Socioeconomic Disadvantage in Pregnancy and Postpartum Risk of Cardiovascular Disease.

BACKGROUND: Pregnancy is an educable and actionable life stage to address social determinants of health (SDOH) and lifelong cardiovascular disease (CVD) prevention. But the link between a risk score that combines multiple neighborhood-level social determinants in pregnancy and the risk of long-term CVD remains to be evaluated. OBJECTIVE: To examine whether neighborhood-level socioeconomic disadvantage measured by the Area Deprivation Index (ADI) in early pregnancy is associated with a higher 30-year predicted risk of CVD postpartum, as measured by the Framingham Risk Score. METHODS: An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be (nuMoM2b) Heart Health Study longitudinal cohort. Participant home addresses during early pregnancy were geocoded at the Census-block level. The exposure was neighborhood-level socioeconomic disadvantage using the 2015 ADI by tertile (least deprived [T1], reference; most deprived [T3]) measured in the first trimester. Outcomes were the predicted 30-year risks of atherosclerotic CVD (ASCVD, composite of fatal and non-fatal coronary heart disease and stroke) and total CVD (composite of ASCVD plus coronary insufficiency, angina pectoris, transient ischemic attack, intermittent claudication, and heart failure) using the Framingham Risk Score measured 2-to-7 years after delivery. These outcomes were assessed as continuous measures of absolute estimated risk in increments of 1%, and, secondarily, as categorical measures with high-risk defined as an estimated probability of CVD >10%. Multivariable linear regression and modified Poisson regression models adjusted for baseline age and individual-level social determinants, including health insurance, educational attainment, and household poverty. RESULTS: Among 4,309 nulliparous individuals at baseline, the median age was 27 years (IQR: 23-31) and the median ADI was 43 (IQR: 22-74). At 2-to-7 years postpartum (median: 3.1 years, IQR: 2.5, 3.7), the median 30-year risk of ASCVD was 2.3% (IQR: 1.5, 3.5) and of total CVD was 5.5% (IQR: 3.7, 7.9); 2.2% and 14.3% of individuals had predicted 30-year risk >10%, respectively. Individuals living in the highest ADI tertile had a higher predicted risk of 30-year ASCVD % (adj. ß: 0.41; 95% CI: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top two ADI tertiles had higher absolute risks of 30-year total CVD % (T2: adj. ß: 0.37; 95% CI: 0.03, 0.72; T3: adj. ß: 0.74; 95% CI: 0.36, 1.13). Similarly, individuals living in neighborhoods in the highest ADI tertile were more likely to have a high 30-year predicted risk of ASCVD (aRR: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). CONCLUSIONS: Neighborhood-level socioeconomic disadvantage in early pregnancy was associated with a higher estimated long-term risk of CVD postpartum. Incorporating aggregated SDOH into existing clinical workflows and future research in pregnancy could reduce disparities in maternal cardiovascular health across the lifespan, and requires further study.

Predicting first time depression onset in pregnancy: applying machine learning methods to patient-reported data.

PURPOSE: To develop a machine learning algorithm, using patient-reported data from early pregnancy, to predict later onset of first time moderate-to-severe depression. METHODS: A sample of 944 U.S. patient participants from a larger longitudinal observational cohortused a prenatal support mobile app from September 2019 to April 2022. Participants self-reported clinical and social risk factors during first trimester initiation of app use and completed voluntary depression screenings in each trimester. Several machine learning algorithms were applied to self-reported data, including a novel algorithm for causal discovery. Training and test datasets were built from a randomized 80/20 data split. Models were evaluated on their predictive accuracy and their simplicity (i.e., fewest variables required for prediction). RESULTS: Among participants, 78% identified as white with an average age of 30 [IQR 26-34]; 61% had income ≥ $50,000; 70% had a college degree or higher; and 49% were nulliparous. All models accurately predicted first time moderate-severe depression using first trimester baseline data (AUC 0.74-0.89, sensitivity 0.35-0.81, specificity 0.78-0.95). Several predictors were common across models, including anxiety history, partnered status, psychosocial factors, and pregnancy-specific stressors. The optimal model used only 14 (26%) of the possible variables and had excellent accuracy (AUC = 0.89, sensitivity = 0.81, specificity = 0.83). When food insecurity reports were included among a subset of participants, demographics, including race and income, dropped out and the model became more accurate (AUC = 0.93) and simpler (9 variables). CONCLUSION: A relatively small amount of self-report data produced a highly predictive model of first time depression among pregnant individuals.

Prediction of COVID-19 Severity at Delivery after Asymptomatic or Mild COVID-19 during Pregnancy.

