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OBJECTIVE: To evaluate the association between seasonal influenza vaccination and miscarriage using data from an ongoing, prospective cohort study. METHODS: We analyzed 2013-2022 data from PRESTO (Pregnancy Study Online), a prospective prepregnancy cohort study of female pregnancy planners and their male partners in the United States and Canada. Female participants completed a baseline questionnaire and then follow-up questionnaires every 8 weeks until pregnancy, during early and late pregnancy, and during the postpartum period. Vaccine information was self-reported on all questionnaires. Miscarriage was identified from self-reported information during follow-up. Male partners were invited to complete a baseline questionnaire only. We used Cox proportional hazard models to estimate the hazard ratio (HR) and 95% CI for the association between vaccination less than 3 months before pregnancy detection through the 19th week of pregnancy and miscarriage, with gestational weeks as the time scale. We modeled vaccination as a time-varying exposure and used propensity-score fine stratification to control for confounding from seasonal and female partner factors. RESULTS: Of 6,946 pregnancies, 23.3% of female partners reported exposure to influenza vaccine before or during pregnancy: 3.2% during pregnancy (gestational age 4-19 weeks) and 20.1% during the 3 months before pregnancy detection. The miscarriage rate was 16.2% in unvaccinated and 17.0% among vaccinated participants. Compared with no vaccine exposure, influenza vaccination was not associated with increased rate of miscarriage when administered before (HR 0.99, 95% CI 0.81-1.20) or during (HR 0.83, 95% CI 0.47-1.47) pregnancy. Of the 1,135 couples with male partner vaccination data available, 10.8% reported vaccination less than 3 months before pregnancy. The HR for the association between male partner vaccination and miscarriage was 1.17 (95% CI 0.73-1.90). CONCLUSION: Influenza vaccination before or during pregnancy was not associated with miscarriage. [ABSTRACT FROM AUTHOR]

Background: Migraine is common among females of reproductive age (estimated prevalence:17–24%) and may be associated with reproductive health through underlying central nervous system excitability, autoimmune conditions, and autonomic dysfunction. We evaluated the extent to which pre-pregnancy migraine diagnosis and medication use are associated with risk of spontaneous abortion (SAB). Methods: We analyzed data from a preconception study of pregnancy planners (2013–2021). Eligible participants self-identified as female, were aged 21–45 years, resided in the USA or Canada, and conceived during follow-up (n = 7890). Participants completed baseline and bimonthly follow-up questionnaires for up to 12 months or until a reported pregnancy, whichever occurred first. Pregnant participants then completed questionnaires during early (~ 8–9 weeks) and late (~ 32 weeks) gestation. We defined migraineurs as participants who reported a migraine diagnosis or use of a medication to treat migraine. Preconception questionnaires elicited migraine medication use during the past 4 weeks, and SAB on follow-up and pregnancy questionnaires. We used Cox regression models with gestational weeks as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations among preconception migraine, migraine medication use, and SAB, controlling for potential demographic, medical, and lifestyle confounders. Results: Nineteen percent of study pregnancies ended in SAB. History of migraine before conception was not appreciably associated with SAB risk (HR = 1.03, 95% CI: 0.91–1.06). Use of any migraine medication was associated with a modest increase in SAB risk overall (HR = 1.14, 95% CI: 0.96–1.36). We observed the greatest increase in risk among those taking migraine medications daily (HR = 1.38, 95% CI: 0.81–2.35) and those taking prescription migraine prophylaxis (HR = 1.43, 95% CI: 0.72–2.84) or combination analgesic and caffeine medications (HR = 1.42, 95% CI: 0.99–2.04). Conclusions: Migraine medication use patterns suggesting greater underlying migraine severity were associated with increased risk of SAB. This research adds to the limited information available on the reproductive effects of migraine. [ABSTRACT FROM AUTHOR]

