Neuroactive steroid hormone trajectories across the menstrual cycle in premenstrual dysphoric disorder (PMDD): the PHASE study.

It is presently not known whether endogenous neuroactive steroid hormone trajectories across the menstrual cycle are distinguishable in women with premenstrual dysphoric disorder (PMDD). To improve the rigor in this area of research, we implemented a validated study methodology, involving blood sample collection at 8 key menstrual cycle timepoints, following which the study data is realigned so that all women are compared at the same biological window (i.e., menstrual cycle subphase). Using liquid chromatography-mass spectrometry (LC-MS), we analyzed serum levels of nine steroid hormones previously implicated in the etiology of PMDD, including allopregnanolone. Other than progesterone (p ≤ 0.001), none of the steroid hormones displayed significant changes across menstrual cycle subphases when comparing participants with PMDD to the healthy controls. A thorough investigation of the progesterone trajectory showed that its left shift in the luteal phase (e.g., earlier rise in progesterone) exposes women with PMDD to a higher periovulatory progesterone and a more acute withdrawal in the late luteal subphase. Results of the present study indicate that the largely overlooked brief periovulatory subphase should be thoroughly examined in PMDD and agree with prior conclusions that rapid progesterone withdrawal associates with the development of negative affect.

Pregnancy Complications and Long-Term Mortality in a Diverse Cohort.

BACKGROUND: Pregnancy complications are associated with increased risk of development of cardiometabolic diseases and earlier mortality. However, much of the previous research has been limited to White pregnant participants. We aimed to investigate pregnancy complications in association with total and cause-specific mortality in a racially diverse cohort and evaluate whether associations differ between Black and White pregnant participants. METHODS: The Collaborative Perinatal Project was a prospective cohort study of 48 197 pregnant participants at 12 US clinical centers (1959-1966). The Collaborative Perinatal Project Mortality Linkage Study ascertained participants' vital status through 2016 with linkage to the National Death Index and Social Security Death Master File. Adjusted hazard ratios (aHRs) for underlying all-cause and cause-specific mortality were estimated for preterm delivery (PTD), hypertensive disorders of pregnancy, and gestational diabetes/impaired glucose tolerance (GDM/IGT) using Cox models adjusted for age, prepregnancy body mass index, smoking, race and ethnicity, previous pregnancies, marital status, income, education, previous medical conditions, site, and year. RESULTS: Among 46 551 participants, 45% (21 107 of 46 551) were Black, and 46% (21 502 of 46 551) were White. The median time between the index pregnancy and death/censoring was 52 years (interquartile range, 45-54). Mortality was higher among Black (8714 of 21 107 [41%]) compared with White (8019 of 21 502 [37%]) participants. Overall, 15% (6753 of 43 969) of participants had PTD, 5% (2155 of 45 897) had hypertensive disorders of pregnancy, and 1% (540 of 45 890) had GDM/IGT. PTD incidence was higher in Black (4145 of 20 288 [20%]) compared with White (1941 of 19 963 [10%]) participants. The following were associated with all-cause mortality: preterm spontaneous labor (aHR, 1.07 [95% CI, 1.03-1.1]); preterm premature rupture of membranes (aHR, 1.23 [1.05-1.44]); preterm induced labor (aHR, 1.31 [1.03-1.66]); preterm prelabor cesarean delivery (aHR, 2.09 [1.75-2.48]) compared with full-term delivery; gestational hypertension (aHR, 1.09 [0.97-1.22]); preeclampsia or eclampsia (aHR, 1.14 [0.99-1.32]) and superimposed preeclampsia or eclampsia (aHR, 1.32 [1.20-1.46]) compared with normotensive; and GDM/IGT (aHR, 1.14 [1.00-1.30]) compared with normoglycemic. P values for effect modification between Black and White participants for PTD, hypertensive disorders of pregnancy, and GDM/IGT were 0.009, 0.05, and 0.92, respectively. Preterm induced labor was associated with greater mortality risk among Black (aHR, 1.64 [1.10-2.46]) compared with White (aHR, 1.29 [0.97-1.73]) participants, while preterm prelabor cesarean delivery was higher in White (aHR, 2.34 [1.90-2.90]) compared with Black (aHR, 1.40 [1.00-1.96]) participants. CONCLUSIONS: In this large, diverse US cohort, pregnancy complications were associated with higher mortality nearly 50 years later. Higher incidence of some complications in Black individuals and differential associations with mortality risk suggest that disparities in pregnancy health may have life-long implications for earlier mortality.

