Bouchard, T., Blackwell, L., Brown, S., Fehring, R., & Parenteau-Carreau, S. (2018). Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women. The Linacre Quarterly, 85(4), 399-411. https://doi.org/10.1177/0024363918809698
Bouchard T, Blackwell L, Brown S, Fehring R, Parenteau-Carreau S. Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women. Linacre Q. 2018;85(4):399-411. doi:10.1177/0024363918809698
Bouchard, T., et al. "Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women." The Linacre Quarterly, vol. 85, no. 4, 2018, pp. 399-411.
Mucus and urine hormones disagree in postpartum breastfeeding women
Only 39.1 percent of daily mucus observations matched hormone changes while periods were absent in a small study of 26 breastfeeding women. Urine samples began in week seven after birth. Over that time, mucus overstated hormone activity in 53.6 percent of observations.
Key Findings
Before first ovulation, during amenorrhea, daily mucus observations overstated hormone changes 53.6 percent of the time, matched them 39.1 percent, and understated them 7.3 percent.
After first menses, 33 of 78 transition cycles (42 percent) showed the expected mucus change after the progesterone rise. The other 45 (58 percent) did not. Three cycles lacked data.
Three of the 26 women became pregnant, at six, twelve and eighteen months postpartum. No cycle in the other women met the study's criteria for a fertile cycle.
Hormone profiles fell into three patterns: quiet ovaries with delayed ovulation (11 women, 42.3 percent), follicular activity with delayed ovulation (4, 15.4 percent), and early ovulation (11, 42.3 percent).
Time to first ovulation averaged 8.4 months (±3.1, N = 22). Five women (22 percent) ovulated while still fully breastfeeding, and their luteal phases lasted only three to five days.
Interpretation
The data come from 26 Montreal women in a 1986 to 1990 study of the symptothermal method, a natural family planning method that combines several fertility signs. The design is descriptive and has no comparison group. The results describe how mucus and hormones lined up in these women. The design cannot show why. The authors name the small sample as the most significant limitation. The three pattern groups were too small for statistical comparison. The authors set the hormone cutoffs for judging mucus from field experience with the assay. A new group of women has not yet replicated the findings.
RRM Context
Fertility awareness methods depend on observed signs. In these 26 women, cervical mucus tracked hormone changes unevenly after birth. The authors suggest urinary hormone measurement may help identify the return of fertility. They name the Marquette Method Postpartum Protocol, which uses a fertility monitor, as the most robust postpartum approach, and cite two earlier efficacy studies. They suggest a lower-cost protocol might pair mucus ratings with ovulation test strips.
Our editorial summary of this paper, not the article's abstract.
Abstract
Identifying the return of fertility with cervical mucus observations is challenging during the postpartum period. Use of urinary measurements of estrogen and progesterone can assist in understanding the return to fertility during this period. The purposes of this study were to describe the postpartum return of fertility by an analysis of total estrogen (TE) and pregnanediol glucuronide (PDG) profiles and to correlate these profiles with cervical mucus observations. Twenty-six participants collected urine samples during the postpartum period and recorded mucus scores. TE and PDG hormones were analyzed and compared with mucus scores. During amenorrhea, mucus reflected TE changes in only 35 percent of women; after amenorrhea, typical mucus patterns were seen in 33 percent of cycles. We concluded that postpartum mucus and hormone profiles are significantly dissociated but that monitoring urinary hormones may assist in identifying the return of fertility. We also identified different hormonal patterns in the return to fertility. The postpartum period is a challenging time for identifying the return of fertility. The purposes of this study were to describe the hormonal patterns during the return of fertility and to correlate these patterns with cervical mucus observations. Twenty-six postpartum women collected urine samples and recorded mucus scores. Urinary estrogen and progesterone hormones were analyzed and compared with mucus scores. Before the return of menses, mucus reflected hormonal changes in only 35 percent women and after first menses in 33 percent of cycles. We found that hormone profiles do not correlate well with mucus observations during the postpartum return of fertility.