Some reproductive-aged individuals remain unvaccinated against coronavirus disease 2019 (COVID-19) because of concerns about potential adverse effects on fertility. Using data from an internet-based preconception cohort study, we examined the associations of COVID-19 vaccination and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with fertility among couples trying to conceive spontaneously. We enrolled 2,126 self-identified female participants aged 21–45 year residing in the United States or Canada during December 2020–September 2021 and followed them through November 2021. Participants completed questionnaires every 8 weeks on sociodemographics, lifestyle, medical factors, and partner information. We fit proportional probabilities regression models to estimate associations between self-reported COVID-19 vaccination and SARS-CoV-2 infection in both partners with fecundability (i.e. the per-cycle probability of conception), adjusting for potential confounders. COVID-19 vaccination was not appreciably associated with fecundability in either partner (female fecundability ratio (FR) = 1.08, 95% confidence interval (CI): 0.95, 1.23; male FR = 0.95, 95% CI: 0.83, 1.10). Female SARS-CoV-2 infection was not strongly associated with fecundability (FR = 1.07, 95% CI: 0.87, 1.31). Male infection was associated with a transient reduction in fecundability (for infection within 60 days, FR = 0.82, 95% CI: 0.47, 1.45; for infection after 60 days, FR = 1.16, 95% CI: 0.92, 1.47). These findings indicate that male SARS-CoV-2 infection may be associated with a short-term decline in fertility and that COVID-19 vaccination does not impair fertility in either partner. [ABSTRACT FROM AUTHOR]

Purpose: Diet quality is increasingly recognized as important for human reproductive capacity. We studied the association between intake of protein-rich foods and risk of spontaneous abortion (SAB). Methods: During 2013–2020, we recruited pregnancy planners from the United States and Canada (Pregnancy Study Online; PRESTO) and Denmark (SnartForaeldre.dk; SF). Participants completed a baseline questionnaire and a validated cohort-specific food frequency questionnaire. We estimated preconception intake of red meat, poultry, processed meat, seafood, eggs, plant-based proteins, and dairy from individual foods and mixed recipes. We included 4,246 PRESTO and 2,953 SF participants who reported a pregnancy during the study. Data on SAB were derived from questionnaires and population registries. We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CI), representing the effect of substituting one type of protein-rich food for another. Results: SAB risk was 23% in PRESTO and 16% in SF. In PRESTO, substitution of seafood with other protein-rich foods was associated with higher SAB risk [for example, the HR for replacing 100 g of seafood/week with 100 g of red meat was 1.10 (95% CI 1.00, 1.20)]. In contrast, in SF, substituting seafood with other protein-rich foods was associated with lower SAB risk [HR for replacing 100 g of seafood/week with 100 g of red meat was 0.89 (95% CI 0.82, 0.98)]. Other protein-rich food substitutions were not meaningfully associated with SAB risk. Conclusions: Preconception intake of protein-rich foods was largely unrelated to SAB risk, with the exception of seafood, which was associated with higher risk of SAB in Denmark, but a lower risk in North America. [ABSTRACT FROM AUTHOR]

Spontaneous abortion (SAB), defined as a pregnancy loss before 20 weeks of gestation, affects up to 30% of conceptions, yet few modifiable risk factors have been identified. We estimated the effect of ambient air pollution exposure on SAB incidence in Pregnancy Study Online (PRESTO), a preconception cohort study of North American couples who were trying to conceive. Participants completed questionnaires at baseline, every 8 weeks during preconception follow-up, and in early and late pregnancy. We analyzed data on 4643 United States (U.S.) participants and 851 Canadian participants who enrolled during 2013–2019 and conceived during 12 months of follow-up. We used country-specific national spatiotemporal models to estimate concentrations of particulate matter <2.5 μm (PM 2.5), nitrogen dioxide (NO 2), and ozone (O 3) during the preconception and prenatal periods at each participant's residential address. On follow-up and pregnancy questionnaires, participants reported information on pregnancy status, including SAB incidence and timing. We fit Cox proportional hazards regression models with gestational weeks as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of time-varying prenatal concentrations of PM 2.5 , NO 2 , and O 3 with rate of SAB, adjusting for individual- and neighborhood-level factors. Nineteen percent of pregnancies ended in SAB. Greater PM 2.5 concentrations were associated with a higher incidence of SAB in Canada, but not in the U.S. (HRs for a 5 μg/m3 increase = 1.29, 95% CI: 0.99, 1.68 and 0.94, 95% CI: 0.83, 1.08, respectively). NO 2 and O 3 concentrations were not appreciably associated with SAB incidence. Results did not vary substantially by gestational weeks or season at risk. In summary, we found little evidence for an effect of residential ambient PM 2.5 , NO 2 , and O 3 concentrations on SAB incidence in the U.S., but a moderate positive association of PM 2.5 with SAB incidence in Canada. • We found a positive association of ambient PM 2.5 concentrations with spontaneous abortion in Canada, but not the USA. • NO 2 and O 3 concentrations were not appreciably associated with rate of SAB. • Results were relatively consistent across season and weeks of gestation. • Protection of pregnant individuals from air pollutionis an important measure to safeguard maternal and fetal health. [ABSTRACT FROM AUTHOR]

