Wearable Devices Reveal Sleep Duration Linked to Menstrual Cycle Regularity, Large-Scale Study Shows
核心洞察
Analysis of 42,759 menstrual cycles from 2,596 women using WHOOP (搜索) wearables found sleeping less than 7.3 hours or having irregular sleep patterns was strongly associated with greater menstrual cycle variability.
Average cycle length was 28.4 days, decreasing from 29.1 days at age 24 to 26.9 days at age 44, with cycle variability following a U-shaped pattern and lowest variability near age 33.
High-resolution biometric data revealed clear physiological rhythms across the menstrual cycle, with resting heart rate, HRV, and respiratory rate closely linked throughout.
Tracking 42,759 menstrual cycles with wearable devices, researchers have uncovered that even modest sleep disruptions may be linked to measurable changes in menstrual health, according to a study published in NPJ Digital Medicine. The findings demonstrate that sleeping less than 7.3 hours per night or maintaining irregular sleep patterns is strongly associated with greater menstrual cycle variability, suggesting a potential role for sleep regularity in supporting menstrual cycle stability.
The study analyzed data from 2,596 regular WHOOP (搜索) device users, encompassing over 1.29 million days of biometric measurements. Participants were required to have consistent device wear and regular cycles with a median length of 21–35 days; women using hormonal contraceptives, those who were pregnant, or those experiencing menopause symptoms were excluded.
Sleep and Cycle Stability
Average menstrual cycle length across the cohort was 28.4 days, decreasing from 29.1 days at age 24 to 26.9 days at age 44. Cycle length variability followed a U-shaped pattern, with the least variability observed near age 33.
Shorter and inconsistent sleep emerged as a key factor associated with cycle irregularity. Sleeping less than 7.3 hours or having irregular sleep patterns was associated with greater menstrual cycle variability, while average cycle length remained largely unchanged. A within-participant analysis of 813 individuals confirmed that greater sleep variability within an individual was associated with more variable cycle lengths.
"Shorter and inconsistent sleep were strongly associated with greater menstrual cycle variability, while average cycle length remained largely unchanged," the authors reported, noting that the findings suggest "a potential role for regular sleep in menstrual cycle stability."
Physiological Rhythms Across the Cycle
High-resolution biometric data revealed clear physiological rhythms across the menstrual cycle. Most biometrics dipped during menstruation and peaked before the next cycle, except heart rate variability (HRV), which showed the opposite pattern. Resting heart rate, HRV, and respiratory rate were closely linked throughout the cycle.
With age, fluctuations in HRV and resting heart rate lessened, while changes in other biometrics were minor. Longer cycles were associated with a greater range of cardiorespiratory biometrics. Blood oxygen saturation showed little cyclicality, indicating that age and cycle length are key factors in shaping menstrual physiology.
Shorter sleep, especially in the premenstrual week, was associated with increased resting heart rate, reduced HRV, and changes in other physiological metrics. This pattern was similar across menstrual phases, underscoring that sleep loss was consistently linked to physiological changes throughout the cycle.
Individual Variability Beyond Population Averages
While population-level biometrics captured main trends, individual cycles showed much greater variability. HRV, for example, often fluctuated by nearly half of a participant's mean value within a single cycle. "Although population waveforms are stable, individual cycles reveal marked variability," the researchers noted, emphasizing the need for personalized approaches to menstrual health.
Wearable Accuracy in Women's Health Research
A separate scoping review published in npj Women's Health, which analyzed 40 studies involving cohorts ranging from small pilot groups to nearly 19 million participants, assessed the accuracy of wearables including the Oura Ring, WHOOP (搜索) band, Fitbit, Apple Watch, and Garmin watches for menstrual cycle research.
The review found that wearables successfully reproduced many known patterns of hormonal physiology. Skin temperature studies consistently showed lower temperatures during the follicular phase and higher temperatures during the luteal phase. Resting heart rate increased by approximately 2.7–3.9 beats per minute from the follicular to the luteal phase, peaking during the five-day period just before and including ovulation.
Regarding device accuracy, the review noted that the Oura Ring may provide reasonably reliable skin-temperature measurements for menstrual-cycle research, though direct comparisons with gold-standard core body temperature measurements remain limited. Existing evidence suggests wearables provide reasonably accurate measurements of heart and respiratory rates, while HRV measurements were useful but sometimes underestimated variability. Sleep stage detection and sleep duration measurement remained relatively inaccurate.
Clinical Implications and Research Gaps
The review highlighted that up to 90% of women report menstrual-associated symptoms, including dysmenorrhea, bloating, and mood swings. Premenstrual syndrome (搜索) (PMS) affects up to 40% of women, and in up to 8%, symptoms are disabling—a condition known as premenstrual dysphoric disorder (搜索) (PMDD). In economic terms, menstrual and perimenopausal symptoms are estimated to cost Japan nearly $8.6 billion and the US over $26 billion annually.
The authors of the NPJ Digital Medicine study concluded that future research should clarify the mechanisms underlying the sleep-cycle associations and assess whether interventions promoting sleep regularity could help improve cycle stability and overall well-being. The scoping review similarly emphasized the need for simultaneous measurement of hormones, physiological and behavioral parameters, and menstrual symptoms—a combination rare in existing studies—and called for more diverse population sampling to validate findings across ethnicities and age groups.