Background and Study Aim. The aim of this study is to determine the effect of e-sports on physical activity level and body composition. Material and Methods.  The athletes who participated in the study were 19.92± 2.21 years of age, 1.73±0.04 m body height and 78.35±6.52 kg body weight. A total of 137 athletes participated in the study, including 27 from Turkey, 47 from South Korea and 63 from the United States (USA). The data was collected by e-mail from the sports clubs. The athletes who representing their country in international competitions involved in the study. The data obtained were evaluated in the SPSS program. Results.  According to the findings of the study, the body mass index (BMI) of e-sport athletes is 26.03±1.85, the number of physical activity steps is 6646±3400 and the daily e-sport hours are 9.34±1.12. The BMI was determined as USA 26.12, South Korea 26.02 and Turkey 25.84 respectively. The number of physical activity steps was identified as 5255 steps in the US, 7785 steps in South Korea and 7909 steps in Turkey. The daily e-sports hour is set at US 9.63 hours, Turkey 9.29 hours and South Korea 8.97 hours. In comparison of country-based athletes, there was a significant difference between physical activity level and daily e-sports hours at p<0.05. The value of BMI is not different. Although it is not statistically related to the physical activity level and BMI. There was no statistically significant relationship between daily e-sports hours and BMI and physical activity step counts. However, as the time of e-sports increases, BMI increases and the number of physical activity steps decreases. Conclusions.  As a result it is seen in the findings of the research that athletes dealing with e-sports are included in the fat group as a body composition and their daily physical activity steps are low. In addition, according to the results of the research, e-sports are thought to have negative effects on physical health. Thanks to the physical activity programs to be applied to these athletes, it is thought that their body composition and physical activity levels can be improved.

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The aim of the study was to identify genetic variants associated with personal best scores in Turkish track and field athletes and to compare allelic frequencies between sprint/power and endurance athletes and controls using a whole-exome sequencing (WES) approach, followed by replication studies in independent cohorts. The discovery phase involved 60 elite Turkish athletes (31 sprint/power and 29 endurance) and 20 ethnically matched controls. The replication phase involved 1132 individuals (115 elite Russian sprinters, 373 elite Russian endurance athletes (of which 75 athletes were with VO2max measurements), 209 controls, 148 Russian and 287 Finnish individuals with muscle fiber composition and cross-sectional area (CSA) data). None of the single nucleotide polymorphisms (SNPs) reached an exome-wide significance level (p < 2.3 × 10−7) in genotype–phenotype and case–control studies of Turkish athletes. However, of the 53 nominally (p < 0.05) associated SNPs, four functional variants were replicated. The SIRT1 rs41299232 G allele was significantly over-represented in Turkish (p = 0.047) and Russian (p = 0.018) endurance athletes compared to sprint/power athletes and was associated with increased VO2max (p = 0.037) and a greater proportion of slow-twitch muscle fibers (p = 0.035). The NUP210 rs2280084 A allele was significantly over-represented in Turkish (p = 0.044) and Russian (p = 0.012) endurance athletes compared to sprint/power athletes. The TRPM2 rs1785440 G allele was significantly over-represented in Turkish endurance athletes compared to sprint/power athletes (p = 0.034) and was associated with increased VO2max (p = 0.008). The AGRN rs4074992 C allele was significantly over-represented in Turkish sprint/power athletes compared to endurance athletes (p = 0.037) and was associated with a greater CSA of fast-twitch muscle fibers (p = 0.024). In conclusion, we present the first WES study of athletes showing that this approach can be used to identify novel genetic markers associated with exercise- and sport-related phenotypes.

Today, long-term athlete development programs are used as an alternative to traditional athlete training programs. They aim to make sport as a lifestyle, rather than compressing athlete development into a short period of time. In long-term athlete development programs, all processes are planned on the basis of the biological development periods of the athletes and their development characteristics in these periods, rather than their chronological age, which is taken as the basis in traditional athlete development methods. Sports branches are divided into two as early specialization and late specialization sports. Gymnastics requires skill, coordination, and a developed central nervous system; thus, it is categorized among the early specialization sports.