A Withings analysis linked the premenstrual week with lower device-recorded sleep scores. Learn what the findings mean for tracking rest in midlife.
On October 15, 2026, Withings published a company-led observational analysis linking the week before menstruation with lower device-recorded sleep scores.
Withings says it analyzed about 469,000 menstrual cycles from roughly 69,000 women who were not using hormonal contraception. Participants were aged 18 to 50 and logged their periods while using connected devices. The data covered 11 countries between September 2025 and September 2026.
The main finding was a recurring difference within participants’ own cycles. In Withings’ analysis, 76% of women had a lower sleep score in the week before menstruation. The average score was 3.4 points lower than in the days just after menstruation.
That comparison is useful because it looks at women against their own records across cycle phases. It asks whether a person’s recorded sleep changes with cycle timing rather than simply comparing different people with one another. The researchers estimated those phases from logged period dates.
For someone who repeatedly notices less satisfying sleep before a period, the finding offers a possible pattern to watch. It gives cycle timing a place in the conversation about rest without turning an ordinary fluctuation into a personal failure.
As reported by Sleep Review, the premenstrual difference was more apparent in estimated sleep composition than in total time asleep. Withings reported about five minutes less sleep in the premenstrual week. Estimated deep sleep fell by 1.8 percentage points and lighter sleep increased.
These findings separate two questions that can become blurred in a tracker app: how long someone slept and how the device classified that sleep. In this analysis, the difference in duration was small while the estimated mix of sleep stages changed.
The distinction helps explain why the headline is about sleep scores rather than simply lost sleep time. The report describes a pattern involving several recorded features of the night. It does not reduce the finding to participants spending much less time asleep.
Withings also reported changes in overnight heart measurements. In the natural-cycle analysis, night-time heart rate rose by an average of 2.8 beats per minute during the premenstrual week. Heart-rate variability, or HRV, fell by 3 milliseconds.
Taken together, the reported pattern involved lower sleep scores and lighter estimated sleep alongside changes in overnight heart readings. That is the core observation. The next question is how much meaning a reader should attach to it.
The findings come from an observational analysis. Withings explicitly cautions that the associations do not establish cause and effect. The data therefore do not prove that menstrual-cycle hormones caused the recorded sleep changes.
The release also does not identify the analysis as peer-reviewed or published in a scientific journal. It does not provide technical definitions or validation details for its sleep-score algorithm or its sleep-stage and HRV measurements. The reported sleep stages should be read as device-derived estimates rather than clinical sleep-lab measurements.
The dataset included users of Withings smartwatches, smart scales and sleep trackers. These were people who owned connected devices and logged periods. The company cautions that this group may not represent the general population.
The age range also sets a boundary for a midlife audience. The headline result is not a specific finding about midlife women, perimenopause or menopause. It should not be used as evidence that the same pattern or size of change applies across those life stages.
There is an unresolved reporting issue in the release. It gives roughly 69,000 women for the headline analysis but lists 32,712 in its country table. Different sections also give different counts for the hormonal-contraception group without explaining those discrepancies on the displayed page.
Finally, this was not a test of a sleep-improvement routine. Noting sleep quality alongside cycle timing is a practical observation strategy suggested by the findings, not an intervention shown here to improve rest. These boundaries make the analysis useful for asking better questions rather than making individual medical decisions.
For an adult in midlife who menstruates, the most useful daily adjustment is modest: place a brief note about sleep quality alongside cycle timing. Over several cycles, look for whether less restful nights repeatedly appear before menstruation.
This approach fits the question the analysis raises. It gives a recurring experience somewhere to be recorded without requiring a complicated recovery schedule. The aim is to notice timing rather than produce a perfect record.
A brief entry could include:
The wearable entry is optional. The observation is about whether a pattern repeats in your experience, not whether you can collect every available metric. A personal impression of poor sleep remains worth recording alongside an app’s account of the night.
If a lower score appears, place it beside the rest of the record before drawing a conclusion. Does the same timing recur? Does the score match how rested you feel, or are the two telling different stories?
Those questions make the number a prompt for reflection rather than a verdict. They also leave room for a night to feel different from the way an app describes it. Relaxopia’s discussion of describing sleep quality beyond a single number offers a broader way to approach that distinction.
The practical adjustment is not to chase a better deep-sleep reading each morning. It is to give an existing reading context. A repeated pre-period dip can become part of your understanding of your records rather than another performance target.
For someone balancing work and home responsibilities, a recurring pattern may be useful when thinking about recovery expectations. A less restful pre-period night does not need to become evidence that you have failed at a routine. The record can acknowledge the experience without demanding an immediate correction.
That is a different task from explaining every difficult night through cycle timing. Keep the question open: is the timing consistent, or does poor sleep also appear elsewhere in the record? The purpose is to understand your experience rather than fit it to the company’s average.
A broader review of what may be interrupting rest can sit alongside this narrow observation. Cycle timing is one piece of context to record, not a requirement to make your whole sleep routine revolve around menstruation.
Withings states that its findings are informational and are not a substitute for medical advice. Persistent or concerning sleep, cycle or heart-rate symptoms warrant discussion with a healthcare professional.
If you have noticed a recurring pattern, the notes can help describe what you have experienced. The useful information is the experience itself and when it occurs, not an attempt to turn a device score into a diagnosis. Personal decisions belong in a conversation with a qualified clinician.
The next useful step would be research that makes the measurements and the population easier to interpret. Clear technical reporting would help readers understand what a change in a device score represents. Results focused on midlife would address the audience question more directly.
Future work could also ask whether the recorded pattern matches changes in how rested participants feel. That would help connect an app’s description of the night with the experience that matters during the following day. Research could then test supportive approaches rather than assume that recognizing a pattern changes sleep.
For now, the practical value is a more focused question about recurring nights rather than a new recovery rule. Could better cycle-aware research eventually help midlife adults plan for recovery without making every restless night a problem to solve?
A lower pre-period sleep score is easy to mistake for a medical result, so Relaxopia keeps the evidence behind recovery technology in view. Adults 35+ facing conflicting tracker messages get clear explanations of sleep and fatigue that leave room for uncertainty without adding a demanding routine.
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