Association between SARS-CoV-2 Infection and Adverse Perinatal Outcomes by Race/Ethnicity in a Large Integrated Health Care System.

OBJECTIVE: Recent studies have reported associations between severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection during pregnancy and adverse perinatal outcomes but the extent to which these associations vary by race/ethnicity remains uncertain. Therefore, we examined how the association between prenatal SARS-CoV-2 infection and adverse perinatal outcomes may be modified by race/ethnicity. STUDY DESIGN: A retrospective cohort study was performed using data on 67,986 pregnant women extracted from the Kaiser Permanente Southern California electronic health records between April 6, 2020, and December 31, 2021. Upon admission to labor and delivery, all women were routinely tested for coronavirus disease 2019 (COVID-19) using real-time reverse-transcriptase polymerase chain reaction test. Adjusted odds ratios (aORs) were used to estimate associations. RESULTS: During the study period, COVID-19 was diagnosed in 4,960 (7%) of singleton pregnancies, with the highest rates observed among Hispanics (9.4%) and non-Hispanic Blacks (6.2%). Compared with non-Hispanic Whites, Hispanics (aOR: 1.12, 95% CI: 1.03, 1.21) with SARS-CoV-2 infection had the highest odds of a pregnancy associated with nonreassuring fetal heart rate tracing. Neonates of all races/ethnicities, except for non-Hispanic Blacks, showed significantly increased odds of SARS-CoV-2 infection, with the highest risk observed among Asians/Pacific Islanders (aOR: 10.88, 95% CI: 1.33, 89.04). Non-Hispanic White mothers who tested positive were admitted to intensive care unit (ICU) at a higher rate at delivery and within 7 days of delivery (aOR: 34.77, 95% CI: 11.3, 107.04; aOR: 26.48, 95% CI: 9.55, 73.46, respectively). Hispanics were also at a significantly higher odds of admission to ICU (aOR: 4.62, 95% CI: 2.69, 7.94; aOR: 4.42, 95% CI: 2.58, 7.56, respectively). Non-Hispanic Black, Hispanic, and Asian/Pacific Islander mothers who tested positive for SARS-CoV-2 prenatally, were at increased risk for preeclampsia/eclampsia, and preterm birth as compared to non-Hispanic White mothers. CONCLUSION: The findings highlight racial/ethnic disparities in the association between SARS-CoV-2 infection and adverse perinatal outcomes. The risk of neonatal SARS-CoV-2 infection was highest for Asian/Pacific Islanders. We also observed a remarkably high risk of ICU admission for non-Hispanic White mothers infected with SARS-CoV-2. KEY POINTS: · Race/ethnicity influences perinatal outcomes in pregnancies impacted by SARS-CoV-2.. · The risk of neonatal SARS-CoV-2 infection was highest for Asian/Pacific Islanders.. · White mothers had a notably high risk of ICU admission at delivery following SARS-CoV-2 infection..

Association of Antepartum and Postpartum Air Pollution Exposure With Postpartum Depression in Southern California.

Importance: Women are especially vulnerable to mental health matters post partum because of biological, emotional, and social changes during this period. However, epidemiologic evidence of an association between air pollution exposure and postpartum depression (PPD) is limited. Objective: To examine the associations between antepartum and postpartum maternal air pollution exposure and PPD. Design, Setting, and Participants: This retrospective cohort study used data from Kaiser Permanente Southern California (KPSC) electronic health records and included women who had singleton live births at KPSC facilities between January 1, 2008, and December 31, 2016. Data were analyzed between January 1 and May 10, 2023. Exposures: Ambient air pollution exposures were assessed based on maternal residential addresses using monthly averages of particulate matter less than or equal to 2.5 µm (PM2.5), particulate matter less than or equal to 10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) from spatial interpolation of monitoring station measurements. Constituents of PM2.5 (sulfate, nitrate, ammonium, organic matter, and black carbon) were obtained from fine-resolution geoscience-derived models based on satellite, ground-based monitor, and chemical transport modeling data. Main Outcomes and Measures: Participants with an Edinburgh Postnatal Depression Scale score of 10 or higher during the 6 months after giving birth were referred to a clinical interview for further assessment and diagnosis. Ascertainment of PPD was defined using a combination of diagnostic codes and prescription medications. Results: The study included 340 679 participants (mean [SD] age, 30.05 [5.81] years), with 25 674 having PPD (7.54%). Increased risks for PPD were observed to be associated with per-IQR increases in antepartum and postpartum exposures to O3 (adjusted odds ratio [AOR], 1.09; 95% CI, 1.06-1.12), PM10 (AOR, 1.02; 95% CI, 1.00-1.04), and PM2.5 (AOR, 1.02; 95% CI, 1. 00-1.03) but not with NO2; PPD risks were mainly associated with PM2.5 organic matter and black carbon. Overall, a higher risk of PPD was associated with O3 during the entire pregnancy and postpartum periods and with PM exposure during the late pregnancy and postpartum periods. Conclusions and Relevance: The study findings suggest that long-term exposure to antepartum and postpartum air pollution was associated with higher PPD risks. Identifying the modifiable environmental risk factors and developing interventions are important public health issues to improve maternal mental health and alleviate the disease burden of PPD.

