Increased Risk of Gestational Hypertension by Periconceptional Exposure to Ambient Air Pollution and Effect Modification by Prenatal Depression.

BACKGROUND: Air pollution has been associated with gestational hypertension (GH) and preeclampsia, but susceptible windows of exposure and potential vulnerability by comorbidities, such as prenatal depression, remain unclear. METHODS: We ascertained GH and preeclampsia cases in a prospective pregnancy cohort in Los Angeles, CA. Daily levels of ambient particulate matters (with a diameter of ≤10 µm [PM10] or ≤2.5 µm [PM2.5]), nitrogen dioxide, and ozone were averaged for each week from 12 weeks preconception to 20 gestational weeks. We used distributed lag models to identify susceptible exposure windows, adjusting for potential confounders. Analyses were additionally stratified by probable prenatal depression to explore population vulnerability. RESULTS: Among 619 participants, 60 developed preeclampsia and 42 developed GH. We identified a susceptible window for exposure to PM2.5 from 1 week preconception to 11 weeks postconception: higher exposure (5 µg/m3) within this window was associated with an average of 8% (95% CI, 1%-15%) higher risk of GH. Among participants with probable prenatal depression (n=179; 32%), overlapping sensitive windows were observed for all pollutants from 8 weeks before to 10 weeks postconception with increased risk of GH (PM2.5, 16% [95% CI, 3%-31%]; PM10, 39% [95% CI, 13%-72%]; nitrogen dioxide, 65% [95% CI, 17%-134%]; and ozone, 45% [95% CI, 9%-93%]), while the associations were close to null among those without prenatal depression. Air pollutants were not associated with preeclampsia in any analyses. CONCLUSIONS: We identified periconception through early pregnancy as a susceptible window of air pollution exposure with an increased risk of GH. Prenatal depression increases vulnerability to air pollution exposure and GH.

Prenatal air pollution exposure is associated with inflammatory, cardiovascular, and metabolic biomarkers in mothers and newborns.

BACKGROUND: Prenatal air pollution exposure has been associated with individual inflammatory, cardiovascular, and metabolic biomarkers in mothers and neonates. However, studies of air pollution and a comprehensive panel of biomarkers across maternal and cord blood samples remain limited. Few studies used data-driven methods to identify biomarker groupings that converge biomarkers from multiple biological pathways. This study aims to investigate the impacts of prenatal air pollution on groups of biomarkers in maternal and cord blood samples. METHODS: In the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort, 87 biomarkers were quantified from 45 trimester 1 maternal blood and 55 cord blood samples. Pregnancy and trimester 1-averaged concentrations of particulate matter ≤2.5 µm and ≤10 µm in diameter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated, using inverse distance squared weighted spatial interpolation from regulatory air monitoring stations. Traffic-related NOx was assessed using California Line Source Dispersion Model: freeway/highway roads, non-freeway major roads, non-freeway minor roads, and their sum as total NOx. Elastic Net (EN) regression within the rexposome R package was used to group biomarkers and assess their associations with air pollution. RESULTS: In maternal samples, trimester 1-averaged PM10 was associated with elevated inflammation biomarkers and lowered cardiovascular biomarkers. NO2 exhibited positive associations with cardiovascular and inflammation markers. O3 was inversely associated with inflammation, metabolic, and cardiovascular biomarkers. In cord blood, pregnancy-averaged PM2.5 was associated with higher cardiovascular biomarkers and lower metabolic biomarkers. PM10 was associated with lower inflammation and higher cardiovascular biomarkers. Total and major road NOx was associated with lower cardiovascular biomarkers. CONCLUSION: Prenatal air pollution exposure was associated with changes in biomarkers related to inflammation, cardiovascular, metabolic, cancer, and neurological function in both mothers and neonates. This study shed light on mechanisms by which air pollution can influence biological function during pregnancy.

Preconceptional and prenatal exposure to air pollutants and risk of gestational diabetes in the MADRES prospective pregnancy cohort study.

