Preeclampsia Onset, Days to Delivery, and Autism Spectrum Disorders in Offspring: Clinical Birth Cohort Study.

BACKGROUND: Maternal preeclampsia is associated with a risk of autism spectrum disorders (ASD) in offspring. However, it is unknown whether the increased ASD risk associated with preeclampsia is due to preeclampsia onset or clinical management of preeclampsia after onset, as clinical expectant management of preeclampsia allows pregnant women with this complication to remain pregnant for potentially weeks depending on the onset and severity. Identifying the risk associated with preeclampsia onset and exposure provides evidence to support the care of high-risk pregnancies and reduce adverse effects on offspring. OBJECTIVE: This study aimed to fill the knowledge gap by assessing the ASD risk in children associated with the gestational age of preeclampsia onset and the number of days from preeclampsia onset to delivery. METHODS: This retrospective population-based clinical cohort study included 364,588 mother-child pairs of singleton births between 2001 and 2014 in a large integrated health care system in Southern California. Maternal social demographic and pregnancy health data, as well as ASD diagnosis in children by the age of 5 years, were extracted from electronic medical records. Cox regression models were used to assess hazard ratios (HRs) of ASD risk in children associated with gestational age of the first occurrence of preeclampsia and the number of days from first occurrence to delivery. RESULTS: Preeclampsia occurred in 16,205 (4.4%) out of 364,588 pregnancies; among the 16,205 pregnancies, 2727 (16.8%) first occurred at <34 weeks gestation, 4466 (27.6%) first occurred between 34 and 37 weeks, and 9012 (55.6%) first occurred at ≥37 weeks. Median days from preeclampsia onset to delivery were 4 (IQR 2,16) days, 1 (IQR 1,3) day, and 1 (IQR 0,1) day for those first occurring at <34, 34-37, and ≥37 weeks, respectively. Early preeclampsia onset was associated with greater ASD risk (P=.003); HRs were 1.62 (95% CI 1.33-1.98), 1.43 (95% CI 1.20-1.69), and 1.23 (95% CI 1.08-1.41), respectively, for onset at <34, 34-37, and ≥37 weeks, relative to the unexposed group. Within the preeclampsia group, the number of days from preeclampsia onset to delivery was not associated with ASD risk in children; the HR was 0.995 (95% CI 0.986-1.004) after adjusting for gestational age of preeclampsia onset. CONCLUSIONS: Preeclampsia during pregnancy was associated with ASD risk in children, and the risk was greater with earlier onset. However, the number of days from first preeclampsia onset to delivery was not associated with ASD risk in children. Our study suggests that ASD risk in children associated with preeclampsia is not increased by expectant management of preeclampsia in standard clinical practice. Our results emphasize the need to identify effective approaches to preventing the onset of preeclampsia, especially during early pregnancy. Further research is needed to confirm if this finding applies across different populations and clinical settings.

Neighborhood Disadvantage and Autism Spectrum Disorder in a Population With Health Insurance.

Importance: Family socioeconomic status has been associated with autism spectrum disorder (ASD) diagnoses. Less is known regarding the role of neighborhood disadvantage in the United States, particularly when children have similar access to health insurance. Objective: To evaluate the association between neighborhood disadvantage and the diagnosis of ASD and potential effect modification by maternal and child demographic characteristics. Design, Setting, and Participants: This cohort study examined a retrospective birth cohort from Kaiser Permanente Southern California (KPSC), an integrated health care system. Children born in 2001 to 2014 at KPSC were followed up through KPSC membership records. Electronic medical records were used to obtain an ASD diagnosis up to December 31, 2019, or the last follow-up. Data were analyzed from February 2022 to September 2023. Exposure: Socioeconomic disadvantage at the neighborhood level, an index derived from 7 US census tract characteristics using principal component analysis. Main Outcomes and Measures: Clinical ASD diagnosis based on electronic medical records. Associations between neighborhood disadvantage and ASD diagnosis were determined by hazard ratios (HRs) from Cox regression models adjusted for birth year, child sex, maternal age at delivery, parity, severe prepregnancy health conditions, maternal race and ethnicity, and maternal education. Effect modification by maternal race and ethnicity, maternal education, and child sex was assessed. Results: Among 318 372 mothers with singleton deliveries during the study period, 6357 children had ASD diagnoses during follow-up; their median age at diagnosis was 3.53 years (IQR, 2.57-5.34 years). Neighborhood disadvantage was associated with a higher likelihood of ASD diagnosis (HR, 1.07; 95% CI, 1.02-1.11, per IQR = 2.70 increase). Children of mothers from minoritized racial and ethnic groups (African American or Black, Asian or Pacific Islander, Hispanic or Latinx groups) had increased likelihood of ASD diagnosis compared with children of White mothers. There was an interaction between maternal race and ethnicity and neighborhood disadvantage (difference in log-likelihood = 21.88; P < .001 for interaction under χ24); neighborhood disadvantage was only associated with ASD among children of White mothers (HR, 1.17; 95% CI, 1.09-1.26, per IQR = 2.00 increase). Maternal education and child sex did not significantly modify the neighborhood-ASD association. Conclusions and Relevance: In this study, children residing in more disadvantaged neighborhoods at birth had higher likelihood of ASD diagnosis among a population with health insurance. Future research is warranted to investigate the mechanisms behind the neighborhood-related disparities in ASD diagnosis, alongside efforts to provide resources for early intervention and family support in communities with a higher likelihood of ASD.