[Display omitted] • Residential ambient concentrations of particulate matter, nitrogen dioxide, and ozone were not strongly associated with fecundability, the per cycle probability of conception. • We examined concentrations during multiple critical windows of exposure. • This is one of the largest studies to examine this association among couples trying to conceive spontaneously. Animal and epidemiologic studies indicate that air pollution may adversely affect fertility. However, the level of evidence is limited and specific pollutants driving the association are inconsistent across studies. We used data from a web-based preconception cohort study of pregnancy planners enrolled during 2013–2019 (Pregnancy Study Online; PRESTO). Eligible participants self-identified as female, were aged 21–45 years, resided in the United States (U.S.) or Canada, and were trying to conceive without fertility treatments. Participants completed a baseline questionnaire and bi-monthly follow-up questionnaires until conception or 12 months. We analyzed data from 8,747 participants (U.S.: 7,304; Canada: 1,443) who had been trying to conceive for < 12 cycles at enrollment. We estimated residential ambient concentrations of particulate matter < 2.5 µm (PM 2.5), nitrogen dioxide (NO 2), and ozone (O 3) using validated spatiotemporal models specific to each country. We fit country-specific proportional probabilities regression models to estimate the association between annual average, menstrual cycle-specific, and preconception average pollutant concentrations with fecundability, the per-cycle probability of conception. We calculated fecundability ratios (FRs) and 95% confidence intervals (CIs) and adjusted for individual- and neighborhood-level confounders. In the U.S., the FRs for a 5-µg/m3 increase in annual average, cycle-specific, and preconception average PM 2.5 concentrations were 0.94 (95% CI: 0.83, 1.08), 1.00 (95% CI: 0.93, 1.07), and 1.00 (95% CI: 0.93, 1.09), respectively. In Canada, the corresponding FRs were 0.92 (95% CI: 0.74, 1.16), 0.97 (95% CI: 0.87, 1.09), and 0.94 (95% CI: 0.80, 1.09), respectively. Likewise, NO 2 and O 3 concentrations were not strongly associated with fecundability in either country. Neither annual average, menstrual cycle-specific, nor preconception average exposure to ambient PM 2.5 , NO 2 , and O 3 were appreciably associated with reduced fecundability in this cohort of pregnancy planners. [ABSTRACT FROM AUTHOR]

While some epidemiologic studies support the hypothesis that stress can adversely affect fertility, few prospective studies have assessed the association in couples from the general population. We used data from Pregnancy Study Online, a web-based preconception cohort study of pregnancy planners from the United States and Canada (2013–2018), to examine the association between women's and men's perceived stress levels prior to conception and fecundability. Women (aged 21–45 years) and their male partners (aged ≥21 years) who were attempting conception without fertility treatment were eligible. We measured perceived stress using the 10-item Perceived Stress Scale (PSS). We ascertained pregnancy information using bimonthly follow-up questionnaires of female participants. We followed 4,769 couples until self-reported pregnancy, initiation of fertility treatment, loss to follow-up, or 12 menstrual cycles of attempt time, whichever came first. We used proportional probabilities regression models to estimate fecundability ratios and 95% confidence intervals, adjusting for potential confounders. Higher PSS scores among the women were associated with slight reductions in fecundability (comparing PSS scores of ≥25 vs. <10, fecundability ratio = 0.87, 95% confidence interval: 0.74, 1.02). PSS scores among the men were not substantially associated with fecundability. [ABSTRACT FROM AUTHOR]