Analysis of Heat Exposure During Pregnancy and Severe Maternal Morbidity.

Importance: The rate of severe maternal morbidity (SMM) is continuously increasing in the US. Evidence regarding the associations of climate-related exposure, such as environmental heat, with SMM is lacking. Objective: To examine associations between long- and short-term maternal heat exposure and SMM. Design, Setting, and Participants: This retrospective population-based epidemiological cohort study took place at a large integrated health care organization, Kaiser Permanente Southern California, between January 1, 2008, and December 31, 2018. Data were analyzed from February to April 2023. Singleton pregnancies with data on SMM diagnosis status were included. Exposures: Moderate, high, and extreme heat days, defined as daily maximum temperatures exceeding the 75th, 90th, and 95th percentiles of the time series data from May through September 2007 to 2018 in Southern California, respectively. Long-term exposures were measured by the proportions of different heat days during pregnancy and by trimester. Short-term exposures were represented by binary variables of heatwaves with 9 different definitions (combining percentile thresholds with 3 durations; ie, ≥2, ≥3, and ≥4 consecutive days) during the last gestational week. Main Outcomes and Measures: The primary outcome was SMM during delivery hospitalization, measured by 20 subconditions excluding blood transfusion. Discrete-time logistic regression was used to estimate associations with long- and short-term heat exposure. Effect modification by maternal characteristics and green space exposure was examined using interaction terms. Results: There were 3446 SMM cases (0.9%) among 403 602 pregnancies (mean [SD] age, 30.3 [5.7] years). Significant associations were observed with long-term heat exposure during pregnancy and during the third trimester. High exposure (≥80th percentile of the proportions) to extreme heat days during pregnancy and during the third trimester were associated with a 27% (95% CI, 17%-37%; P < .001) and 28% (95% CI, 17%-41%; P < .001) increase in risk of SMM, respectively. Elevated SMM risks were significantly associated with short-term heatwave exposure under all heatwave definitions. The magnitude of associations generally increased from the least severe (HWD1: daily maximum temperature >75th percentile lasting for ≥2 days; odds ratio [OR], 1.32; 95% CI, 1.17-1.48; P < .001) to the most severe heatwave exposure (HWD9: daily maximum temperature >95th percentile lasting for ≥4 days; OR, 2.39; 95% CI, 1.62-3.54; P < .001). Greater associations were observed among mothers with lower educational attainment (OR for high exposure to extreme heat days during pregnancy, 1.43; 95% CI, 1.26-1.63; P < .001) or whose pregnancies started in the cold season (November through April; OR, 1.37; 95% CI, 1.24-1.53; P < .001). Conclusions and Relevance: In this retrospective cohort study, long- and short-term heat exposure during pregnancy was associated with higher risk of SMM. These results might have important implications for SMM prevention, particularly in a changing climate.

Maternal exposure to ambient air pollution mixture and premature rupture of membranes: Evidence from a large cohort in Southern California (2008-2018).

BACKGROUND: There is minimal evidence of relationships between maternal air pollution exposure and spontaneous premature rupture of membranes (SPROM), a critical obstetrical problem that can significantly increase maternal and fetal mortality and morbidity. No prior study has explored the PROM risk related to specific components of particulate matter with aerodynamic diameters of ≤ 2.5 µm (PM2.5). We examined associations between maternal exposure to nitrogen dioxide (NO2), ozone (O3), PM2.5, PM10, and PM2.5 constituents and SPROM. METHODS: A large retrospective cohort study was conducted and included 427,870 singleton live births from Kaiser Permanente Southern California during 2008-2018. Monthly averages of NO2, O3 (8-h daily maximum), PM2.5, and PM10 were measured using empirical Bayesian kriging based on measurements from monitoring stations. Data on PM2.5 sulfate, nitrate, ammonium, organic matter, and black carbon were obtained from a fine-resolution model. A discrete time approach with pooled logistic regressions was used to estimate associations throughout the pregnancy and based on trimesters and gestational months. The quantile-based g-computation models were fitted to examine the effects of 1) the air pollution mixture of four pollutants of interest and 2) the mixture of PM2.5 components. RESULTS: There were 37,857 SPROM cases (8.8%) in our study population. We observed relationships between SPROM and maternal exposure to NO2, O3, and PM2.5. PM2.5 sulfate, nitrate, ammonium, and organic matter were associated with higher SPROM risks in the single-pollutant model. Mixture analyses demonstrated that the overall effects of the air pollution mixture and PM2.5 mixture in this study were mainly driven by O3 and PM2.5 nitrate, respectively. Underweight mothers had a significantly higher risk of SPROM associated with NO2. CONCLUSION: Our findings add to the literature on associations between air pollution exposure and SPROM. This is the first study reporting the impact of PM2.5 constituents on SPROM.

