Repeated cross-sectional analysis reveals annual variations in nutrition and training practices among elite athletes, indicating valuable monitoring insights.
Purpose This study aimed to describe year-to-year transitions in nutrition-related behaviors, training practices, lifestyle indicators, and psychosocial factors among athletes in an elite Japanese university rowing program over a 6-year period (2018–2023). The objective was to characterize team-level seasonal patterns using a repeated cross-sectional approach. Methods Anonymous questionnaires were administered annually after the competitive season (excluding 2021). All questionnaire items were assessed using either a 0–100 visual analogue scale (VAS) or open numerical responses. Descriptive statistics were calculated for each year and sex. Year-to-year differences were examined using one-way ANOVA, followed by Games–Howell post hoc tests to account for unequal variances and sample sizes. Effect sizes and 95% confidence intervals were reported. Because some athletes may have participated in multiple years, all analyses were interpreted within a repeated cross-sectional framework. Results A total of 152 male and 59 female athletes participated across the five survey years. Several variables showed significant year-to-year differences, including body composition satisfaction, performance satisfaction, and training frequency, with patterns differing by sex. Female athletes exhibited markedly higher bodyweight and weight-training frequency in 2018 compared with later years. Many other variables—such as strength, power, endurance satisfaction, lifestyle regularity, supplement literacy, and psychosocial indicators—showed descriptive but non-significant fluctuations across seasons. Conclusion This repeated cross-sectional analysis revealed substantial annual variation in nutritional behaviors, training exposure, lifestyle indicators, and psychosocial factors within a nationally competitive collegiate rowing program. The findings highlight the practical value of multidomain, team-level monitoring in environments characterized by high roster turnover, while emphasizing the descriptive and non-causal nature of the observed patterns.
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Hayakawa et al. (2026) studied this question.
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