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Study Question: To what extent are ambient concentrations of particulate matter <2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) associated with risk of self-reported physician-diagnosed uterine leiomyomata (UL)?Summary Answer: In this large prospective cohort study of Black women, ambient concentrations of O3, but not PM2.5 or NO2, were associated with increased risk of UL.What Is Known Already: UL are benign tumors of the myometrium that are the leading cause of gynecologic inpatient care among reproductive-aged women. Black women are clinically diagnosed at two to three times the rate of white women and tend to exhibit earlier onset and more severe disease. Two epidemiologic studies have found positive associations between air pollution exposure and UL risk, but neither included large numbers of Black women.Study Design, Size, Duration: We conducted a prospective cohort study of 21 998 premenopausal Black women residing in 56 US metropolitan areas from 1997 to 2011.Participants/material, Setting, Methods: Women reported incident UL diagnosis and method of confirmation (i.e. ultrasound, surgery) on biennial follow-up questionnaires. We modeled annual residential concentrations of PM2.5, NO2 and O3 throughout the study period. We used Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for a one-interquartile range (IQR) increase in air pollutant concentrations, adjusting for confounders and co-pollutants.Main Results and the Role Of Chance: During 196 685 person-years of follow-up, 6238 participants (28.4%) reported physician-diagnosed UL confirmed by ultrasound or surgery. Although concentrations of PM2.5 and NO2 were not appreciably associated with UL (HRs for a one-IQR increase: 1.01 (95% CI: 0.93, 1.10) and 1.05 (95% CI: 0.95, 1.16), respectively), O3 concentrations were associated with increased UL risk (HR for a one-IQR increase: 1.19, 95% CI: 1.07, 1.32). The association was stronger among women age <35 years (HR: 1.26, 95% CI: 0.98, 1.62) and parous women (HR: 1.28, 95% CI: 1.11, 1.48).Limitations, Reasons For Caution: Our measurement of air pollution is subject to misclassification, as monitoring data are not equally spatially distributed and we did not account for time-activity patterns. Our outcome measure was based on self-report of a physician diagnosis, likely resulting in under-ascertainment of UL. Although we controlled for several individual- and neighborhood-level confounding variables, residual confounding remains a possibility.Wider Implications Of the Findings: Inequitable burden of air pollution exposure has important implications for racial health disparities, and may be related to disparities in UL. Our results emphasize the need for additional research focused on environmental causes of UL.Study Funding/competing Interest(s): This research was funded by the National Cancer Institute (U01-CAA164974) and the National Institute of Environmental Health Sciences (R01-ES019573). L.A.W. is a fibroid consultant for AbbVie, Inc. and accepts in-kind donations from Swiss Precision Diagnostics, Sandstone Diagnostics, FertilityFriend.com and Kindara.com for primary data collection in Pregnancy Study Online (PRESTO). M.J. declares consultancy fees from the Health Effects Institute (as a member of the review committee). The remaining authors declare they have no actual or potential competing financial interests.Trial Registration Number: N/A. [ABSTRACT FROM AUTHOR]

Study Question: To what extent does fecundability vary across seasons?Summary Answer: After accounting for seasonal patterns in pregnancy planning, we observed higher fecundability in the fall and lower fecundability in the spring, particularly at lower latitudes.What Is Known Already: In human populations, there are strong seasonal patterns of births that vary across geographic regions and time periods. However, previous studies of seasonality and fecundity are limited because they examine season of birth rather than season of conception and therefore neglect to account for seasonal variation in initiating attempts to conceive or pregnancy loss or differences in gestational length.Study Design, Size, Duration: We conducted a preconception cohort study of 14 331 women residing in North America (June 2013-May 2018: n = 5827) and Denmark (June 2007-May 2018: n = 8504). Participants were attempting to conceive without fertility treatment and had been attempting pregnancy for ≤6 menstrual cycles at enrolment.Participants/material, Setting, Methods: We collected information on season of each pregnancy attempt using last menstrual period dates over the study period. Pregnancy was reported on female bi-monthly follow-up questionnaires. We fit log-binomial models with trigonometric regression to examine periodic variation in fecundability. We accounted for seasonal variation in initiation of pregnancy attempts by including indicator variables for menstrual cycle of attempt in the regression models.Main Results and the Role Of Chance: Initiation