Modeling spatially varying compliance effects of PM2.5 exposure reductions on gestational diabetes mellitus in southern California: Results from electronic health record data of a large pregnancy cohort.

Gestational diabetes mellitus (GDM) is a major pregnancy complication affecting approximately 14.0% of pregnancies around the world. Air pollution exposure, particularly exposure to PM2.5, has become a major environmental issue affecting health, especially for vulnerable pregnant women. Associations between PM2.5 exposure and adverse birth outcomes are generally assumed to be the same throughout a large geographical area. However, the effects of air pollution on health can very spatially in subpopulations. Such spatially varying effects are likely due to a wide range of contextual neighborhood and individual factors that are spatially correlated, including SES, demographics, exposure to housing characteristics and due to different composition of particulate matter from different emission sources. This combination of elevated environmental hazards in conjunction with socioeconomic-based disparities forms what has been described as a "double jeopardy" for marginalized sub-populations. In this manuscript our analysis combines both an examination of spatially varying effects of a) unit-changes in exposure and examines effects of b) changes from current exposure levels down to a fixed compliance level, where compliance levels correspond to the Air Quality Standards (AQS) set by the U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality guideline values. Results suggest that exposure reduction policies should target certain "hotspot" areas where size and effects of potential reductions will reap the greatest rewards in terms of health benefits, such as areas of southeast Los Angeles County which experiences high levels of PM2.5 exposures and consist of individuals who may be particularly vulnerable to the effects of air pollution on the risk of GDM.

Association between urban green space and postpartum depression, and the role of physical activity: a retrospective cohort study in Southern California.

Background: Little research exists regarding the relationships between green space and postpartum depression (PPD). We aimed to investigate the relationships between PPD and green space exposure, and the mediating role of physical activity (PA). Methods: Clinical data were obtained from Kaiser Permanente Southern California electronic health records in 2008-2018. PPD ascertainment was based on both diagnostic codes and prescription medications. Maternal residential green space exposures were assessed using street view-based measures and vegetation types (i.e., street tree, low-lying vegetation, and grass), satellite-based measures [i.e., Normalized Difference Vegetation Index (NDVI), land-cover green space, and tree canopy cover], and proximity to the nearest park. Multilevel logistic regression was applied to estimate the association between green space and PPD. A causal mediation analysis was performed to estimate the proportion mediated by PA during pregnancy in the total effects of green space on PPD. Findings: In total, we included 415,020 participants (30.2 ± 5.8 years) with 43,399 (10.5%) PPD cases. Hispanic mothers accounted for about half of the total population. A reduced risk for PPD was associated with total green space exposure based on street-view measure [500 m buffer, adjusted odds ratio (OR) per interquartile range: 0.98, 95% CI: 0.97-0.99], but not NDVI, land-cover greenness, or proximity to a park. Compared to other types of green space, tree coverage showed stronger protective effects (500 m buffer, OR = 0.98, 95% CI: 0.97-0.99). The proportions of mediation effects attributable to PA during pregnancy ranged from 2.7% to 7.2% across green space indicators. Interpretation: Street view-based green space and tree coverage were associated with a decreased risk of PPD. The observed association was primarily due to increased tree coverage, rather than low-lying vegetation or grass. Increased PA was a plausible pathway linking green space to lower risk for PPD. Funding: National Institute of Environmental Health Sciences (NIEHS; R01ES030353).

The role of extreme heat exposure on premature rupture of membranes in Southern California: A study from a large pregnancy cohort.

