Short-chain fatty acids (SCFAs) are metabolites produced in the gut via microbial fermentation of dietary fibers referred to as microbiota-accessible carbohydrates (MACs). Acetate, propionate, and butyrate have been observed to regulate host dietary nutrient metabolism, energy balance, and local and systemic immune functions. In vitro and in vivo experiments have shown links between the presence of bacteria-derived SCFAs and host health through the blunting of inflammatory processes, as well as purported protection from the development of illness associated with respiratory infections. This bank of evidence suggests that SCFAs could be beneficial to enhance the athlete’s immunity, as well as act to improve exercise recovery via anti-inflammatory activity and to provide additional energy substrates for exercise performance. However, the mechanistic basis and applied evidence for these relationships in humans have yet to be fully established. In this narrative review, we explore the existing knowledge of SCFA synthesis and the functional importance of the gut microbiome composition to induce SCFA production. Further, changes in gut microbiota associated with exercise and various dietary MACs are described. Finally, we provide suggestions for future research and practical applications, including how these metabolites could be manipulated through dietary fiber intake to optimize immunity and energy metabolism.

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.

The present study compared changes in body composition during the COVID-19-associated lockdown with the same period of the following season in elite soccer players. Fifteen elite male soccer players (30.5 ± 3.6 years.) underwent a bioelectrical impedance analysis (BIA) before (end of February) and after (end of May) the lockdown, which occurred during the 2019/2020 season, and at the same period during the following competitive season in 2020/2021, when restrictions were lifted. Fat and muscle mass were estimated using predictive equations, while phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) patterns were directly measured. After lockdown, fat mass remained unchanged (p > 0.05), while muscle mass (95%CI = −1.12/−0.64; ES = −2.04) and PhA (95%CI = 0.51/−0.24, ES = −1.56) decreased. A rightward displacement of the BIVA vector was also found (p < 0.001, ES = 1.50). After the same period during the regular season, FM% and muscle mass did not change (p > 0.05), while the PhA increased (95%CI = 0.01/0.22; ES = 0.63). A leftward vector displacement (p < 0.001, ES = 1.05) was also observed. The changes in muscle mass correlated with changes in PhA (“lockdown” season 2019/2020: ß = −1.128, p = 0.011; “regular” season 2020/21: ß = 1.963, p = 0.011). In conclusion, coaches and strength conditioners should monitor muscle mass in soccer players during detraining periods as this parameter appears to be mainly affected by changes in training plans.

Body composition assessment is a relevant element in the biomedical field, in research and daily practice in the medical and nutritional fields, and in the management of athletes. This paper aimed to operate in an Italian sample investigating the possibility of predicting the somatotype from bioimpedance analysis and comparing the predicted results with those obtained from anthropometric measurements. This observational study was conducted with retrospective data collected from 2827 subjects. The somatotype of each subject was calculated both with the Heath–Carter method and by a multiple regression model based on bioimpedance and anthropometric parameters. Somatotypes (endomorph, mesomorph, and ectomorph) were predicted with a high goodness of fit (R² adjusted > 0.80). Two different somatocharts were obtained from anthropometric measures and bioimpedance parameters and subsequentially compared. Bland–Altman plots showed acceptable accuracy. This study could be a first step in developing a new approach that allows the detection of a subject’s somatotype via bioimpedance analysis, stratified according to sex, with a time-saving and more standardized procedure. It would allow, for example, during the COVID-19 pandemic, to minimize operator–patient contact in having measurements.

Purpose: This observational longitudinal investigation aimed to investigate whether change in bioelectrical regional phase angle (PhA) is a predictor of change in vertical jump performance in elite soccer players. Methods: Fifteen soccer players (age: 28.7 ± 5.0 years, body weight: 82.4 ± 6.8 kg, height: 186.0 ± 0.1 cm, body mass index: 23.8 ± 1.2 kg/m²) competing in the first Italian division (Serie A) were included in this study and tested before the pre-season period and after the first half of the championship. Whole body and lower hemisoma PhA were obtained with a phase-sensitive 50 kHz bioelectrical impedance analyzer and legs lean soft tissue was estimated using specific bioimpedance-based equation developed for athletes. Vertical jump performance was assessed using the countermovement jump (CMJ). Results: The major findings of the study are that changes in lower hemisoma PhA are more strongly related with changes in jump performance (r² = 0.617, p = 0.001) than changes in whole-body PhA (r² = 0.270, p = 0.047), even after adjusting for legs lean soft tissue and for body mass index (β = 5.17, p = 0.004). Conclusions: These data suggest that changes in lower hemisoma PhA might be used as a tool for evaluating performance related parameters in sports where specific body segments are involved, in preference to the whole-body measured value.