Bouchard TP et al., 2026·Reproductive biomedicine online·Free to read
Do quantitative urinary hormone measurements on the Mira monitor predict and confirm ovulation accurately compared with ultrasound in women with regular menstrual cycles? Do Mira urine hormones correlate with serum hormones?
This was a prospective, single-centre, blinded diagnostic accuracy study with 52 women aged 19-44 years with regular cycles (24-38 days) who tracked 153 cycles over 18 months. Daily first-morning urine was tested with the Mira monitor for follicle stimulating hormone (FSH), oestrone-3-glucuronide (E13G), luteinizing hormone (LH) and pregnanediol glucuronide (PDG). Serial transvaginal ultrasounds (890 scans) confirmed the day of ovulation. Serum hormones were measured twice per cycle. The 121 ovulatory cycles from 49 participants with sufficient index test and reference standard data were included in the final analysis.
The Mira LH peak day strongly predicted ultrasound-confirmed ovulation (R² = 0.96, P < 0.001; intraclass correlation coefficient = 0.971), with 96% of ovulations occurring within ±1 day. The Mira PDG increase was also strongly associated with ultrasound-confirmed day of ovulation (R² = 0.87, P < 0.001). First-morning urine hormones were significantly associated with serum hormones when collected within 90 min (LH: R² = 0.92; E13G: R² = 0.73; R² = 0.61; R² = 0.75). Anovulatory cycles were identified in 11% of regularly cycling participants.
Quantitative urinary hormone monitoring with the Mira monitor provides accurate prediction and confirmation of ovulation, with strong urine-serum associations supporting reduced reliance on serial serum draws in select patients. These findings support clinical adoption of quantitative urinary fertility monitoring.
Cycle Across the Lifespan · Cycle and General Health
Bouchard TP et al., 2026·Journal of ovarian research·Free to read
Reproductive hormones of the fertile window are often referenced to women in regular cycles, but this may not be representative of the hormonal profiles of women in different circumstances like polycystic ovarian syndrome, the postpartum period, and the perimenopause transition. This observational cohort study sought to identify the variability in the reproductive hormones in various clinical circumstances and to establish potential thresholds for each category based on hormone measurements with the Mira urinary hormone monitor. A total of 57 women (ages 22-51) in various circumstances (regular cycles, polycystic ovarian syndrome, postpartum and perimenopause) tracked Mira urine hormone measurements (estrone-3-glucuronide, luteinizing hormone, pregnanediol glucuronide), contributing 444 cycles of data. Using additive mixed models, hormone values were stratified by the four different reproductive categories. The perimenopause and polycystic ovarian syndrome groups demonstrated relative hypoestrogenic states, while the perimenopause group showed low luteal pregnanediol glucuronide and the polycystic ovarian syndrome/polyendocrine metabolic ovarian syndrome (PCOS/PMOS) group showed high luteal pregnanediol glucuronide. The perimenopause group had significantly higher luteinizing hormone values throughout the whole cycle. The fertile window hormone thresholds vary depending on a woman's specific reproductive category. Women in different circumstances should not necessarily use the same hormonal thresholds for the fertile window and ovulation. A larger dataset with ultrasound correlation to ovulation is required to delineate the fertile window with more precision. Hormone differences across the menstrual cycle could be used for targeted treatments in polycystic ovarian syndrome and perimenopause women.