OBJECTIVE: This study aimed to develop a prediction model that estimates the probability that a pregnant person who has had asymptomatic or mild coronavirus disease 2019 (COVID-19) prior to delivery admission will progress in severity to moderate, severe, or critical COVID-19. STUDY DESIGN: This was a secondary analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients who delivered from March through December 2020 at hospitals across the United States. Those eligible for this analysis presented for delivery with a current or previous asymptomatic or mild SARS-CoV-2 infection. The primary outcome was moderate, severe, or critical COVID-19 during the delivery admission through 42 days postpartum. The prediction model was developed and internally validated using stratified cross-validation with stepwise backward elimination, incorporating only variables that were known on the day of hospital admission. RESULTS: Of the 2,818 patients included, 26 (0.9%; 95% confidence interval [CI], 0.6-1.3%) developed moderate-severe-critical COVID-19 during the study period. Variables in the prediction model were gestational age at delivery admission (adjusted odds ratio [aOR], 1.15; 95% CI, 1.08-1.22 per 1-week decrease), a hypertensive disorder in a prior pregnancy (aOR 3.05; 95% CI, 1.25-7.46), and systolic blood pressure at admission (aOR, 1.04; 95% CI, 1.02-1.05 per mm Hg increase). This model yielded an area under the receiver operating characteristic curve of 0.82 (95% CI, 0.72-0.91). CONCLUSION: Among individuals presenting for delivery who had asymptomatic-mild COVID-19, gestational age at delivery admission, a hypertensive disorder in a prior pregnancy, and systolic blood pressure at admission were predictive of delivering with moderate, severe, or critical COVID-19. This prediction model may be a useful tool to optimize resources for SARS-CoV-2-infected pregnant individuals admitted for delivery. KEY POINTS: · Three factors were associated with delivery with more severe COVID-19.. · The developed model yielded an area under the receiver operating characteristic curve of 0.82 and model fit was good.. · The model may be useful tool for SARS-CoV-2 infected pregnancies admitted for delivery..

Genetic polymorphisms associated with adverse pregnancy outcomes in nulliparas.

Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Adverse Pregnancy Outcomes and Predicted 30-Year Risk of Maternal Cardiovascular Disease 2-7 Years After Delivery.

OBJECTIVE: To determine whether adverse pregnancy outcomes are associated with a higher predicted 30-year risk of atherosclerotic cardiovascular disease (CVD; ie, coronary artery disease or stroke). METHODS: This was a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort. The exposures were adverse pregnancy outcomes during the first pregnancy (ie, gestational diabetes mellitus [GDM], hypertensive disorder of pregnancy, preterm birth, and small- and large-for-gestational-age [SGA, LGA] birth weight) modeled individually and secondarily as the cumulative number of adverse pregnancy outcomes (ie, none, one, two or more). The outcome was the 30-year risk of atherosclerotic CVD predicted with the Framingham Risk Score assessed at 2-7 years after delivery. Risk was measured both continuously in increments of 1% and categorically, with high predicted risk defined as a predicted risk of atherosclerotic CVD of 10% or more. Linear regression and modified Poisson models were adjusted for baseline covariates. RESULTS: Among 4,273 individuals who were assessed at a median of 3.1 years after delivery (interquartile range 2.5-3.7), the median predicted 30-year atherosclerotic CVD risk was 2.2% (interquartile range 1.4-3.4), and 1.8% had high predicted risk. Individuals with GDM (least mean square 5.93 vs 4.19, adjusted ß=1.45, 95% CI, 1.14-1.75), hypertensive disorder of pregnancy (4.95 vs 4.22, adjusted ß=0.49, 95% CI, 0.31-0.68), and preterm birth (4.81 vs 4.27, adjusted ß=0.47, 95% CI, 0.24-0.70) were more likely to have a higher absolute risk of atherosclerotic CVD. Similarly, individuals with GDM (8.7% vs 1.4%, adjusted risk ratio [RR] 2.02, 95% CI, 1.14-3.59), hypertensive disorder of pregnancy (4.4% vs 1.4%, adjusted RR 1.91, 95% CI, 1.17-3.13), and preterm birth (5.0% vs 1.5%, adjusted RR 2.26, 95% CI, 1.30-3.93) were more likely to have a high predicted risk of atherosclerotic CVD. A greater number of adverse pregnancy outcomes within the first birth was associated with progressively greater risks, including per 1% atherosclerotic CVD risk (one adverse pregnancy outcome: 4.86 vs 4.09, adjusted ß=0.59, 95% CI, 0.43-0.75; two or more adverse pregnancy outcomes: 5.51 vs 4.09, adjusted ß=1.16, 95% CI, 0.82-1.50), and a high predicted risk of atherosclerotic CVD (one adverse pregnancy outcome: 3.8% vs 1.0%, adjusted RR 2.33, 95% CI, 1.40-3.88; two or more adverse pregnancy outcomes: 8.7 vs 1.0%, RR 3.43, 95% CI, 1.74-6.74). Small and large for gestational age were not consistently associated with a higher atherosclerotic CVD risk. CONCLUSION: Individuals who experienced adverse pregnancy outcomes in their first birth were more likely to have a higher predicted 30-year risk of CVD measured at 2-7 years after delivery. The magnitude of risk was higher with a greater number of adverse pregnancy outcomes experienced.