To use self-reported preconception data to derive models that predict the risk of miscarriage. Prospective preconception cohort study. Not applicable. Study participants were female, aged 21–45 years, residents of the United States or Canada, and attempting spontaneous pregnancy at enrollment during 2013–2022. Participants were followed for up to 12 months of pregnancy attempts; those who conceived were followed through pregnancy and postpartum. We restricted analyses to participants who conceived during the study period. On baseline and follow-up questionnaires completed every 8 weeks until pregnancy, we collected self-reported data on sociodemographic factors, reproductive history, lifestyle, anthropometrics, diet, medical history, and male partner characteristics. We included 160 potential predictor variables in our models. The primary outcome was a miscarriage, defined as pregnancy loss before 20 weeks of gestation. We followed participants from their first positive pregnancy test until miscarriage or a censoring event (induced abortion, ectopic pregnancy, loss of follow-up, or 20 weeks of gestation), whichever occurred first. We fit both survival and static models using Cox proportional hazards models, logistic regression, support vector machines, gradient-boosted trees, and random forest algorithms. We evaluated model performance using the concordance index (survival models) and the weighted F1 score (static models). Among the 8,720 participants who conceived, 20.4% reported miscarriage. In multivariable models, the strongest predictors of miscarriage were female age, history of miscarriage, and male partner age. The weighted F1 score ranged from 73%–89% for static models and the concordance index ranged from 53%–56% for survival models, indicating better discrimination for the static models compared with the survival models (i.e., the ability of the model to discriminate between individuals with and without miscarriage). No appreciable differences were observed across strata of miscarriage history or among models restricted to ≥8 weeks of gestation. Our findings suggest that miscarriage is not easily predicted on the basis of preconception lifestyle characteristics and that advancing age and a history of miscarriage are the most important predictors of incident miscarriage. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate the association between menstrual cycle characteristics in early life and adulthood and fecundability.Methods: Pregnancy Study Online (PRESTO) is an Internet-based preconception cohort study of pregnancy planners from the United States and Canada. During the preconception period, we enrolled 2189 female pregnancy planners aged 21-45 years who had been attempting conception for ≤6 cycles. Women self-reported menstrual cycle characteristics via an online baseline questionnaire, and pregnancy status was ascertained through bimonthly follow-up questionnaires. Proportional probabilities models were used to estimate fecundability ratios (FRs) and 95% confidence intervals (CIs), adjusting for potential confounders.Results: Compared with usual menstrual cycle lengths of 27-29 days, cycle lengths of <25 (FR = 0.81, 95% CI: 0.54-1.22) and 25-26 days (FR = 0.92, 95% CI: 0.75-1.14) were associated with reduced fecundability. Compared with women who reached menarche at the age of 12-13 years, those who reached menarche at <12 years had reduced fecundability (FR = 0.87, 95% CI: 0.76-0.99). Women whose cycles never regularized after menarche (FR = 0.93, 95% CI: 0.81-1.06) had slightly reduced fecundability compared with women whose cycles regularized within 2 years of menarche. Bleed length and heaviness of bleeding were not appreciably associated with fecundability.Conclusions: Menstrual cycle characteristics, specifically cycle length and age at menarche, may act as markers of fertility potential among pregnancy planners. [ABSTRACT FROM AUTHOR]

