The Influence of Maturity Status on Anthropometric Profile and Body Composition of Youth Goalkeepers

Heart rate variability, recovery and stress analysis of an elite rally driver and co-driver during a competition period

To ensure both optimal health and performances, monitoring physiological and psychological states is of main importance for athletes. It is well known that monitoring heart rate variability and using validated questionnaires is useful for monitoring both the health and training status of athletes of different sports. Motorsports such as rally require high levels of physical and mental preparation thus information about psychophysiological status of rally athletes is fundamental. The aim of this study was to assess the autonomic regulation, stress, recovery conditions of one driver and one co-driver competing at the Italian National Rally Championship during their competition period. Heart rate variability parameters, acute recovery and stress states were assessed the day before, during the two days of race and the day following the races. Results showed that driver and co-driver had a sharp decrease of mean RR intervals, root mean square of successive differences between normal heartbeats, and standard deviation of the N-N interval during race days, while the stress index showed the inverse trend, and this behaviour was clearly visible in the Poincaré plots and power spectrum density graphs. The acute recovery and stress states questionnaire showed significant differences in recovery and stress scoring for the driver but not for the co-driver, although the trends were similar. This study describes the psychophysiological demands of a rally competition period suggesting that a daily evaluation of heart rate variability, recovery, stress states is useful for monitoring health status in rally athletes and could be implemented to make decision about training and recovery strategies.

The Influence of Somatic Maturity on Anthropometrics and Body Composition in Youth Soccer Players

The primary aim of this investigation was to compare players' anthropometric (AP) and body composition (BC) characteristics between distinct maturity bands (pre-PHV, circa-PHV, post-PHV) in youth elite soccer. This study considered 320 male soccer players (mean age 13.8 y). Participants were from U14 (n = 157) and U15 (n = 163) age categories. The Khamis-Roche method was applied to calculate the percentage of predicted adult height (PAH) at the time of assessment based on which the players were further divided into maturity bands (pre-PHV ≤ 87%, circa-PHV = 88-95%, post-PHV > 95%). The findings indicated that most of the players were in the circa-PHV stage at the time of investigation. Measurements included height and weight. The estimates of BC parameters were derived using bioelectrical impedance (BIA) analysis. These various AP and BC attributes displayed significant differences among the maturity bands (F = 139.344-7.925; p < 0.001; large effect sizes) except in body fat mass (BFM) (F = 2.998; p = 0.051; small effect size). The current somatic maturity stage of the athletes should be considered when evaluating BC results, otherwise there is a risk of misinterpretation.

Betaine Treatment Prevents TNF-α-Mediated Muscle Atrophy by Restoring Total Protein Synthesis Rate and Morphology in Cultured Myotubes

Skeletal muscle atrophy is represented by a dramatic decrease in muscle mass, and it is related to a lower life expectancy. Among the different causes, chronic inflammation and cancer promote protein loss through the effect of inflammatory cytokines, leading to muscle shrinkage. Thus, the availability of safe methods to counteract inflammation-derived atrophy is of high interest. Betaine is a methyl derivate of glycine and it is an important methyl group donor in transmethylation. Recently, some studies found that betaine could promote muscle growth, and it is also involved in anti-inflammatory mechanisms. Our hypothesis was that betaine would be able to prevent tumor necrosis factor-α (TNF-α)-mediated muscle atrophy in vitro. We treated differentiated C2C12 myotubes for 72 hr with either TNF-α, betaine, or a combination of them. After the treatment, we analyzed total protein synthesis, gene expression, and myotube morphology. Betaine treatment blunted the decrease in muscle protein synthesis rate exerted by TNF-α, and upregulated Mhy1 gene expression in both control and myotube treated with TNF-α. In addition, morphological analysis revealed that myotubes treated with both betaine and TNF-α did not show morphological features of TNF-α-mediated atrophy. We demonstrated that in vitro betaine supplementation counteracts the muscle atrophy led by inflammatory cytokines.

Correlations between Anthropometric Measurements and Sports Discipline Aptitude

Background: Sports specialization is required for the advancement of elite-level skills of a competitor. Therefore, this study attempted to assess the applicability of anthropometric measurements for a tailored selection of sports disciplines. Methods: The sports disciplines studied in this report were wrestling, triple jumping, badminton, and tennis. The data used in this study were obtained from a PubMed search. Literature-derived data were used as a template to build a random Gaussian population of N = 500 subjects used for ratio calculation using the error propagation approach. The obtained ratios encompassed height/sitting height, height/length, height/arm length, height/waist circumference, height/chest circumference, sitting height/leg length, sitting height/arm length, sitting height/waist circumference, sitting height/chest circumference, arm/leg length, and arm length/forearm length. Results: There is a clear relationship between a sports discipline and the distribution of the anthropometric ratio. The anthropometric measurements of wrestlers are the most outstanding among the disciplines studied. The use of machine learning algorithms, that is, the decision tree classifier, allows for building a model able to distinguish between the disciplines of sports studied. Conclusions: The presented approach allows for selection of a specific sports discipline for a young person. Moreover, an extension of the model built by other sports disciplines and anthropometric measurement may be a practical tool for selecting sports subjects.