Prediction of metabolic syndrome following a first pregnancy.

BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome. OBJECTIVE: This study aimed to develop machine learning models to predict the development of metabolic syndrome using factors ascertained in nulliparous pregnant individuals. STUDY DESIGN: This was a secondary analysis of a prospective cohort study (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be Heart Health Study [nuMoM2b-HHS]). Data were collected from October 2010 to October 2020, and analyzed from July 2023 to October 2023. Participants had in-person visits 2 to 7 years after their first delivery. The primary outcome was metabolic syndrome, defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, which was measured within 2 to 7 years after delivery. A total of 127 variables that were obtained during pregnancy were evaluated. The data set was randomly split into a training set (70%) and a test set (30%). We developed a random forest model and a lasso regression model using variables obtained during pregnancy. We compared the area under the receiver operating characteristic curve for both models. Using the model with the better area under the receiver operating characteristic curve, we developed models that included fewer variables based on SHAP (SHapley Additive exPlanations) values and compared them with the original model. The final model chosen would have fewer variables and noninferior areas under the receiver operating characteristic curve. RESULTS: A total of 4225 individuals met the inclusion criteria; the mean (standard deviation) age was 27.0 (5.6) years. Of these, 754 (17.8%) developed metabolic syndrome. The area under the receiver operating characteristic curve of the random forest model was 0.878 (95% confidence interval, 0.846-0.909), which was higher than the 0.850 of the lasso model (95% confidence interval, 0.811-0.888; P<.001). Therefore, random forest models using fewer variables were developed. The random forest model with the top 3 variables (high-density lipoprotein, insulin, and high-sensitivity C-reactive protein) was chosen as the final model because it had the area under the receiver operating characteristic curve of 0.867 (95% confidence interval, 0.839-0.895), which was not inferior to the original model (P=.08). The area under the receiver operating characteristic curve of the final model in the test set was 0.847 (95% confidence interval, 0.821-0.873). An online application of the final model was developed (https://kawakita.shinyapps.io/metabolic/). CONCLUSION: We developed a model that can accurately predict the development of metabolic syndrome in 2 to 7 years after delivery.

Postpartum pharmacologic thromboprophylaxis and complications in a US cohort.

BACKGROUND: Venous thromboembolism accounts for approximately 9% of pregnancy-related deaths in the United States. National guidelines recommend postpartum risk stratification and pharmacologic prophylaxis in at-risk individuals. Knowledge on modern rates of postpartum pharmacologic thromboprophylaxis and its associated risks is limited. OBJECTIVE: This study aimed to describe the rate of, and factors associated with, initiation of postpartum pharmacologic prophylaxis for venous thromboembolism, and to assess associated adverse outcomes. STUDY DESIGN: This was a secondary analysis of a multicenter cohort of individuals delivering on randomly selected days at 17 US hospitals (2019-2020). Medical records were reviewed by trained and certified personnel. Those with an antepartum diagnosis of venous thromboembolism, receiving antepartum anticoagulation, or known SARS-CoV-2 infection were excluded. The primary outcome was use of postpartum pharmacologic thromboprophylaxis. Secondary outcomes included bleeding complications, surgical site infection, hospital readmission, and venous thromboembolism through 6 weeks postpartum. The rate of thromboprophylaxis administration was assessed by mode of delivery, institution, and continuance to the outpatient setting. Multivariable regression models were developed using k-fold cross-validation with stepwise backward elimination to evaluate factors associated with thromboprophylaxis administration. Univariable and multivariable logistic models with propensity score covariate adjustment were performed to assess the association between thromboprophylaxis administration and adverse outcomes. RESULTS: Of 21,114 individuals in the analytical cohort, 11.9% (95% confidence interval, 11.4%-12.3%) received postpartum pharmacologic thromboprophylaxis; the frequency of receipt was 29.8% (95% confidence interval, 28.7%-30.9%) following cesarean and 3.5% (95% confidence interval, 3.2%-3.8%) following vaginal delivery. Institutional rates of prophylaxis varied from 0.21% to 34.8%. Most individuals (83.3%) received thromboprophylaxis only as inpatients. In adjusted analysis, cesarean delivery (adjusted odds ratio, 19.17; 95% confidence interval, 16.70-22.00), hysterectomy (adjusted odds ratio, 15.70; 95% confidence interval, 4.35-56.65), and obesity (adjusted odds ratio, 3.45; 95% confidence interval, 3.02-3.95) were the strongest factors associated with thromboprophylaxis administration. Thromboprophylaxis administration was not associated with surgical site infection (0.9% vs 0.6%; odds ratio, 1.48; 95% confidence interval, 0.80-2.74), bleeding complications (0.2% vs 0.1%; odds ratio, 2.60; 95% confidence interval, 0.99-6.80), or postpartum readmission (0.9% vs 0.3%; adjusted odds ratio, 1.38; 95% confidence interval, 0.68-2.81). The overall rate of venous thromboembolism was 0.06% (95% confidence interval, 0.03%-0.10%) and was higher in those receiving prophylaxis (0.2%) compared with those not receiving prophylaxis (0.04%). CONCLUSION: Approximately 1 in 10 patients received postpartum pharmacologic thromboprophylaxis in this US cohort. Rates of prophylaxis varied widely by institution. Cesarean delivery, hysterectomy, and obesity were predominant factors associated with postpartum thromboprophylaxis administration.

