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Title: Predictive models of pregnancy based on data from a preconception cohort study
Abstract 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.

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NSF-PAR ID:
10363434
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Human Reproduction
Volume:
37
Issue:
3
ISSN:
0268-1161
Format(s):
Medium: X Size: p. 565-576
Size(s):
p. 565-576
Sponsoring Org:
National Science Foundation
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    Abstract STUDY QUESTION

    To what extent is preconception maternal or paternal coronavirus disease 2019 (COVID-19) vaccination associated with miscarriage incidence?

     SUMMARY ANSWER

    COVID-19 vaccination in either partner at any time before conception is not associated with an increased rate of miscarriage.

     WHAT IS KNOWN ALREADY

    Several observational studies have evaluated the safety of COVID-19 vaccination during pregnancy and found no association with miscarriage, though no study prospectively evaluated the risk of early miscarriage (gestational weeks [GW] <8) in relation to COVID-19 vaccination. Moreover, no study has evaluated the role of preconception vaccination in both male and female partners.

     STUDY DESIGN, SIZE, DURATION

    An Internet-based, prospective preconception cohort study of couples residing in the USA and Canada. We analyzed data from 1815 female participants who conceived during December 2020–November 2022, including 1570 couples with data on male partner vaccination.

     PARTICIPANTS/MATERIALS, SETTING, METHODS

    Eligible female participants were aged 21–45 years and were trying to conceive without use of fertility treatment at enrollment. Female participants completed questionnaires at baseline, every 8 weeks until pregnancy, and during early and late pregnancy; they could also invite their male partners to complete a baseline questionnaire. We collected data on COVID-19 vaccination (brand and date of doses), history of SARS-CoV-2 infection (yes/no and date of positive test), potential confounders (demographic, reproductive, and lifestyle characteristics), and pregnancy status on all questionnaires. Vaccination status was categorized as never (0 doses before conception), ever (≥1 dose before conception), having a full primary sequence before conception, and completing the full primary sequence ≤3 months before conception. These categories were not mutually exclusive. Participants were followed up from their first positive pregnancy test until miscarriage or a censoring event (induced abortion, ectopic pregnancy, loss to follow-up, 20 weeks’ gestation), whichever occurred first. We estimated incidence rate ratios (IRRs) for miscarriage and corresponding 95% CIs using Cox proportional hazards models with GW as the time scale. We used propensity score fine stratification weights to adjust for confounding.

     MAIN RESULTS AND THE ROLE OF CHANCE

    Among 1815 eligible female participants, 75% had received at least one dose of a COVID-19 vaccine by the time of conception. Almost one-quarter of pregnancies resulted in miscarriage, and 75% of miscarriages occurred <8 weeks’ gestation. The propensity score-weighted IRR comparing female participants who received at least one dose any time before conception versus those who had not been vaccinated was 0.85 (95% CI: 0.63, 1.14). COVID-19 vaccination was not associated with increased risk of either early miscarriage (GW: <8) or late miscarriage (GW: 8–19). There was no indication of an increased risk of miscarriage associated with male partner vaccination (IRR = 0.90; 95% CI: 0.56, 1.44).

     LIMITATIONS, REASONS FOR CAUTION

    The present study relied on self-reported vaccination status and infection history. Thus, there may be some non-differential misclassification of exposure status. While misclassification of miscarriage is also possible, the preconception cohort design and high prevalence of home pregnancy testing in this cohort reduced the potential for under-ascertainment of miscarriage. As in all observational studies, residual or unmeasured confounding is possible.

     WIDER IMPLICATIONS OF THE FINDINGS

    This is the first study to evaluate prospectively the relation between preconception COVID-19 vaccination in both partners and miscarriage, with more complete ascertainment of early miscarriages than earlier studies of vaccination. The findings are informative for individuals planning a pregnancy and their healthcare providers.