Gestational weight change in a diverse pregnancy cohort and mortality over 50 years: a prospective observational cohort study.

BACKGROUND: High weight gain in pregnancy is associated with greater postpartum weight retention, yet long-term implications remain unknown. We aimed to assess whether gestational weight change was associated with mortality more than 50 years later. METHODS: The Collaborative Perinatal Project (CPP) was a prospective US pregnancy cohort (1959-65). The CPP Mortality Linkage Study linked CPP participants to the National Death Index and Social Security Death Master File for vital status to 2016. Adjusted hazard ratios (HRs) with 95% CIs estimated associations between gestational weight gain and loss according to the 2009 National Academy of Medicine recommendations and mortality by pre-pregnancy BMI. The primary endpoint was all-cause mortality. Secondary endpoints included cardiovascular and diabetes underlying causes of mortality. FINDINGS: Among 46 042 participants, 20 839 (45·3%) self-identified as Black and 21 287 (46·2%) as White. Median follow-up time was 52 years (IQR 45-54) and 17 901 (38·9%) participants died. For those who were underweight before pregnancy (BMI <18·5 kg/m2; 3809 [9·4%] of 40 689 before imputation for missing data]), weight change above recommendations was associated with increased cardiovascular mortality (HR 1·84 [95% CI 1·08-3·12]) but not all-cause mortality (1·14 [0·86-1·51]) or diabetes-related mortality (0·90 [0·13-6·35]). For those with a normal pre-pregnancy weight (BMI 18·5-24·9 kg/m2; 27 921 [68·6%]), weight change above recommendations was associated with increased all-cause (HR 1·09 [1·01-1·18]) and cardiovascular (1·20 [1·04-1·37]) mortality, but not diabetes-related mortality (0·95 [0·61-1·47]). For those who were overweight pre-pregnancy (BMI 25·0-29·9 kg/m2; 6251 [15·4%]), weight change above recommendations was associated with elevated all-cause (1·12 [1·01-1·24]) and diabetes-related (1·77 [1·23-2·54]) mortality, but not cardiovascular (1·12 [0·94-1·33]) mortality. For those with pre-pregnancy obesity (≥30·0 kg/m2; 2708 [6·7%]), all associations between gestational weight change and mortality had wide CIs and no meaningful relationships could be drawn. Weight change below recommended levels was associated only with a reduced diabetes-related mortality (0·62 [0·48-0·79]) in people with normal pre-pregnancy weight. INTERPRETATION: This study's novel findings support the importance of achieving healthy gestational weight gain within recommendations, adding that the implications might extend beyond the pregnancy window to long-term health, including cardiovascular and diabetes-related mortality. FUNDING: National Institutes of Health.

Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.

Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Maternal mortality in the United States: are the high and rising rates due to changes in obstetrical factors, maternal medical conditions, or maternal mortality surveillance?