of pregnancy attempts peaked in September, with stronger seasonality in North America than in Denmark (48 vs. 16% higher probability initiating attempts in September compared with March). After accounting for seasonal variation in initiation of pregnancy attempts, we observed modest seasonal variation in fecundability, with a peak in the late fall and early winter in both cohorts, but stronger peak/low ratios in North America (1.16; 95% confidence interval [CI]: 1.05, 1.28) than in Denmark (1.08; 95% CI: 1.00, 1.16). When we stratified the North American data by latitude, we observed the strongest seasonal variation in the southern USA (peak/low ratio of 1.45 [95% CI: 1.14, 1.84]), with peak fecundability in late November.Limitations, Reasons For Caution: We estimated menstrual cycle dates between follow-up questionnaires, which may have introduced exposure misclassification, particularly when women skipped follow-up questionnaires. We were unable to measure seasonally varying factors that may have influenced fecundability, including ambient temperature, vitamin D levels or infectious disease.Wider Implications Of the Findings: An understanding of how fecundability varies across seasons could help identify factors that can impair reproductive function. Neglecting to account for seasonal variation in initiation of pregnancy attempts could bias estimates of seasonal patterns in fecundability. This is the first preconception cohort study to examine seasonal variation in fecundability after accounting for seasonality in initiation of pregnancy attempts. Fecundability was highest in the fall and lowest in the spring, with stronger effects in southern latitudes of North America, suggesting that seasonal exposures may affect fecundity.Study Funding/competing Interest(s): This research was funded by the Eunice K. Shriver National Institute of Child Health and Human Development (R21-050264, R01-HD060680, R21-HD072326 and R01-HD086742) and the Danish Medical Research Council (271-07-0338). The authors declare no conflicts of interest. [ABSTRACT FROM AUTHOR]

Study Question: To what extent is cigarette smoking associated with reduced fecundability?Summary Answer: Current female smokers, particularly those who had smoked ≥10 cigarettes/day for ≥10 years, had lower fecundability than never smokers, but current male smoking and passive smoking in either partner showed little association with reduced fecundability.What Is Known Already: Female smoking has been identified as a cause of infertility, yet there has been limited characterization of the dose and duration at which an effect is observed. Results for male active smoking and passive smoking in both partners are less consistent.Study Design, Size, Duration: We analyzed data from a North American internet-based preconception cohort study of 5473 female and 1411 male pregnancy planners, enrolled from 2013 to 2018. Participants had been attempting conception for ≤6 menstrual cycles at study entry.Participants/materials, Setting, Methods: We collected information on active and passive smoking history on baseline questionnaires. Pregnancy was reported on female bi-monthly follow-up questionnaires. We calculated fecundability ratios (FR) and 95% CI using proportional probabilities regression models, adjusted for demographic, behavioral, medical, reproductive and dietary variables.Main Results and the Role Of Chance: Female current regular smoking (FR = 0.90, 95% CI: 0.77, 1.07), current occasional smoking (FR = 0.88, 95% CI: 0.73, 1.06), and former smoking (FR = 0.89, 95% CI: 0.81, 0.98) were associated with small reductions in fecundability. Results were stronger among women who smoked ≥10 cigarettes/day for ≥10 years (FR = 0.77, 95% CI: 0.53, 1.10). Male current regular and former smoking, and current passive smoking in either partner were not meaningfully associated with reduced fecundability. In utero exposure to ≥10 cigarettes/day among females was associated with reduced fecundability (FR = 0.75, 95% CI: 0.52, 1.06).Limitations, Reasons For Caution: Numbers of cigarette smokers, particularly within categories of intensity and duration, were small. Under-reporting of smoking may have resulted in non-differential misclassification, and smokers were more likely to be lost to follow-up.Wider Implications Of the Findings: Given the consistency of our findings with results from previous studies and our observation of a dose-response relation in intensity of smoking, this study supports an association between female cigarette smoking and lower fecundability.Study Funding/competing Interest(s): This study was funded by the National Institute of Child Health and Human Development (R01-HD086742, R21-HD072326, R03-HD090315 and T32-HD052458). The authors declare no competing interests. [ABSTRACT FROM AUTHOR]

