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BackgroundStructural racism contributes to racial disparities in adverse perinatal outcomes. We sought to determine if structural racism is associated with adverse outcomes among Black preterm infants postnatally.MethodsObservational cohort study of 13,321 Black birthing people who delivered preterm (gestational age 22-36 weeks) in California in 2011-2017 using a statewide birth cohort database and the American Community Survey. Racial and income segregation was quantified by the Index of Concentration at the Extremes (ICE) scores. Multivariable generalized estimating equations regression models were fit to test the association between ICE scores and adverse postnatal outcomes: frequent acute care visits, readmissions, and pre- and post-discharge death, adjusting for infant and birthing person characteristics and social factors.ResultsBlack birthing people who delivered preterm in the least privileged ICE tertiles were more likely to have infants who experienced frequent acute care visits (crude risk ratio [cRR] 1.3 95% CI 1.2-1.4), readmissions (cRR 1.1 95% CI 1.0-1.2), and post-discharge death (cRR 1.9 95% CI 1.2-3.1) in their first year compared to those in the privileged tertile. Results did not differ significantly after adjusting for infant or birthing person characteristics.ConclusionStructural racism contributes to adverse outcomes for Black preterm infants after hospital discharge.Impact statementStructural racism, measured by racial and income segregation, was associated with adverse postnatal outcomes among Black preterm infants including frequent acute care visits, rehospitalizations, and death after hospital discharge. This study extends our understanding of the impact of structural racism on the health of Black preterm infants beyond the perinatal period and provides reinforcement to the concept of structural racism contributing to racial disparities in poor postnatal outcomes for preterm infants. Identifying structural racism as a primary cause of racial disparities in the postnatal period is necessary to prioritize and implement appropriate structural interventions to improve outcomes.

Background: The objectives of this study were to describe trends in the prevalence of postpartum suicidal behaviors in California, 2013-2018, and to estimate associations between adverse perinatal outcomes and suicidal behaviors. Materials and Methods: We used data from a population-based cohort derived from all birth and fetal death certificates. Records were individually linked to maternal hospital discharge records for the years before and after delivery. We estimated the prevalence of postpartum suicidal ideation and attempt by year. Then, we estimated crude and adjusted associations between adverse perinatal outcomes and these suicidal behaviors. The sample included 2,563,288 records. Results: The prevalence of postpartum suicidal ideation and attempt increased from 2013 to 2018. People with postpartum suicidal behavior were younger, had less education, and were more likely to live in rural areas. A greater proportion of those with postpartum suicidal behavior were Black and publicly insured. Severe maternal morbidity, neonatal intensive care unit admission, and fetal death were associated with greater risk of ideation and attempt. Major structural malformation was not associated with either outcome. Conclusions: The burden of postpartum suicidal behavior has increased over time and is unequally distributed across population subgroups. Adverse perinatal outcomes may help identify individuals that could benefit from additional care during the postpartum period.

ObjectiveDevelop and validate a resiliency score to predict survival and survival without neonatal morbidity in preterm neonates

ImportanceUnderstanding the causes of infant mortality shapes public health, surveillance, and research investments. However, the association of single-locus (mendelian) genetic diseases with infant mortality is poorly understood.ObjectiveTo determine the association of genetic diseases with infant mortality.Design, setting, and participantsThis cohort study was conducted at a large pediatric hospital system in San Diego County (California) and included 546 infants (112 infant deaths [20.5%] and 434 infants [79.5%] with acute illness who survived; age, 0 to 1 year) who underwent diagnostic whole-genome sequencing (WGS) between January 2015 and December 2020. Data analysis was conducted between 2015 and 2022.ExposureInfants underwent WGS either premortem or postmortem with semiautomated phenotyping and diagnostic interpretation.Main outcomes and measuresProportion of infant deaths associated with single-locus genetic diseases.ResultsAmong 112 infant deaths (54 girls [48.2%]; 8 [7.1%] African American or Black, 1 [0.9%] American Indian or Alaska Native, 8 [7.1%] Asian, 48 [42.9%] Hispanic, 1 [0.9%] Native Hawaiian or Pacific Islander, and 34 [30.4%] White infants) in San Diego County between 2015 and 2020, single-locus genetic diseases were the most common identifiable cause of infant mortality, with 47 genetic diseases identified in 46 infants (41%). Thirty-nine (83%) of these diseases had been previously reported to be associated with childhood mortality. Twenty-eight death certificates (62%) for 45 of the 46 infants did not mention a genetic etiology. Treatments that can improve outcomes were available for 14 (30%) of the genetic diseases. In 5 of 7 infants in whom genetic diseases were identified postmortem, death might have been avoided had rapid, diagnostic WGS been performed at time of symptom onset or regional intensive care unit admission.Conclusions and relevanceIn this cohort study of 112 infant deaths, the association of genetic diseases with infant mortality was higher than previously recognized. Strategies to increase neonatal diagnosis of genetic diseases and immediately implement treatment may decrease infant mortality. Additional study is required to explore the generalizability of these findings and measure reduction in infant mortality.