BACKGROUND: National Vital Statistics System reports show that maternal mortality rates in the United States have nearly doubled, from 17.4 in 2018 to 32.9 per 100,000 live births in 2021. However, these high and rising rates could reflect issues unrelated to obstetrical factors, such as changes in maternal medical conditions or maternal mortality surveillance (eg, due to introduction of the pregnancy checkbox). OBJECTIVE: This study aimed to assess if the high and rising rates of maternal mortality in the United States reflect changes in obstetrical factors, maternal medical conditions, or maternal mortality surveillance. STUDY DESIGN: The study was based on all deaths in the United States from 1999 to 2021. Maternal deaths were identified using the following 2 approaches: (1) per National Vital Statistics System methodology, as deaths in pregnancy or in the postpartum period, including deaths identified solely because of a positive pregnancy checkbox, and (2) under an alternative formulation, as deaths in pregnancy or in the postpartum period, with at least 1 mention of pregnancy among the multiple causes of death on the death certificate. The frequencies of major cause-of-death categories among deaths of female patients aged 15 to 44 years, maternal deaths, deaths due to obstetrical causes (ie, direct obstetrical deaths), and deaths due to maternal medical conditions aggravated by pregnancy or its management (ie, indirect obstetrical deaths) were quantified. RESULTS: Maternal deaths, per National Vital Statistics System methodology, increased by 144% (95% confidence interval, 130-159) from 9.65 in 1999-2002 (n=1550) to 23.6 per 100,000 live births in 2018-2021 (n=3489), with increases occurring among all race and ethnicity groups. Direct obstetrical deaths increased from 8.41 in 1999-2002 to 14.1 per 100,000 live births in 2018-2021, whereas indirect obstetrical deaths increased from 1.24 to 9.41 per 100,000 live births: 38% of direct obstetrical deaths and 87% of indirect obstetrical deaths in 2018-2021 were identified because of a positive pregnancy checkbox. The pregnancy checkbox was associated with increases in less specific and incidental causes of death. For example, maternal deaths with malignant neoplasms listed as a multiple cause of death increased 46-fold from 0.03 in 1999-2002 to 1.42 per 100,000 live births in 2018-2021. Under the alternative formulation, the maternal mortality rate was 10.2 in 1999-2002 and 10.4 per 100,000 live births in 2018-2021; deaths from direct obstetrical causes decreased from 7.05 to 5.82 per 100,000 live births. Deaths due to preeclampsia, eclampsia, postpartum hemorrhage, puerperal sepsis, venous complications, and embolism decreased, whereas deaths due to adherent placenta, renal and unspecified causes, cardiomyopathy, and preexisting hypertension increased. Maternal mortality increased among non-Hispanic White women and decreased among non-Hispanic Black and Hispanic women. However, rates were disproportionately higher among non-Hispanic Black women, with large disparities evident in several causes of death (eg, cardiomyopathy). CONCLUSION: The high and rising rates of maternal mortality in the United States are a consequence of changes in maternal mortality surveillance, with reliance on the pregnancy checkbox leading to an increase in misclassified maternal deaths. Identifying maternal deaths by requiring mention of pregnancy among the multiple causes of death shows lower, stable maternal mortality rates and declines in maternal deaths from direct obstetrical causes.

History of multifetal gestation and long-term maternal mortality.

BACKGROUND: Multifetal gestation could be associated with higher long-term maternal mortality because it increases the risk of pregnancy complications such as preeclampsia and preterm birth, which are in turn linked to postpartum cardiovascular risk. OBJECTIVES: We examined whether spontaneously conceived multifetal versus singleton gestation was associated with long-term maternal mortality in a racially diverse U.S. METHODS: We ascertained vital status as of 2016 via linkage to the National Death Index and Social Security Death Master File of 44,174 mothers from the Collaborative Perinatal Project (CPP; 1959-1966). Cox proportional hazards models with maternal age as the time scale assessed associations between history of spontaneous multifetal gestation (in the last CPP observed pregnancy or prior pregnancy) and all-cause and cardiovascular mortality, adjusted for demographics, smoking status, and preexisting medical conditions. We calculated hazard ratios (HR) for all-cause and cause-specific mortality over the study period and until age 50, 60, and 70 years (premature mortality). RESULTS: Of eligible participants, 1672 (3.8%) had a history of multifetal gestation. Participants with versus without a history of multifetal gestation were older, more likely to have a preexisting condition, and more likely to smoke. By 2016, 51% of participants with and 38% of participants without a history of multifetal gestation had died (unadjusted all-cause HR 1.14, 95% confidence interval [CI] 1.07, 1.23). After adjustment for smoking and preexisting conditions, a history of multifetal gestation was not associated with all-cause (adjusted HR 1.00, 95% CI 0.93, 1.08) or cardiovascular mortality (adjusted HR 0.99, 95% CI 0.87, 1.11) over the study period. However, history of multifetal gestation was associated with an 11% lower risk of premature all-cause mortality (adjusted HR 0.89, 95% CI 0.82, 0.96). CONCLUSIONS: In a cohort with over 50 years of follow-up, history of multifetal gestation was not associated with all-cause mortality, but may be associated with a lower risk of premature mortality.

The association between preconception cannabis use and gestational diabetes mellitus: The Preconception Period Analysis of Risks and Exposures Influencing health and Development (PrePARED) consortium.

