The timing of sexual intercourse in relation to ovulation strongly influences the chance of conception, although the actual number of fertile days in a woman's menstrual cycle is uncertain. The timing of intercourse may also be associated with the sex of the baby.
Methods
We recruited 221 healthy women who were planning to become pregnant. At the same time the women stopped using birth-control methods, they began collecting daily urine specimens and keeping daily records of whether they had sexual intercourse. We measured estrogen and progesterone metabolites in urine to estimate the day of ovulation.
Results
In a total of 625 menstrual cycles for which the dates of ovulation could be estimated, 192 pregnancies were initiated, as indicated by increases in the urinary concentration of human chorionic gonadotropin around the expected time of implantation. Two thirds (n = 129) ended in live births. Conception occurred only when intercourse took place during a six-day period that ended on the estimated day of ovulation. The probability of conception ranged from 0.10 when intercourse occurred five days before ovulation to 0.33 when it occurred on the day of ovulation itself. There was no evident relation between the age of sperm and the viability of the conceptus, although only 6 percent of the pregnancies could be firmly attributed to sperm that were three or more days old. Cycles producing male and female babies had similar patterns of intercourse in relation to ovulation.
Conclusions
Among healthy women trying to conceive, nearly all pregnancies can be attributed to intercourse during a six-day period ending on the day of ovulation. For practical purposes, the timing of sexual intercourse in relation to ovulation has no influence on the sex of the baby.
Wilcox fertile window six day conception probability, timing intercourse relation ovulation conception probability, fertile days menstrual cycle urinary hormone metabolites, sperm survival age conception viability pregnancy outcome, sex of baby timing intercourse ovulation day, urinary estrogen progesterone metabolites ovulation estimation, prospective cohort natural conception daily urine collection, probability conception days before ovulation fertile period, sex selection timing intercourse relative to ovulation, implantation detection urinary hCG early pregnancy loss, Wilcox Weinberg Baird fertile window New England Journal
PMID 7477165 7477165 DOI 10.1056/NEJM199512073332301 10.1056/NEJM199512073332301 Wilcox et al. 1995, Wilcox 1995
Cite this article
Wilcox, A. J., Weinberg, C. R., & Baird, D. D. (1995). Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby. The New England journal of medicine, 333(23), 1517-1521. https://doi.org/10.1056/NEJM199512073332301
Wilcox AJ, Weinberg CR, Baird DD. Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby. N Engl J Med. 1995;333(23):1517-1521. doi:10.1056/NEJM199512073332301
Wilcox, A. J., et al. "Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby." The New England journal of medicine, vol. 333, no. 23, 1995, pp. 1517-1521.
Keywords
Adult, Age Factors, Chorionic Gonadotropin/urine, Coitus, Female, Fertilization/physiology, Humans, Male, Ovulation, Pregnancy, Prospective Studies, Sex Preselection/methods, Spermatozoa, Time Factors, Chorionic Gonadotropin
It is commonplace for gynecologists to refer to "midcycle" ovulation of women. This concept has often led to the routine diagnosis of ovulatory status on day 14 of what is expected to be a 28-day menstrual cycle. For example, the postcoital test in an infertile patient, or intercourse to achieve pregnancy in a normally fertile patient, is often timed around day 14 under the assumption that ovulation is occurring then. Advocates of natural family planning (NFP) have criticized the concept of "midcycle" ovulation, because their clinical experience suggests that the natural irregularity of menstrual-cycle length militates against ovulation's occurring with any great frequency on day 14.
This report analyzes the relationship of day 14 and the actual midcycle of the menstrual cycle to each other and to indirect hormonal parameters that more directly estimate the time of ovulation.
menstrual-cycle/cycle-physiology/ovulationreproductive-endocrinology/ovulation-physiology/follicular-developmentfertility-awareness/use-and-experience/user-satisfaction
Open Access
menstrual-cycle/cycle-physiology/ovulationfertility-awareness/methods/calendar-and-rhythm-methodsreproductive-endocrinology/ovulation-physiology/follicular-development
Open Access
There are many mobile phone apps aimed at helping women map their ovulation and menstrual cycles and facilitating successful conception (or avoiding pregnancy). These apps usually ask users to input various biological features and have accumulated the menstrual cycle data of a vast number of women. The purpose of our study was to clarify how the data obtained from a self-tracking health app for female mobile phone users can be used to improve the accuracy of prediction of the date of next ovulation. Using the data of 7043 women who had reliable menstrual and ovulation records out of 8,000,000 users of a mobile phone app of a health care service, we analyzed the relationship between the menstrual cycle length, follicular phase length, and luteal phase length. Then we fitted a linear function to the relationship between the length of the menstrual cycle and timing of ovulation and compared it with the existing calendar-based methods. The correlation between the length of the menstrual cycle and the length of the follicular phase was stronger than the correlation between the length of the menstrual cycle and the length of the luteal phase, and there was a positive correlation between the lengths of past and future menstrual cycles. A strong positive correlation was also found between the mean length of past cycles and the length of the follicular phase. The correlation between the mean cycle length and the luteal phase length was also statistically significant. In most of the subjects, our method (ie, the calendar-based method based on the optimized function) outperformed the Ogino method of predicting the next ovulation date. Our method also outperformed the ovulation date prediction method that assumes the middle day of a mean menstrual cycle as the date of the next ovulation. The large number of subjects allowed us to capture the relationships between the lengths of the menstrual cycle, follicular phase, and luteal phase in more detail than previous studies. We then demonstrated how the present calendar methods could be improved by the better grouping of women. This study suggested that even without integrating various biological metrics, the dataset collected by a self-tracking app can be used to develop formulas that predict the ovulation day when the data are aggregated. Because the method that we developed requires data only on the first day of menstruation, it would be the best option for couples during the early stages of their attempt to have a baby or for those who want to avoid the cost associated with other methods. Moreover, the result will be the baseline for more advanced methods that integrate other biological metrics.
fertility-awareness/biomarkers/urinary-hormone-monitoringmenstrual-cycle/cycle-biomarkers/basal-body-temperaturereproductive-endocrinology/ovulation-physiology/follicular-development
Open Access
An affordable, user-friendly fertility-monitoring tool remains an unmet need. We examine in this study the correlation between pulse rate (PR) and the menstrual phases using wrist-worn PR sensors. 91 healthy, non-pregnant women, between 22-42 years old, were recruited for a prospective-observational clinical trial. Participants measured PR during sleep using wrist-worn bracelets with photoplethysmographic sensors. Ovulation day was estimated with "Clearblue Digital-Ovulation-urine test". Potential behavioral and nutritional confounders were collected daily. 274 ovulatory cycles were recorded from 91 eligible women, with a mean cycle length of 27.3 days (±2.7). We observed a significant increase in PR during the fertile window compared to the menstrual phase (2.1 beat-per-minute, p < 0.01). Moreover, PR during the mid-luteal phase was also significantly elevated compared to the fertile window (1.8 beat-per-minute, p < 0.01), and the menstrual phase (3.8 beat-per-minute, p < 0.01). PR increase in the ovulatory and mid-luteal phase was robust to adjustment for the collected confounders. There is a significant increase of the fertile-window PR (collected during sleep) compared to the menstrual phase. The aforementioned association was robust to the inter- and intra-person variability of menstrual-cycle length, behavioral, and nutritional profiles. Hence, PR monitoring using wearable sensors could be used as one parameter within a multi-parameter fertility awareness-based method.