BACKGROUND: Significant mortality and morbidity in pregnant women and their offspring are linked to premature rupture of membranes (PROM). Epidemiological evidence for heat-related PROM risk is extremely limited. We investigated associations between acute heatwave exposure and spontaneous PROM. METHODS: We conducted this retrospective cohort study among mothers in Kaiser Permanente Southern California who experienced membrane ruptures during the warm season (May-September) from 2008 to 2018. Twelve definitions of heatwaves with different cut-off percentiles (75th, 90th, 95th, and 98th) and durations (≥ 2, 3, and 4 consecutive days) were developed using the daily maximum heat index, which incorporates both daily maximum temperature and minimum relative humidity in the last gestational week. Cox proportional hazards models were fitted separately for spontaneous PROM, term PROM (TPROM), and preterm PROM (PPROM) with zip codes as the random effect and gestational week as the temporal unit. Effect modification by air pollution (i.e., PM2.5 and NO2), climate adaptation measures (i.e., green space and air conditioning [AC] penetration), sociodemographic factors, and smoking behavior was examined. RESULTS: In total, we included 190,767 subjects with 16,490 (8.6%) spontaneous PROMs. We identified a 9-14% increase in PROM risks associated with less intense heatwaves. Similar patterns as PROM were found for TPROM and PPROM. The heat-related PROM risks were greater among mothers exposed to a higher level of PM2.5 during pregnancy, under 25 years old, with lower education and household income level, and who smoked. Even though climate adaptation factors were not statistically significant effect modifiers, mothers living with lower green space or lower AC penetration were at consistently higher heat-related PROM risks compared to their counterparts. CONCLUSION: Using a rich and high-quality clinical database, we detected harmful heat exposure for spontaneous PROM in preterm and term deliveries. Some subgroups with specific characteristics were more susceptible to heat-related PROM risk.

Postpartum Glucose Tolerance Testing Among Patients With Gestational Diabetes During the Coronavirus Disease 2019 Pandemic.

Introduction The impact of the coronavirus disease (COVID-19) COVID-19 pandemic on the care of pregnant patients with gestational diabetes (GDM) is largely unreported. The objective of this study was to compare the completion of postpartum oral glucose tolerance testing (GTT) prior to and during the COVID-19 pandemic among patients with GDM. Methods This was a retrospective review of patients diagnosed with GDM between April 2019 and March 2021. Medical records of patients diagnosed with GDM prior to and during the pandemic were compared. The primary outcome was the difference in the completion of postpartum GTT prior to and during the COVID-19 pandemic. Completion was defined as testing between four weeks to six months postpartum. Secondary objectives were: 1) to compare maternal and neonatal outcomes prior to and during the pandemic among patients with GDM, and 2) to compare pregnancy characteristics and outcomes by compliance with postpartum GTT. Results There were 185 patients included in the study, of whom 83 (44.9%) delivered prior to the pandemic and 102 (55.1%) delivered during the pandemic. There was no difference in completion of postpartum diabetes testing prior, compared to during the pandemic (27.7% vs 33.3%, p=0.47). Postpartum diagnosis of pre-diabetes and type two diabetes mellitus (T2DM) did not differ between groups (p=0.36 and p=1.00, respectively). Patients who completed postpartum testing were less likely to have preeclampsia with severe features compared to patients who did not (OR 0.08, 95% CI 0.01-0.96, p=0.02). Conclusion Completion of postpartum testing for T2DM remained poor prior to and during the COVID-19 pandemic. These findings underscore the need for the adoption of more accessible methods of postpartum testing for T2DM among patients with GDM.

Examining recent trends in spontaneous and iatrogenic preterm birth across race and ethnicity in a large managed care population.