Maternal obesity and diabetes during pregnancy and early autism screening score at well-child visits in standard clinical practice.

LAY ABSTRACT: Early intervention and treatment can help reduce disability in children diagnosed with autism spectrum disorder. Screening for autism spectrum disorder in young children identifies those at increased likelihood of diagnosis who may need further support. Previous research has reported that exposure to maternal obesity and diabetes during pregnancy is associated with higher likelihood of autism spectrum disorder diagnosis in children. However, little is known about whether these maternal conditions are associated with how very young children score on autism spectrum disorder screening tools. This study examined associations between exposure to maternal obesity and diabetes during pregnancy and offspring scores on the Quantitative Checklist for Autism in Toddlers, an autism spectrum disorder screening questionnaire administered between 18-24 months at well-child visits. A higher score on the Quantitative Checklist for Autism in Toddlers suggests a higher likelihood of autism spectrum disorder; children with scores 3 or greater are referred to developmental pediatricians for evaluation. Our study found that children of mothers with obesity or diabetes during pregnancy had higher scores than children whose mothers did not have these conditions. Associations with maternal obesity and gestational diabetes diagnosed at or before 26 weeks of pregnancy were also present in children who did not have later autism spectrum disorder diagnoses, suggesting that exposure to these conditions during early pregnancy may be associated with a broad range of social and behavioral abilities. Identifying associations between maternal health conditions and early Quantitative Checklist for Autism in Toddlers screening scores could influence future screening and provision of support for children of mothers with these conditions.

Types of diabetes during pregnancy and risk of depression and anxiety in offspring from childhood to young adulthood.

AIMS: To assess maternal pre-existing type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes mellitus (GDM) during pregnancy and risk of depression and anxiety from childhood to young adulthood in offspring. MATERIALS AND METHODS: This birth cohort included singletons born during 1995-2015, followed using electronic medical records through 2020. Cox regression was used to estimate hazard ratio (HR) of depression or anxiety diagnosis during follow-up associated with in-utero exposure to maternal diabetes. RESULTS: Among 439 590 offspring, 29 891 (6.8%) had depression and 51 918 (11.8%) had anxiety. T1D, followed by T2D and GDM requiring antidiabetes medication were associated with risk of depression and anxiety in offspring. Compared with no diabetes during pregnancy, the adjusted HRs (95% confidence interval) of depression in offspring associated with T1D, T2D or GDM requiring medications were 1.44 (1.09-1.91), 1.30 (1.15-1.47) and 1.18 (1.11-1.26) respectively; conversely, HRs were 0.97 (0.82-1.15) for T2D and 0.99 (0.94-1.04) for GDM without medications. The associations with anxiety followed similar patterns. The significant associations were observed for offspring ages 5-12 and >12-18 years and attenuated for 18-25 years. CONCLUSION: These data suggest that the severity of diabetes (T1D vs. T2D requiring medications vs. GDM requiring medications) during pregnancy may increase the vulnerability of offspring for depression or anxiety.

Prenatal air pollution, maternal immune activation, and autism spectrum disorder.