Universal newborn screening (NBS) is a highly successful public health intervention. Archived dried bloodspots (DBS) collected for NBS represent a rich resource for population genomic studies. To fully harness this resource in such studies, DBS must yield high-quality genomic DNA (gDNA) for whole genome sequencing (WGS). In this pilot study, we hypothesized that gDNA of sufficient quality and quantity for WGS could be extracted from archived DBS up to 20 years old without PCR (Polymerase Chain Reaction) amplification. We describe simple methods for gDNA extraction and WGS library preparation from several types of DBS. We tested these methods in DBS from 25 individuals who had previously undergone diagnostic, clinical WGS and 29 randomly selected DBS cards collected for NBS from the California State Biobank. While gDNA from DBS had significantly less yield than from EDTA blood from the same individuals, it was of sufficient quality and quantity for WGS without PCR. All samples DBS yielded WGS that met quality control metrics for high-confidence variant calling. Twenty-eight variants of various types that had been reported clinically in 19 samples were recapitulated in WGS from DBS. There were no significant effects of age or paper type on WGS quality. Archived DBS appear to be a suitable sample type for WGS in population genomic studies.

Background and aimsThe American Academy of Pediatrics describes late preterm infants, born at 34 to 36 completed weeks' gestation, as at-risk for rehospitalization and severe morbidity as compared to term infants. While there are prediction models that focus on specific morbidities, there is limited research on risk prediction for early readmission in late preterm infants. The aim of this study is to derive and validate a model to predict 7-day readmission.MethodsThis is a population-based retrospective cohort study of liveborn infants in California between January 2007 to December 2011. Birth certificates, maintained by California Vital Statistics, were linked to a hospital discharge, emergency department, and ambulatory surgery records maintained by the California Office of Statewide Health Planning and Development. Random forest and logistic regression were used to identify maternal and infant variables of importance, test for association, and develop and validate a predictive model. The predictive model was evaluated for discrimination and calibration.ResultsWe restricted the sample to healthy late preterm infants (n = 122,014), of which 4.1% were readmitted to hospital within 7-day after birth discharge. The random forest model with 24 variables had better predictive ability than the 8 variable logistic model with c-statistic of 0.644 (95% confidence interval 0.629, 0.659) in the validation data set and Brier score of 0.0408. The eight predictors of importance length of stay, delivery method, parity, gestational age, birthweight, race/ethnicity, phototherapy at birth hospitalization, and pre-existing or gestational diabetes were used to drive individual risk scores. The risk stratification had the ability to identify an estimated 19% of infants at greatest risk of readmission.ConclusionsOur 7-day readmission predictive model had moderate performance in differentiating at risk late preterm infants. Future studies might benefit from inclusion of more variables and focus on hospital practices that minimize risk.

ObjectiveLate preterm infants have an increased risk of morbidity relative to term infants. We sought to determine the rate, temporal trend, risk factors, and reasons for 30-day readmission.MethodsThis is a retrospective cohort study of infants born at 34 to 42 weeks' gestation in California between January 1, 2011, and December 31, 2017. Birth certificates maintained by California Vital Statistics were linked to discharge records maintained by the California Office of Statewide Health Planning and Development. Multivariable logistic regression was used to identify risk factors and derive a predictive model.ResultsLate preterm infants represented 4.3% (n = 122 014) of the study cohort (n = 2 824 963), of which 5.9% (n = 7243) were readmitted within 30 days. Compared to term infants, late preterm infants had greater odds of readmission (odds ratio [OR]: 2.34 [95% confidence interval (CI): 2.28-2.40]). The temporal trend indicated increases in all-cause and jaundice-specific readmission infants (P < .001). The common diagnoses at readmission were jaundice (58.9%), infections (10.8%), and respiratory complications (3.5%). In the adjusted model, factors that were associated with greater odds of readmission included assisted vaginal birth, maternal age ≥34 years, diabetes, chorioamnionitis, and primiparity. The model had predictive ability of 60% (c-statistic 0.603 [95% CI: 0.596-0.610]) in late preterm infants who had

IntroductionPrevious studies that used traditional multivariable and sibling matched analyses to investigate interpregnancy interval (IPI) and birth outcomes have reached mixed conclusions about a minimum recommended IPI, raising concerns about confounding. Our objective was to isolate the contribution of interpregnancy interval to the risk for adverse birth outcomes using propensity score matching.MethodsFor this retrospective cohort study, data were drawn from a California Department of Health Care Access and Information database with linked vital records and hospital discharge records (2007-2012). We compared short IPIs of