BACKGROUND: For the past several decades, epidemiological studies originating from the United States have consistently reported increasing rates of preterm birth (PTB). Despite the implementation of several clinical and public health interventions to reduce PTB rates, it remains the leading cause of infant morbidity and mortality in the United States and around the world. OBJECTIVE: This study aimed to examine recent trends in preterm birth and its clinical subtypes by maternal race and ethnicity among singleton births. STUDY DESIGN: Kaiser Permanente Southern California electronic health records for all singleton births between 2009 and 2020 (n=427,698) were used to examine preterm birth trends and their subtypes (spontaneous and iatrogenic preterm births). Data on preterm labor triage extracted from electronic health records using natural language processing were used to define preterm birth subtypes. Maternal race and ethnicity are categorized as non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian or Pacific Islander. Multiple logistic regression was used to quantify the linear trend for preterm birth and its subtypes. Racial and ethnic trends were further examined by considering statistical interactions and stratifications. RESULTS: From 2009 to 2020, the overall preterm birth rate decreased by 9.12% (from 8.04% to 7.31%; P<.001). The rates decreased by 19.29% among non-Hispanic Whites (from 7.23% to 5.83%; P<.001), 6.15% among Hispanics (from 7.82% to 7.34%; P=.036), and 12.60% among non-Hispanic Asian or Pacific Islanders (from 8.90% to 7.78%; P<.001), whereas a nonsignificantly increased preterm birth rate (8.45%) was observed among non-Hispanic Blacks (from 9.91% to 10.75%; P=.103). Between 2009 and 2020, overall spontaneous preterm birth rates decreased by 28.85% (from 5.75% to 4.09%; P<.001). However, overall iatrogenic preterm birth rates increased by 40.45% (from 2.29% to 3.22%; p<.001). Spontaneous preterm birth rates decreased by 34.73% among non-Hispanic Whites (from 5.44% to 3.55%; P<.001), 19.75% among non-Hispanic Blacks (from 6.82% to 5.47%; P<.001), 22.96% among Hispanics (from 5.55% to 4.28%; P<.001), and 28.19% among non-Hispanic Asian or Pacific Islanders (from 6.50% to 4.67%; P<.001). Iatrogenic preterm birth rates increased by 52.42% among non-Hispanic Whites (from 1.88% to 2.61%; P<.001), 107.89% among non-Hispanic Blacks (from 3.18% to 6.13%; P<.001), 46.88% among Hispanics (from 2.29% to 3.26%; P<.001), and 42.21% among non-Hispanic Asian or Pacific Islanders (from 2.45% to 3.44%; P<.001). CONCLUSION: The overall preterm birth rate decreased over time and was driven by a decrease in the spontaneous preterm birth rate. There is racial and ethnic variability in the rates of spontaneous preterm birth and iatrogenic preterm birth. The observed increase in iatrogenic preterm birth among all racial and ethnic groups, especially non-Hispanic Blacks, is disconcerting and needs further investigation.

Identification of Preterm Labor Evaluation Visits and Extraction of Cervical Length Measures from Electronic Health Records Within a Large Integrated Health Care System: Algorithm Development and Validation.

BACKGROUND: Preterm birth (PTB) represents a significant public health problem in the United States and throughout the world. Accurate identification of preterm labor (PTL) evaluation visits is the first step in conducting PTB-related research. OBJECTIVE: We aimed to develop a validated computerized algorithm to identify PTL evaluation visits and extract cervical length (CL) measures from electronic health records (EHRs) within a large integrated health care system. METHODS: We used data extracted from the EHRs at Kaiser Permanente Southern California between 2009 and 2020. First, we identified triage and hospital encounters with fetal fibronectin (fFN) tests, transvaginal ultrasound (TVUS) procedures, PTL medications, or PTL diagnosis codes within 240/7-346/7 gestational weeks. Second, clinical notes associated with triage and hospital encounters within 240/7-346/7 gestational weeks were extracted from EHRs. A computerized algorithm and an automated process were developed and refined by multiple iterations of chart review and adjudication to search the following PTL indicators: fFN tests, TVUS procedures, abdominal pain, uterine contractions, PTL medications, and descriptions of PTL evaluations. An additional process was constructed to extract the CLs from the corresponding clinical notes of these identified PTL evaluation visits. RESULTS: A total of 441,673 live birth pregnancies were identified between 2009 and 2020. Of these, 103,139 pregnancies (23.35%) had documented PTL evaluation visits identified by the computerized algorithm. The trend of pregnancies with PTL evaluation visits slightly decreased from 24.41% (2009) to 17.42% (2020). Of the first 103,139 PTL visits, 19,439 (18.85%) and 44,423 (43.97%) had an fFN test and a TVUS, respectively. The percentage of first PTL visits with an fFN test decreased from 18.06% at 240/7 gestational weeks to 2.32% at 346/7 gestational weeks, and TVUS from 54.67% at 240/7 gestational weeks to 12.05% in 346/7 gestational weeks. The mean (SD) of the CL was 3.66 (0.99) cm with a mean range of 3.61-3.69 cm that remained stable across the study period. Of the pregnancies with PTL evaluation visits, the rate of PTB remained stable over time (20,399, 19.78%). Validation of the computerized algorithms against 100 randomly selected records from these potential PTL visits showed positive predictive values of 97%, 94.44%, 100%, and 96.43% for the PTL evaluation visits, fFN tests, TVUS, and CL, respectively, along with sensitivity values of 100%, 90%, and 90%, and specificity values of 98.8%, 100%, and 98.6% for the fFN test, TVUS, and CL, respectively. CONCLUSIONS: The developed computerized algorithm effectively identified PTL evaluation visits and extracted the corresponding CL measures from the EHRs. Validation against this algorithm achieved a high level of accuracy. This computerized algorithm can be used for conducting PTL- or PTB-related pharmacoepidemiologic studies and patient care reviews.