Bouchard TP et al., 2026·Reproductive biomedicine online·Free to read
Does formation of the corpus luteum help to identify the day of ovulation on ultrasound when follicular collapse is missed, and how reliable are sonographers versus a review panel in identifying the day of ovulation on ultrasound? Sonographers in a clinic in Canada performed serial endovaginal ultrasound scans (six to eight per cycle) to identify the day of ovulation in regularly cycling women (n = 40) who were followed for one to five cycles (n = 85). The day of ovulation was identified by: (i) identification of the dominant follicle; (ii) disappearance of the dominant follicle; and (iii) identification and dating of the corpus luteum. The main outcome measures were inter-rater reliability between two sonographers, and Bland-Altman agreement between the supervising sonographer and a panel that reviewed each scan to identify the day of ovulation. Of the 85 menstrual cycles reviewed, two cycles did not have sufficient data to date ovulation, one cycle showed an incidental dermoid cyst, and 11 cycles showed anovulatory patterns. This left a total of 71 cycles (84%) for which intra-rater reliability between two sonographers for identifying the day of ovulation was high (intraclass correlation coefficient = 0.99, P < 0.0001), and Bland-Altman agreement showed no significant difference in the estimated day of ovulation between the supervising sonographer and the panel (t = -0.28, P = 0.78). Corpus luteum criteria were necessary to help identify the day of ovulation in 14 of 71 cycles (20%). The estimated day of ovulation can be determined reliably on ultrasound by trained sonographers using collapse of the dominant follicle and formation of the corpus luteum based on six to eight scans per cycle.
Malliou-Becher MN et al., 2026·Human reproduction (Oxford, England)
What are the variations in ovulation time and menstrual cycle characteristics among and within various individuals over the course of 12 menstrual cycles? There are considerable variations in both cycle length and ovulation time, with pronounced intra-individual variability over a 12-cycle observation period. Although it is commonly believed that healthy women have regular cycles with a predictable mid-cycle ovulation, more recent research shows a significant variation in cycle length and ovulation time. Previous studies have focused only on cycle length, often excluding cycles outside the 25-35-day range, thus limiting the understanding of natural variation; they have also lacked precise ovulation diagnostics or included small sample sizes, making it difficult to capture the full scope of cycle and ovulation variability. Similarly, a recent big data study, while valuable, was limited by a self-selected group and the absence of accurate ovulation diagnostics, reducing its generalizability. STUDY DESIGN, SIZE, This study was designed as a prospective long-term observational study, which involved collecting data from 1923 women with a total of 43 999 menstrual cycles from January 1985 to July 2019. After fulfilling the inclusion criteria, the main group consisted of 1051 women, all of whom contributed data for 12 cycles (12 612 cycles), including 420 conception cycles. PARTICIPANTS/MATERIALS, SETTING, Participants in the study were between 18 and 44 years of age at study entry and did not take any reproductive hormones. Women who were postpartum, breastfeeding, amenorrheic, or within a 3-month period after stopping hormonal contraception were excluded. Participants agreed to keep cycle records according to the symptothermal method, 'Sensiplan'. Ovulation time was determined using an evidence-based algorithm based on evaluating cervical mucus patterns and basal body temperature shifts, with ovulation time defined as the day before the temperature rise. Data analysis was descriptive, using absolute and relative frequencies, standard deviation, percentiles, and ranges. Age dependency was assessed using unpaired sample t-tests and one-way ANOVA. Linear regression was used to assess long-term trends. MAIN In 62.4% of women, cycle lengths varied by 1 week or more within 12 cycles. Accordingly, the time of ovulation varied by 1 week or more within 12 cycles in 54.8% of women, with 96.5% experiencing fluctuations of 4 days or more over the 12 months. The median spontaneous cycle length was 28 days, with a mean of 29.66 days (SD = 7.55). Only 52.7% of women consistently had cycle lengths between 23 and 35 days across all 12 cycles. Ovulation occurred most frequently between Days 12 and 16, with almost half of conceptions (45.7%) occurring after Day 16. A one-way analysis of variance revealed a significant reduction in mean cycle length with increasing age (P < 0.001), showing the shortest median cycle length of 27 days being in women aged 40-44 years. Age also impacted ovulation time, with women aged 35-39 years showing more stable ovulation patterns compared to younger women. Over the 34-year study period, average cycle length increased slightly but significantly (β = 0.0161, P = 0.0306), corresponding to approximately half a day. Intra-individual variability also showed a slight, but non-significant, upward trend (β = 0.0262, P = 0.2173). LIMITATIONS, Comorbidities such as hyperprolactinemia, obesity, and PCOS were not systematically excluded. However, by including only women with at least 12 cycles, the study largely avoided severe hormonal disorders. This study highlights the considerable individual variation of ovulation time and cycle length over 12 menstrual cycles. These findings contribute to a better understanding of fertility awareness, and highlight the implications for family planning and reproductive health management. STUDY FUNDING/COMPETING INTEREST(S): The authors declare no conflicts of interest. No funding was provided. N/A.