ObjectiveThe objective was to investigate maternal and pregnancy characteristics associated with neonatal encephalopathy (NE).Study designWe queried an administrative birth cohort from California between 2011 and 2017 to determine the association between each factor and NE with and without hypothermia treatment.ResultsFrom 3 million infants born at 35 or more weeks of gestation, 6,857 cases of NE were identified (2.3 per 1000 births), 888 (13%) received therapeutic hypothermia. Risk factors for NE were stronger among cases receiving hypothermia therapy. Substance-related diagnosis, preexisting diabetes, preeclampsia, and any maternal infection were associated with a two-fold increase in risk. Maternal overweight/obesity, nulliparity, advanced maternal age, depression, gestational diabetes or hypertension, and short or long gestations also predicted NE. Young maternal age, Asian race and Hispanic ethnicity, and cannabis-related diagnosis lowered risk of NE.ConclusionsBy disseminating these results, we encourage further interrogation of these perinatal factors.

ObjectivesAmong childbearing women, insurance coverage determines degree of access to preventive and emergency care for maternal and infant health. Maternal-infant dyads with dual burden of severe maternal morbidity and preterm birth experience high physical and psychological morbidity, and the risk of dual burden varies by insurance type. We examined whether sociodemographic and perinatal risk factors of dual burden differed by insurance type.MethodsWe estimated relative risks of dual burden by maternal sociodemographic and perinatal characteristics in the 2007-2012 California birth cohort dataset stratified by insurance type and compared effects across insurance types using Wald Z-statistics.ResultsDual burden ranged from 0.36% of privately insured births to 0.41% of uninsured births. Obstetric comorbidities, multiple gestation, parity, and birth mode conferred the largest risks across all insurance types, but effect magnitude differed. The adjusted relative risk of dual burden associated with preeclampsia superimposed on preexisting hypertension ranged from 9.1 (95% CI 7.6-10.9) for privately insured to 15.9 (95% CI 9.1-27.6) among uninsured. The adjusted relative risk of dual burden associated with cesarean birth ranged from 3.1 (95% CI 2.7-3.5) for women with Medi-Cal to 5.4 (95% CI 3.5-8.2) for women with other insurance among primiparas, and 7.0 (95% CI 6.0-8.3) to 19.4 (95% CI 10.3-36.3), respectively, among multiparas.ConclusionsRisk factors of dual burden differed by insurance type across sociodemographic and perinatal factors, suggesting that care quality may differ by insurance type. Attention to peripartum care access and care quality provided by insurance type is needed to improve maternal and neonatal health.

BackgroundBirthing people of color are more likely to deliver low birthweight and preterm infants, populations at significant risk of morbidity and mortality. Birthing people of color are also at higher risk for mental health conditions and emergency mental healthcare utilization postpartum. Although this group has been identified as high risk in these contexts, it is not known whether racial and ethnic disparities exist in mental healthcare utilization among birthing people who have delivered preterm.ObjectiveWe sought to determine if racial and ethnic disparities exist in postpartum mental healthcare-associated emergency department visits or hospitalizations for birthing people with preterm infants in a large and diverse population.Study designThis population-based historic cohort study used a sample of Californian live-born infants born between 2011 and 2017 with linked birth certificates and emergency department visit and hospital admission records from the California Statewide Health Planning and Development database. The sample was restricted to preterm infants (

Background The pathogenesis of congenital heart disease (CHD) remains largely unknown, with only a small percentage explained solely by genetic causes. Modifiable environmental risk factors, such as alcohol, are suggested to play an important role in CHD pathogenesis. We sought to evaluate the association between prenatal alcohol exposure and CHD to gain insight into which components of cardiac development may be most vulnerable to the teratogenic effects of alcohol. Methods and Results This was a retrospective analysis of hospital discharge records from the California Office of Statewide Health Planning and Development and linked birth certificate records restricted to singleton, live-born infants from 2005 to 2017. Of the 5 820 961 births included, 16 953 had an alcohol-related International Classification of Diseases, Ninth and Tenth Revisions (ICD-9; ICD-10) code during pregnancy. Log linear regression was used to calculate risk ratios (RR) for CHD among individuals with an alcohol-related ICD-9 and ICD10 code during pregnancy versus those without. Three models were created: (1) unadjusted, (2) adjusted for maternal demographic factors, and (3) adjusted for maternal demographic factors and comorbidities. Maternal alcohol-related code was associated with an increased risk for CHD in all models (RR, 1.33 to 1.84); conotruncal (RR, 1.62 to 2.11) and endocardial cushion (RR, 2.71 to 3.59) defects were individually associated with elevated risk in all models. Conclusions Alcohol-related diagnostic codes in pregnancy were associated with an increased risk of an offspring with a CHD, with a particular risk for endocardial cushion and conotruncal defects. The mechanistic basis for this phenotypic enrichment requires further investigation.

