Does sexual intercourse in the implantation time window (5-9 days after ovulation) reduce fecundability?
Summary Answer
After adjustment for intercourse in the fecund window and clustering by couple, there was no association between intercourse in the implantation time window and fecundity.
What Is Known Already
Previous research has suggested an association between intercourse in the peri-implantation time window (5-9 days after estimated ovulation) and reduced fecundability.
Study Design, Size, Duration
We used data from the FERTILI study, a prospective observational study conducted in five European countries, with data collected from 1992 to 1996.
Participants/Materials, Setting, Methods
Women who were experienced in fertility awareness tracking kept a daily diary of cervical mucus observations, basal body temperature measurements, coitus and clinically identified pregnancy. We estimated the day of ovulation as cycle length minus 13 days. From 661 women, 2606 cycles had intercourse during the fecund window (from 5 days before to 3 days after the estimated day of ovulation), resulting in 418 pregnancies (conception cycles). An established Bayesian fecundability model was used to estimate the fecundability ratio (FR) of peri-implantation intercourse on fecundability, while adjusting for each partner's age, prior pregnancy, the couple's probability of conception and intercourse pattern(s). We conducted sensitivity analyses estimating ovulation as cycle length minus 12 days, or alternatively, as the peak day of estrogenic cervical mucus.
MAIN RESULTS AND THE ROLE OF CHANCE: There was no effect of peri-implantation intercourse on fecundability: adjusted FR for three or more acts of peri-implantation intercourse versus none: 1.00, 95% credible interval: 0.76-1.13. Results were essentially the same with sensitivity analyses. There was an inverse relationship between frequency of intercourse in the fecund window and intercourse in the peri-implantation window.
Limitations, Reasons for Caution
Women with known subfertility were excluded from this study. Many couples in the study were avoiding pregnancy during much of the study, so 61% of otherwise eligible cycles in the database were not at meaningful risk of pregnancy and did not contribute to the analysis. Some couples may not have recorded all intercourse.
Wider Implications of the Findings
We believe the current balance of evidence does not support a recommendation for avoiding intercourse in the peri-implantation period among couples trying to conceive.
STUDY FUNDING/COMPETING INTEREST(S): No external funding. The authors have no potential competing interests.
PMID 32756956 32756956 DOI 10.1093/humrep/deaa156 10.1093/humrep/deaa156 Hansen et al. 2020, Hansen 2020
Cite this article
Stanford, J. B., Hansen, J. L., Willis, S. K., Hu, N., & Thomas, A. (2020). Peri-implantation intercourse does not lower fecundability. Human reproduction (Oxford, England), 35(9), 2107-2112. https://doi.org/10.1093/humrep/deaa156
Stanford JB, Hansen JL, Willis SK, Hu N, Thomas A. Peri-implantation intercourse does not lower fecundability. Hum Reprod. 2020;35(9):2107-2112. doi:10.1093/humrep/deaa156
Stanford, J. B., et al. "Peri-implantation intercourse does not lower fecundability." Human reproduction (Oxford, England), vol. 35, no. 9, 2020, pp. 2107-2112.
Keywords
Bayes Theorem, Coitus, Embryo Implantation, Europe, Female, Fertility, Humans, Pregnancy, Time-to-Pregnancy, Conception, Day-specific Probabilities of Conception, Fecund Window, Fecundability, Fertile Window, Sexual Intercourse, Time to Pregnancy
To what extent does the use of mobile computing apps to track the menstrual cycle and the fertile window influence fecundability among women trying to conceive? After adjusting for potential confounders, use of any of several different apps was associated with increased fecundability ranging from 12% to 20% per cycle of attempt. Many women are using mobile computing apps to track their menstrual cycle and the fertile window, including while trying to conceive. STUDY DESIGN, SIZE, The Pregnancy Study Online (PRESTO) is a North American prospective internet-based cohort of women who are aged 21-45 years, trying to conceive and not using contraception or fertility treatment at baseline. PARTICIPANTS/MATERIALS, SETTING, We restricted the analysis to 8363 women trying to conceive for no more than 6 months at baseline; the women were recruited from June 2013 through May 2019. Women completed questionnaires at baseline and every 2 months for up to 1 year. The main outcome was fecundability, i.e. the per-cycle probability of conception, which we assessed using self-reported data on time to pregnancy (confirmed by positive home pregnancy test) in menstrual cycles. On the baseline and follow-up questionnaires, women reported whether they used mobile computing apps to track their menstrual cycles ('cycle apps') and, if so, which one(s). We estimated fecundability ratios (FRs) for the use of cycle apps, adjusted for female age, race/ethnicity, prior pregnancy, BMI, income, current smoking, education, partner education, caffeine intake, use of hormonal contraceptives as the last method of contraception, hours of sleep per night, cycle regularity, use of prenatal supplements, marital status, intercourse frequency and history of subfertility. We also examined the impact of concurrent use of fertility indicators: basal body temperature, cervical fluid, cervix position and/or urine LH. MAIN Among 8363 women, 6077 (72.7%) were using one or more cycle apps at baseline. A total of 122 separate apps were reported by women. We designated five of these apps before analysis as more likely to be effective (Clue, Fertility Friend, Glow, Kindara, Ovia; hereafter referred to as 'selected