BACKGROUND: Autism Spectrum Disorder (ASD) risk is highly heritable, with potential additional non-genetic factors, such as prenatal exposure to ambient particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and maternal immune activation (MIA) conditions. Because these exposures may share common biological effect pathways, we hypothesized that synergistic associations of prenatal air pollution and MIA-related conditions would increase ASD risk in children. OBJECTIVES: This study examined interactions between MIA-related conditions and prenatal PM2.5 or major PM2.5 components on ASD risk. METHODS: In a population-based pregnancy cohort of children born between 2001 and 2014 in Southern California, 318,751 mother-child pairs were followed through electronic medical records (EMR); 4,559 children were diagnosed with ASD before age 5. Four broad categories of MIA-related conditions were classified, including infection, hypertension, maternal asthma, and autoimmune conditions. Average exposures to PM2.5 and four PM2.5 components, black carbon (BC), organic matter (OM), nitrate (NO3-), and sulfate (SO42-), were estimated at maternal residential addresses during pregnancy. We estimated the ASD risk associated with MIA-related conditions, air pollution, and their interactions, using Cox regression models to adjust for covariates. RESULTS: ASD risk was associated with MIA-related conditions [infection (hazard ratio 1.11; 95% confidence interval 1.05-1.18), hypertension (1.30; 1.19-1.42), maternal asthma (1.22; 1.08-1.38), autoimmune disease (1.19; 1.09-1.30)], with higher pregnancy PM2.5 [1.07; 1.03-1.12 per interquartile (3.73 µg/m3) increase] and with all four PM2.5 components. However, there were no interactions of each category of MIA-related conditions with PM2.5 or its components on either multiplicative or additive scales. CONCLUSIONS: MIA-related conditions and pregnancy PM2.5 were independently associations with ASD risk. There were no statistically significant interactions of MIA conditions and prenatal PM2.5 exposure with ASD risk.

Maternal exposure to aircraft emitted ultrafine particles during pregnancy and likelihood of ASD in children.

BACKGROUND: There is increasing evidence for adverse health effects associated with aircraft-emitted particulate matter (PM) exposures, which are largely in the ultrafine (PM0.1) size fraction, but no previous study has examined neurodevelopmental outcomes. OBJECTIVE: To assess associations between maternal exposure to aircraft ultrafine particles (UFP) during pregnancy and offspring autism spectrum disorder (ASD) diagnosis. METHODS: This large, representative cohort study included 370,723 singletons born in a single healthcare system. Demographic data, maternal health information, and child's ASD diagnosis by age 5 were extracted from electronic medical records. Aircraft exposure estimates for PM0.1 were generated by the University of California Davis/California Institute of Technology Source Oriented Chemical Transport model. Cox proportional hazard models were used to assess associations between maternal exposure to aircraft PM0·1 in pregnancy and ASD diagnosis, controlling for covariates. RESULTS: Over the course of follow-up, 4,554 children (1.4 %) were diagnosed with ASD. Increased risk of ASD was associated with maternal exposure to aircraft PM0.1 [hazard ratio, HR: 1.02, (95 % confidence interval (CI): 1.01-1.03) per IQR = 0.02 µg/m3 increase during pregnancy. Associations were robust to adjustment for total PM0.1 and fine particulate matter (PM2.5), near-roadway air pollution, and other covariates. Noise adjustment modestly attenuated estimates of UFP effects, which remained statistically significant. DISCUSSION: The results strengthen the emerging evidence that maternal particulate matter exposure during pregnancy is associated with offspring ASD diagnosis and identify aircraft-derived PM0.1 as novel targets for further study and potential regulation.

Prenatal exposure to tailpipe and non-tailpipe tracers of particulate matter pollution and autism spectrum disorders.

BACKGROUND: Traffic-related air pollution exposure is associated with increased risk of autism spectrum disorder (ASD). It is unknown whether carbonaceous material from vehicular tailpipe emissions or redox-active non-tailpipe metals, eg. from tire and brake wear, are responsible. We assessed ASD associations with fine particulate matter (PM2.5) tracers of tailpipe (elemental carbon [EC] and organic carbon [OC]) and non-tailpipe (copper [Cu]; iron [Fe] and manganese [Mn]) sources during pregnancy in a large cohort. METHODS: This retrospective cohort study included 318,750 children born in Kaiser Permanente Southern California (KPSC) hospitals during 2001-2014, followed until age 5. ASD cases were identified by ICD codes. Monthly estimates of PM2.5 and PM2.5 constituents EC, OC, Cu, Fe, and Mn with 4 km spatial resolution were obtained from a source-oriented chemical transport model. These exposures and NO2 were assigned to each maternal address during pregnancy, and associations with ASD were assessed using Cox regression models adjusted for covariates. PM constituent effect estimates were adjusted for PM2.5 and NO2 to assess independent effects. To distinguish ASD risk associated with non-tailpipe from tailpipe sources, the associations with Cu, Fe, and Mn were adjusted for EC and OC, and vice versa. RESULTS: There were 4559 children diagnosed with ASD. In single-pollutant models, increased ASD risk was associated with gestational exposures to tracers of both tailpipe and non-tailpipe emissions. The ASD hazard ratios (HRs) per inter-quartile increment of exposure) for EC, OC, Cu, Fe, and Mn were 1.11 (95% CI: 1.06-1.16), 1.09 (95% CI: 1.04-1.15), 1.09 (95% CI: 1.04-1.13), 1.14 (95% CI: 1.09-1.20), and 1.17 (95% CI: 1.12-1.22), respectively. Estimated effects of Cu, Fe, and Mn (reflecting non-tailpipe sources) were largely unchanged in two-pollutant models adjusting for PM2.5, NO2, EC or OC. In contrast, ASD associations with EC and OC were markedly attenuated by adjustment for non-tailpipe sources. CONCLUSION: Results suggest that non-tailpipe emissions may contribute to ASD. Implications are that reducing tailpipe emissions, especially from vehicles with internal combustion engines, may not eliminate ASD associations with traffic-related air pollution.