Comparing IADPSG and NICE Diagnostic Criteria for GDM in Predicting Adverse Pregnancy Outcomes.

OBJECTIVE: To compare the performance of diagnostic criteria for gestational diabetes mellitus (GDM) proposed by the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) with those endorsed by the National Institute for Health and Care Excellence (NICE) in predicting adverse pregnancy outcomes. RESEARCH DESIGN AND METHODS: We performed a secondary data analysis of the Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) study participants in five study centers. Logistic regression analyses were performed, and Akaike information criterion were applied for the comparison of different statistical prediction models. We further analyzed the performance by four racial/ethnic subgroups, namely, Whites, Hispanics, Asians, and Blacks. RESULTS: Among all, IADPSG criteria diagnosed 267 (4.1%) more women with GDM, but predicted primary caesarean section (CS) and large for gestational age (LGA) and neonatal adiposity better than did NICE criteria after adjustment for potential confounders. Among Whites, IADPSG criteria diagnosed 65 (2.5%) more subjects with GDM and predicted LGA and neonatal adiposity better, but predicted hypertensive disorders, primary CS and clinical neonatal hypoglycemia worse. Among Hispanics, the IADPSG criteria diagnosed 203 (12.1%) more with GDM but performed better in predicting hypertensive disorders, LGA, neonatal adiposity, and hyperinsulinemia. Among Asians, the IADPSG criteria diagnosed 34 (2.0%) fewer subjects with GDM but predicted hypertensive disorders better in the unadjusted model. In Blacks, IADPSG criteria diagnosed 34 (10.5%) more women with GDM. CONCLUSIONS: IADPSG criteria appear to be more favorable than NICE for identification of adverse pregnancy outcomes among Hispanic and Asian women, while they are comparable to NICE among White women.

Association between SARS-CoV-2 Infection and Adverse Perinatal Outcomes in a Large Health Maintenance Organization.

OBJECTIVE: This study aimed to examine whether severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection during pregnancy is associated with increased odds of perinatal complications and viral transmission to the infant. STUDY DESIGN: A retrospective cohort study of women who delivered at Kaiser Permanente Southern California hospitals (April 6, 2020-February 28, 2021) was performed using data extracted from electronic health records (EHRs). During this time polymerize chain reaction (PCR)-based tests for SARS-CoV-2 was universally offered to all pregnant women at labor and delivery admission, as well as earlier in the pregnancy, if they were displaying symptoms consistent with SARS-CoV-2 infection or a possible exposure to the virus. Adjusted odds ratio (aOR) was used to estimate the strength of associations between positive test results and adverse perinatal outcomes. RESULTS: Of 35,123 women with a singleton pregnancy, 2,203 (6%) tested positive for SARS-CoV-2 infection with 596 (27%) testing positive during the first or second trimester and 1,607 (73%) during the third trimester. Women testing positive were younger than those who tested negative (29.7 [5.4] vs. 31.1 [5.3] years; mean [standard deviation (SD)]; p < .001). The SARS-CoV-2 infection tended to increase the odds of an abnormal fetal heart rate pattern (aOR: 1.10; 95% confidence interval [CI]: 1.00, 1.21; p = 0.058), spontaneous preterm birth (aOR: 1.28; 95% CI: 1.03, 1.58; p = 0.024), congenital anomalies (aOR: 1.69; 95% CI: 1.15, 2.50; p = 0.008), and maternal intensive care unit admission at delivery (aOR: 7.44; 95% CI: 4.06, 13.62; p < 0.001) but not preeclampsia/eclampsia (aOR: 1.14; 95% CI: 0.98, 1.33; p = 0.080). Eighteen (0.8%) neonates of mothers who tested positive also had a positive SARS-CoV-2 test after 24 hours of birth, but all were asymptomatic during the neonatal period. CONCLUSION: These findings suggest that prenatal SARS-CoV-2 infection increases the odds of some adverse perinatal outcomes. The likelihood of vertical transmission from the mother to the fetus was low (0.3%), suggesting that pregnancy complications resulting from SARS-CoV-2 infection pose more risk to the baby than transplacental viral transmission. KEY POINTS: · SARS-CoV-2 infection is associated with increased odds of adverse perinatal outcomes.. · The odds of specific adverse outcomes were greater when a mother was infected earlier in pregnancy.. · The proportion of vertical transmission from mother to fetus was 0.3%.

