Relationship Between Menstrual Phase-Induced Sleep Variations and Performance in Elite Female Rowers

Background Hormonal variations inherent to the menstrual cycle have been shown to affect recovery physiology in female athletes; however, their integrated effects on sleep architecture and sports performance remain poorly elucidated. Emerging evidence suggests that sleep quality varies across menstrual phases, with low-hormone states predisposing to sleep disturbance and impaired recovery. Given the role of sleep in neuromuscular function, recovery, and high-intensity performance, such variations may cause performance decrements, especially in physiologically demanding sports such as rowing. Despite this, current athlete monitoring frameworks do not evaluate menstrual cycle status and sleep parameters together. There are also limited studies in this regard among Indian female rowers. This study aims to evaluate menstrual phase-specific variations in sleep efficiency and rowing performance in elite female rowers. Methods This prospective observational study was conducted at a private sports medicine facility in South India. After obtaining informed consent, 15 elite female rowers aged between 18 and 25 years were monitored across three menstrual phases for nine consecutive menstrual cycles. Menstrual-cycle phases were categorized as high-estrogen late follicular, high-progesterone early luteal, and low-hormone early follicular plus late luteal phases. Sleep efficiency (%) was calculated from sleep metrics (duration of rapid eye movement (REM) sleep, awake periods, light sleep, deep sleep) recorded from Garmin (Garmin Ltd., Olathe, KS) wearable devices. Performance was measured by a standardized 500-m ergometer time trial. Phase-wise differences were assessed using Friedman repeated-measures analysis, with chi-square (χ²) reported as the test statistic and Kendall’s W as the effect size. Pairwise within-athlete comparisons between high-estrogen and low-hormone phases were performed using the Wilcoxon signed-rank test. Pearson correlation assessed the association between sleep efficiency and 500-m performance time using pooled phase-level observations. Results Mean sleep efficiency was significantly (p < 0.001) higher in the high-estrogen phase (96.90 ± 1.90%), followed by the high-progesterone phase (94.20 ± 2.30%) and lowest in the low-hormone phase (88.70 ± 2.80%). Performance was significantly (p < 0.001) reduced in the low hormone phase (119.80 ± 3.00 s), followed by the high progesterone phase (115.80 ± 2.40 s), with the best performance in the high estrogen phase (111.20 ± 2.80 s). Sleep efficiency showed a strong negative correlation with performance time (r = -0.86, p < 0.001), indicating that low sleep efficiency affects performance. Conclusion Menstrual cycle phase-specific variations significantly influence sleep efficiency and rowing performance, with low-hormone phases demonstrating the most unfavorable sleep-performance profile. These findings support the integration of menstrual cycle tracking with objective sleep monitoring to inform phase-specific, individualized training and recovery strategies for optimizing performance in elite female athletes.