Background: Several studies indicate adverse effects of selected heat exposures on semen quality, but few studies have directly evaluated fertility as an endpoint. Objective: We evaluated prospectively the association between male heat exposures and fecundability, the per‐cycle probability of conception. Materials and methods: We analyzed data from 3041 couples residing in the United States or Canada who enrolled in a prospective preconception cohort study (2013–2021). At enrollment, males reported on several heat‐related exposures, such as use of saunas, hot baths, seat heaters, and tight‐fitting underwear. Pregnancy status was updated on female follow‐up questionnaires every 8 weeks until conception or a censoring event (initiation of fertility treatment, cessation of pregnancy attempts, withdrawal, loss to follow‐up, or 12 cycles), whichever came first. We used proportional probabilities regression models to estimate fecundability ratios (FR) and 95% confidence intervals (CIs) for the association between heat exposures and fecundability, mutually adjusting for heat exposures and other potential confounders. Results: We observed small inverse associations for hot bath/tub use (≥3 vs. 0 times/month: FR = 0.87, 95% CI: 0.70–1.07) and fever in the 3 months before baseline (FR = 0.94, 95% CI: 0.79–1.12; one cycle of follow‐up: FR = 0.84, 95% CI: 0.64–1.11). Little association was found for sauna use, hours of laptop use on one's lap, seat heater use, time spent sitting, and use of tight‐fitting underwear. Based on a cumulative heat metric, FRs for 1, 2, 3, and ≥4 versus 0 heat exposures were 0.99 (95% CI: 0.87–1.12), 1.03 (95% CI: 0.89–1.19), 0.94 (95% CI: 0.74–1.19), and 0.77 (95% CI: 0.50–1.17), respectively. Associations were stronger among men aged ≥30 years (≥4 vs. 0 heat exposures: FR = 0.60, 95% CI: 0.34–1.04). Conclusion: Male use of hot tubs/baths and fever showed weak inverse associations with fecundability. Cumulative exposure to multiple heat sources was associated with a moderate reduction in fecundability, particularly among males aged ≥30 years. [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]

Objective: To evaluate the association between adiposity, physical activity (PA), and fecundability.Design: Prospective cohort study.Setting: Not applicable.Patient(s): A total of 2,062 female pregnancy planners from the United States and Canada who were enrolled during the preconception period.Intervention(s): None.Main Outcome Measure(s): Self-reported pregnancy. Fecundability ratios (FRs) and 95% confidence intervals (CIs) were estimated using proportional probabilities models that adjusted for potential confounders.Result(s): Relative to body mass index (BMI) 18.5-24 kg/m(2), FRs for BMI <18.5, 25-29, 30-34, 35-39, 40-44, and ≥45 kg/m(2) were 1.05 (95% CI 0.76-1.46), 1.01 (95% CI 0.89-1.15), 0.98 (95% CI 0.82-1.18), 0.78 (95% CI 0.60-1.02), 0.61 (95% CI 0.42-0.88), and 0.42 (95% CI 0.23-0.76), respectively. Reduced fecundability was observed among women with the largest waist-to-hip ratios (≥0.85 vs. <0.75; FR = 0.87, 95% CI 0.74-1.01) and waist circumferences (≥36 vs. <26 inches [≥90 vs. <66 cm]; FR = 0.80, 95% CI 0.59-1.01). Tendency to gain weight in the chest/shoulders (FR = 0.63, 95% CI 0.36-1.08) and waist/stomach (FR = 0.90, 95% CI 0.79-1.02), relative to hips/thighs, was associated with lower fecundability. Moderate PA was associated with increased fecundability (≥5 vs. <1 h/wk; FR = 1.26, 95% CI 0.96-1.65), but there was no dose-response relation. Among overweight/obese women (BMI ≥25 kg/m(2)), fecundability was 27% higher for vigorous PA of ≥5 versus <1 h/wk (95% CI 1.02-1.57).Conclusion(s): Various measures of overall and central adiposity were associated with decreased fertility among pregnancy planners. Vigorous PA was associated with improved fertility among overweight and obese women only; moderate PA was associated with improved fertility among all women. [ABSTRACT FROM AUTHOR]