Segmenting hypothalamic subunits in human newborn magnetic resonance imaging data.

Preclinical evidence suggests that inter-individual variation in the structure of the hypothalamus at birth is associated with variation in the intrauterine environment, with downstream implications for future disease susceptibility. However, scientific advancement in humans is limited by a lack of validated methods for the automatic segmentation of the newborn hypothalamus. N = 215 healthy full-term infants with paired T1-/T2-weighted MR images across four sites were considered for primary analyses (mean postmenstrual age = 44.3 ± 3.5 weeks, nmale /nfemale = 110/106). The outputs of FreeSurfer's hypothalamic subunit segmentation tools designed for adults (segFS) were compared against those of a novel registration-based pipeline developed here (segATLAS) and against manually edited segmentations (segMAN) as reference. Comparisons were made using Dice Similarity Coefficients (DSCs) and through expected associations with postmenstrual age at scan. In addition, we aimed to demonstrate the validity of the segATLAS pipeline by testing for the stability of inter-individual variation in hypothalamic volume across the first year of life (n = 41 longitudinal datasets available). SegFS and segATLAS segmentations demonstrated a wide spread in agreement (mean DSC = 0.65 ± 0.14 SD; range = {0.03-0.80}). SegATLAS volumes were more highly correlated with postmenstrual age at scan than segFS volumes (n = 215 infants; RsegATLAS 2 = 65% vs. RsegFS 2 = 40%), and segATLAS volumes demonstrated a higher degree of agreement with segMAN reference segmentations at the whole hypothalamus (segATLAS DSC = 0.89 ± 0.06 SD; segFS DSC = 0.68 ± 0.14 SD) and subunit levels (segATLAS DSC = 0.80 ± 0.16 SD; segFS DSC = 0.40 ± 0.26 SD). In addition, segATLAS (but not segFS) volumes demonstrated stability from near birth to ~1 years age (n = 41; R2 = 25%; p < 10-3 ). These findings highlight segATLAS as a valid and publicly available (https://github.com/jerodras/neonate_hypothalamus_seg) pipeline for the segmentation of hypothalamic subunits using human newborn MRI up to 3 months of age collected at resolutions on the order of 1 mm isotropic. Because the hypothalamus is traditionally understudied due to a lack of high-quality segmentation tools during the early life period, and because the hypothalamus is of high biological relevance to human growth and development, this tool may stimulate developmental and clinical research by providing new insight into the unique role of the hypothalamus and its subunits in shaping trajectories of early life health and disease.

Associations of Organophosphate Ester Flame Retardant Exposures during Pregnancy with Gestational Duration and Fetal Growth: The Environmental influences on Child Health Outcomes (ECHO) Program.

