® athletes is quite heterogeneous and within average values for the athlete's reference. The mesomorphic and endomorphic components were associated with a higher phase angle. Conclusions: CrossFit® practitioners predominantly present a mesomorphic component and show a body type like other power athletes, although with less pronounced characteristics. The somatotype may influence the vector's position in the RXc graphs. This study provided the bioelectrical tolerance ellipses for CrossFit® practitioners in classic and specific approaches for the first time.

Purpose This study aimed to assess hydration status before and after training using the bioelectrical impedance vector analysis (BIVA) method. Design Pre-post quasi-experimental designs. Method Twenty-four young water polo players (mean age: 13.30 ± 0.55) underwent assessment for bioelectrical and anthropometric measurements before and after a water polo training session. Results Most players fell within the 50% percentile of the bioelectrical tolerance ellipses of the reference population. The BIA vector differed statistically between players who achieved growth peaks (PGA: T2 = 9.1, p = 0.013) and those who did not (GPNA, T2 = 28.9, p < 0.001) compared to the reference and also differed between them (T2 = 37.7, p < 0.001). After training, a decrease in body mass (BM) and BM adjusted for water intake (p = 0.0001) and changes in BIA variables (p < 0.05) were observed. BIVA also showed a significant pre-post vector migration in both GPA (T2 = 24.7; p < 0.001) and GNPA (T2 = 43.1; p < 0.001), characterized by a decrease in resistance and opposite reactance directions (T2 = 33.6, p < 0.001). Conclusion Young water polo players exhibit a significant BM loss after training (∼ 2.5%). Ad libitum water intake seems to partially compensate dehydration. The resistance reduction indicates that BIVA captured the compensation for dehydration resulting from fluid intake.

Objectives The study aimed to investigate the relationship between raw bioelectrical data and physical performance in track and field athletes. Specifically, the objectives were to determine: 1) whether a regional bioelectrical impedance approach provides additional insights compared to whole-body analysis, 2) the reliability of the Levi Muscle Index (LMI) in this context, and 3) whether there are differences in these relationships between male and female athletes. Design This study utilized a cross-sectional design involving thirty-one female athletes (mean age 21.4 ± 3.8 years) and thirty male athletes (mean age 21.1 ± 2.6 years) from track and field. On a single day, participants underwent whole-body and regional bioelectrical impedance assessments focusing on the lower limbs, alongside strength and speed performance tests. Results The study found no significant differences in the relationship between whole-body versus regional bioelectrical impedance and performance tests. Resistance (R) demonstrated an inverse correlation, while phase angle (PhA) and Levi Muscle Index (LMI) showed direct correlations with most performance variables in track and field athletes. Significant differences were observed between male and female athletes across all parameters, with male athletes exhibiting superior performance, higher PhA and LMI values, and stronger correlation coefficients compared to females. Conclusions In summary, this study highlights the intricate relationship between body composition and physical performance in athletes. It underscores the importance of considering sex differences and the reliability of raw bioelectrical data, whether obtained through regional or whole-body approaches, in assessing athletic performance.

This study aimed to assess the physical characteristics of elite international soccer referees, compare them with other referee populations in the literature, and establish reference tolerance ellipses for the bioelectrical impedance vector analysis (BIVA) point graph. Forty-one elite international soccer referees (age 38.8 ± 3.6 years) participated in the study. The participants underwent body composition assessments, including dual-energy X-ray absorptiometry, BIVA, and somatotype. The Somatotype Attitudinal Distance (SAD), the two-sample Hotelling’s T2 test and the Mahalanobis test were used to determine somatotype and bioelectrical vector differences with the literature. The average somatotype of the referees was a balanced mesomorph (2.8, 6.5, 2.8). Elite international referees significantly differed from other samples in the literature (SAD = 2.1, 2.6, 2.9 with respect to Zimbabwean, Brazilian, and South African referees, respectively). The bioelectrical vector was significantly different from the general population (T2 ≤ 76.6; F = 38.8; D = 1.44; p < 0.001) and athletes (T2 ≤ 25.3; F = 12.6; D = 0.8; p < 0.001). Somatotype values and tolerance ellipses from this study may be useful as a reference for developing training programs and improving the selection process of referees in soccer.

Purpose To investigate the anthropometric profile of youth soccer goalkeepers in relation to the maturity offset after the COVID-19 pandemic. Methods Forty-two young male goalkeepers took part in the study. The anthropometric profile and body composition were assessed through the anthropometric method and the peak height velocity (PHV) was estimated. Participants were classified as pre-PHV ( n = 16, age = 11.31 ± 0.94), circa-PHV ( n = 7, age = 13.27 ± 1.02) and post-PHV ( n = 19, age = 16.86 ± 2.00). Results The adiposity was significantly higher in pre-PHV goalkeepers than circa- and post-PHV and in circa-PHV than in post-PHV, according to BMI ( p = 0.017), the percentage of fat mass ( p < 0.001) and the fat mass index ( p = 0.023). Compared with similar sample in literature assessed before the COVID-19 pandemic, the pre-PHV subgroup showed a higher prevalence of children at abdominal obesity risk (62.5 vs. 33.3%). Conclusion The current study shows a relationship between the maturity offset and goalkeepers’ anthropometric profile. The COVID-19 pandemic seemed to affect the abdominal obesity risk of pre-PHV children.

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.