Study Question: To what extent is preconception use of pain-relieving medication associated with female fecundability?Summary Answer: Women who used naproxen or opioids had slightly lower fecundability than women who did not use any pain-relieving medications; use of acetaminophen, aspirin and ibuprofen was not appreciably associated with fecundability.What Is Known Already: Over-the-counter pain-relieving medications are commonly used by women of reproductive age in the USA. Studies investigating the effects of pain-relieving medication use on ovulation, implantation and fecundability have shown conflicting results.Study Design, Size, Duration: We analyzed data from an internet-based prospective cohort study of 2573 female pregnancy planners aged 21-45 years from the USA and Canada. Participants were enrolled and followed from June 2013 through September 2015. Participants completed a baseline questionnaire and bimonthly follow-up questionnaires until a reported pregnancy or for 12 months, whichever occurred first. Over 80% of participants completed at least one follow-up questionnaire.Participants/materials, Setting, Methods: Use of pain-relieving medication during the past month was assessed at baseline and on each follow-up questionnaire. Medications were categorized according to type (acetaminophen, aspirin, ibuprofen, naproxen and opioids) and total monthly dose. Self-reported pregnancy was assessed at each follow-up. Multivariable-adjusted fecundability ratios (FRs) and 95% CI were calculated using proportional probabilities regression. Models were adjusted for demographic, lifestyle and anthropometric factors; reproductive history; gynecologic morbidity; and indications for use of pain medications. Models were also run with and without adjustment for parity. After restricting to women with 6 or fewer months of attempt time at study entry, 1763 were included in the analyses.Main Results and the Role Of Chance: At baseline, 1279 (73%) women reported using ≥1 pain-relieving medications in the previous month. When compared with non-use of pain-relieving medications, FRs for use of naproxen and opioids at baseline were 0.78 (95% CI: 0.64-0.97) and 0.81 (95% CI: 0.60-1.10), respectively. A dose-response relation was observed between naproxen use and fecundability; FRs for use of <1500 and ≥1500 mg of naproxen were 0.85 (95% CI: 0.68-1.07) and 0.58 (95% CI: 0.36-0.94), respectively. Small numbers (n = 74) precluded the examination of opioid use by dose. Overall, there was little evidence of an association between fecundability and acetaminophen (FR 1.04, 95% CI: 0.92-1.18), aspirin (FR 1.00, 95% CI: 0.80-1.25), or ibuprofen (FR 1.00, 95% CI: 0.89-1.11). Similar results were observed when exposure information was updated over time.Limitations, Reasons For Caution: Numbers of opioid users were small. Information collected on reason for use of pain medications was not specific to each type of pain medication. Therefore, we cannot rule out confounding by indication as an explanation of these results.Wider Implications Of the Findings: Use of naproxen and opioids was associated with a small reduction in fecundability, but there was little association between other pain-relieving medications and fecundability.Study Funding/competing Interests: This study was supported through funds provided by National Institute of Child Health and Human Development, National Institute of Health (R21 HD072326, T32 HD052458). The authors have no conflicts of interest to disclose.Trial Registration Number: Not applicable. [ABSTRACT FROM AUTHOR]

Study Question: To what extent is dietary folate intake and total folate intake (dietary and supplemental intakes) associated with fecundability, the per cycle probability of conception?Summary Answer: Preconception dietary folate intake was positively associated with fecundability in a monotonic pattern.What Is Known Already: Supplemental folic acid has been associated with improved fertility, but little is known about the relation between dietary folate and fecundability.Study Design, Size, Duration: A prospective cohort study including 9559 women trying to conceive without fertility treatment and enrolled in the period 2013-2020.Participants/materials, Setting, Methods: We used data from two internet-based prospective cohort studies of pregnancy planners from Denmark, where folic acid fortification is not performed (SnartForældre.dk (SF); n = 3755) and North America, where the food supply is fortified with folic acid (Pregnancy Study Online (PRESTO); n = 5804). Women contributed menstrual cycles at risk until they reported conception or experienced a censoring event. We used proportional probabilities regression models to compute fecundability ratios (FRs) and 95% CI, adjusting for potential confounders.Main Results and the Role Of Chance: Compared with a dietary folate intake ≥400 µg/day, the adjusted FRs for women in SF were 0.92 (95% CI: 0.85-0.99) for intake 250-399 µg/day, and 0.80 (95% CI: 0.68-0.94) for intake of <250 µg/day. The corresponding FRs in PRESTO were 0.95 (95% CI: 0.89-1.01) and 0.81 (95% CI: 0.65-1.00). Compared with the highest level of total folate intake (diet folate ≥400 µg/day plus folic acid supplementation), in both cohorts fecundability was lowest among