Your Cycle Has Been Telling You Something For Years — Researchers Explain

For decades, the menstrual cycle has been treated primarily as a reproductive signal; just something to track when trying to conceive, or to avoid pregnancy.

But new research suggests it may be something far more useful, a personalized window into your overall health and how your body is aging.

Researchers developed WAVES as an open-source algorithm designed to pull detailed health metrics from physiological signals that follow menstrual patterns, starting with basal body temperature (BBT): the temperature you measure first thing in the morning before getting out of bed.

The tool captures 32 distinct metrics across four dimensions: temperature level, timing, within-cycle variations, and wave shape.

To test it, the team analyzed 5,674 menstrual cycles from 753 participants between the ages of 18 and 42.

The data came from a historical dataset collected across seven European centers in the 1990s, with participants recording daily temperature measurements and cervical mucus observations over several months to years.

No single participant was followed across her entire reproductive lifespan, but combining data from many individuals created a picture spanning most of the reproductive years.

The researchers were motivated by a gap in women's health research. Of the roughly 450 menstrual cycles a woman in the United States will have across her reproductive life, about 99% are nonconceptive.

When researchers compared two age groups (18 to 35 years versus 35 to 42 years), 27 of the 32 metrics differed significantly between them.

Within individuals, the researchers also tracked how these metrics shifted over time as participants aged. Of the 32 metrics, 16 changed significantly within individuals.

The follicular phase shortened by about 0.118 days per year, the lowest temperatures of the cycle crept up by about 0.004°C per year, and the amplitude of the cycle rhythm decreased by about 0.002°C per year. Cycle length also became less predictable with aging, linked to greater variability in the luteal phase.

These findings align with what researchers already know about reproductive aging. The pool of follicles (the structures in the ovaries that contain eggs) declines steadily over time, and by age 40, only about 3% of the original supply remains.

One of the most compelling findings from the study is what researchers call an individual "footprint," the idea that many cycle characteristics aren't just population-level averages, but deeply personal traits unique to you.

To measure this, researchers used a statistical tool called intraclass correlation coefficients (ICCs). A high ICC simply means that a given metric is more consistent within one person over time than it varies between different people, signaling a stable personal signature.

For temperature level metrics, the ICCs were notably high. Mean follicular temperature, mean luteal temperature, and the minimum and maximum temperature values all showed ICCs above 0.7, indicating strong individual consistency.

Cycle duration and phase lengths also showed moderate to high ICCs (above 0.5). Each person has their own temperature baseline around which menstrual fluctuations are organized, and that baseline is highly stable across cycles.

This has real implications for how we interpret cycle data. The study notes that only 12.4% of people actually have a 28-day cycle, and ovulation day varies widely even among those who do.

The researchers are clear: a personalized approach isn't just preferable; it may be essential for meaningful menstrual health monitoring.

Rather than comparing your cycle to a population average, the more useful question is: what is your baseline, and is it changing? A cycle that has always been 32 days is not inherently less healthy than a 28-day cycle.

But a cycle that was consistently 32 days and is now consistently 26 days may be worth paying attention to, especially if other patterns are shifting alongside it.

The WAVES algorithm is open-source and available for researchers, which means it could eventually be integrated into consumer tools.

The study authors specifically highlight conditions like PCOS (polycystic ovary syndrome), endometriosis, and ovarian cancer as areas where menstrual cycle metrics could one day serve as accessible, noninvasive health markers.

With the growing availability of wearables tracking physiological data, the infrastructure to make this kind of personalized monitoring mainstream is already being built.

Your menstrual cycle carries far more health information than most of us have been taught to look for. This study shows that cycle patterns shift with age in measurable, meaningful ways, and that many of those patterns are uniquely yours.