     STUDY FUNDING/COMPETING INTEREST(S)

    This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Health [R01-HD086742 (PI: L.A.W.); R01-HD105863S1 (PI: L.A.W. and M.L.E.)], the National Institute of Allergy and Infectious Diseases (R03-AI154544; PI: A.K.R.), and the National Science Foundation (NSF-1914792; PI: L.A.W.). The funders had no role in the study design, data collection, analysis and interpretation of data, writing of the report, or the decision to submit the paper for publication. L.A.W. is a fibroid consultant for AbbVie, Inc. She also receives in-kind donations from Swiss Precision Diagnostics (Clearblue home pregnancy tests) and Kindara.com (fertility apps). M.L.E. received consulting fees from Ro, Hannah, Dadi, VSeat, and Underdog, holds stock in Ro, Hannah, Dadi, and Underdog, is a past president of SSMR, and is a board member of SMRU. K.F.H. reports being an investigator on grants to her institution from UCB and Takeda, unrelated to this study. S.H.-D. reports being an investigator on grants to her institution from Takeda, unrelated to this study, and a methods consultant for UCB and Roche for unrelated drugs. The authors report no other relationships or activities that could appear to have influenced the submitted work.

     TRIAL REGISTRATION NUMBER

    N/A.

     
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  2. ; ; ; ; ; ; ( , Human Reproduction)
    Abstract STUDY QUESTION

    To what extent is male fatty acid intake associated with fecundability among couples planning pregnancy?

     SUMMARY ANSWER

    We observed weak positive associations of male dietary intakes of total and saturated fatty acids with fecundability; no other fatty acid subtypes were appreciably associated with fecundability.

     WHAT IS KNOWN ALREADY

    Male fatty acid intake has been associated with semen quality in previous studies. However, little is known about the extent to which male fatty acid intake is associated with fecundability among couples attempting spontaneous conception.

     STUDY DESIGN, SIZE, DURATION

    We conducted an internet-based preconception prospective cohort study of 697 couples who enrolled during 2015–2022. During 12 cycles of observation, 53 couples (7.6%) were lost to follow-up.

     PARTICIPANTS/MATERIALS, SETTING, METHODS

    Participants were residents of the USA or Canada, aged 21–45 years, and not using fertility treatment at enrollment. At baseline, male participants completed a food frequency questionnaire from which we estimated intakes of total fat and fatty acid subtypes. We ascertained time to pregnancy using questionnaires completed every 8 weeks by female participants until conception or up to 12 months. We used proportional probabilities regression models to estimate fecundability ratios (FRs) and 95% CIs for the associations of fat intakes with fecundability, adjusting for male and female partner characteristics. We used the multivariate nutrient density method to account for energy intake, allowing for interpretation of results as fat intake replacing carbohydrate intake. We conducted several sensitivity analyses to assess the potential for confounding, selection bias, and reverse causation.

     MAIN RESULTS AND THE ROLE OF CHANCE

    Among 697 couples, we observed 465 pregnancies during 2970 menstrual cycles of follow-up. The cumulative incidence of pregnancy during 12 cycles of follow-up after accounting for censoring was 76%. Intakes of total and saturated fatty acids were weakly, positively associated with fecundability. Fully adjusted FRs for quartiles of total fat intake were 1.32 (95% CI 1.01–1.71), 1.16 (95% CI 0.88–1.51), and 1.43 (95% CI 1.09–1.88) for the second, third, and fourth vs the first quartile, respectively. Fully adjusted FRs for saturated fatty acid intake were 1.21 (95% CI 0.94–1.55), 1.16 (95% CI 0.89–1.51), and 1.23 (95% CI 0.94–1.62) for the second, third, and fourth vs the first quartile, respectively. Intakes of monounsaturated, polyunsaturated, trans-, omega-3, and omega-6 fatty acids were not strongly associated with fecundability. Results were similar after adjustment for the female partner’s intakes of trans- and omega-3 fats.

     LIMITATIONS, REASONS FOR CAUTION

    Dietary intakes estimated from the food frequency questionnaire may be subject to non-differential misclassification, which is expected to bias results toward the null in the extreme categories when exposures are modeled as quartiles. There may be residual confounding by unmeasured dietary, lifestyle, or environmental factors. Sample size was limited, especially in subgroup analyses.