BACKGROUND: The metabolic changes that ultimately lead to gestational diabetes mellitus (GDM) likely begin before pregnancy. Cannabis use might increase the risk of GDM by increasing appetite or promoting fat deposition and adipogenesis. OBJECTIVES: We aimed to assess the association between preconception cannabis use and GDM incidence. METHODS: We analysed individual-level data from eight prospective cohort studies. We identified the first, or index, pregnancy (lasting ≥20 weeks of gestation with GDM status) after cannabis use. In analyses of pooled individual-level data, we used logistic regression to estimate study-type-specific odds ratios (OR) and 95% confidence intervals (CI), adjusting for potential confounders using random effect meta-analysis to combine study-type-specific ORs and 95% CIs. Stratified analyses assessed potential effect modification by preconception tobacco use and pre-pregnancy body mass index (BMI). RESULTS: Of 17,880 participants with an index pregnancy, 1198 (6.7%) were diagnosed with GDM. Before the index pregnancy, 12.5% of participants used cannabis in the past year. Overall, there was no association between preconception cannabis use in the past year and GDM (OR 0.97, 95% CI 0.79, 1.18). Among participants who never used tobacco, however, those who used cannabis more than weekly had a higher risk of developing GDM than those who did not use cannabis in the past year (OR 2.65, 95% CI 1.15, 6.09). This association was not present among former or current tobacco users. Results were similar across all preconception BMI groups. CONCLUSIONS: In this pooled analysis of preconception cohort studies, preconception cannabis use was associated with a higher risk of developing GDM among individuals who never used tobacco but not among individuals who formerly or currently used tobacco. Future studies with more detailed measurements are needed to investigate the influence of preconception cannabis use on pregnancy complications.

Low-dose aspirin, maternal cardiometabolic health, and offspring respiratory health 9 to 14 years after delivery: Findings from the EAGeR Follow-up Study.

BACKGROUND: Accumulating evidence shows that peri-conceptional and in-utero exposures have lifetime health impacts for mothers and their offspring. OBJECTIVES: We conducted a Follow-Up Study of the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial with two objectives. First, we determined if women who enrolled at the Utah site (N = 1001) of the EAGeR trial (2007-2011, N = 1228) could successfully be contacted and agree to complete an online questionnaire on their reproductive, cardio-metabolic, and offspring respiratory health 9-14 years after original enrollment. Second, we evaluated if maternal exposure to low-dose aspirin (LDA) during pregnancy was associated with maternal cardio-metabolic health and offspring respiratory health. METHODS: The original EAGeR study population included women, 18-40 years of age, who had 1-2 prior pregnancy losses, and who were trying to become pregnant. At follow-up (2020-2021), participants from the Utah cohort completed a 13-item online questionnaire on reproductive and cardio-metabolic health, and those who had a live birth during EAGeR additionally completed a 7-item questionnaire on the index child's respiratory health. Primary maternal outcomes included hypertension and hypercholesterolemia; primary offspring outcomes included wheezing and asthma. RESULTS: Sixty-eight percent (n = 678) of participants enrolled in the follow-up study, with 10% and 15% reporting maternal hypertension and hypercholesterolemia, respectively; and 18% and 10% reporting offspring wheezing and asthma. We found no association between maternal LDA exposure and hypertension (risk difference [RD] -0.001, 95% confidence interval [CI] -0.05, 0.04) or hypercholesterolemia (RD -0.01, 95% CI -0.06, 0.05) at 9-14 years follow-up. Maternal LDA exposure was not associated with offspring wheezing (RD -0.002, 95% CI -0.08, 0.08) or asthma (RD 0.13, 95% CI 0.11, 0.37) at follow-up. Findings remained robust after considering potential confounding and selection bias. CONCLUSIONS: We observed no association between LDA exposure during pregnancy and maternal cardiometabolic or offspring respiratory health.

A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and G-Computation in Survival Analysis.