Associations of Autism Spectrum Disorder with PM2.5 Components: A Comparative Study Using Two Different Exposure Models.

This retrospective cohort study examined associations of autism spectrum disorder (ASD) with prenatal exposure to major fine particulate matter (PM2.5) components estimated using two independent exposure models. The cohort included 318 750 mother-child pairs with singleton deliveries in Kaiser Permanente Southern California hospitals from 2001 to 2014 and followed until age five. ASD cases during follow-up (N = 4559) were identified by ICD codes. Prenatal exposures to PM2.5, elemental (EC) and black carbon (BC), organic matter (OM), nitrate (NO3-), and sulfate (SO42-) were constructed using (i) a source-oriented chemical transport model and (ii) a hybrid model. Exposures were assigned to each maternal address during the entire pregnancy, first, second, and third trimester. In single-pollutant models, ASD was associated with pregnancy-average PM2.5, EC/BC, OM, and SO42- exposures from both exposure models, after adjustment for covariates. The direction of effect estimates was consistent for EC/BC and OM and least consistent for NO3-. EC/BC, OM, and SO42- were generally robust to adjustment for other components and for PM2.5. EC/BC and OM effect estimates were generally larger and more consistent in the first and second trimester and SO42- in the third trimester. Future PM2.5 composition health effect studies might consider using multiple exposure models and a weight of evidence approach when interpreting effect estimates.

Maternal obesity, diabetes, preeclampsia, and asthma during pregnancy and likelihood of autism spectrum disorder with gastrointestinal disturbances in offspring.

LAY ABSTRACT: Autism spectrum disorder is heterogeneous and often accompanied by co-occurring conditions. Previous studies have shown that maternal health conditions during pregnancy including obesity, diabetes, preeclampsia, and asthma were associated with increased likelihood of autism. However, little has been done examining the likelihood associated with autism with co-occurring conditions. This study assessed these maternal health conditions in relationship to autism and gastrointestinal disturbances, a common co-occurring condition in children diagnosed with autism. Data included 308,536 mother-child pairs from one integrated health care system with comprehensive electronic medical records. Among the study cohort, 5,131 (1.7%) children had a diagnosis of autism by age 5. Gastrointestinal disturbances were present in 35.4% of children diagnosed with autism and 25.1% of children without autism diagnoses. Our results showed that each of the four maternal health conditions during pregnancy was associated with increased likelihood of gastrointestinal disturbances, autism without gastrointestinal disturbances, and autism with gastrointestinal disturbances. For all four maternal health conditions, the association was greatest for likelihood of autism with gastrointestinal disturbances. Given that children diagnosed with autism are more likely to have gastrointestinal disturbances and over 80% of gastrointestinal disturbances in this cohort were diagnosed prior to autism diagnosis, this study suggests that there may be common biological pathways between autism and gastrointestinal disturbances impacted by these maternal exposures. Future studies are warranted to assess associations between different exposures and autism with other co-occurring conditions to increase our understanding of autism heterogeneity.

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of Patients with COVID-19 in Southern California.