Associations of glycemia and lipid levels in pregnancy with dyslipidemia 10-14 years later: The HAPO follow-up study.

AIMS: To examine associations of pregnancy glycemia with future dyslipidemia. METHODS: We analyzed data from Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study participants. We examined associations of gestational diabetes (GDM), sum of fasting, 1-hour, and 2-hour glucose z-scores after 75-g load, insulin sensitivity, and lipid levels at 24-32 weeks' gestation with dyslipidemia 10-14 years postpartum. RESULTS: Among 4,693 women, 14.3% had GDM. At follow-up, mean (SD) age was 41.7 (5.7) years, 32.3% had total cholesterol (TC) ≥ 5.17, 27.2% had HDL cholesterol < 1.29, 22.4% had LDL cholesterol (LDL-C) ≥ 3.36, 10.9% had triglycerides ≥ 1.69 mmol/L, and 2.9% had type 2 diabetes. After covariate adjustment, pregnancy glycemic measures were associated with all follow-up dyslipidemias. After additional adjustment for pregnancy lipids, GDM remained associated with TC ≥ 5.17 mmol/L (odds ratio [95% CI], 1.63 [1.22-2.18]) and LDL-C ≥ 3.36 mmol/L (1.63 [1.20-2.22]), even in the absence of type 2 diabetes development (1.55 [1.15-2.10] and 1.56 [1.13-2.16], respectively). Continuous glycemic measures in pregnancy were significantly associated with all follow-up dyslipidemias, independent of pregnancy lipids and type 2 diabetes. CONCLUSIONS: Pregnancy glycemia was associated with dyslipidemia 10-14 years later, independent of pregnancy lipid levels and in the absence of type 2 diabetes development. Lipid screening after GDM deserves special consideration.

Perinatal outcomes after bariatric surgery.

BACKGROUND: Bariatric surgery is a widely used treatment option for obesity that often provides long-term weight control and health benefits. Although a growing number of women are becoming pregnant after bariatric surgery, only a few population-based studies have assessed the impact thereof on perinatal outcomes. OBJECTIVE: This study aimed to examine the association between bariatric surgery and adverse perinatal outcomes in pregnant women and to examine whether the risk for adverse perinatal outcomes is modified by the postsurgery weight, gestational weight gain, type of bariatric surgery, timing of pregnancy after bariatric surgery, and maternal comorbidities. STUDY DESIGN: A retrospective cohort study was performed with the use of the Bariatric Surgery Registry and hospital inpatient and outpatient physician encounter records. The International Classification of Diseases, Ninth and Tenth Revision codes from hospitalizations during pregnancy and infant birth records were used to ascertain the outcomes of interest. Women eligible for BS who delivered at ≥20 weeks of gestation (n=20,213) at Kaiser Permanente Southern California hospitals (January 1, 2007 to December 31, 2018) were included in the study. Adjusted odds ratios were derived from logistic regression models with inverse probability of treatment weighting to adjust for confounding using propensity scores. RESULTS: Bariatric surgery was associated with a reduction in the risks for gestational diabetes (adjusted odds ratio, 0.60; 95% confidence interval, 0.53-0.69; P<.001), preeclampsia (adjusted odds ratio, 0.53; 95% confidence interval, 0.46-0.61; P<.001), chorioamnionitis (adjusted odds ratio, 0.45; 95% confidence interval, 0.32-0.63; P<.001), cesarean delivery (adjusted odds ratio, 0.65; 95% confidence interval, 0.59-0.72; P<.001), large for gestational age neonate (adjusted odds ratio, 0.23; 95% confidence interval, 0.19-0.29; P<.001), macrosomia (adjusted odds ratio, 0.24; 95% confidence interval, 0.19-0.30; P<.001), and neonatal intensive care unit admission (adjusted odds ratio, 0.70; 95% confidence interval, 0.61-0.81; P<.001). However, bariatric surgery was also associated with a significantly increased risk for small for gestational age neonates (adjusted odds ratio, 2.46; 95% confidence interval, 2.16-2.79; P<.001). The risk for the adverse outcomes is independent of the time interval between the surgery and subsequent pregnancy. CONCLUSION: These data suggest that there are many pregnancy outcome benefits for women with severe obesity who undergo bariatric surgery; however, women who have undergone bariatric surgery before pregnancy should be monitored closely to reduce the risk for small for gestational age neonates and postpartum hemorrhage.

Exposure to air pollutant mixture and gestational diabetes mellitus in Southern California: Results from electronic health record data of a large pregnancy cohort.