Inverse probability weighting (IPW) and g-computation are commonly used in time-varying analyses. To inform decisions on which to use, we compared these methods using a plasmode simulation based on data from the Effects of Aspirin in Gestation and Reproduction (EAGeR) Trial (June 15, 2007-July 15, 2011). In our main analysis, we simulated a cohort study of 1,226 individuals followed for up to 10 weeks. The exposure was weekly exercise, and the outcome was time to pregnancy. We controlled for 6 confounding factors: 4 baseline confounders (race, ever smoking, age, and body mass index) and 2 time-varying confounders (compliance with assigned treatment and nausea). We sought to estimate the average causal risk difference by 10 weeks, using IPW and g-computation implemented using a Monte Carlo estimator and iterated conditional expectations (ICE). Across 500 simulations, we compared the bias, empirical standard error (ESE), average standard error, standard error ratio, and 95% confidence interval coverage of each approach. IPW (bias = 0.02; ESE = 0.04; coverage = 92.6%) and Monte Carlo g-computation (bias = -0.01; ESE = 0.03; coverage = 94.2%) performed similarly. ICE g-computation was the least biased but least precise estimator (bias = 0.01; ESE = 0.06; coverage = 93.4%). When choosing an estimator, one should consider factors like the research question, the prevalences of the exposure and outcome, and the number of time points being analyzed.

The Role of Maternal Preconception Adiposity in Human Offspring Sex and Sex Ratio.

We evaluated relationships between preconception adiposity and human offspring sex and sex ratio. Using data from a prospective preconception cohort nested within a randomized controlled trial based at 4 US clinical sites (2006-2012), we used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for male:female sex ratio, and log-identity regression to estimate risk differences (RDs) and 95% CIs for male and female livebirth according to preconception adiposity measures. Inverse-probability weights accounted for potential selection bias. Among 603 women attempting pregnancy, there were meaningful reductions in sex ratio for the highest category of each adiposity measure. The lowest sex ratios were observed for obesity (body mass index of ≥30, calculated as weight (kg)/height (m)2, OR = 0.48, 95% CI: 0.26, 0.88) relative to normal body mass index, and the top tertiles (tertile 3) of serum leptin (OR = 0.50, 95% CI: 0.32, 0.80) and skinfold measurements (OR = 0.50, 95% CI: 0.32, 0.79) relative to the lowest tertiles. Reductions were driven by 11-15 fewer male livebirths per 100 women (for obesity, RD = -15, 95% CI: -23, -6.7; for leptin tertile 3, RD = -11, 95% CI: -20, -3.2; and for skinfolds tertile 3, RD = -11, 95% CI: -19, -3.3). We found that relationships between preconception adiposity measures and reduced sex ratio were driven by a reduction in male births.

Variability in Sleep Duration and Biomarkers of Cardiovascular Disease Across the Menstrual Cycle.

Variability in sleep duration and cardiovascular health have been infrequently investigated, particularly among reproductive-age women. We examined these associations across the menstrual cycle among a cohort of 250 healthy premenopausal women, aged 18-44 years. The BioCycle study (New York, 2005-2007) collected cardiovascular biomarkers (serum high- and low-density lipoprotein (HDL, LDL), total cholesterol, triglycerides, and C-reactive protein (CRP)) at key time points along the menstrual cycle (follicular, ovulatory, and luteal phases). Women also recorded sleep duration in daily diaries. From these data, we computed L-moments, robust versions of location, dispersion, skewness, and kurtosis. We fitted linear mixed models with random intercepts and inverse probability weighting to estimate associations between sleep variability and cardiovascular biomarkers, accounting for demographic, lifestyle, health, and reproductive factors. Sleep dispersion (any deviation from mean duration) was associated with lower mean LDL for nonshift workers and non-White women. Skewed sleep duration was associated with higher mean CRP and lower mean total cholesterol. Sleep durations with extreme short and long bouts (kurtosis) were associated with a lower mean HDL, but not mean CRP, LDL, or triglycerides. Sleep duration modified associations between sleep dispersion and LDL, HDL, and total cholesterol. Even in young and healthy women, sleep duration variability could influence cardiovascular health.

Large-Scale Data Harmonization Across Prospective Studies.