Rationale: Ecological studies have shown air pollution associations with coronavirus disease (COVID-19) outcomes. However, few cohort studies have been conducted. Objectives: To conduct a cohort study investigating the association between air pollution and COVID-19 severity using individual-level data from the electronic medical record. Methods: This cohort included all individuals who received diagnoses of COVID-19 from Kaiser Permanente Southern California between March 1 and August 31, 2020. One-year and 1-month averaged ambient air pollutant (particulate matter ⩽2.5 µm in aerodynamic diameter [PM2.5], NO2, and O3) exposures before COVID-19 diagnosis were estimated on the basis of residential address history. Outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and ICU admissions within 30 days and mortality within 60 days after COVID-19 diagnosis. Covariates included socioeconomic characteristics and comorbidities. Measurements and Main Results: Among 74,915 individuals (mean age, 42.5 years; 54% women; 66% Hispanic), rates of hospitalization, IRS, ICU admission, and mortality were 6.3%, 2.4%, 1.5%, and 1.5%, respectively. Using multipollutant models adjusted for covariates, 1-year PM2.5 and 1-month NO2 average exposures were associated with COVID-19 severity. The odds ratios associated with a 1-SD increase in 1-year PM2.5 (SD, 1.5 µg/m3) were 1.24 (95% confidence interval [CI], 1.16-1.32) for COVID-19-related hospitalization, 1.33 (95% CI, 1.20-1.47) for IRS, and 1.32 (95% CI, 1.16-1.51) for ICU admission; the corresponding odds ratios associated with 1-month NO2 (SD, 3.3 ppb) were 1.12 (95% CI, 1.06-1.17) for hospitalization, 1.18 (95% CI, 1.10-1.27) for IRS, and 1.21 (95% CI, 1.11-1.33) for ICU admission. The hazard ratios for mortality were 1.14 (95% CI, 1.02-1.27) for 1-year PM2.5 and 1.07 (95% CI, 0.98-1.16) for 1-month NO2. No significant interactions with age, sex or ethnicity were observed. Conclusions: Ambient PM2.5 and NO2 exposures may affect COVID-19 severity and mortality.

Prenatal Exposure to Air Pollution and Autism Spectrum Disorder: Sensitive Windows of Exposure and Sex Differences.

BACKGROUND: Studies have shown that air pollution exposures during pregnancy are associated with an increased risk of autism spectrum disorder (ASD) in children, and the risk appears to be greater for boys. However, studies assessing gestational windows of susceptibility have been mostly limited by trimesters. OBJECTIVE: We identified sensitive windows of exposure to regional air pollution and risk of ASD and examined sex differences in a large birth cohort. METHODS: This population-based retrospective cohort study included 294,937 mother-child pairs with singleton deliveries in Kaiser Permanente Southern California (KPSC) hospitals from 2001 to 2014. Children were followed using electronic medical records until clinical ASD diagnosis, non-KPSC membership, death, or 31 December 2019, whichever came first. Weekly mean fine particulate matter [PM with an aerodynamic diameter of ≤2.5µm (PM2.5)], nitrogen dioxide (NO2), and ozone (O3) pregnancy exposures were estimated using spatiotemporal prediction models. Cox proportional hazard models with distributed lags were used to estimate weekly pollutant exposure associations with ASD risk for the entire cohort, and separately for boys and for girls. Models were adjusted for child sex (for full cohort), maternal race/ethnicity, maternal age at delivery, parity, maternal education, maternal comorbidities, medical center, census tract median household income, birth year, and season. RESULTS: There were 5,694 ASD diagnoses (4,636 boys, 1,058 girls). Sensitive PM2.5 exposure windows associated with ASD were found early in pregnancy, statistically significant throughout the first two trimesters [1-27 wk of gestation, cumulative hazard ratio (HR)=1.14 [95% confidence interval (CI): 1.06, 1.23] per interquartile range (IQR) (7.4-µg/m3) increase]. O3 exposure during 34-37 wk of gestation was associated with increased risk [HR=1.06 (95% CI: 1.01, 1.11) per IQR (17.4 ppb) increase] but with reduced risk during 20-28 wk of gestation [HR=0.93 (95% CI: 0.89, 0.98)]. No associations were observed with NO2. Sex-stratified early gestational PM2.5 associations were stronger among boys [boys HR=1.16 (95% CI: 1.08, 1.26); girls HR=1.06 (95% CI: 0.89, 1.26)]. O3 associations in later gestation were observed only in boys [boys HR=1.10 (95% CI: 1.04, 1.16); girls HR=0.94 (95% CI: 0.84, 1.05)]. CONCLUSIONS: Exposures to PM2.5 in the first two gestational trimesters were associated with increased ASD risk in children, with stronger associations observed for boys. The role of O3 exposure on ASD risk merits further investigation. https://doi.org/10.1289/EHP9509.

Ambient air pollution and COVID-19 incidence during four 2020-2021 case surges.