BACKGROUND: Widespread exposure to organophosphate ester (OPE) flame retardants with potential reproductive toxicity raises concern regarding the impacts of gestational exposure on birth outcomes. Previous studies of prenatal OPE exposure and birth outcomes had limited sample sizes, with inconclusive results. OBJECTIVES: We conducted a collaborative analysis of associations between gestational OPE exposures and adverse birth outcomes and tested whether associations were modified by sex. METHODS: We included 6,646 pregnant participants from 16 cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program. Nine OPE biomarkers were quantified in maternal urine samples collected primarily during the second and third trimester and modeled as log2-transformed continuous, categorized (high/low/nondetect), or dichotomous (detect/nondetect) variables depending on detection frequency. We used covariate-adjusted linear, logistic, and multinomial regression with generalized estimating equations, accounting for cohort-level clustering, to estimate associations of OPE biomarkers with gestational length and birth weight outcomes. Secondarily, we assessed effect modification by sex. RESULTS: Three OPE biomarkers [diphenyl phosphate (DPHP), a composite of dibutyl phosphate and di-isobutyl phosphate (DBUP/DIBP), and bis(1,3-dichloro-2-propyl) phosphate] were detected in >85% of participants. In adjusted models, DBUP/DIBP [odds ratio (OR) per doubling=1.07; 95% confidence interval (CI): 1.02, 1.12] and bis(butoxyethyl) phosphate (OR for high vs. nondetect=1.25; 95% CI: 1.06, 1.46), but not other OPE biomarkers, were associated with higher odds of preterm birth. We observed effect modification by sex for associations of DPHP and high bis(2-chloroethyl) phosphate with completed gestational weeks and odds of preterm birth, with adverse associations among females. In addition, newborns of mothers with detectable bis(1-chloro-2-propyl) phosphate, bis(2-methylphenyl) phosphate, and dipropyl phosphate had higher birth weight-for-gestational-age z-scores (ß for detect vs. nondetect=0.04-0.07); other chemicals showed null associations. DISCUSSION: In the largest study to date, we find gestational exposures to several OPEs are associated with earlier timing of birth, especially among female neonates, or with greater fetal growth. https://doi.org/10.1289/EHP13182.

Breastfeeding Initiation, Duration, and Associated Factors Among People With Hepatitis C Virus Infection.

OBJECTIVE: To characterize breastfeeding behaviors and identify factors associated with breastfeeding initiation among people with hepatitis C virus (HCV) infection. METHODS: We conducted a secondary analysis of a multicenter observational cohort of pregnant people with singleton gestations and HCV seropositivity. This analysis includes individuals with data on breastfeeding initiation and excludes those with human immunodeficiency virus (HIV) co-infection. The primary outcome was self-reported initiation of breastfeeding or provision of expressed breast milk. Secondary outcomes included duration of breastfeeding. Demographic and obstetric characteristics were compared between those who initiated breastfeeding and those who did not to identify associated factors. Univariable and multivariable analyses were performed. RESULTS: Overall, 579 individuals (75.0% of participants in the parent study) were included. Of those, 362 (62.5%) initiated breastfeeding or provided breast milk to their infants, with a median duration of breastfeeding of 1.4 months (interquartile range 0.5-6.0). People with HCV viremia , defined as a detectable viral load at any point during pregnancy, were less likely to initiate breastfeeding than those who had an undetectable viral load (59.4 vs 71.9%, adjusted odds ratio [aOR] 0.61, 95% CI, 0.41-0.92). People with private insurance were more likely to initiate breastfeeding compared with those with public insurance or no insurance (80.0 vs 60.1%; aOR 2.43, 95% CI, 1.31-4.50). CONCLUSION: Although HCV seropositivity is not a contraindication to breastfeeding regardless of viral load, rates of breastfeeding initiation were lower among people with HCV viremia than among those with an undetectable viral load. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov , NCT01959321 .

Community-level social determinants of health and pregestational and gestational diabetes.