women with the lowest dietary intake <250 µg/day dietary folate and no supplementation (FR: 0.76, 95% CI: 0.59-0.98 [SF] and 0.49, 95% CI: 0.31-0.77 [PRESTO]). Further, total intake dietary folate <250 µg/day plus supplementation was associated with reduced fecundability for SF participants (FR; 0.79, 95% CI: 0.65-0.98) and for PRESTO participants (FR; 0.92, 95% CI: 0.72-1.16).Limitations, Reasons For Caution: It is unknown whether dietary folate and folic acid intake affect fecundability on its own or if there is an interaction with other micronutrients provided in healthy diet. Thus, the observed associations may not reflect dietary folate intake alone, but overall healthy diet.Wider Implications Of the Findings: Recommendations for preconception dietary folate intake and folic acid supplementation are of importance not only to prevent neural tube defects but also to enhance fecundability.Study Funding/competing Interest(s): The study was supported by the National Institute of Child Health and Human Development (R01-HD086742). The authors report no competing interests.Trial Registration Number: N/A. [ABSTRACT FROM AUTHOR]

Study Question: Can we derive adequate models to predict the probability of conception among couples actively trying to conceive?Summary Answer: Leveraging data collected from female participants in a North American preconception cohort study, we developed models to predict pregnancy with performance of ∼70% in the area under the receiver operating characteristic curve (AUC).What Is Known Already: Earlier work has focused primarily on identifying individual risk factors for infertility. Several predictive models have been developed in subfertile populations, with relatively low discrimination (AUC: 59-64%).Study Design, Size, Duration: Study participants were female, aged 21-45 years, residents of the USA or Canada, not using fertility treatment, and actively trying to conceive at enrollment (2013-2019). Participants completed a baseline questionnaire at enrollment and follow-up questionnaires every 2 months for up to 12 months or until conception. We used data from 4133 participants with no more than one menstrual cycle of pregnancy attempt at study entry.Participants/materials, Setting, Methods: On the baseline questionnaire, participants reported data on sociodemographic factors, lifestyle and behavioral factors, diet quality, medical history and selected male partner characteristics. A total of 163 predictors were considered in this study. We implemented regularized logistic regression, support vector machines, neural networks and gradient boosted decision trees to derive models predicting the probability of pregnancy: (i) within fewer than 12 menstrual cycles of pregnancy attempt time (Model I), and (ii) within 6 menstrual cycles of pregnancy attempt time (Model II). Cox models were used to predict the probability of pregnancy within each menstrual cycle for up to 12 cycles of follow-up (Model III). We assessed model performance using the AUC and the weighted-F1 score for Models I and II, and the concordance index for Model III.Main Results and the Role Of Chance: Model I and II AUCs were 70% and 66%, respectively, in parsimonious models, and the concordance index for Model III was 63%. The predictors that were positively associated with pregnancy in all models were: having previously breastfed an infant and using multivitamins or folic acid supplements. The predictors that were inversely associated with pregnancy in all models were: female age, female BMI and history of infertility. Among nulligravid women with no history of infertility, the most important predictors were: female age, female BMI, male BMI, use of a fertility app, attempt time at study entry and perceived stress.Limitations, Reasons For Caution: Reliance on self-reported predictor data could have introduced misclassification, which would likely be non-differential with respect to the pregnancy outcome given the prospective design. In addition, we cannot be certain that all relevant predictor variables were considered. Finally, though we validated the models using split-sample replication techniques, we did not conduct an external validation study.Wider Implications Of the Findings: Given a wide range of predictor data, machine learning algorithms can be leveraged to analyze epidemiologic data and predict the probability of conception with discrimination that exceeds earlier work.Study Funding/competing Interest(s): The research was partially supported by the U.S. National Science Foundation (under grants DMS-1664644, CNS-1645681 and IIS-1914792) and the National Institutes for Health (under grants R01 GM135930 and UL54 TR004130). In the last 3 years, L.A.W. has received in-kind donations for primary data collection in PRESTO from FertilityFriend.com, Kindara.com, Sandstone Diagnostics and Swiss Precision Diagnostics. L.A.W. also serves as a fibroid consultant to AbbVie, Inc. The other authors declare no competing interests.Trial Registration Number: N/A. [ABSTRACT FROM AUTHOR]