ObjectiveExamine the risk of adverse perinatal outcomes among the United States (US)-born and foreign-born Black women in California.Study designThe study comprised all singleton live births to Black women in California between 2011 and 2017. We defined maternal nativity as US-born or foreign-born. Using Poisson regression, we computed risk ratios (RR) and 95% confidence intervals (CI) for three adverse perinatal outcomes: preterm birth, small for gestational age deliveries, and infant mortality.ResultsRates of adverse perinatal outcomes were significantly higher among US-born Black women. In adjusted models, US-born Black women experienced an increased risk of preterm birth (RR 1.51, 95% CI 1.39, 1.65) and small for gestational age deliveries (RR 1.52, 95% CI 1.41, 1.64), compared to foreign-born Black women.ConclusionsFuture studies should consider experiences of racism across the life course when exploring heterogeneity in the risk of adverse perinatal outcomes by nativity among Black women in the US.

This project examines risk and protective factors for preterm birth (PTB) among Black women in Oakland, California. Women with singleton births in 2011-2017 (n = 6199) were included. Risk and protective factors for PTB and independent risk groups were identified using logistic regression and recursive partitioning. Having less than 3 prenatal care visits was associated with highest PTB risk. Hypertension (preexisting, gestational), previous PTB, and unknown Women, Infant, Children (WIC) program participation were associated with a two-fold increased risk for PTB. Maternal birth outside of the USA and participation in WIC were protective. Broad differences in rates, risks, and protective factors for PTB were observed.

IntroductionOur understanding of the association between coronavirus disease 19 (COVID-19) and preterm or early term birth among racially and ethnically diverse populations and people with chronic medical conditions is limited.MethodsWe determined the association between COVID-19 and preterm (PTB) birth among live births documented by California Vital Statistics birth certificates between July 2020 and January 2021 (n=240,147). We used best obstetric estimate of gestational age to classify births as very preterm (VPTB,

BackgroundCannabis use and cannabis use disorders are increasing in prevalence, including among pregnant women. The objective was to evaluate the association of a cannabis-related diagnosis (CRD) in pregnancy and adverse maternal and infant outcomes.MethodsWe queried an administrative birth cohort of singleton deliveries in California between 2011-2017 linked to maternal and infant hospital discharge records. We classified pregnancies with CRD from International Classification of Disease codes. We identified nicotine and other substance-related diagnoses (SRD) in the same manner. Outcomes of interest included maternal (hypertensive disorders) and infant (prematurity, small for gestational age, NICU admission, major structural malformations) adverse outcomes.ResultsFrom 3,067,069 pregnancies resulting in live births, 29,112 (1.0 %) had a CRD. CRD was associated with an increased risk of all outcomes studied; the strongest risks observed were for very preterm birth (aRR 1.4, 95 % CI 1.3, 1.6) and small for gestational age (aRR 1.4, 95 % CI 1.3, 1.4). When analyzed with or without co-exposure diagnoses, CRD alone conferred increased risk for all outcomes compared to no use. The strongest effects were seen for CRD with other SRD (preterm birth aRR 2.3, 95 % CI 2.2, 2.5; very preterm birth aRR 2.6, 95 % CI 2.3, 3.0; gastrointestinal malformations aRR 2.0, 95 % CI 1.6, 2.6). The findings were generally robust to unmeasured confounding and misclassification analyses.ConclusionsCRD in pregnancy was associated with increased risk of adverse maternal and infant outcomes. Providing education and effective treatment for women with a CRD during prenatal care may improve maternal and infant health.

BackgroundIdentifying preterm infants at risk for mortality or major morbidity traditionally relies on gestational age, birth weight, and other clinical characteristics that offer underwhelming utility. We sought to determine whether a newborn metabolic vulnerability profile at birth can be used to evaluate risk for neonatal mortality and major morbidity in preterm infants.MethodsThis was a population-based retrospective cohort study of preterm infants born between 2005 and 2011 in California. We created a newborn metabolic vulnerability profile wherein maternal/infant characteristics along with routine newborn screening metabolites were evaluated for their association with neonatal mortality or major morbidity.ResultsNine thousand six hundred and thirty-nine (9.2%) preterm infants experienced mortality or at least one complication. Six characteristics and 19 metabolites were included in the final metabolic vulnerability model. The model demonstrated exceptional performance for the composite outcome of mortality or any major morbidity (AUC 0.923 (95% CI: 0.917-0.929). Performance was maintained across mortality and morbidity subgroups (AUCs 0.893-0.979).ConclusionsMetabolites measured as part of routine newborn screening can be used to create a metabolic vulnerability profile. These findings lay the foundation for targeted clinical monitoring and further investigation of biological pathways that may increase the risk of neonatal death or major complications in infants born preterm.ImpactWe built a newborn metabolic vulnerability profile that could identify preterm infants at risk for major morbidity and mortality. Identifying high-risk infants by this method is novel to the field and outperforms models currently in use that rely primarily on infant characteristics. Utilizing the newborn metabolic vulnerability profile for precision clinical monitoring and targeted investigation of etiologic pathways could lead to reductions in the incidence and severity of major morbidities associated with preterm birth.