BACKGROUND: Individual adverse social determinants of health are associated with increased risk of diabetes in pregnancy, but the relative influence of neighborhood or community-level social determinants of health is unknown. OBJECTIVE: This study aimed to determine whether living in neighborhoods with greater socioeconomic disadvantage, food deserts, or less walkability was associated with having pregestational diabetes and developing gestational diabetes. STUDY DESIGN: We conducted a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. Home addresses in the first trimester were geocoded at the census tract level. The exposures (modeled separately) were the following 3 neighborhood-level measures of adverse social determinants of health: (1) socioeconomic disadvantage, defined by the Area Deprivation Index and measured in tertiles from the lowest tertile (ie, least disadvantage [T1]) to the highest (ie, most disadvantage [T3]); (2) food desert, defined by the United States Department of Agriculture Food Access Research Atlas (yes/no by low income and low access criteria); and (3) less walkability, defined by the Environmental Protection Agency National Walkability Index (most walkable score [15.26-20.0] vs less walkable score [<15.26]). Multinomial logistic regression was used to model the odds of gestational diabetes or pregestational diabetes relative to no diabetes as the reference, adjusted for age at delivery, chronic hypertension, Medicaid insurance status, and low household income (<130% of the US poverty level). RESULTS: Among the 9155 assessed individuals, the mean Area Deprivation Index score was 39.0 (interquartile range, 19.0-71.0), 37.0% lived in a food desert, and 41.0% lived in a less walkable neighborhood. The frequency of pregestational and gestational diabetes diagnosis was 1.5% and 4.2%, respectively. Individuals living in a community in the highest tertile of socioeconomic disadvantage had increased odds of entering pregnancy with pregestational diabetes compared with those in the lowest tertile (T3 vs T1: 2.6% vs 0.8%; adjusted odds ratio, 2.52; 95% confidence interval, 1.41-4.48). Individuals living in a food desert (4.8% vs 4.0%; adjusted odds ratio, 1.37; 95% confidence interval, 1.06-1.77) and in a less walkable neighborhood (4.4% vs 3.8%; adjusted odds ratio, 1.33; 95% confidence interval, 1.04-1.71) had increased odds of gestational diabetes. There was no significant association between living in a food desert or a less walkable neighborhood and pregestational diabetes, or between socioeconomic disadvantage and gestational diabetes. CONCLUSION: Nulliparous individuals living in a neighborhood with higher socioeconomic disadvantage were at increased odds of entering pregnancy with pregestational diabetes, and those living in a food desert or a less walkable neighborhood were at increased odds of developing gestational diabetes, after controlling for known covariates.

The effect of a neonatal sleep intervention on maternal postpartum hypertension: a randomized trial.

BACKGROUND: In nonpregnant adults, poor sleep is associated with higher blood pressure. Poor sleep is common in the postpartum period and is often attributed to infant caretaking needs. However, its effects on cardiovascular health in individuals with a hypertensive disorder of pregnancy are unknown. OBJECTIVE: This study aimed to determine the effect of a neonatal sleep intervention on maternal postpartum blood pressure in individuals with a hypertensive disorder of pregnancy. STUDY DESIGN: In this single-institution pilot randomized controlled trial from July 2021 to March 2022, 110 individuals with a hypertensive disorder of pregnancy were randomized to receive a neonatal sleep intervention (SNOO responsive bassinet) plus usual care of safe sleep education (n=54) or usual care alone (n=56). Remote follow-up visits were conducted at 1 week, 6 weeks, and 4 months after delivery and involved blood pressure and weights, sleep and mood questionnaires, and self-reported infant and maternal sleep logs. Based on institutional data, the sample size had 80% power to detect a 4.5-mm Hg difference in the primary outcome of mean arterial pressure at 6 weeks after delivery. RESULTS: Baseline characteristics were similar between the arms. At 1 week after delivery, the intervention arm had lower mean arterial pressure and less antihypertensive medication use than the control arm (99±10 vs 103±7 mm Hg [P=.04] and 23% vs 35% [P=.15], respectively). At 6 weeks after delivery, mean arterial pressure was similar between arms (93±8 vs 94±8 mm Hg; P=.54), but there was a lower rate of antihypertensive use in the intervention arm (15% vs 26%; P=.19). Scores from maternal sleep and mood questionnaires at 6 weeks after delivery and self-reported infant and maternal sleep duration at 6 weeks and 4 months after delivery were similar between arms (P>.05). CONCLUSION: The SNOO responsive bassinet as a neonatal sleep intervention did not result in improved mean arterial pressure at 6 weeks after delivery after hypertensive disorders of pregnancy.

Desirability of outcome ranking for obstetrical trials: illustration and application to the ARRIVE trial.