BACKGROUND: Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. OBJECTIVE: To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. METHODS: The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM2.5, NO2, and O3) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020-5/31/2020, 6/1/202-9/30/2020, 10/1/2020-12/31/2020, and 1/1/2021-2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. RESULTS: The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM2.5, NO2, and O3 were 1.11 (1.04, 1.18) per 2.3 µg/m3,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 µg/m3 for PM2.5, 1.09 (1.01, 1.17) per 6.0 ppb for NO2 and 0.96 (0.85, 1.08) per 12.0 ppb for O3. CONCLUSION: Long-term PM2.5 and NO2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM2.5 and NO2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.

In utero exposure to near-roadway air pollution and autism spectrum disorder in children.

IMPORTANCE: Previous studies have reported associations between in utero exposure to regional air pollution and autism spectrum disorders (ASD). In utero exposure to components of near-roadway air pollution (NRAP) has been linked to adverse neurodevelopment in animal models, but few studies have investigated NRAP association with ASD risk. OBJECTIVE: To identify ASD risk associated with in utero exposure to NRAP in a large, representative birth cohort. DESIGN, SETTING, AND PARTICIPANTS: This retrospective pregnancy cohort study included 314,391 mother-child pairs of singletons born between 2001 and 2014 at Kaiser Permanente Southern California (KPSC) hospitals. Maternal and child data were extracted from KPSC electronic medical records. Children were followed until: clinical diagnosis of ASD, non-KPSC membership, death, or December 31, 2019, whichever came first. Exposure to the complex NRAP mixture during pregnancy was assessed using line-source dispersion models to estimate fresh vehicle emissions from freeway and non-freeway sources at maternal addresses during pregnancy. Vehicular traffic load exposure was characterized using advanced telematic models combining traditional traffic counts and travel-demand models with cell phone and vehicle GPS data. Cox proportional-hazard models estimated hazard ratios (HR) of ASD associated with near-roadway traffic load and dispersion-modeled NRAP during pregnancy, adjusted for covariates. Non-freeway NRAP was analyzed using quintile distribution due to nonlinear associations with ASD. EXPOSURES: Average NRAP and traffic load exposure during pregnancy at maternal residential addresses. MAIN OUTCOMES: Clinical diagnosis of ASD. RESULTS: A total of 6,291 children (5,114 boys, 1,177 girls) were diagnosed with ASD. The risk of ASD was associated with pregnancy-average exposure to total NRAP [HR(95% CI): 1.03(1.00,1.05) per 5 ppb increase in dispersion-modeled NOx] and to non-freeway NRAP [HR(95% CI) comparing the highest to the lowest quintile: 1.19(1.11, 1.27)]. Total NRAP had a stronger association in boys than in girls, but the association with non-freeway NRAP did not differ by sex. The association of freeway NRAP with ASD risk was not statistically significant. Non-freeway traffic load exposure demonstrated associations with ASD consistent with those of NRAP and ASD. CONCLUSIONS: In utero exposure to near-roadway air pollution, particularly from non-freeway sources, may increase ASD risk in children.

Near-roadway air pollution associated with COVID-19 severity and mortality - Multiethnic cohort study in Southern California.

BACKGROUND: Air pollution exposure has been associated with increased risk of COVID-19 incidence and mortality by ecological analyses. Few studies have investigated the specific effect of traffic-related air pollution on COVID-19 severity. OBJECTIVE: To investigate the associations of near-roadway air pollution (NRAP) exposure with COVID-19 severity and mortality using individual-level exposure and outcome data. METHODS: The retrospective cohort includes 75,010 individuals (mean age 42.5 years, 54% female, 66% Hispanic) diagnosed with COVID-19 at Kaiser Permanente Southern California between 3/1/2020-8/31/2020. NRAP exposures from both freeways and non-freeways during 1-year prior to the COVID-19 diagnosis date were estimated based on residential address history using the CALINE4 line source dispersion model. Primary outcomes include COVID-19 severity defined as COVID-19-related hospitalizations, intensive respiratory support (IRS), intensive care unit (ICU) admissions within 30 days, and mortality within 60 days after COVID-19 diagnosis. Covariates including socio-characteristics and comorbidities were adjusted for in the analysis. RESULT: One standard deviation (SD) increase in 1-year-averaged non-freeway NRAP (0.5 ppb NOx) was associated with increased odds of COVID-19-related IRS and ICU admission [OR (95% CI): 1.07 (1.01, 1.13) and 1.11 (1.04, 1.19) respectively] and increased risk of mortality (HR = 1.10, 95% CI = 1.03, 1.18). The associations of non-freeway NRAP with COVID-19 outcomes were largely independent of the effect of regional fine particulate matter and nitrogen dioxide exposures. These associations were generally consistent across age, sex, and race/ethnicity subgroups. The associations of freeway and total NRAP with COVID-19 severity and mortality were not statistically significant. CONCLUSIONS: Data from this multiethnic cohort suggested that NRAP, particularly non-freeway exposure in Southern California, may be associated with increased risk of COVID-19 severity and mortality among COVID-19 infected patients. Future studies are needed to assess the impact of emerging COVID-19 variants and chemical components from freeway and non-freeway NRAP.