Objective  The aim of the study is to evaluate the risk of preterm birth (PTB,

BackgroundDespite the disproportionate prevalence of gestational diabetes (GDM) and preterm birth (PTB) and their associated adverse perinatal outcomes among Black women, little is known about PTB among Black women with GDM. Specifically, the relationship between PTB by subtype (defined as indicated PTB and spontaneous PT labor) and severity, GDM, and nativity has not been well characterized. Here we examine the risk of PTB by severity (early

Objective  The aim of this study was to evaluate rates of preterm birth (PTB) and obstetric complication with maternal serum analytes > 2.5 multiples of the median (MoM) by degree of elevation. Study Design  Retrospective cohort study of singleton live-births participating in the California Prenatal Screening Program (2005-2011) examining PTB and obstetric complication for α-fetoprotein (AFP), human chorionic gonadotropin (hCG), unconjugated estriol (uE3), and inhibin A (INH) by analyte subgroup (2.5 to  2.5 MoM confer an increased risk of PTB and, except for uE3, obstetric complication, and risks for each are not uniformly linear. These data can help guide patient counseling and antenatal management.

AimsTo evaluate the clinical utility of first and second trimester prenatal screening biomarkers for early pregnancy prediction of gestational diabetes mellitus (GDM) risk in nulliparous women.MethodsWe conducted a population-based cohort study of nulliparous women participating in the California Prenatal Screening Program from 2009 to 2011 (n = 105,379). GDM was ascertained from hospital discharge records or birth certificates. Models including maternal characteristics and prenatal screening biomarkers were developed and validated. Risk stratification and reclassification were performed to assess clinical utility of the biomarkers.ResultsDecreased levels of first trimester pregnancy-associated plasma protein A (PAPP-A) and increased levels of second trimester unconjugated estriol (uE3) and dimeric inhibin A (INH) were associated with GDM. The addition of PAPP-A only and PAPP-A, uE3, and INH to maternal characteristics resulted in small, yet significant, increases in area under the receiver operating characteristic curve (AUC) (maternal characteristics only: AUC 0.714 (95% CI 0.703-0.724), maternal characteristics + PAPP-A: AUC 0.718 (95% CI 0.707-0.728), maternal characteristics + PAPP-A, uE3, and INH: AUC 0.722 (0.712-0.733)); however, no net improvement in classification was observed.ConclusionsPAPP-A, uE3, and INH have limited clinical utility for prediction of GDM risk in nulliparous women. Utility of other readily accessible clinical biomarkers in predicting GDM risk warrants further investigation.

BACKGROUND The development of congenital heart disease (CHD) is multifactorial with genetic and environmental influences. We sought to determine the relationship between socioeconomic and environmental factors with the incidence of CHD among live-born infants in California and to determine whether maternal comorbidities are in the causal pathway. METHODS AND RESULTS This was a population-based cohort study in California (2007-2012). The primary outcome was having significant CHD. Predictors included socioeconomic status and environmental exposure to pollutants determined by U.S. Census data. A social deprivation index and environmental exposure index was assigned based on neighborhood socioeconomic variables, categorized into 4 quartiles. Quartile 1 was the best with the least exposure to pollutants and social deprivation, and quartile 4 was the worst. Multivariate logistic regression and mediation analyses were performed. Among 2 419 651 live-born infants, the incidence of CHD was 3.2 per 1000 live births. The incidence of CHD was significantly higher among those in quartile 4 compared with quartile 1 (social deprivation index: 0.35% versus 0.29%; odds ratio [OR], 1.31; 95% CI, 1.21-1.41; environmental exposure index: 0.35% versus 0.29%; OR, 1.23; 95% CI, 1.15-1.31) after adjusting for maternal race/ethnicity and age and accounting for the relationship between the 2 primary predictors. Maternal comorbidities explained 13% (95% CI, 10%-20%) of the relationship between social deprivation index and environmental exposure index with the incidence of CHD. CONCLUSIONS Increased social deprivation and exposure to environmental pollutants are associated with the incidence of live-born CHD in California. Maternal comorbidities explain some, but not all, of this relationship. These findings identify targets for social policy initiatives to minimize health disparities.