In this study we have evaluated the score, sperm migration and ultrastructural characteristics of cervical mucus present in amenorrhoeic women under exclusive breastfeeding at 30, 60, 90, 120, 150 and 180 days post-partum. Periovulatory mucus samples from seven normally cycling women were used as a control. The average scores of post-partum and periovulatory mucus were 4.6 +/- 0.4 and 14.1 +/- 0.5 respectively. Twenty-one (39%) of the 54 post-partum cervical mucus samples and all (100%) periovulatory mucus samples allowed sperm migration. Positive sperm migration into post-partum mucus was observed at all time intervals studied. The only parameter that correlated with sperm migration into post-partum mucus was ferning formation. Sperm migration was obtained in all post-partum mucus samples with a score greater than 8, but samples with scores between 2 and 7 also showed sperm penetration. Scanning electron microscopic studies showed the characteristic spongy appearance of periovulatory mucus. Post-partum mucus was formed by a dense mesh (rocky appearance), when samples were generally unable to sustain sperm migration, but samples where sperm migration occurred showed small areas of spongy mucus mixed with areas in which a dense mesh and high cellularity was observed.
Schneider MM et al., 2023·Linacre Q·Free full text on PubMed Central
The uses of cervical mucus and basal body temperature as indicators of return to fertility postpartum have resulted in high unintended pregnancy rates. In 2013, a study found that when women used urine hormone signs in a postpartum/breastfeeding protocol this resulted in fewer pregnancies. To improve the original protocol's effectiveness, three revisions were made: (1) women were to increase the number of days tested with the Clearblue Fertility Monitor, (2) an optional second luteinizing hormone test could be done in the evening, and (3) instructions were given to manage the beginning of the fertile window for the first six cycles postpartum. The purpose of this study was to determine the correct and typical use effectiveness rates to avoid pregnancy in women who used a revised postpartum/breastfeeding protocol. A cohort review of an established data set from 207 postpartum breastfeeding women who used the protocol to avoid pregnancy was completed using Kaplan-Meier survival analysis. Total pregnancy rates that included correct and incorrect use pregnancies were eighteen per one hundred women over twelve cycles of use. For the pregnancies that met a priori criteria, the correct use pregnancy rates were two per one hundred over twelve months and twelve cycles of use and typical use rates were four per one hundred women at twelve cycles of use. The protocol had fewer unplanned pregnancies than the original, however, the cost of the method increased.
Fehring RJ et al., 2004·Contraception·Free to read
The purpose of this study was to compare the fertile phase of the menstrual cycle as determined by the Clearplan Easy Fertility Monitor (CPEFM) with self-monitoring of cervical mucus. One-hundred women (mean age = 29.4 years) observed their cervical mucus and monitored their urine for estrogen and luteinizing hormone metabolites with the CPEFM on a daily basis for 2-6 cycles and generated 378 cycles of data; of these, 347 (92%) had a CPEFM peak. The beginning of the fertile window was, on average, day 11.8 (SD = 3.4) by the monitor and day 9.9 (SD = 3.0) by cervical mucus (r = 0.43, p < 0.001). The average first day of peak fertility by the monitor was 16.5 (SD = 3.6) and by cervical mucus 16.3 (SD = 3.7) (r = 0.85, p < 0.001). The mean length of the fertile phase by the monitor was 7.7 days (SD = 3.1) and by cervical mucus 10.9 days (SD = 3.7) (t = 12.7, p < 0.001). The peak in fertility as determined by the monitor and by self-assessment of cervical mucus is similar but the monitor tends to underestimate and self-assessment of cervical mucus tends to overestimate the actual fertile phase.
Do the basal body temperature (BBT) shift and the cervical mucus markers for the beginning of the post-ovulatory infertile phase (POIP) of a menstrual cycle agree with the corresponding urinary pregnanediol glucuronide (PdG) threshold value? Perfect agreement between the cervical mucus markers and BBT shift and the hormonal definition of the start of post-ovulatory infertility occurred for only 7-17% of the cycles. The PdG threshold of 7.0 µmol/24 h is an objective and accurate marker for the beginning of the POIP. The rise in serum progesterone also produces the BBT shift and changes in cervical mucus which determine the mucus peak. Serum progesterone and urinary PdG are closely correlated when variations in urine volume are taken into account. STUDY DESIGN, SIZE, Individual menstrual cycle profiles of urinary PdG excretion rates for 91 fertile cycles from normally cycling women were analysed to identify the day of the beginning of the POIP. These days were compared with those determined by the day of the BBT shift +2 days, the day of the mucus peak +4 days and the later of these two indicators. The study lasted 3 years. PARTICIPANTS/MATERIALS, SETTING, A total of 62 women with normal menstrual cycles were recruited from three centres: Palmerston North, New Zealand; Sydney, Australia and Santiago, Chile. The cycles were displayed individually in a proprietary database program which recorded the PdG excretion rates, the BBT shift day and the cervical mucus peak day. A group of 15 women from a separate Chilean study had PdG urinary data measured as well as their day of ovulation determined by ultrasound. MAIN The BBT and cervical mucus markers differed significantly in their identification of the beginning of the POIP when compared with the PdG excretion rate of 7.0 µmol/24 h. The observation that the BBT shift day and the mucus peak day could be identified even though the PdG excretion rates were still at baseline levels in some cycles could lead to an unexpected pregnancy for women using these natural family planning (NFP) indicators. LIMITATIONS, The study consisted only of fertile cycles from women with regular cycles of 20-40 days duration. All the women were intending to avoid a pregnancy during the study, thus the limits of the fertile window were not tested. The NFP signals occurring earlier than the PdG threshold day could lead to an unexpected pregnancy. The signals occurring on the same day or later than the PdG threshold would not lead to unexpected pregnancies, but would require extra abstinence that could lead to non-compliance with the NFP method. A possible improvement in reliability of NFP methods is suggested. This study (project #90905) was funded by the NDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP). D.G.C. currently works for a diagnostic development company, Science Haven Ltd. The other authors have nothing to declare.
Thomas P Bouchard, Leonard F Blackwell, Len Blackwell, Simon Brown, Richard J Fehring, Suzanne Parenteau-Carreau
Tom Bouchard, T Bouchard, L Blackwell, S Brown, Rick Fehring, Dick Fehring, Rich Fehring, R Fehring, S Parenteau-Carreau
PMID 32431376 32431376 DOI 10.1177/0024363918809698 10.1177/0024363918809698 Bouchard et al. 2018, Bouchard 2018
Cite this article
Bouchard, T., Blackwell, L., Brown, S., Fehring, R., & Parenteau-Carreau, S. (2018). Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women. The Linacre Quarterly, 85(4), 399-411. https://doi.org/10.1177/0024363918809698
Bouchard T, Blackwell L, Brown S, Fehring R, Parenteau-Carreau S. Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women. Linacre Q. 2018;85(4):399-411. doi:10.1177/0024363918809698
Bouchard, T., et al. "Dissociation between Cervical Mucus and Urinary Hormones during the Postpartum Return of Fertility in Breastfeeding Women." The Linacre Quarterly, vol. 85, no. 4, 2018, pp. 399-411.
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