Background: Air pollution has been associated with gestational diabetes mellitus (GDM). We aim to investigate susceptible windows of air pollution exposure and factors determining population vulnerability. Methods: We ascertained GDM status in the prospective Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) pregnancy cohort from Los Angeles, California, USA. We calculated the relative risk of GDM by exposure to ambient particulate matter (PM10; PM2.5), nitrogen dioxide (NO2), and ozone (O3) in each week from 12 weeks before to 24 weeks after conception, adjusting for potential confounders, with distributed lag models to identify susceptible exposure windows. We examined effect modification by prenatal depression, median-split pre-pregnancy BMI (ppBMI) and age. Findings: Sixty (9.7%) participants were diagnosed with GDM among 617 participants (mean age: 28.2 years, SD: 5.9; 78.6% Hispanic, 11.8% non-Hispanic Black). GDM risk increased with exposure to PM2.5, PM10, and NO2 in a periconceptional window ranging from 5 weeks before to 5 weeks after conception: interquartile-range increases in PM2.5, PM10, and NO2 during this window were associated with increased GDM risk by 5.7% (95% CI: 4.6-6.8), 8.9% (8.1-9.6), and 15.0% (13.9-16.2), respectively. These sensitive windows generally widened, with greater effects, among those with prenatal depression, with age ≥28 years, or with ppBMI ≥27.5 kg/m2, than their counterparts. Interpretation: Preconception and early-pregnancy are susceptible windows of air pollutants exposure that increased GDM risk. Prenatal depression, higher age, or higher ppBMI may increase one's vulnerability to air pollution-associated GDM risk. Funding: National Institutes of Health, Environmental Protection Agency.

Prenatal ambient air pollution exposure and child weight trajectories from the 3rd trimester of pregnancy to 2 years of age: a cohort study.

BACKGROUND: Prenatal air pollution exposure may increase risk for childhood obesity. However, few studies have evaluated in utero growth measures and infant weight trajectories. This study will evaluate the associations of prenatal exposure to ambient air pollutants with weight trajectories from the 3rd trimester through age 2 years. METHODS: We studied 490 pregnant women who were recruited from the Maternal and Development Risks from Environmental and Social Stressors (MADRES) cohort, which comprises a low-income, primarily Hispanic population in Los Angeles, California. Nitrogen dioxide (NO2), particulate matter < 10 µm (PM10), particulate matter < 2.5 µm (PM2.5), and ozone (O3) concentrations during pregnancy were estimated from regulatory air monitoring stations. Fetal weight was estimated from maternal ultrasound records. Infant/child weight measurements were extracted from medical records or measured during follow-up visits. Piecewise spline models were used to assess the effect of air pollutants on weight, overall growth, and growth during each period. RESULTS: The mean (SD) prenatal exposure concentrations for NO2, PM2.5, PM10, and O3 were 16.4 (2.9) ppb, 12.0 (1.1) µg/m3, 28.5 (4.7) µg/m3, and 26.2 (2.9) ppb, respectively. Comparing an increase in prenatal average air pollutants from the 10th to the 90th percentile, the growth rate from the 3rd trimester to age 3 months was significantly increased (1.55% [95%CI 1.20%, 1.99%] for PM2.5 and 1.64% [95%CI 1.27%, 2.13%] for NO2), the growth rate from age 6 months to age 2 years was significantly decreased (0.90% [95%CI 0.82%, 1.00%] for NO2), and the attained weight at age 2 years was significantly lower (- 7.50% [95% CI - 13.57%, - 1.02%] for PM10 and - 7.00% [95% CI - 11.86%, - 1.88%] for NO2). CONCLUSIONS: Prenatal ambient air pollution was associated with variable changes in growth rate and attained weight from the 3rd trimester to age 2 years. These results suggest continued public health benefits of reducing ambient air pollution levels, particularly in marginalized populations.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis.

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 µg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 µg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Metabolic pathways altered by air pollutant exposure in association with lipid profiles in young adults.

