Why the study?
Heart rate variability is influenced by female sex hormone fluctuations and serves as an indicator of adaptation, but HRV responses across menstrual cycle and oral contraceptive phases in elite female athletes remain to be explored.
How do heart rate variability and resting heart rate fluctuate across the menstrual cycle and oral contraceptive phases in elite female swimmers?
How do heart rate variability and resting heart rate fluctuate across the menstrual cycle and oral contraceptive phases in elite female swimmers?
Heart rate variability fluctuates significantly across menstrual and oral contraceptive phases in elite female athletes, suggesting that phase-based monitoring could help periodize training.
HRV phase shifts in elite female swimmers may inform monitoring; leaves open performance effects and requires larger validation.
The heart rate variability (HRV), influenced by female sex hormone fluctuations, is an indicator of athletes’ adaptation. This case study explores HRV responses over 18 months across a natural menstrual cycle (MC) and during oral contraceptive (OC) use in two Olympic female swimmers. HRV measurements—including mean heart rate (HR); root mean square of successive differences (RMSSD); and frequency-domain indices—were collected at rest in supine (SU) and standing (ST) positions across two competitive seasons. Nocturnal HR and RMSSD were assessed using the Ōura® ring. MC and OC phases were identified through specific tracking, and training load was controlled. In both athletes, resting HR was lower during bleeding phases, increasing from menstruation to the luteal phase (MC) and from withdrawal to active pill phases (OC). In the ST position, RMSSD was higher but decreased throughout the phases. Nocturnal measurements confirmed these trends. Overall, findings suggest a phase-related parasympathetic overactivity shift. This study provides novel insights into HRV responses across hormonal cycles in elite female athletes, which present unique characteristics. Such monitoring tools may support a data-informed approach to guide and periodize training more effectively.
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Dupuit et al. (2025) studied this question.
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