     WIDER IMPLICATIONS OF THE FINDINGS

    Our results do not support a strong causal effect of male fatty acid intakes on fecundability among couples attempting to conceive spontaneously. The weak positive associations we observed between male dietary fat intakes and fecundability may reflect a combination of causal associations, measurement error, chance, and residual confounding.

     STUDY FUNDING/COMPETING INTEREST(S)

    The study was funded by the National Institutes of Health, grant numbers R01HD086742 and R01HD105863. In the last 3 years, PRESTO has received in-kind donations from Swiss Precision Diagnostics (home pregnancy tests) and Kindara.com (fertility app). L.A.W. is a consultant for AbbVie, Inc. M.L.E. is an advisor to Sandstone, Ro, Underdog, Dadi, Hannah, Doveras, and VSeat. The other authors have no competing interests to report.

     TRIAL REGISTRATION NUMBER

    N/A.

     
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  3. ; ; ; ; ( , Human Reproduction)
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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 RESULTS AND THE ROLE OF CHANCE 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, REASONS FOR CAUTION 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. WIDER IMPLICATIONS OF THE FINDINGS 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. TRIAL REGISTRATION NUMBER N/A. 
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  4. ; ; ; ; ; ; ; ; ; ( , BMJ Medicine)
    Objectives

    To evaluate the association between preconception contraceptive use and miscarriage.

     Design

    Prospective cohort study.

     Setting

    Residents of the United States of America or Canada, recruited from 2013 until the end of 2022.

     Participants

    13 460 female identified participants aged 21-45 years who were planning a pregnancy were included, of whom 8899 conceived. Participants reported data for contraceptive history, early pregnancy, miscarriage, and potential confounders during preconception and pregnancy.

     Main outcome measure

    Miscarriage, defined as pregnancy loss before 20 weeks of gestation.

     Results

    Preconception use of combined and progestin-only oral contraceptives, hormonal intrauterine devices, copper intrauterine devices, rings, implants, or natural methods was not associated with miscarriage compared with use of barrier methods. Participants who most recently used patch (incidence rate ratios 1.34 (95% confidence interval 0.81 to 2.21)) or injectable contraceptives (1.44 (0.99 to 2.12)) had higher rates of miscarriage compared with recent users of barrier methods, although results were imprecise due to the small numbers of participants who used patch and injectable contraceptives.

     Conclusions

    Use of most contraceptives before conception was not appreciably associated with miscarriage rate. Individuals who used patch and injectable contraceptives had higher rates of miscarriage relative to users of barrier methods, although these results were imprecise and residual confounding was possible.

     
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  5. ; ; ; ; ; ; ; ; ; ; et al ( , Obesity)
    Abstract Objective

    A mother–child dyad trajectory model of weight and body composition spanning from conception to adolescence was developed to understand how early life exposures shape childhood body composition.

     Methods

    African American (49.3%) and Dominican (50.7%) pregnant mothers (n= 337) were enrolled during pregnancy, and their children (47.5% female) were followed from ages 5 to 14. Gestational weight gain (GWG) was abstracted from medical records. Child weight, height, percentage body fat, and waist circumference were measured. GWG and child body composition trajectories were jointly modeled with a flexible latent class model with a class membership component that included prepregnancy BMI.

     Results

    Four prenatal and child body composition trajectory patterns were identified, and sex‐specific patterns were observed for the joint GWG–postnatal body composition trajectories with more distinct patterns among girls but not boys. Girls of mothers with high GWG across gestation had the highest BMIzscore, waist circumference, and percentage body fat trajectories from ages 5 to 14; however, boys in this high GWG group did not show similar growth patterns.

     Conclusions

    Jointly modeled prenatal weight and child body composition trajectories showed sex‐specific patterns. Growth patterns from childhood though early adolescence appeared to be more profoundly affected by higher GWG patterns in females, suggesting sex differences in developmental programming.

     
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