The Preconception Period Analysis of Risks and Exposures Influencing Health and Development (PrePARED) Consortium creates a novel resource for addressing preconception health by merging data from numerous cohort studies. In this paper, we describe our data harmonization methods and results. Individual-level data from 12 prospective studies were pooled. The crosswalk-cataloging-harmonization procedure was used. The index pregnancy was defined as the first postbaseline pregnancy lasting more than 20 weeks. We assessed heterogeneity across studies by comparing preconception characteristics in different types of studies. The pooled data set included 114,762 women, and 25,531 (22%) reported at least 1 pregnancy of more than 20 weeks' gestation during the study period. Babies from the index pregnancies were delivered between 1976 and 2021 (median, 2008), at a mean maternal age of 29.7 (standard deviation, 4.6) years. Before the index pregnancy, 60% of women were nulligravid, 58% had a college degree or more, and 37% were overweight or obese. Other harmonized variables included race/ethnicity, household income, substance use, chronic conditions, and perinatal outcomes. Participants from pregnancy-planning studies had more education and were healthier. The prevalence of preexisting medical conditions did not vary substantially based on whether studies relied on self-reported data. Use of harmonized data presents opportunities to study uncommon preconception risk factors and pregnancy-related events. This harmonization effort laid the groundwork for future analyses and additional data harmonization.

The Relationship of Preconception and Early Pregnancy Isoprostanes with Fecundability and Pregnancy Loss.

BACKGROUND: Although redox stress likely plays an important role in reproductive health, the utility of peripheral biomarkers of oxidative stress, such as isoprostanes, during the periconception period remains underexplored. We evaluated the relationship between isoprostanes during preconception and gestational week 4 and women's reproductive health outcomes. METHODS: The Effects of Aspirin in Gestation and Reproduction trial (2007-2011) enrolled 1228 women attempting pregnancy and followed them for up to 6 menstrual cycles and throughout pregnancy if they became pregnant. We measured creatinine-adjusted, log-transformed isoprostanes 8-iso-prostaglandin F 2α (8-iso-PGF2α), its metabolite 2,3-dinor-iPF2α-III, and stereoisomers 5-iso-PGF2α-VI and 8,12-iso-iPF2α-VI in urine during preconception and 4 weeks gestation. We evaluated pregnancy among participants in each menstrual cycle using human chorionic gonadotropin (hCG) and defined pregnancy loss as observed loss following positive hCG. We calculated fecundability odds ratios (FOR) and 95% confidence intervals (CI) using discrete-time Cox proportional hazards models and relative risk of pregnancy loss using adjusted log-binomial models. RESULTS: Higher preconception isoprostane levels were associated with lower fecundability [e.g., FOR = 0.89; 95% CI = 0.81, 0.97 per interquartile range (IQR) increase in 8-iso-PGF2α]. Among 797 pregnancies, isoprostane levels increased from preconception to 4 weeks gestation (e.g., mean difference = 0.12; 95% CI = 0.10, 0.14 ng/mL for 8-iso-PGF2α) and higher isoprostanes at 4 weeks gestation were associated with lower risk of pregnancy loss (e.g., RR = 0.79; 95% CI = 0.62, 1.00 per IQR increase in 8-iso-PGF2α). CONCLUSIONS: Preconception urinary isoprostanes may identify redox stress pathways associated with lower fecundability. However, the increase in isoprostanes into gestational week 4 and the associated lower risk of pregnancy loss may suggest confounding by latent factors in early pregnancy.

Infant sex at birth and long-term maternal mortality.

BACKGROUND: Maternal adaptations may vary by foetal sex. Whether male infants influence long-term mortality in mothers remains uncertain. OBJECTIVE: The objective of the study was to examine whether male infants increase the risk of maternal mortality. METHODS: This study included pregnant women enrolled at 12 US sites from 1959 to 1966 in the Collaborative Perinatal Project (CPP). Collaborative Perinatal Project records were linked to the National Death Index and the Social Security Master Death File to ascertain deaths until 2016. Foetal sex was determined by infant sex at birth, defined as the total number of male or female infants in pregnancies prior to or during enrolment in the CPP. In secondary analyses, exposure was defined as infant sex at the last CPP delivery. Outcomes included all-cause and underlying causes of mortality. We used Cox proportional hazards models weighted by the number of prior live births and stratified our models by parity and race/ethnicity. RESULTS: Among 48,188 women, 50.8% had a male infant at their last registered CPP pregnancy and 39.0% had a recorded death after a mean follow-up of 47.8 years (SD 10.5 years). No linear association was found between the number of liveborn males and all-cause mortality (primipara women: HR 1.02, 95% CI 0.95, 1.09, multipara women, 1 prior live birth: HR 0.96, 95% CI 0.89, 1.03, multipara women, ≥2 prior live births: HR 0.97, 95% CI 0.85, 1.11). A similar trend was noted for cardiovascular- and cancer-related mortality. At the last delivery, women with a male infant did not have an increased risk of all-cause or cause-specific mortality compared to women with a female infant. These findings were consistent across racial/ethnic groups. CONCLUSIONS: Women who give birth to male infants, regardless of number, are not at increased risk of all-cause and cause-specific mortality. These findings suggest that giving birth to male infants may not independently influence the long-term health of women.

