Some medical professional organizations have advocated for including the menstrual cycle as a vital sign in adolescence, but not in adulthood. However, documenting menstrual cycle patterns is not routine clinical or research practice. Vital signs are used to predict health outcomes, indicate needed treatment, and monitor a clinical course. They can help identify pathologies, affirm wellness, and are responsive to exposures. Here we review the scientific evidence showing how the menstrual cycle meets these criteria and should therefore be treated as a vital sign. Using key words and controlled vocabulary terms, we carried out multiple literature searches, prioritizing the inclusion of systematic reviews, meta-analyses, and clinical practice guidelines. This review describes how the menstrual cycle is a health indicator, can cyclically impact health conditions, and its associations with long-term post-menopausal health outcomes. We review exposures influencing the menstrual cycle, evidence underlying its use to optimize wellness, and available tools for documenting cycles. Supplementary materials include patient handouts on menstrual cycle tracking, and an index of related clinical practice guidelines and reviews by subject. The menstrual cycle is a vital sign from menarche through menopause, an underutilized but powerful tool for understanding gynecological and general health.
PMID 39906529 39906529 DOI 10.1016/j.xfnr.2024.100081 10.1016/j.xfnr.2024.100081 Vollmar et al. 2025, Vollmar 2025
Cite this article
Vollmar, A. K. R., Mahalingaiah, S., & Jukic, A. M. (2025). The Menstrual Cycle as a Vital Sign: a comprehensive review.. F&S reviews, 6(1). https://doi.org/10.1016/j.xfnr.2024.100081
Vollmar AKR, Mahalingaiah S, Jukic AM. The Menstrual Cycle as a Vital Sign: a comprehensive review.. F&S reviews. 2025;6(1). doi:10.1016/j.xfnr.2024.100081
Bouchard T et al., 2025·J Restorative Reprod Med·
Open Access
There is considerable individual day-to-day variation within the menstrual cycle and between cycles in women. Average hormone curves inadequately describe the individual hormone patterns experienced by women. The present study applies a novel application of a statistical array (heat map) to demonstrate both individual and group menstrual cycle hormone variability.
Using pre-existing datasets, two cohorts of women were analysed using a statistical method to visualise quantitative hormonal variation. In one cohort, 107 women contributed a total of 283 menstrual cycles and in the second cohort, 21 women contributed a total of 62 menstrual cycles. Exposure: Women collected first morning urine samples for analysis of estrone-3-glucuronide (E1G) and luteinizing hormone (LH) in both datasets. In the larger dataset, pregnanediol-3-alpha-glucuronide (PDG) and follicle-stimulating hormone (FSH) were also collected. Serial ultrasounds identified the precise day of ovulation in the larger dataset. In the smaller dataset, peak LH was used to identify the estimated day of ovulation.
The main outcome measure was identifying hormonal variability using hormone array heat maps. Heat maps were able to quickly show clustering of hormone patterns in the fertile window and on the day of ovulation. Individual differences were identified in rows on the heat map relative to the day of ovulation. This new tool to visually represent hormonal changes with heat maps identifies both individual and group variability of menstrual cycle hormones.
Measurement and Statistics · Instrument Development and Validation
Bouchard TP et al., 2025·Womens Health Rep (New Rochelle)·
Open Access
Measuring quantitative menstrual cycle hormones at home may help women better understand their postpartum and perimenopause fertility transitions, but these quantitative fertility monitors require validation. This study included 16 North American women, aged 28-51, during either the postpartum (n = 8, cycles = 18) or perimenopause (n = 8, cycles = 35) fertility transitions testing daily first-morning urine testing with both the Mira Monitor and ClearBlue Fertility Monitor (CBFM) along with menstrual cycle parameter tracking. The main outcome measures were a rise in estrone-3-glucuronide (E13G) and luteinizing hormone (LH) urine hormone values from the Mira monitor correlated to low, high, or peak values on the CBFM. Both in the postpartum and perimenopause transitions, the identification of the day of ovulation based on the LH surge on the Mira and CBFM monitors was highly correlated (R = 0.94 and 0.83, p < 0.001). The E13G levels on the Mira monitor were significantly higher for a CBFM reading of "High" compared with "Low" for both the postpartum and perimenopausal cycles (all p < 0.001). Similarly, the LH levels on the Mira monitor were significantly higher for a CBFM reading of "Peak" (LH surge) compared with "High" for both the postpartum and perimenopausal cycles (all p < 0.001). The LH surge and levels of E13G in urine identified on the quantitative Mira fertility monitor strongly correlate to the LH surge and the shift from low to high on the CBFM during the postpartum and perimenopause transitions.
Mei M et al., 2022·Proceedings. Biological sciences
Odour cues associated with shifts in ovarian hormones indicate ovulatory timing in females of many nonhuman species. Although prior evidence supports women's body odours smelling more attractive on days when conception is possible, that research has left ambiguous how diagnostic of ovulatory timing odour cues are, as well as whether shifts in odour attractiveness are correlated with shifts in ovarian hormones. Here, 46 women each provided six overnight scent and corresponding day saliva samples spaced five days apart, and completed luteinizing hormone tests to determine ovulatory timing. Scent samples collected near ovulation were rated more attractive, on average, relative to samples from the same women collected on other days. Importantly, however, signal detection analyses showed that rater discrimination of fertile window timing from odour attractiveness ratings was very poor. Within-women shifts in salivary oestradiol and progesterone were not significantly associated with within-women shifts in odour attractiveness. Between-women, mean oestradiol was positively associated with mean odour attractiveness. Our findings suggest that raters cannot reliably detect women's ovulatory timing from their scent attractiveness. The between-women effect of oestradiol raises the possibility that women's scents provide information about overall cycle fecundity, though further research is necessary to rigorously investigate this possibility.
A new fertility monitor is now available that provides quantitative measurement of urinary hormones, but clinical use requires validation against an established fertility monitor that provides only qualitative results. Two fertility monitors were compared using daily first morning urine samples over 3 cycles of use in 21 women users with experience using a fertility monitor with the Marquette Method of Natural Family Planning. Women were aged 33.4 ± 5.5 years and had menstrual cycles ranging between 23 and 41 days. The quantitative Mira Monitor estimates of ovulation were highly correlated with the qualitative ClearBlue Fertility Monitor (CBFM) estimates of ovulation. Both monitors provided an accurate estimate of the fertile window. In this preliminary trial, the Mira monitor was shown to be effective at delineating the fertile window and ovulation. We demonstrated the feasibility of applying the Marquette Method algorithm with the use of the Mira monitor. Satisfaction differences between the two monitors did not reach statistical significance. We anticipate that quantitative fertility monitoring will give couples and health-care providers new and unprecedented insights into the menstrual cycle and fertility.