BACKGROUND: Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents. OBJECTIVES: To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents. METHODS: Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 µm (PM2.5), <10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery. RESULTS: The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM2.5, PM10, NO2 and PM2.5 constituents. The association was strongest for NO2 [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO2, PM2.5, and PM10, OR = 1.095, 95% CI: 1.082-1.108) and PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO2 (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers. CONCLUSION: This study found that exposure to a mixture of ambient PM2.5, PM10, NO2, and PM2.5 chemical constituents was associated with an increased risk of GDM. NO2 and black carbon PM2.5 contributed most to GDM risk.

Prediction of large-for-gestational age infants in relation to hyperglycemia in pregnancy - A comparison of statistical models.

AIMS: Using data from a large multi-centre cohort, we aimed to create a risk prediction model for large-for-gestational age (LGA) infants, using both logistic regression and naïve Bayes approaches, and compare the utility of these two approaches. METHODS: We have compared the two techniques underpinning machine learning: logistic regression (LR) and naïve Bayes (NB) in terms of their ability to predict large-for-gestational age (LGA) infants. Using data from five centres involved in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, we developed LR and NB models and compared the predictive ability and stability between the models. Models were developed combining the risks of hyperglycaemia (assessed in three forms: IADPSG GDM yes/no, GDM subtype, OGTT z-score quintiles), demographic and clinical variables as potential predictors. RESULTS: The two approaches resulted in similar estimates of LGA risk (intraclass correlation coefficient 0.955, 95% CI 0.952, 0.958) however the AUROC for the LR model was significantly higher (0.698 vs 0.682; p < 0.001). When comparing the three LR models, use of individual OGTT z-score quintiles resulted in statistically higher AUROCs than the other two models. CONCLUSIONS: Logistic regression can be used with confidence to assess the relationship between clinical and biochemical variables and outcome.

Resolving the Gestational Diabetes Diagnosis Conundrum: The Need for a Randomized Controlled Trial of Treatment.

The diagnosis of and criteria for gestational diabetes mellitus (GDM) continue to divide the scientific and medical community, both between and within countries. Many argue for universal adoption of the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria and feel that further clinical trials are unjustified and even unethical. However, there are concerns about the large increase in number of women who would be diagnosed with GDM using these criteria and the subsequent impact on health care resources and the individual. This Perspective reviews the origins of the IADPSG consensus and points out some of its less well-known limitations, particularly with respect to identifying women at risk for an adverse pregnancy outcome. It also questions the clinical and cost-effectiveness data often cited to support the IADPSG glycemic thresholds. We present the argument that adoption of diagnostic criteria defining GDM should be based on response to treatment at different diagnostic thresholds of maternal glycemia. This will likely require an international multicenter trial of treatment.

Role of maternal glucose metabolism in the association between maternal BMI and neonatal size and adiposity.

BACKGROUND/OBJECTIVE: One potential mechanism by which maternal obesity impacts fetal growth is through hyperglycemia below the threshold for gestational diabetes. Data regarding which measures of maternal glucose metabolism mediate this association is sparse. The objectives of this study were to (i) quantify the associations of maternal pre-pregnancy body mass index (BMI) with neonatal size and adiposity and (ii) examine the role of markers of maternal glucose metabolism as mediators in these associations. SUBJECTS/METHODS: This is a secondary analysis of 6,379 mother-infant dyads from the Hyperglycemia and Adverse Pregnancy Outcome cohort. Markers of glucose metabolism, including plasma glucose and c-peptide values, Stumvoll first-phase estimate, modified Matsuda index, and oral disposition index were measured and calculated from an oral glucose tolerance test (OGTT) between 24- and 32-weeks' gestation. We calculated the direct effect of maternal BMI category, measured at the time of the OGTT and regressed to estimate pre-pregnancy BMI, on neonatal (1) birth weight (BW), (2) fat mass (FM), (3) % body fat (BF%), and (4) sum of skinfold thickness (sSFT). We then calculated the indirect effect of BMI category on these measures through markers of glucose metabolism. RESULTS: Maternal BMI category was positively associated with neonatal BW, FM, BF%, and sSFT. Additionally, mothers who were overweight or obese had higher odds of delivering an infant with BW, FM, BF%, or sSFT >90th percentile. Fasting glucose and c-peptide values were the strongest mediators in the linear associations between maternal BMI category and neonatal size and adiposity. CONCLUSIONS: Maternal overweight and obesity were associated with higher odds of neonatal BW and adiposity >90th percentile. Fasting measures of glucose metabolism were the strongest mediators of these associations, suggesting that future studies should investigate whether incorporation of these markers in pregnant women with obesity may improve prediction of neonatal size and adiposity.