ObjectiveAutoimmune conditions are associated with an increased risk of adverse pregnancy complications and outcomes, suggesting that pregnancy complications may mediate the excess risk. We performed a causal mediation analysis to quantify the mediated effects of autoimmune conditions on adverse pregnancy outcomes.MethodsWe queried a California birth cohort created from linked birth certificates and hospital discharge summaries. From 2,963,888 births, we identified women with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), psoriasis, and inflammatory bowel disease (IBD). Pregnancy complications included preeclampsia/hypertension, gestational diabetes mellitus, and infection in pregnancy. Adverse pregnancy outcomes were preterm birth, cesarean delivery, and small for gestational age. We performed a mediation analysis to estimate the total effects of each autoimmune condition and adverse pregnancy outcome and the indirect effects through pregnancy complications.ResultsAll 4 autoimmune conditions were associated with preterm birth and cesarean delivery, and RA, SLE, and IBD were associated with offspring that were small for gestational age. The strongest mediator of RA, SLE, and psoriasis was preeclampsia/hypertension, accounting for 20-33% of the excess risk of preterm births and 10-19% of excess cesarean deliveries. Gestational diabetes mellitus and infections generally mediated

Disparities in adverse birth outcomes for Black women continue. Research suggests that societal factors such as structural racism explain more variation in adverse birth outcomes than individual-level factors and societal poverty alone. The Index of Concentration at the Extremes (ICE) measures spatial social polarization by quantifying extremes of deprived and privileged social groups using a single metric and has been shown to partially explain racial disparities in black carbon exposures, mortality, fatal and non-fatal assaults, and adverse birth outcomes such as preterm birth and infant mortality. The objective of this analysis was to assess if local measures of racial and economic segregation as proxies for structural racism are associated and preterm birth and infant mortality experienced by Black women residing in California. California birth cohort files were merged with the American Community Survey by zip code (2011-2012). The ICE was used to quantify privileged and deprived groups (i.e., Black vs. White; high income vs. low income; Black low income vs. White high income) by zip code. ICE scores range from - 1 (deprived) to 1 (privileged). ICE scores were categorized into five quintiles based on sample distributions of these measures: quintile 1 (least privileged)-quintile 5 (most privileged). Generalized linear mixed models were used to test the likelihood that ICE measures were associated with preterm birth or with infant mortality experienced by Black women residing in California. Black women were most likely to reside in zip codes with greater extreme income concentrations, and moderate extreme race and race + income concentrations. Bivariate analysis revealed that greater extreme income, race, and race + income concentrations increased the odds of preterm birth and infant mortality. For example, women residing in least privileged zip codes (quintile 1) were significantly more likely to experience preterm birth (race + income ICE OR = 1.31, 95% CI = 1.72-1.46) and infant mortality (race + income ICE OR = 1.70, 95% CI = 1.17-2.47) compared to women living in the most privileged zip codes (quintile 5). Adjusting for maternal characteristics, income, race, and race + income concentrations remained negatively associated with preterm birth. However, only race and race + income concentrations remained associated with infant mortality. Findings support that ICE is a promising measure of structural racism that can be used to address racial disparities in preterm birth and infant mortality experienced by Black women in California.

ObjectiveInflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia.Study designA sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios.ResultsHigher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia.ConclusionsAmong women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth.

Our objective was to assess the relationship between hyperbilirubinemia with and without kernicterus and metabolic profile at newborn screening. Included were 1,693,658 infants divided into a training or testing subset in a ratio of 3:1. Forty-two metabolites were analyzed using logistic regression (odds ratios (ORs), area under the receiver operating characteristic curve (AUC), 95% confidence intervals (CIs)). Several metabolite patterns remained consistent across gestational age groups for hyperbilirubinemia without kernicterus. Thyroid stimulating hormone (TSH) and C-18:2 were decreased, whereas tyrosine and C-3 were increased in infants across groupings. Increased C-3 was also observed for kernicterus (OR: 3.17; 95% CI: 1.18-8.53). Thirty-one metabolites were associated with hyperbilirubinemia without kernicterus in the training set. Phenylalanine (OR: 1.91; 95% CI: 1.85-1.97), ornithine (OR: 0.76; 95% 0.74-0.77), and isoleucine + leucine (OR: 0.63; 95% CI: 0.61-0.65) were the most strongly associated. This study showed that newborn metabolic function is associated with hyperbilirubinemia with and without kernicterus.

Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007-2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009-2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman's risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