Asthma Disease Status, COPD, and COVID-19 Severity in a Large Multiethnic Population.

BACKGROUND: Current studies of asthma history on coronavirus disease 2019 (COVID-19) outcomes are limited and lack consideration of disease status. OBJECTIVE: To conduct a population-based study to assess asthma disease status and chronic obstructive pulmonary disease (COPD) in relation to COVID-19 severity. METHODS: Patients diagnosed with COVID-19 (n = 61,338) in a large, diverse integrated health care system were identified. Asthma/COPD history, medication use, and covariates were extracted from electronic medical records. Asthma patients were categorized into those with and without clinical visits for asthma 12 or fewer months prior to COVID-19 diagnosis and labeled as active and inactive asthma, respectively. Primary outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and intensive care unit admissions within 30 days, and mortality within 60 days after COVID-19 diagnosis. Logistic and Cox regression were used to relate COVID-19 outcomes to asthma/COPD history. RESULTS: The cohort was 53.9% female and 66% Hispanic and had a mean age of 43.9 years. Patients with active asthma had increased odds of hospitalization, IRS, and intensive care unit admission (odds ratio 1.47-1.66; P < .05) compared with patients without asthma or COPD. No increased risks were observed for patients with inactive asthma. Chronic obstructive pulmonary disease was associated with increased risks of hospitalization, IRS, and mortality (odds ratio and hazard ratio 1.27-1.67; P < .05). Among active asthma patients, those using asthma medications had greater than 25% lower odds for COVID-19 outcomes than those without medication. CONCLUSIONS: Patients with asthma who required clinical care 12 or fewer months prior to COVID-19 or individuals with COPD history are at increased risk for severe COVID-19 outcomes. Proper medication treatment for asthma may lower this risk.

Liver Fat Reduction After Gastric Banding and Associations with Changes in Insulin Sensitivity and ß-Cell Function.

OBJECTIVE: The aim of this study was to examine the relationship between changes in liver fat and changes in insulin sensitivity and ß-cell function 2 years after gastric banding surgery. METHODS: Data included 23 adults with the surgery who had prediabetes or type 2 diabetes for less than 1 year and BMI 30 to 40 kg/m2 at baseline. Body adiposity measures including liver fat content (LFC), insulin sensitivity (M/I), and ß-cell responses (acute, steady-state, and arginine-stimulated maximum C-peptide) were assessed at baseline and 2 years after surgery. Regression models were used to assess associations adjusted for age and sex. RESULTS: Two years after surgery, all measures of body adiposity, LFC, fasting and 2-hour glucose, and hemoglobin A1c significantly decreased; M/I significantly increased; and ß-cell responses adjusted for M/I did not change significantly. Among adiposity measures, reduction in LFC had the strongest association with M/I increase (r = -0.61, P = 0.003). Among ß-cell measures, change in LFC was associated with change in acute C-peptide response to arginine at maximal glycemic potentiation adjusted for M/I (r = 0.66, P = 0.007). Significant reductions in glycemic measures and increase in M/I were observed in individuals with LFC loss >2.5%. CONCLUSIONS: Reduction in LFC after gastric banding surgery appears to be an important factor associated with long-term improvements in insulin sensitivity and glycemic profiles in adults with obesity and prediabetes or early type 2 diabetes.

Types of diabetes during pregnancy and longitudinal BMI in offspring from birth to age 10 years.

OBJECTIVE: To examine longitudinal BMI trajectory from birth to age 10 years in a clinical cohort after exposure to maternal pre-existing type 1 (T1D), type 2 (T2D), gestational diabetes managed with or without anti-diabetes medication, and no diabetes during pregnancy. METHODS: Data included 218 227 singleton children born in 2008-2015 from a population-based integrated healthcare system; 537 exposed to maternal T1D, 7836 to T2D, 6982 to medicated GDM and 12 576 to unmedicated GDM. Differences in BMI over time among groups were assessed by non-linear mixed-effects models adjusting for covariates. RESULTS: Children's BMI was significantly lower 6-months after birth for all diabetes exposed groups compared to no diabetes. Beginning at approximately age 2.5 years, BMI was significantly higher for T1D, T2D and medicated GDM groups compared to the no diabetes group. At age 3, the growth pattern started separating with highest BMI in T1D and T2D groups, followed by medicated GDM, unmedicated GDM, and the no diabetes groups. By age 7, BMI was significantly higher for the unmedicated GDM group compared to the no diabetes group. Adjusted BMI was generally comparable between T1D and T2D groups for all ages. Starting at age 5, T1D, T2D and medicated GDM groups had BMI greater than one SD over the BMI in the no diabetes group. CONCLUSION: In a clinical cohort with standard diabetes management approaches, a hierarchical BMI growth pattern exists in offspring exposed to different types of diabetes during pregnancy after adjusting for important covariates, starting as early as age 3 years.