apps'). The use of any app at baseline was associated with 20% increased fecundability, with little difference between selected apps versus other apps (selected apps FR (95% CI): 1.20 (1.13, 1.28); all other apps 1.21 (1.13, 1.30)). In time-varying analyses, cycle app use was associated with 12-15% increased fecundability (selected apps FR (95% CI): 1.12 (1.04, 1.21); all other apps 1.15 (1.07, 1.24)). When apps were used at baseline with one or more fertility indicators, there was higher fecundability than without fertility indicators (selected apps with indicators FR (95% CI): 1.23 (1.14, 1.34) versus without indicators 1.17 (1.05, 1.30); other apps with indicators 1.30 (1.19, 1.43) versus without indicators 1.16 (1.06, 1.27)). In time-varying analyses, results were similar when stratified by time trying at study entry (<3 vs. 3-6 cycles) or cycle regularity. For use of the selected apps, we observed higher fecundability among women with a history of subfertility: FR 1.33 (1.05-1.67). LIMITATIONS, Neither regularity nor intensity of app use was ascertained. The prospective time-varying assessment of app use was based on questionnaires completed every 2 months, which would not capture more frequent changes. Intercourse frequency was also reported retrospectively and we do not have data on timing of intercourse relative to the fertile window. Although we controlled for a wide range of covariates, we cannot exclude the possibility of residual confounding (e.g. choosing to use an app in this observational study may be a marker for unmeasured health habits promoting fecundability). Half of the women in the study received a free premium subscription for one of the apps (Fertility Friend), which may have increased the overall prevalence of app use in the time-varying analyses, but would not affect app use at baseline. Most women in the study were college educated, which may limit application of results to other populations. Use of a cycle app, especially in combination with observation of one or more fertility indicators (basal body temperature, cervical fluid, cervix position and/or urine LH), may increase fecundability (per-cycle pregnancy probability) by about 12-20% for couples trying to conceive. We did not find consistent evidence of improved fecundability resulting from use of one specific app over another. STUDY FUNDING/COMPETING INTEREST(S): This research was supported by grants, R21HD072326 and R01HD086742, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, USA. In the last 3 years, Dr L.A.W. has served as a fibroid consultant for AbbVie.com. Dr L.A.W. has also received in-kind donations from Sandstone Diagnostics, Swiss Precision Diagnostics, FertilityFriend.com and Kindara.com for primary data collection and participant incentives in the PRESTO cohort. Dr J.B.S. reports personal fees from Swiss Precision Diagnostics, outside the submitted work. The remaining authors have nothing to declare. N/A.
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.
Are dietary patterns associated with age at menarche after accounting for BMI-for-age (BMIz) and height? We observed associations between both the Alternative Healthy Eating Index (AHEI) and the Empirical Dietary Inflammatory Pattern (EDIP) and age at menarche. Dietary patterns have been sparsely examined in relation to age at menarche and no studies have examined the association between the AHEI, a healthier diet, and EDIP, a pro-inflammatory diet, and menarche. STUDY DESIGN, SIZE, The Growing Up Today Study (GUTS) is a prospective cohort of children ages 9-14 years at study enrollment. GUTS enrolled in two waves with enrollment beginning in 1996 (GUTS1) and 2004 (GUTS2). For this analysis, GUTS1 and GUTS2 participants were followed through 2001 and 2008, respectively. PARTICIPANTS/MATERIALS, SETTING, We included 7530 participants who completed food frequency questionnaire(s) (FFQ) prior to menarche who then self-reported age at menarche during study follow-up. Cox proportional hazard models were used to calculate multivariable hazard ratios (HRs) and 95% CIs for the associations between two dietary patterns, the AHEI and EDIP, and age at menarche, with and without adjustment for time-varying BMIz and height. MAIN Six thousand nine hundred ninety-two participants (93%) reported menarche during the study period. On average, participants completed the baseline FFQ 1.75 years prior to menarche. Participants in the highest quintile of AHEI diet score (indicating a healthier diet) were 8% less likely to attain menarche within the next month compared to those in the lowest quintile (95% CI = 0.85-0.99; Ptrend = 0.03). This association remained after adjustment for BMIz and height (corresponding HR = 0.93; 95% CI = 0.86-1.00; Ptrend = 0.04). Participants in the highest quintile of the EDIP score (i.e. most inflammatory diet), were 15% more likely to attain menarche in the next month relative to those in the lowest quintile (95% CI = 1.06-1.25; Ptrend = 0.0004), and the association remained following adjustment for BMIz and height (corresponding HR = 1.15; 95% CI = 1.06-1.25; Ptrend = 0.0004). LIMITATIONS, Self-reported questionnaires are subject to some error; however, given our prospective study design it is likely this error is non-differential with respect to the outcome. Our findings of an association between both the AHEI and EDIP and age at menarche indicate that diet quality may play a role in age at menarche independent of BMI or height. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the Breast Cancer Research Foundation. The GUTS is supported by the National Institutes of Health U01 HL145386. C.P.D. was supported by National Institutes of Health T32 CA094880. The authors have no conflicts of interest to disclose. N/A.