BACKGROUND: In randomized trials, 1 primary outcome is typically chosen to evaluate the consequences of an intervention, whereas other important outcomes are relegated to secondary outcomes. This issue is amplified for many obstetrical trials in which an intervention may have consequences for both the pregnant person and the child. In contrast, desirability of outcome ranking, a paradigm shift for the design and analysis of clinical trials based on patient-centric evaluation, allows multiple outcomes-including from >1 individual-to be considered concurrently. OBJECTIVE: This study aimed to describe desirability of outcome ranking methodology tailored to obstetrical trials and to apply the methodology to maternal-perinatal paired (dyadic) outcomes in which both individuals may be affected by an intervention but may experience discordant outcomes (eg, an obstetrical intervention may improve perinatal but worsen maternal outcomes). STUDY DESIGN: This secondary analysis applies the desirability of outcome ranking methodology to data from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network ARRIVE trial. The original analysis found no substantial difference in the primary (perinatal composite) outcome, but a decreased risk of the secondary outcome of cesarean delivery with elective induction at 39 weeks. In the present desirability-of-outcome-ranking analysis, dyadic outcomes ranging from spontaneous vaginal delivery without severe neonatal complication (most desirable) to cesarean delivery with perinatal death (least desirable) were classified into 8 categories ranked by overall desirability by experienced investigators. Distributions of the desirability of outcome ranking were compared by estimating the probability of having a more desirable dyadic outcome with elective induction at 39 weeks of gestation than with expectant management. To account for various perspectives on these outcomes, a complementary analysis, called the partial credit strategy, was used to grade outcomes on a 100-point scale and estimate the difference in overall treatment scores between groups using a t test. RESULTS: All 6096 participants from the trial were included. The probability of a better dyadic outcome for a randomly selected patient who was randomized to elective induction was 53% (95% confidence interval, 51-54), implying that elective induction led to a better overall outcome for the dyad when taking multiple outcomes into account concurrently. Furthermore, the desirability-of-outcome-ranking probability of averting cesarean delivery with elective induction was 52% (95% confidence interval, 51-53), which was not at the expense of an operative vaginal delivery or a poorer outcome for the perinate (ie, survival with a severe neonatal complication or perinatal death). Randomization to elective induction was also advantageous in most of the partial credit score scenarios. CONCLUSION: Desirability-of-outcome-ranking methodology is a useful tool for obstetrical trials because it provides a concurrent view of the effect of an intervention on multiple dyadic outcomes, potentially allowing for better translation of data for decision-making and person-centered care.

Social determinants of health and obstetric outcomes: A report and recommendations of the workshop of the Society for Maternal-Fetal Medicine.

This article is a report of a 2-day workshop, entitled "Social determinants of health and obstetric outcomes," held during the Society for Maternal-Fetal Medicine 2022 Annual Pregnancy Meeting. Participants' fields of expertise included obstetrics, pediatrics, epidemiology, health services, health equity, community-based research, and systems biology. The Commonwealth Foundation and the Alliance of Innovation on Maternal Health cosponsored the workshop and the Society for Women's Health Research provided additional support. The workshop included presentations and small group discussions, and its goals were to accomplish the following.

Validation of Three Models for Prediction of Blood Transfusion during Cesarean Delivery Admission.

OBJECTIVE: Prediction of blood transfusion during delivery admission allows for clinical preparedness and risk mitigation. Although prediction models have been developed and adopted into practice, their external validation is limited. We aimed to evaluate the performance of three blood transfusion prediction models in a U.S. cohort of individuals undergoing cesarean delivery. STUDY DESIGN: This was a secondary analysis of a multicenter randomized trial of tranexamic acid for prevention of hemorrhage at time of cesarean delivery. Three models were considered: a categorical risk tool (California Maternal Quality Care Collaborative [CMQCC]) and two regression models (Ahmadzia et al and Albright et al). The primary outcome was intrapartum or postpartum red blood cell transfusion. The CMQCC algorithm was applied to the cohort with frequency of risk category (low, medium, high) and associated transfusion rates reported. For the regression models, the area under the receiver-operating curve (AUC) was calculated and a calibration curve plotted to evaluate each model's capacity to predict receipt of transfusion. The regression model outputs were statistically compared. RESULTS: Of 10,785 analyzed individuals, 3.9% received a red blood cell transfusion during delivery admission. The CMQCC risk tool categorized 1,970 (18.3%) individuals as low risk, 5,259 (48.8%) as medium risk, and 3,556 (33.0%) as high risk with corresponding transfusion rates of 2.1% (95% confidence interval [CI]: 1.5-2.9%), 2.2% (95% CI: 1.8-2.6%), and 7.5% (95% CI: 6.6-8.4%), respectively. The AUC for prediction of blood transfusion using the Ahmadzia and Albright models was 0.78 (95% CI: 0.76-0.81) and 0.79 (95% CI: 0.77-0.82), respectively (p = 0.38 for difference). Calibration curves demonstrated overall agreement between the predicted probability and observed likelihood of blood transfusion. CONCLUSION: Three models were externally validated for prediction of blood transfusion during cesarean delivery admission in this U.S. COHORT: Overall, performance was moderate; model selection should be based on ease of application until a specific model with superior predictive ability is developed. KEY POINTS: · A total of 3.9% of individuals received a blood transfusion during cesarean delivery admission.. · Three models used in clinical practice are externally valid for blood transfusion prediction.. · Institutional model selection should be based on ease of application until further research identifies the optimal approach..