Factors associated with self-report of polycystic ovary syndrome in the Coronary Artery Risk Development in Young Adults study (CARDIA).

BACKGROUND: Polycystic ovary syndrome (PCOS) is underdiagnosed, but factors associated with women's report of diagnosis are not well-understood, particularly social determinants of health. Therefore, in a population-based cohort, we compared the characteristics of women with self-reported PCOS vs. women who have unrecognized PCOS vs. women without PCOS. METHODS: We performed a secondary data analysis of the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a population-based, prospective cohort of Black and White women. Participants were women (n = 2028) who responded to the question, "Did a doctor or nurse ever tell you that you had polycystic ovarian syndrome or polycystic ovarian disease?" at the year 15 examination. Women who answered "yes" were defined as having self-reported PCOS. Women who answered "no or not sure" were defined as having unrecognized PCOS if they also had irregular menses and hyperandrogenemia between 20 and 30 years of age. Exposures of interest included social determinants of health, symptoms including irregular menses and hirsutism, and comorbid conditions. RESULTS: Forty-three (2.1%) of women had self-reported PCOS, 135 (6.7%) had unrecognized PCOS, and 1850 (91%) women were without PCOS. In logistic regression models adjusting for age, race, and center, women with self-reported PCOS were more likely to have obesity (OR 1.83, 95% CI 1.22, 2.75) and diabetes (OR 2.37, 95% CI 1.05, 5.33) compared to women without PCOS. Women with unrecognized PCOS were more likely to have hypertension (OR 1.68, 95% CI 1.03, 2.74) and food insecurity (OR 1.94, 95% CI 1.25, 3.01) compared to women without PCOS. CONCLUSIONS: Unrecognized PCOS is common. Self-report of PCOS is not associated with access to healthcare. Women who report PCOS are more often obese and comorbidities may contribute to recognition of PCOS.

Estimation of the Average Causal Effect in Longitudinal Data With Time-Varying Exposures: The Challenge of Nonpositivity and the Impact of Model Flexibility.

There are important challenges to the estimation and identification of average causal effects in longitudinal data with time-varying exposures. Here, we discuss the difficulty in meeting the positivity condition. Our motivating example is the per-protocol analysis of the Effects of Aspirin in Gestation and Reproduction (EAGeR) Trial. We estimated the average causal effect comparing the incidence of pregnancy by 26 weeks that would have occurred if all women had been assigned to aspirin and complied versus the incidence if all women had been assigned to placebo and complied. Using flexible targeted minimum loss-based estimation, we estimated a risk difference of 1.27% (95% CI: -9.83, 12.38). Using a less flexible inverse probability weighting approach, the risk difference was 5.77% (95% CI: -1.13, 13.05). However, the cumulative probability of compliance conditional on covariates approached 0 as follow-up accrued, indicating a practical violation of the positivity assumption, which limited our ability to make causal interpretations. The effects of nonpositivity were more apparent when using a more flexible estimator, as indicated by the greater imprecision. When faced with nonpositivity, one can use a flexible approach and be transparent about the uncertainty, use a parametric approach and smooth over gaps in the data, or target a different estimand that will be less vulnerable to positivity violations.

The Role of the Natural Course in Causal Analysis.

The average causal effect compares counterfactual outcomes if everyone had been exposed versus if everyone had been unexposed, which can be an unrealistic contrast. Alternatively, we can target effects that compare counterfactual outcomes against the factual outcomes observed in the sample (i.e., we can compare against the natural course). Here, we demonstrate how the natural course can be estimated and used in causal analyses for model validation and effect estimation. Our example is an analysis assessing the impact of taking aspirin on pregnancy, 26 weeks after randomization, in the Effects of Aspirin in Gestation and Reproduction trial (United States, 2006-2012). To validate our models, we estimated the natural course using g-computation and then compared that against the observed incidence of pregnancy. We observed good agreement between the observed and model-based natural courses. We then estimated an effect that compared the natural course against the scenario in which participants assigned to aspirin always complied. If participants had always complied, there would have been 5.0 (95% confidence interval: 2.2, 7.8) more pregnancies per 100 women than was observed. It is good practice to estimate the natural course for model validation when using parametric models, but whether one should estimate a natural course contrast depends on the underlying research questions.