What is the association between endometriosis and the type and age of menopause? Women with endometriosis had a 7-fold increased risk of undergoing surgical menopause rather than natural menopause and were more likely to experience premature or early menopause, both surgically and naturally. Endometriosis is associated with reduced ovarian reserve, but evidence on its relationship with the type of menopause (surgical vs natural) and timing (especially premature and early menopause) is limited. Women with endometriosis are more likely to undergo hysterectomy and/or oophorectomy (either unilateral or bilateral), but the average age of these surgeries remains unclear. STUDY DESIGN, SIZE, The study analysed individual-level data from 279 948 women in five cohort studies conducted in the UK, Australia, Sweden, and Japan between 1996 and 2022. PARTICIPANTS/MATERIALS, SETTING, Women whose menopause type and age could not be determined due to premenopausal hysterectomy with ovarian preservation or use of menopausal hormone therapy were excluded. Endometriosis was identified through self-reports and administrative data. Surgical menopause was defined as premenopausal bilateral oophorectomy. Fine-Gray subdistribution hazard models estimated hazard ratios (HRs) for surgical and natural menopause. Age at menopause was determined by the ages at the final menstrual period or bilateral oophorectomy. Linear regression assessed mean differences in menopause age, while multinomial logistic regression estimated odds ratios (ORs) for categorical menopause age: <40 (premature), 40-44 (early), 45-49, 50-51 (reference), 52-54, and ≥55 years. Spontaneous premature ovarian insufficiency (POI) was defined as natural menopause before age 40 years. MAIN Endometriosis was identified in 3.7% of women. By the end of follow-up, 7.9% had surgical menopause and 58.2% experienced natural menopause. Using a competing risk model, women with endometriosis had a 7-fold increased risk of surgical menopause (HR: 7.54, 95% CI 6.84, 8.32) and were less likely to experience natural menopause (HR: 0.40, 95% CI 0.33, 0.49). On average, surgical menopause occurred 1.6 years (19 months) earlier (β: -1.59, 95% CI -1.77, -1.42) in women with endometriosis. Among women who experienced natural menopause, it was 0.4 years (5 months) earlier (β: -0.37, 95% CI -0.46, -0.28) for those with endometriosis. Women with endometriosis were twice as likely to experience premature surgical menopause (<40 years) (OR: 2.11, 95% CI 2.02, 2.20) or 1.4 times more likely to develop spontaneous POI (OR: 1.36, 95% CI 1.17, 1.59). They were also at increased odds of early surgical and natural menopause (40-44 years). LIMITATIONS, This study could not differentiate between subtypes and stages of endometriosis or assess treatments for ovarian endometrioma, which may impact ovarian reserve. Self-reported menopause type and age could introduce recall bias. Given the consistent findings across individual studies, our results are likely to be generalizable to different populations, highlighting the need for tailored management of endometriosis to prevent medically induced or premature menopause. Long-term monitoring of women with endometriosis is recommended, given their elevated risk of surgical menopause and premature or early menopause, which are associated with adverse health outcomes in later life. STUDY FUNDING/COMPETING INTEREST(S): The InterLACE Consortium is funded by the Australian National Health and Medical Research Council project grant (APP1027196) and Centres of Research Excellence (APP1153420). G.D.M. is funded by the Australian National Health and Medical Research Council Leadership Fellowship (APP2009577). This research is funded in part by the Japan Society for the Promotion of Science (JSPS 19KK0235, 23KK0167). The authors have no conflict of interest. Where authors are identified as personnel of the International Agency for Research on Cancer or WHO, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer or WHO. N/A.