Estimation of Heart Rate Variability Parameters by Machine Learning Approaches Applied to Facial Infrared Thermal Imaging

Heart rate variability (HRV) is a reliable tool for the evaluation of several physiological factors modulating the heart rate (HR). Importantly, variations of HRV parameters may be indicative of cardiac diseases and altered psychophysiological conditions. Recently, several studies focused on procedures for contactless HR measurements from facial videos. However, the performances of these methods decrease when illumination is poor. Infrared thermography (IRT) could be useful to overcome this limitation. In fact, IRT can measure the infrared radiations emitted by the skin, working properly even in no visible light illumination conditions. This study investigated the capability of facial IRT to estimate HRV parameters through a face tracking algorithm and a cross-validated machine learning approach, employing photoplethysmography (PPG) as the gold standard for the HR evaluation. The results demonstrated a good capability of facial IRT in estimating HRV parameters. Particularly, strong correlations between the estimated and measured HR (r = 0.7), RR intervals (r = 0.67), TINN (r = 0.71), and pNN50 (%) (r = 0.70) were found, whereas moderate correlations for RMSSD (r = 0.58), SDNN (r = 0.44), and LF/HF (r = 0.48) were discovered. The proposed procedure allows for a contactless estimation of the HRV that could be beneficial for evaluating both cardiac and general health status in subjects or conditions where contact probe sensors cannot be used.

Age-Related Differences in the Anthropometric and Physical Fitness Characteristics of Young Soccer Players: A Cross-Sectional Study

Considering that most professional academies seek to optimize the early detection and physical development of their younger players, the purpose of this study was to examine the anthropometric and physical fitness characteristics in a large cross-sectional sample of youth soccer players in Eastern Europe, starting from a very young age during their in-season period. Three hundred and thirteen soccer players (n = 313), grouped into eight age categories, participated in the study. On the basis of chronological age, the group categories were: 7 (n = 26), 8 (n = 41), 9 (n = 46), 10 (n = 48), 11 (n = 42), 12 (n = 47), 13 (n = 43), and 14 years old (n = 20). The players underwent an anthropometric evaluation, flexibility, handgrip strength, vertical jump performance, speed, and agility assessments. A one-way multivariate analysis of variance (MANOVA) indicated significant differences in the anthropometric and physical fitness variables based on chronological age (F = 13.40, p < 0.05, Wilk’s Λ = 0.08, partial η2 = 0.30). Concurrently, there were significant growth and physical fitness differences even in players born in the same chronological year. It is believed that the results have important practical implications, especially for those involved in youth soccer. Based on our results, coaches should contemplate speed and agility development in training sessions starting from a much younger age, as sprinting while changing directions has been considered an essential prerequisite in soccer.

Toward an Anthropometric Pattern in Elite Male Handball

We investigated the anthropometric characteristics associated with specific handball skills in competition. The body anthropometric profiles differ significantly among the playing positions in handball due to the specific tasks. The aim of this study is to identify the anthropometric patterns for each playing position by collecting data from elite male handball players. To determine the anthropometric profile of the elite handball players for each playing position, we used descriptive statistics for every indicator in order to identify the optimal patterns for elite handball players from the top-four ranked teams at the most important competitions over a period of 18 years (2004-2021). Over time, the anthropometric indices evolved: the average height increased (from 190 to 192.6 cm) but less than weight increased (from 90.5 to 95.28 kg), and these affected the body mass index (increase from 25.2 to 25.67). The novelty of our study is that we identified an anthropometric pattern for each playing position and for all teams in elite male handball. Our study also covered a period of 18 years to give our results more accuracy and reliability.

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.

The Prediction of Running Velocity during the 30-15 Intermittent Fitness Test Using Accelerometry-Derived Metrics and Physiological Parameters: A Machine Learning Approach

Measuring exercise variables is one of the most important points to consider to maximize physiological adaptations. High-intensity interval training (HIIT) is a useful method to improve both cardiovascular and neuromuscular performance. The 30–15_IFT is a field test reflecting the effort elicited by HIIT, and the final velocity reached in the test is used to set the intensity of HIIT during the training session. In order to have a valid measure of the velocity during training, devices such as GPS can be used. However, in several situations (e.g., indoor setting), such devices do not provide reliable measures. The aim of the study was to predict exact running velocity during the 30–15_IFT using accelerometry-derived metrics (i.e., Player Load and Average Net Force) and heart rate (HR) through a machine learning (ML) approach (i.e., Support Vector Machine) with a leave-one-subject-out cross-validation. The SVM approach showed the highest performance to predict running velocity (r = 0.91) when compared to univariate approaches using PL (r = 0.62), AvNetForce (r = 0.73) and HR only (r = 0.87). In conclusion, the presented multivariate ML approach is able to predict running velocity better than univariate ones, and the model is generalizable across subjects.

Body Composition and Physical Health in Sports Practice: An Editorial

The assessment of the health status of athletes, at all ages, is an aspect of fundamental importance, and, in recent years, the analysis of body composition has become a fundamental and essential part in its evaluation, such as in the optimization of sports performance [...].