Background: The US still has a high burden of preterm birth (PTB), with important disparities by race/ethnicity and poverty status. There is a large body of literature looking at the impact of pre-pregnancy obesity on PTB, but fewer studies have explored the association between underweight status on PTB, especially with a lens toward health disparities. Furthermore, little is known about how weight, specifically pre-pregnancy underweight status, and socio-economic-demographic factors such as race/ethnicity and insurance status, interact with each other to contribute to risks of PTB. Objectives: The objective of this study was to measure the association between pre-pregnancy underweight and PTB and small for gestational age (SGA) among a large sample of births in the US. Our secondary objective was to see if underweight status and two markers of health disparities – race/ethnicity and insurance status (public vs. other) – on PTB. Study design: We used data from all births in California from 2011 to 2017, which resulted in 3,070,241 singleton births with linked hospital discharge records. We ran regression models to estimate the relative risk of PTB by underweight status, by race/ethnicity, and by poverty (Medi-cal status). We then looked at the interaction between underweight status and race/ethnicity and underweight and poverty on PTB. Results: Black and Asian women were more likely to be underweight (aRR = 1.0, 95% CI: 1.01, 1.1 and aRR = 1.4, 95% CI: 1.4, 1.5, respectively), and Latina women were less likely to be underweight (aRR = 0.7, 95% CI: 0.7, 0.7). Being underweight was associated with increased odds of PTB (aRR = 1.3, 95% CI 1.3–1.3) and, after controlling for underweight, all nonwhite race/ethnic groups had increased odds of PTB compared to white women. In interaction models, the combined effect of being both underweight and Black, Indigenous and People of Color (BIPOC) statistically significantly reduced the relative risk of PTB (aRR = 0.9, 95% CI: 0.8, 0.9) and SGA (aRR = 1.0, 95% CI: 0.9, 1.0). The combined effect of being both underweight and on public insurance increased the relative risk of PTB (aRR = 1.1, 95% CI: 1.1, 1.2) but there was no additional effect of being both underweight and on public insurance on SGA (aRR = 1.0, 95% CI: 1.0, 1.0). Conclusions: We confirm and build upon previous findings that being underweight preconception is associated with increased risk of PTB and SGA – a fact often overlooked in the focus on overweight and adverse birth outcomes. Additionally, our findings suggest that the effect of being underweight on PTB and SGA differs by race/ethnicity and by insurance status, emphasizing that other factors related to inequities in access to health care and poverty are contributing to disparities in PTB. [ABSTRACT FROM AUTHOR]

Background and aims: Stimulant‐related disorders (SRD), or the continued misuse of illicit or prescribed stimulants, during pregnancy can have adverse health effects for mothers and infants. This study aimed to measure prevalence and trends of SRD diagnosis in pregnancy, and associations between SRD diagnosis and adverse maternal and infant health outcomes, among pregnant individuals in California. Design: Retrospective cohort study. Setting: California, USA. Participants: Pregnant individuals from the Study of Outcomes in Mothers and Infants (SOMI) with singleton live births between 2012 and 2020 (n = 3 740 079). Measurements: SRD diagnosis (excluding cocaine) and maternal (gestational diabetes, gestational hypertension [gHTN], severe maternal morbidity [SMM]) and infant (very preterm birth [gestational age <32 weeks], preterm birth [gestational age 32–37 weeks], neonatal intensive care unit [NICU] admission, small for gestational age [SGA]) outcomes were classified using International Classification of Disease (ICD) codes and vital statistics. Risk ratios were estimated with modified Poisson log linear regression that accounted for sibling pregnancies. Covariates included maternal sociodemographic characteristics, mental and physical health problems, nicotine use and co‐occurrence of other diagnosed substance use disorders. Bias analyses were conducted to address unmeasured confounding and exposure misclassification. Findings SRD diagnosis among pregnant individuals increased from 2012 to 2020 (554 to 748 per 100 000 births). SRD diagnosis was associated with an increased risk of SMM (adjusted risk ratio [aRR] = 2.3; 95% confidence interval [CI] = 2.2–2.5), gHTN (aRR = 1.8; 95% CI = 1.7–1.9), very preterm birth (aRR = 2.2, 95% CI = 2.0–2.5), preterm birth (aRR = 2.1, 95% CI = 2.1–2.2) and NICU admission (aRR = 2.0, 95%CI = 1.9–2.0), and a decreased risk of gestational diabetes (aRR = 0.8; 95% CI = 0.8–0.9). SRD diagnosis was not associated with infants born SGA. Findings were generally robust to unmeasured confounding and misclassification of diagnosis. Conclusions: Stimulant‐related disorder diagnosis during pregnancy appears to be associated with an increased risk for select adverse maternal and infant health outcomes including severe maternal morbidity, gestational hypertension, very preterm birth, preterm birth and neonatal intensive care unit admission. [ABSTRACT FROM AUTHOR]

BackgroundPreterm birth (PTB),2 defined as birth at gestational age

BackgroundEnvironmental pollution exposure during pregnancy has been identified as a risk factor for preterm birth. Most studies have evaluated exposures individually and in limited study populations.MethodsWe examined the associations between several environmental exposures, both individually and cumulatively, and risk of preterm birth in Fresno County, California. We also evaluated early (

