The ovarian cycle has a well-established circa-monthly rhythm, but the mechanisms involved in its regularity are unknown. Is the rhythmicity driven by an endogenous clock-like timer or by other internal or external processes? Here, using two large epidemiological datasets (26,912 cycles from 2303 European women and 4786 cycles from 721 North American women), analyzed with time series and circular statistics, we find evidence that the rhythmic characteristics of the menstrual cycle are more likely to be explained by an endogenous clock-like driving mechanism than by any other internal or external process. We also show that the menstrual cycle is weakly but significantly influenced by the 29.5-day lunar cycle and that the phase alignment between the two cycles differs between the European and the North American populations. Given the need to find efficient treatments of subfertility in women, our results should be confirmed in larger populations, and chronobiological approaches to optimize the ovulatory cycle should be evaluated.

To determine the influence of mutual motivation on unintended pregnancy rates of couples who used natural family planning (NFP) methods to avoid pregnancy. Using an online taught NFP method, 358 women and (their male partners) indicated "how much" and "how hard" they wished to avoid pregnancy on a scale of 0 to 10 before each menstrual cycle charted over 12 month of use. This motivation scale is used in the National Survey of Family Growth as a measure of motivation. All pregnancies were verified with an online pregnancy evaluation and urine-based pregnancy test. A combined motivation score was used in analysis. There were 28 pregnancies among the low-motivation participants (N = 60) and 16 among the high-motivation participants (N = 298). At 12 months of use, there were 75 pregnancies per 100 users for the low-motivation group and only 8 for the high-motivation group. There was an 80% greater likelihood of a pregnancy with the low-motivation group (χ = 25.5, p < .001, odds ratio = 1.80; 95% confidence interval = 1.61-1.90). High motivation to avoid pregnancy by both the female user of a behavioral method of family planning and her male partner is required for high efficacy. Assessing motivation of both the woman and her male partner before prescribing NFP methods is recommended.

Background and Objectives: The Marquette Method (MM) has been used for many years to track the postpartum return of fertility using the ClearBlue Fertility Monitor (CBFM). A new quantitative urine hormone monitor (the Mira Analyzer) was compared to the CBFM in one previous study, and using this pilot data, several women have started to use the Mira Analyzer in the postpartum transition to fertility. Materials and Methods: This study was a retrospective, observational case series that analyzed hormone data on the Mira Analyzer during the postpartum period. Participants were invited to share their postpartum cycle and hormone observations. Quantitative hormones in the urine included estrone-3-glucuronide (E3G), luteinizing hormone (LH), and pregnanediol glucuronide (PDG). Data were collected using an electronic survey and an online portal for hormone data. Data collected included participant demographics, menstrual cycle characteristics, and reproductive health history. Hormone range values were calculated, and thresholds were identified that would best predict the first ovulation that led to the first postpartum menstrual period, as well as in transition cycles. Hormone patterns were identified in the context of previous studies. Results: Twenty participants contributed data for the analysis. Triggering ovulation before the first period postpartum (Cycle 0) usually required higher LH thresholds than for regularly cycling women. Three different patterns were observed in the return of fertility postpartum: minimal ovarian activity, follicular activity without ovulation, and the early return of fertility. Abstinence rates for avoiding pregnancy with experimental thresholds were calculated. Conclusions: Higher LH thresholds in Cycle 0 suggest a decreased responsiveness of the ovaries to LH stimulation from the pituitary. This study replicates postpartum hormone patterns from a previous study. Larger studies are planned to evaluate the effectiveness for avoiding pregnancy using the Mira Analyzer in the postpartum return of fertility.

The fertility tracking of menstrual cycles during perimenopause with a quantitative hormone monitor is a novel undertaking. Women in regular menstrual cycles have been tracking their fertility using different biomarkers since the 1960′s. Presently, there are newer electronic hormonal devices used to track fertility that provide more exact and objective data to help delineate the fertile time frame of a woman’s cycle. These devices measure quantitative levels of estrogen, the luteinizing hormone, progesterone, and follicle-stimulating hormone, all of which occur at varying levels during the menstrual cycle. As women advance toward menopause, their cycles vary in length, and their hormones fluctuate. In this retrospective analysis, forty-two women aged 40 to 50 tracked their cycles over time, and eight of these forty-two women used the quantitative hormonal device. With the use of this device, the perimenopausal period has revealed distinct hormonal cycle characteristics that are unique to this group of women. It is the purpose of this paper to discuss these cycle’s characteristics during perimenopause, which were found with the use of the quantitative hormonal device.

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.

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). Methods: 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. Results: 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). Conclusions: 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.