Human Serum Albumin Cys34 Adducts in Newborn Dried Blood Spots: Associations With Air Pollution Exposure During Pregnancy.

Background: Increasing evidence suggests that exposure to air pollution during pregnancy is associated with adverse pregnancy outcomes. However, biomarkers associated with air pollution exposure are widely lacking and often transient. In addition, ascertaining biospecimens during pregnacy to assess the prenatal environment remains largely infeasible. Objectives: To address these challenges, we investigated relationships between air pollution exposure during pregnancy and human serum albumin Cys34 (HSA-Cys34) adducts in newborn dried blood spots (DBS) samples, which captures an integration of perinatal exposures to small reactive molecules in circulating blood. Methods: Newborn DBS were obtained from a state archive for a cohort of 120 children born at one Kaiser Permanente Southern California (KPSC) hospitals in 2007. These children were selected to maximize the range of residential air pollution exposure during the entire pregnancy to PM2.5, PM10, NO2, O3, based on monthly estimates interpolated from regulatory monitoring sites. HSA-Cys34 adducts were selected based on previously reported relationships with air pollution exposure and oxidative stress. Results: Six adducts measured in newborn DBS samples were associated with air pollution exposures during pregnancy; these included direct oxidation products, adducts formed with small thiol compounds, and adducts formed with reactive aldehydes. Two general trends were identified: Exposure to air pollution late in pregnancy (i.e., in the last 30 days) was associated with increased oxidative stress, and exposure to air pollution earlier in pregnancy (i.e., not in the last 30 days) was associated with decreased oxidative stress around the time of birth. Discussion: Air pollution exposure occurring during pregnancy can alter biology and leave measurable impacts on the developing infant captured in the newborn DBS adductome, which represents a promising tool for investigating adverse birth outcomes in population-based studies.

Maternal Gestational Diabetes and Type 2 Diabetes During Pregnancy and Risk of Childhood Asthma in Offspring.

OBJECTIVE: To examine maternal preexisting type 2 diabetes (T2D) and gestational diabetes mellitus (GDM) on risk of childhood asthma. STUDY DESIGN: This retrospective birth cohort study included 97 554 singletons born in 2007-2011 within hospitals from a single integrated healthcare system. Children were prospectively followed from age 5 until December 31, 2017, using electronic medical records. Relative risks of childhood asthma associated with maternal diabetes in utero were estimated by hazard ratios using Cox regression adjusting for potential confounders. RESULTS: There were 3119 children (3.2%) who were exposed to preexisting T2D and 9836 (10.1%) to GDM. Among mothers with GDM, 3380 (34.4%) were dispensed antidiabetic medication during pregnancy. During a median of 7.6 years (IQR, 6.3-9.0 years) after birth, 15 125 children (15.5%) were diagnosed with asthma after age 5. Maternal diabetes interacted with maternal asthma history to affect child's asthma risk (P = .05). Among children without maternal asthma (n = 89 487), the adjusted hazard ratios for childhood asthma were 1.21 (95% CI, 1.08-1.36; P < .001) for exposure to T2D, 1.12 (95% CI, 1.01-1.25; P = .04) for GDM requiring antidiabetic medications, and 1.01 (95% CI, 0.93-1.10; P = .82) for GDM not requiring medications compared with no diabetes during pregnancy. The corresponding hazard ratios were 1.53 (95% CI, 1.19-1.96; P < .001), 1.11 (95% CI, 0.65-1.46; P = .44), and 0.84 (95% CI, 0.66-1.08; P = .17) among children without maternal asthma (n = 8067). Gestational age at GDM diagnosis was not associated with childhood asthma (P = .27). CONCLUSIONS: The risk of childhood asthma was predominately observed for exposure to preexisting T2D, small for GDM requiring medication, and not increased for GDM not requiring medication during pregnancy, compared with no diabetes during pregnancy.