Purpose. To establish the relationship between body mass, body composition with indicators of anaerobic productivity of women aged 25-35. Materials and methods. 392 women aged 25-35 years participated in the study. The power of anaerobic alactate productivity was determined by the 10-second Wingate test. The power of anaerobic lactate productivity was determined by the 30-second Wingate test. The capacity of anaerobic lactate productivity was determined by the e maximum amount of external mechanical work per 1 minute. Body fat percentage, body muscle percentage, and visceral fat content were determined by the bioelectrical impedance method. The results. It was found that the correlation of body mass, body mass index and percentage of the muscle component of women aged 25-35 with performance in anaerobic tests is characterized as direct. The degree of correlation of indicators of physical development with absolute indicators of anaerobic productivity is higher than with relative indicators. Performance in anaerobic tests is most strongly correlated with body mass and body mass index. The degree of correlation of body mass, body mass index with tests characterizing the power of anaerobic alactate and lactate productivity of the body corresponds to "high". A "high" degree of correlation of the capacity of anaerobic lactate productivity of the body was established only with body mass. Conclusions. Among indicators of physical development, body mass and body mass index have the greatest influence on the anaerobic capabilities of the body of women aged 25-35, who do not play sports. Higher values of body mass and body mass index are predictive of higher level of anaerobic productivity. The high degree of correlation with body mass and body mass index is due to the specifics of the cycle ergometeric tests. Running anaerobic tests will not give a direct correlation of a high degree, because they are related to the movement of body weight along the distance. The percentage content of fat and muscle components, the level of visceral fat cannot be predictors of the level of anaerobic productivity of the body in women who do not do sports.

Background: Athletes’ skin is exposed to increased microbial challenges due to rigorous physical activity, perspiration, constant “skin-to-skin” contact, frequent showering, use of hygiene products, and environmental factors present in training settings. This study aims to characterize the skin microbiome communities of young wrestlers and kickboxers in comparison with their non-athlete age-peers. Methods: A total of 56 combat sport athletes (30 males and 26 females, mean age ± SD = 18.2 ± 1.5 years) and 25 non-athlete youths (control group: 13 males and 12 females, mean age ± SD = 19.8 ± 1.2 years) voluntarily consented to participate in the study conducted by our research team in 2023 and 2024. The skin microbiome analysis involved standardized sampling, DNA isolation, molecular sequencing, and bioinformatic analysis, thus enabling detailed characterization and comparison of the skin microbial community in contact sports athletes and the control group. Results: Our results revealed notable sexual dimorphism in the skin microbiome composition of youth. Males showed a higher relative abundance of bacterial genera associated with nosocomial infections and respiratory diseases, while females had more skin inflammation- and infection-related genera (relative abundances in males vs. in females: Corynebacterium—12.0 vs. 7.2; Luteimonas—4.4. vs. 1.4; Paracoccus—8.8 vs. 5.0; Psychrobacter—6.3 vs. 4.4; Cutibacterium—6.4 vs. 11.4; Kocuria—1.6 vs. 3.9; Micrococcus—5.8 vs. 8.5; Pseudomonas—1.2 vs. 3.4; Streptococcus 3.3 vs. 6.2). We also found skin microbiome differences between athletes and non-athletes in both sexes: wrestlers, who experience frequent skin-to-skin contact and wear less covering sportswear, had microbiome profiles distinct from both kickboxers and non-athletes (relative abundances in athletes vs. in non-athletes: Psychrobacter—7.3 vs. 0.4; Staphylococcus 9.5 vs. 18.5; predominance of genera by sports type: relative abundance of Cutibacterium and Streptococcus was higher in kickboxers, and relative abundance of Acinetobacter, Enhydrobacter, Micrococcus, and Enhydrobacter was higher in wrestlers). Bacteria linked to skin infections (e.g., Aliterella, Arthrobacter, and Empedobacter) were present in around 30% of wrestlers and kickboxers but were absent in the control group. Conclusions: These results underscore the heightened risk of skin infections in contact sports and highlight the importance of regular microbiome monitoring and hygiene protocols among young athletes.

The accuracy of body composition assessments with bioelectrical impedance (BIA) based devices may be affected, besides the well-known factors (e.g. hydration status), by factors which are related to anthropometric characteristics. The aim of this study was to investigate the effects of somatotype on body composition estimation, especially on lean body mass (LBM), using BIA. 539 male (mean age: 15.8 ± 2.5 years) and 121 female young athletes (mean age: 16.5 ± 3.2 years) were included. Body composition was assessed by BIA and dual-energy X-ray absorptiometry (DXA). Somatotype was determined using the Heath-Carter method (endomorphy, mesomorphy, and ectomorphy). Intergroup differences were analysed with one-way and repeated measures analysis of variance. On average, BIA underestimated percent body fat (PBF) by 7.6% and overestimated LBM by 3.9 kg compared to DXA. Significantly smaller bias between the two methods was found in mesomorphy for both LBM and PBF. The ectomorph group demonstrated the largest underestimation in PBF, while the endomorph group the largest overestimation in LBM. Segmental analysis revealed larger overestimation of LBM of the lower limbs in ectomorphy. Findings suggest that LBM estimates are affected by somatotype with mesomorphy reducing, while ectomorphy and endomorphy increase, the estimation bias between BIA and DXA.