Workplace Productivity Loss and Indirect Costs Associated With Preterm Birth in the United States.

OBJECTIVE: To estimate workplace productivity loss and indirect costs in the year after birth among individuals who deliver preterm in the United States. METHODS: This retrospective, observational cohort study estimated workplace productivity loss and indirect costs for individuals aged 18-55 years with an inpatient delivery between January 1, 2016, and September 30, 2021, using data from the Merative MarketScan Commercial Claims and Encounters database and the Health and Productivity Management database. Workdays lost and costs attributable to medical-related absenteeism, workplace absenteeism (defined as sick leave, leave, recreational leave, Family Medical Leave Act); disability (defined as short-term and long-term disability), and aggregate workplace productivity loss, a combined outcome measure, were compared between propensity-score-matched birth cohorts: preterm birth (before 37 weeks of gestation) and full-term birth (at or after 37 weeks of gestation). Outcomes were also compared between the full-term birth cohort and preterm birth subgroups (before 32 weeks of gestation and before 34 weeks of gestation). Estimations of indirect costs assumed an 8-hour workday. Costs were inflated to December 2021 U.S. dollars. RESULTS: In total, 37,522 individuals were eligible for medical-related absenteeism, 1,028 for workplace absenteeism, 7,880 for disability, and 396 for aggregate workplace productivity loss after propensity score matching. Compared with full-term birth, preterm birth was associated with more workdays lost and costs in the year after childbirth attributable to medical-related absenteeism (differences of 4.2 days and $1,045, P <.001) and disability (differences of 2.8 days and $422, P <.001). Preterm birth was not associated with workplace absenteeism (differences of 1.4 days and $347, P =.787) and aggregate workplace productivity loss (differences of 5.2 days [ P =.080] and $1,021 [ P =.093]). Numerical differences were greater in magnitude and inversely related to gestational age at birth across outcomes. CONCLUSION: Preterm birth was associated with medical-related absenteeism, disability claims, and indirect costs in the year after birth compared with full-term birth.

Cannabis Exposure and Adverse Pregnancy Outcomes Related to Placental Function.

Importance: Cannabis use is increasing among reproductive-age individuals and the risks associated with cannabis exposure during pregnancy remain uncertain. Objective: To evaluate the association between maternal cannabis use and adverse pregnancy outcomes known to be related to placental function. Design, Setting, and Participants: Ancillary analysis of nulliparous individuals treated at 8 US medical centers with stored urine samples and abstracted pregnancy outcome data available. Participants in the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be cohort were recruited from 2010 through 2013; the drug assays and analyses for this ancillary project were completed from June 2020 through April 2023. Exposure: Cannabis exposure was ascertained by urine immunoassay for 11-nor-9-carboxy-Δ9-tetrahydrocannabinol using frozen stored urine samples from study visits during the pregnancy gestational age windows of 6 weeks and 0 days to 13 weeks and 6 days (visit 1); 16 weeks and 0 days to 21 weeks and 6 days (visit 2); and 22 weeks and 0 days to 29 weeks and 6 days (visit 3). Positive results were confirmed with liquid chromatography tandem mass spectrometry. The timing of cannabis exposure was defined as only during the first trimester or ongoing exposure beyond the first trimester. Main Outcome and Measure: The dichotomous primary composite outcome included small-for-gestational-age birth, medically indicated preterm birth, stillbirth, or hypertensive disorders of pregnancy ascertained by medical record abstraction by trained perinatal research staff with adjudication of outcomes by site investigators. Results: Of 10 038 participants, 9257 were eligible for this analysis. Of the 610 participants (6.6%) with cannabis use, 32.4% (n = 197) had cannabis exposure only during the first trimester and 67.6% (n = 413) had ongoing exposure beyond the first trimester. Cannabis exposure was associated with the primary composite outcome (25.9% in the cannabis exposure group vs 17.4% in the no exposure group; adjusted relative risk, 1.27 [95% CI, 1.07-1.49]) in the propensity score-weighted analyses after adjustment for sociodemographic characteristics, body mass index, medical comorbidities, and active nicotine use ascertained via urine cotinine assays. In a 3-category cannabis exposure model (no exposure, exposure only during the first trimester, or ongoing exposure), cannabis use during the first trimester only was not associated with the primary composite outcome; however, ongoing cannabis use was associated with the primary composite outcome (adjusted relative risk, 1.32 [95% CI, 1.09-1.60]). Conclusions and Relevance: In this multicenter cohort, maternal cannabis use ascertained by biological sampling was associated with adverse pregnancy outcomes related to placental dysfunction.