There is a growing interest in knowing the relationship between biological maturation and sport performance-related variables of young athletes. The objective of this study is to analyze the relationship between biological maturation, physical fitness, and kinanthropometric variables of athletes during their growing period, according to their sex. The systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and the search protocol was registered in PROSPERO, code: CRD42020208397. A search through the PubMed, Web of Sciences, and EBSCO databases was performed. A total of 423 studies were screened and 13 were included in the meta-analysis. The meta-analysis was completed by using the mean and standard deviation of each variable according to each maturation status (early, on time, or late). Differences depending on maturation were found on physical fitness, with better results in the advanced maturational groups in the male population (standard mean difference (SMD) = 0.17–2.31; p < 0.001–0.05). Differences depending on maturation were found for kinanthropometric variables in males (SMD = 0.37–2.31; p < 0.001–0.002) and height and body mass in females (SMD = 0.96–1.19; p < 0.001). In conclusion, the early maturation group showed higher values in kinanthropometric variables and better results in physical fitness, highlighting the importance of the maturational process in the talent selection programs. Despite that, more research is needed to clarify the relationship of maturation with the other variables on female populations and the changes in the muscle and bone variables during the maturation processes of both sexes.

Background: The aim of this study was to analyze the validity of four different skinfold calipers, as well as to establish the differences between them in a healthy young adult population. Methods: The present study followed a cross-sectional design, including 138 participants, with 69 males (21.46 ± 2.52 years) and 69 females (22.19 ± 2.85 years). The measurement protocol included basic measurements of body mass and stretch stature and eight skinfolds with a Harpenden, Holtain, Slim Guide, and Lipowise. The ∑6 and ∑8 skinfolds and fat mass were calculated. The order in which the skinfold calipers were used was randomized. Results: No significant differences were found in either the Σ6 and Σ8 skinfolds or masses and fat percentages calculated with the skinfolds obtained with the different calipers (p > 0.05), and the inclusion of the covariates of sex, BMI, and hydration status of the participants showed no effect on the differences. The Bland–Altman test showed significant differences between the calipers (p < 0.001). Conclusion: It has been observed that the analyzed calipers have shown validity for the assessment of adiposity-related variables in a male and female sample of non-overweight, young healthy adults, but they are not interchangeable with each other when the assessment is meant to be compared over time or with other samples.

Changes in body composition and specifically fat mass, has traditionally been used as a way to monitor the changes produced by nutrition and training. The objective of the present study was to analyse the differences between the formulas used to estimate fat mass and to establish the existing relationship with the body mass index and sums of skinfolds measurement in kinanthropometry. A total of 2458 active adults participated in the study. Body mass index (BMI) and skinfolds were measured, and the Kerr, Durnin-Womersley, Faulkner and Carter equations were used to assess fat mass. Significant differences were found between all the formulas for the percentage of fat mass, ranging from 10.70 ± 2.48 to 28.43 ± 5.99% (p < 0.001) and fat mass from 7.56 ± 2.13 to 19.89 ± 4.24 kg (p < 0.001). The correlations among sums of skinfolds and the different equations were positive, high and significant in all the cases (r from 0.705 to 0.926 p < 0.001), unlike in the case of BMI, were the correlation was lower and both positive or negative (r from −0.271 to 0.719; p < 0.001). In conclusion, there were differences between all the formulas used to estimate fat mass; thus, for the evaluation of fat mass with kinanthropometry of an active adult, the use of the same formula is recommended on all occasions when the results are going to be compared or when an athlete is compared with a reference.

Background: Differences in kinanthropometric and physical fitness performance between boys and girls usually start during adolescence, as a result of the changes in the hormonal environment that occur with the advance of age and biological maturation; Methods: A total of 96 1st Regional Division players adolescent volleyball players, 48 males, (age = 14.17 ± 1.00 years-old) and 48 females (age = 14.41 ± 1.21 years-old) underwent a kinanthropometric assessment, were asked to perform different physical fitness test and to complete a questionnaire. Chronological age, maturity offset, age at peak height velocity (APHV), and birth quartile were calculated; Results: Statistical differences were observed between male and female players in the APHV (p < 0.001). Male players showed higher values in the bone and muscle-related variables (p < 0.001–0.040), as well as in the strength and power production-related physical tests (p < 0.001–0.012), while the female showed higher values in the fat-related variables (p = 0.003–0.013), and performed better in the flexibility tests. Age, maturity offset, and birth quartile showed to have statistical influence in the differences found between sex groups; Conclusions: There is a clear influence of age and biological maturation on the differences found between sexes in adolescent volleyball players that could be taken into account regarding grouping in early stages.