Objective To develop a pre-pregnancy or first-trimester risk score to identify women at high risk of preterm birth. Study design In this retrospective cohort analysis, the sample was drawn from California singleton livebirths from 2007 to 2012 with linked birth certificate and hospital discharge records. The dataset was divided into a training (2/3 of sample) and a testing (1/3 of sample) set for discovery and validation. Predictive models for preterm birth using pre-pregnancy or first-trimester maternal factors were developed using backward stepwise logistic regression on a training dataset. A risk score for preterm birth was created for each pregnancy using beta-coefficients for each maternal factor remaining in the final multivariable model. Risk score utility was replicated in a testing dataset and by race/ethnicity and payer for prenatal care. Results The sample included 2,339,696 pregnancies divided into training and testing datasets. Twenty-three maternal risk factors were identified including several that were associated with a two or more increased odds of preterm birth (preexisting diabetes, preexisting hypertension, sickle cell anemia, and previous preterm birth). Approximately 40% of women with a risk score ≥ 3.0 in the training and testing samples delivered preterm (40.6% and 40.8%, respectively) compared to 3.1-3.3% of women with a risk score of 0.0 [odds ratio (OR) 13.0, 95% confidence interval (CI) 10.7-15.8, training; OR 12.2, 95% CI 9.4-15.9, testing). Additionally, over 18% of women with a risk score ≥ 3.0 had an adverse outcome other than preterm birth. Conclusion Maternal factors that are identifiable prior to pregnancy or during the first-trimester can be used create a cumulative risk score to identify women at the lowest and highest risk for preterm birth regardless of race/ethnicity or socioeconomic status. Further, we found that this cumulative risk score could also identify women at risk for other adverse outcomes who did not have a preterm birth. The risk score is not an effective screening test, but does identify women at very high risk of a preterm birth.

Background Racial/ethnic and socioeconomic disparities exist in outcomes for children with congenital heart disease. We sought to determine the influence of race/ethnicity and mediating socioeconomic factors on 1-year outcomes for live-born infants with hypoplastic left heart syndrome and dextro-Transposition of the great arteries. Methods and Results The authors performed a population-based cohort study using the California Office of Statewide Health Planning and Development database. Live-born infants without chromosomal anomalies were included. The outcome was a composite measure of mortality or unexpected hospital readmissions within the first year of life defined as >3 (hypoplastic left heart syndrome) or >1 readmissions (dextro-Transposition of the great arteries). Hispanic ethnicity was compared with non-Hispanic white ethnicity. Mediation analyses determined the percent contribution to outcome for each mediator on the pathway between race/ethnicity and outcome. A total of 1796 patients comprised the cohort (n=964 [hypoplastic left heart syndrome], n=832 [dextro-Transposition of the great arteries]) and 1315 were included in the analysis (n=477 non-Hispanic white, n=838 Hispanic). Hispanic ethnicity was associated with a poor outcome (crude odds ratio, 1.72; 95% confidence interval [CI], 1.37-2.17). Higher maternal education (crude odds ratio 0.5; 95% CI , 0.38-0.65) and private insurance (crude odds ratio, 0.65; 95% CI , 0.45-0.71) were protective. In the mediation analysis, maternal education and insurance status explained 33.2% (95% CI , 7-66.4) and 27.6% (95% CI , 6.5-63.1) of the relationship between race/ethnicity and poor outcome, while infant characteristics played a minimal role. Conclusions Socioeconomic factors explain a significant portion of the association between Hispanic ethnicity and poor outcome in neonates with critical congenital heart disease. These findings identify vulnerable populations that would benefit from resources to lessen health disparities.

Background: There is an emerging evidence that pulmonary hypertension is associated with amino acid, carnitine, and thyroid hormone aberrations. We aimed to characterize metabolic profiles measured by the newborn screen (NBS) in infants with persistent pulmonary hypertension of the newborn (PPHN) METHODS: Nested case-control study from population-based database. Cases were infants with ICD-9 code for PPHN receiving mechanical ventilation. Controls receiving mechanical ventilation were matched 2:1 for gestational age, sex, birth weight, parenteral nutrition administration, and age at NBS collection. Infants were divided into derivation and validation datasets. A multivariable logistic regression model was derived from candidate metabolites, and the area under the receiver operator characteristic curve (AUROC) was generated from the validation dataset.Results: We identified 1076 cases and 2152 controls. Four metabolites remained in the final model. Ornithine (OR 0.32, CI 0.26-0.41), tyrosine (OR 0.48, CI 0.40-0.58), and TSH 0.50 (0.45-0.55) were associated with decreased odds of PPHN; phenylalanine was associated with increased odds of PPHN (OR 4.74, CI 3.25-6.90). The AUROC was 0.772 (CI 0.737-0.807).Conclusions: In a large, population-based dataset, infants with PPHN have distinct, early metabolic profiles. These data provide insight into the pathophysiology of PPHN, identifying potential therapeutic targets and novel biomarkers to assess the response.

ObjectiveTo evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia.Study designIncluded were 400 women with singleton deliveries in California in 2009-2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15-20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC).ResultsTwenty-five serum biomarkers along with maternal age 80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822-0.959) training; 0.883 (0.804-0.963) testing).ConclusionTogether with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia.