Fehring, R. J., & Schneider, M. (2008). Variability in the hormonally estimated fertile phase of the menstrual cycle. Fertility and sterility, 90(4), 1232-1235. https://doi.org/10.1016/j.fertnstert.2007.10.050
Fehring RJ, Schneider M. Variability in the hormonally estimated fertile phase of the menstrual cycle. Fertil Steril. 2008;90(4):1232-1235. doi:10.1016/j.fertnstert.2007.10.050
Fehring, R. J., and M. Schneider. "Variability in the hormonally estimated fertile phase of the menstrual cycle." Fertility and sterility, vol. 90, no. 4, 2008, pp. 1232-1235.
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The purpose of this study was to determine the variability in length of the fertile phase of the menstrual cycle with 140 participants who produced 1,060 cycles with an electronic hormonal fertility monitor. The length of the fertile phase, as defined by the first day with a threshold level of urinary E3G and ending with a second day above a threshold of LH, varied from <1 to >7 days, with the most frequent length being 3 days.
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.
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.
Bouchard TP et al., 2025·Preprints.org·Free to read
Background/Objectives: Quantitative urine monitors are increasingly being used for a personalized approach to improve menstrual cycle knowledge and to manage fertility. Although several studies have evaluated urine fertility monitors in regular cycles, there is limited research in the use of quantitative monitors in reproductive disorders, such as polycystic ovarian syndrome (PCOS). Urine hormone data was collected with the Mira monitor from 20 participants, 10 of whom had PCOS and a matched group who had regular cycles. The main aim of this study was to evaluate the levels of luteinizing hormone (LH), estrone-3-glucuronide (E13G), and pregnanediol glucuronide (PDG) in PCOS menstrual cycles compared to regular cycles. Women with PCOS had higher BMI than regular cycling women (p=0.02). PCOS cycles were longer (p<0.05), peak day was later in the menstrual cycle (p<0.001), and luteal length was shorter (p < 0.01) compared to regular cycles. In whole cycle comparisons, E13G was found to be lower in PCOS cycles (p<0.01) and PDG was found to be higher in PCOS cycles (p<0.05). E13G was also lower in the follicular phase of and late luteal phase of PCOS cycles (p<0.00001). The results of this study demonstrate the feasibility of detecting hormonal differences in PCOS compared to regular cycles with at-home measurements with the Mira monitor. The metabolic dysregulation of PCOS is a possible factor in these hormone changes. Larger studies with different sub-types of PCOS will be needed to further clarify these changes and to understand the pathophysiology behind these hormonal changes.
Fehring RJ et al., 2006·J Obstet Gynecol Neonatal Nurs·Free to read
To determine variability in the phases of the menstrual cycle among healthy, regularly cycling women.
A prospective descriptive study of a new data set with biological markers to estimate parameters of the menstrual cycles. One hundred forty one healthy women (mean age 29 years) who monitored 3 to 13 menstrual cycles with an electronic fertility monitor and produced 1,060 usable cycles of data. Outcomes: Variability in the length of the menstrual cycle and of the follicular, fertile, and luteal phases, and menses. The estimated day of ovulation and end of the fertile phase was the peak fertility reading on the monitor (i.e., the urinary luteinizing hormone surge). Mean total length was 28.9 days (SD = 3.4) with 95% of the cycles between 22 and 36 days. Intracycle variability of greater than 7 days was observed in 42.5% of the women. Ninety-five percent of the cycles had all 6 days of fertile phase between days 4 and 23, but only 25% of participants had all days of the fertile phase between days 10 and 17. Among regularly cycling women, there is considerable normal variability in the phases of the menstrual cycle. The follicular phase contributes most to this variability.
Wilcox AJ et al., 2000·BMJ·Free full text on PubMed Central
To provide specific estimates of the likely occurrence of the six fertile days (the "fertile window") during the menstrual cycle.
Prospective cohort study. 221 healthy women who were planning a pregnancy. The timing of ovulation in 696 menstrual cycles, estimated using urinary metabolites of oestrogen and progesterone. The fertile window occurred during a broad range of days in the menstrual cycle. On every day between days 6 and 21, women had at minimum a 10% probability of being in their fertile window. Women cannot predict a sporadic late ovulation; 4-6% of women whose cycles had not yet resumed were potentially fertile in the fifth week of their cycle. In only about 30% of women is the fertile window entirely within the days of the menstrual cycle identified by clinical guidelines-that is, between days 10 and 17. Most women reach their fertile window earlier and others much later. Women should be advised that the timing of their fertile window can be highly unpredictable, even if their cycles are usually regular.
Murcia-Lora JM et al., 2011·pers.bioét.·Free to read
El objetivo de este artículo es revisar los principales conceptos en la literatura acerca de la ventana de la fertilidad en pacientes con ciclos menstruales normales. El énfasis principal del artículo se ha dirigido al análisis de la teoría de Brown de la ovulación, revisar conceptos básicos de la ovulación, secreción y metabolismo de la hormona folículo estimulante, y al estudio clínico, ecográfico y bioquímicos del desarrollo folicular de la ventana de la fertilidad. Este artículo también repasa los biomarcadores clínicos y los diferentes metabolitos endocrinos que delimitan en la fase fértil del ciclo. Se revisan diferentes estudios en los cuales las valoraciones en suero y orina de los esteroides sexuales, han corroborado tener una correlación directa para enmarcar el período fértil. Actualmente tienen relevancia estos conocimientos en diferentes grupos de interés, sobre todo en mujeres con un alto nivel de motivación interesadas en el reconocimiento de su fertilidad, las cuales pueden beneficiarse mediante la aplicación de conocimientos técnicos actuales que detectan la ventana fértil. También estos conocimientos suelen cobrar importancia en aquellas personas que pertenecen a programas de regulación de la fertilidad (PRF), con intención de distanciar un embarazo, o de reconocer el periodo fértil del ciclo para conseguir un embarazo espontáneamente, o mediante programas de NaProTecnología. Otros grupos de interés, son aquellos en los cuales no se tiene experiencia en cursos de PRF, pero desean mejorar sus conocimientos en el reconocimiento de la fertilidad por medio de una breve entrevista, o por medio de cursos de orientación familiar.
To improve prediction of ovulation in normal cycles. Collection of women's characteristics and their menstrual cycles. Monitoring and analysis of time relationships between several indicators of ovulation: transvaginal ultrasonography, cervical mucus, basal body temperature, urinary luteinising hormone, and ratio of urinary oestrogen to progesterone metabolites. Each of eight natural family planning clinics was to study 12 women for at least three cycles. One hundred and seven normally fertile and cycling women aged 18 to 45. Daily measurements of urinary luteinising hormone, follicle stimulating hormone, oestrone-3-glucuronide and pregnanediol-3alpha-glucuronide. Basal body temperature recording and cervical mucus checking. Transvaginal ultrasound examination of the ovaries. Delays between the expected day of ovulation according to the luteinising hormone peak or to ultrasound evidence and the expected days according to the other indices of ovulation. Ultrasonography was able to show evidence of ovulation in 283 out of 326 cycles. The average time lag between luteinising hormone peak and ultrasound evidence was less than one day (+0.46) but premature and late luteinising hormone-expected date of ovulation were observed in nearly 10% and 23% of cycles, respectively. Basal body temperature rise was observed in 98% of cycles. Cervical mucus peak symptom, rapid drop in the ratio of urinary metabolites, and luteinising hormone initial rise were all close to ultrasonographic evidence in more than 72% of cycles. For accuracy and practical reasons, the cervical mucus peak symptom, the ratio of urinary metabolites and luteinising hormone initial rise might be better indices of ovulation than the luteinising hormone peak.
Rick Fehring, Dick Fehring, Rich Fehring, R Fehring, M Schneider
PMID 18249381 18249381 DOI 10.1016/j.fertnstert.2007.10.050 10.1016/j.fertnstert.2007.10.050 Fehring et al. 2008, Fehring 2008
Cite this article
Fehring, R. J., & Schneider, M. (2008). Variability in the hormonally estimated fertile phase of the menstrual cycle. Fertility and sterility, 90(4), 1232-1235. https://doi.org/10.1016/j.fertnstert.2007.10.050
Fehring RJ, Schneider M. Variability in the hormonally estimated fertile phase of the menstrual cycle. Fertil Steril. 2008;90(4):1232-1235. doi:10.1016/j.fertnstert.2007.10.050
Fehring, R. J., and M. Schneider. "Variability in the hormonally estimated fertile phase of the menstrual cycle." Fertility and sterility, vol. 90, no. 4, 2008, pp. 1232-1235.
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