International Registry of Coronavirus Exposure in Pregnancy (IRCEP): Cohort Description and Methodological Considerations.

Limited data are available about the potential health effects of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on pregnant women and their developing offspring. We established the International Registry of Coronavirus Exposure in Pregnancy (IRCEP) to provide data on the risk of major adverse obstetric and neonatal outcomes among women with varying degrees of severity and timing of coronavirus disease 2019 (COVID-19) during pregnancy. We describe here the cohort and share the lessons learned. The IRCEP enrolls women tested for SARS-CoV-2 or with a clinical diagnosis of COVID-19 during pregnancy and obtains information using an online data collection system. By March 2021, 17,532 participants from 77 countries had enrolled; 54% enrolled during pregnancy and 46% afterward. Among women with symptomatic COVID-19 with a positive SARS-CoV-2 test (n = 4,934), symptoms were mild in 41%, moderate in 52%, and severe in 7%; 7.7% were hospitalized for COVID-19 and 1.7% were admitted to an intensive care unit. The biggest challenges were retention of participants enrolled during pregnancy and the potential bias introduced when participants enroll after pregnancy outcomes are known. Multiple biases need to be considered and addressed when estimating and interpreting the effects of COVID-19 in pregnancy in these types of cohorts.

Performance Evaluation of Parametric and Nonparametric Methods When Assessing Effect Measure Modification.

Effect measure modification is often evaluated using parametric models. These models, although efficient when correctly specified, make strong parametric assumptions. While nonparametric models avoid important functional form assumptions, they often require larger samples to achieve a given accuracy. We conducted a simulation study to evaluate performance tradeoffs between correctly specified parametric and nonparametric models to detect effect modification of a binary exposure by both binary and continuous modifiers. We evaluated generalized linear models and doubly robust (DR) estimators, with and without sample splitting. Continuous modifiers were modeled with cubic splines, fractional polynomials, and nonparametric DR-learner. For binary modifiers, generalized linear models showed the greatest power to detect effect modification, ranging from 0.42 to 1.00 in the worst and best scenario, respectively. Augmented inverse probability weighting had the lowest power, with an increase of 23% when using sample splitting. For continuous modifiers, the DR-learner was comparable to flexible parametric models in capturing quadratic and nonlinear monotonic functions. However, for nonlinear, nonmonotonic functions, the DR-learner had lower integrated bias than splines and fractional polynomials, with values of 141.3, 251.7, and 209.0, respectively. Our findings suggest comparable performance between nonparametric and correctly specified parametric models in evaluating effect modification.

Long-Term Mortality in Women With Pregnancy Loss and Modification by Race/Ethnicity.

Pregnancy loss is a common reproductive complication, but its association with long-term mortality and whether this varies by maternal race/ethnicity is not well understood. Data from a racially diverse cohort of pregnant women enrolled in the Collaborative Perinatal Project (CPP) from 1959 to 1966 were used for this study. CPP records were linked to the National Death Index and the Social Security Death Master File to identify deaths and underlying cause (until 2016). Pregnancy loss comprised self-reported losses, including abortions, stillbirths, and ectopic pregnancies. Among 48,188 women (46.0% White, 45.8% Black, 8.2% other race/ethnicity), 25.6% reported at least 1 pregnancy loss and 39% died. Pregnancy loss was associated with a higher absolute risk of all-cause mortality (risk difference, 4.0 per 100 women, 95% confidence interval: 1.4, 6.5) and cardiovascular mortality (risk difference, 2.2 per 100 women, 95% confidence interval: 0.8, 3.5). Stratified by race/ethnicity, a higher risk of mortality persisted in White, but not Black, women. Women with recurrent losses are at increased risk of death, both overall and across all race/ethnicity groups. Pregnancy loss is associated with death; however, it does not confer an excess risk above the observed baseline risk in Black women. These findings support the need to assess reproductive history as part of routine screening in women.