A small wearable-sensor study suggests that daily movement may rise and fall with shifts in estradiol levels, offering new clues about how menstrual-cycle physiology shapes real-world activity.
Study: Physical activity data correlate with fluctuations in estradiol. Image Credit: LariBat / Shutterstock
According to a recent study published as an article in press in the journal npj Women’s Health, women's daily physical activity was correlated with fluctuations in the hormone estradiol across the menstrual cycle. The findings suggest that wearable movement data may help researchers study menstrual-cycle effects and complement reproductive-health monitoring, although the study did not measure hormones and activity in the same participants.
Background
The menstrual cycle profoundly influences health and physical activity among approximately 1.8 billion people worldwide. Prior research has demonstrated reduced physical activity on symptomatic days of the menstrual cycle. However, little is known about the variability of physical activity in relation to hormonal changes during the menstrual cycle.
Menstrual phases
The menstrual cycle is divided into early follicular, late follicular, ovulation, and luteal phases. Estradiol and progesterone are at their lowest and show the least change during the early follicular phase. Estradiol rises in the late follicular phase and peaks just before ovulation. This rise triggers a surge in luteinizing hormone that initiates ovulation. Ovulation marks the onset of the luteal phase, during which progesterone reaches its peak.
Prior research suggests that increased physical activity is associated with higher levels of estradiol, whether exogenous or endogenous, in both animal and human studies. Other investigators have explored physical activity during different parts of the cycle, but self-reported data may be unreliable.
Previous studies using wearable sensors have focused on physiological measures such as skin temperature, resting heart rate, and heart rate variability. Step count has also been used, but this does not reflect the intensity of exercise.
Menstrual variation in physical activity
Physical inactivity is among the major risk factors for premature death and disproportionately affects women globally, motivating the current study. Here, the researchers monitored physical activity in a cohort of 26 healthy young, naturally menstruating women who were not using hormonal contraceptives using a single shank-worn inertial measurement unit, or IMU.
This was used to compute active energy expenditure using a validated machine-learning model, which was compared with external reference hormone data collected from multiple menstrual cycles from earlier studies of healthy, eumenorrheic women. The aim of the study was to examine how far changes in physical activity corresponded to variations in estradiol and progesterone.
Activity correlated with estradiol changes
The findings revealed a significant correlation between daily activity and estradiol fluctuations when activity was shifted by 2 days relative to estradiol, suggesting that estradiol changes may have preceded changes in movement. However, the progesterone-activity relationship was weak and negative, with the best alignment occurring without a time delay.
In general, at the cohort level, active energy expenditure tended to rise after estradiol rose and decline after estradiol fell. This pattern was strongest across a 10-day window around ovulation that captured major estradiol fluctuations, including the pre-ovulatory peak.
The greatest association was observed with estradiol compared to progesterone. Unlike some earlier studies, activity increased during the early follicular phase; specifically, active energy expenditure was higher than in the late follicular phase, mainly because participants took more steps rather than expending more energy per step. Since the study did not examine factors like menstrual symptoms, pain medication, food intake, or other behavioral factors, the reason for the increase remains unclear.
The findings are consistent with the possibility that naturally occurring hormonal changes may influence physical activity. Conversely, this suggests that activity patterns could eventually provide complementary information about menstrual-cycle physiology, but only after validation with simultaneous hormone and activity measurements in the same participants.
Taken together, the findings suggest that rising estradiol may influence physical activity, possibly through its physiological and psychological effects. For instance, it may act on certain parts of the hypothalamus to influence physical activity. The current study suggests a delayed association between estradiol and movement, although the authors note that the apparent delay could also reflect analytical misalignment between the activity cohort and the external hormone reference cohorts.
Based on this, the authors propose that wearable activity monitors could provide useful data to complement other menstrual-cycle and reproductive-health measures.
The authors point to the potential advantages of understanding how hormonal fluctuations affect energy expenditure in women. Besides providing evidence for more accommodating workplace and school environments, it could shed light on clinically relevant problems in women with altered hormonal profiles, including menopause or polycystic ovarian syndrome (PCOS).
Limitations
The study has several limitations. Different cohorts were used to derive activity patterns and hormone measurements, with cycles aligned using the LH surge. This means the findings should be interpreted as cohort-level associations, not proof that wearable activity data can track an individual’s hormone levels.
The sample size was relatively small and consisted of young, healthy, naturally menstruating women, limiting its generalizability. Factors outside hormonal fluctuations might affect activity levels, such as work schedules, illness, sleep duration and quality, stress, and lifestyle. Activity was recorded for 28 days, which may have truncated luteal or follicular phases in participants with cycles longer than 30 days, and some phase data were circularly realigned from consecutive cycles.
The study also lacked participant-specific hormone measurements, so it could not determine whether any participants had an anovulatory cycle, which could affect progesterone patterns.
Conclusions
Overall, the study suggests that daily physical activity measured by wearable devices correlates at the cohort level with fluctuations in estradiol during the menstrual cycle and may offer a convenient, non-invasive way to study how menstrual-cycle physiology relates to movement. Further research in larger and more diverse populations, with simultaneous activity and hormone measurements in the same participants, is needed to validate the findings.
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