The Investigation of Aerobic Performance and Body Composition in Young Athletes in Terms of Chronotype

Abstract

Background and Study Aim. Chronotype is an important physiological characteristic that influences individuals’ daily performance levels based on their biological rhythms. In athletes, chronotype-related timing differences are known to affect physical fitness and exercise responses. In this context, this study aimed to investigate the effects of chronotype on aerobic performance, body composition, and exercise-induced physiological responses in young athletes. Material and methods. A total of 28 volunteer athletes (14 morning type and 14 evening type) aged between 18-22 years were categorised using the Morningness-Eveningness Questionnaire (MEQ). All tests were performed in the morning (09:00-10:00). Measurements included the Cooper test, VO2max, body mass index (BMI), muscle mass, body fat percentage, body temperature, and heart rate before and after exercise. Statistical analyses were conducted using independent sample t-tests and two-way repeated measures ANOVA. Results. The findings showed that morning-type individuals showed significantly greater running distance and VO2max values compared to evening-type individuals. Furthermore, morning types were found to have a lower BMI and demonstrated changes in heart rate and body temperature. Although differences in muscle mass and fat percentage were not statistically significant, moderate to large effect sizes indicate better body composition in morning types. In contrast, evening-type individuals showed lower physiological adaptation to exercise and less efficient thermoregulation. Conclusions. These findings emphasise that adapting exercise timing to an athlete's chronotype can enhance aerobic performance and improve physiological adaptation. Consideration of biological rhythms in training design may contribute to both optimal performance and metabolic health, especially in young athletes. In future research, chronotype-based interventions at different times of the day could be analysed. © 2025 The Author(s) and Asan et al.