Mounting evidence suggests that air pollution influences lipid metabolism and dyslipidemia. However, the metabolic mechanisms linking air pollutant exposure and altered lipid metabolism is not established. In year 2014-2018, we conducted a cross-sectional study on 136 young adults in southern California, and assessed lipid profiles (triglycerides, total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, very-low-density lipoprotein (VLDL)-cholesterol), and untargeted serum metabolomics using liquid chromatography-high-resolution mass spectrometry, and one-month and one-year averaged exposures to NO2, O3, PM2.5 and PM10 air pollutants at residential addresses. A metabolome-wide association analysis was conducted to identify metabolomic features associated with each air pollutant. Mummichog pathway enrichment analysis was used to assess altered metabolic pathways. Principal component analysis (PCA) was further conducted to summarize 35 metabolites with confirmed chemical identity. Lastly, linear regression models were used to analyze the associations of metabolomic PC scores with each air pollutant exposure and lipid profile outcome. In total, 9309 metabolomic features were extracted, with 3275 features significantly associated with exposure to one-month or one-year averaged NO2, O3, PM2.5 and PM10 (p < 0.05). Metabolic pathways associated with air pollutants included fatty acid, steroid hormone biosynthesis, tryptophan, and tyrosine metabolism. PCA of 35 metabolites identified three main PCs which together explained 44.4% of the variance, representing free fatty acids and oxidative byproducts, amino acids and organic acids. Linear regression indicated that the free fatty acids and oxidative byproducts-related PC score was associated with air pollutant exposure and outcomes of total cholesterol and LDL-cholesterol (p < 0.05). This study suggests that exposure to NO2, O3, PM2.5 and PM10 contributes to increased level of circulating free fatty acids, likely through increased adipose lipolysis, stress hormone and response to oxidative stress pathways. These alterations were associated with dysregulation of lipid profiles and potentially could contribute to dyslipidemia and other cardiometabolic disorders.

Ambient temperature and air pollution associations with suicide and homicide mortality in California: A statewide case-crossover study.

BACKGROUND: Higher ambient temperature and air pollution may contribute to increased risk of behaviors harmful to oneself or to others; however, quantitative evidence is limited. We examined the relationship of deaths due to suicide and homicide with temperature and air pollution in California-a state prone to high levels of both exposures. METHOD: California death certificates from 2014 to 2019 were used to identify deaths due to suicide and homicide. Residential data for decedents were used to assign exposure to daily temperature (maximum[Tmax], minimum[Tmin]) and daily average air pollution concentrations (particulate matter <10 µm[PM10] and < 2.5 µm[PM2.5], nitrogen dioxide[NO2], ozone[O3]). Tmin served as a surrogate for nighttime temperature. A time-stratified case-crossover study design using conditional logistic regression was used to assess the effects of daily exposure to temperature and air pollutants on suicide and homicide mortality, adjusting for relative humidity. Effect modification by sex and age was assessed. RESULTS: We observed 24,387 deaths due to suicide and 10,767 deaths due to homicide. We found a monotonic temperature association for both outcomes. A 5 °C increase in Tmax at lag-2 and Tmin at lag-0 was associated with 3.1 % (95 % confidence interval [CI]: 1.1 %-5.2 %) and 3.8 % (95%CI: 0.9 %-6.8 %) increased odds of death due to suicide, respectively. The increased odds of homicide mortality per 5 °C increase in Tmax at lag-0 and Tmin at lag-1 were 4.9 % (95%CI: 1.6 %-8.1 %) and 6.2 % (95%CI: 1.6 %-11.0 %), respectively. No air pollutant associations were statistically significant. Temperature associations were robust after adjustment for PM2.5. Some temperature effects were larger among women for suicide and men for homicide mortality, and among those over age 65 years for both outcomes. CONCLUSION: Risk of suicide and homicide mortality increases with increasing daily ambient temperatures. Findings have public health relevance given anticipated increases in temperatures due to global climate change.

Associations between prenatal and early-life air pollution exposure and lung function in young children: Exploring influential windows of exposure on lung development.

BACKGROUND: Evidence in the literature suggests that air pollution exposures experienced prenatally and early in life can be detrimental to normal lung development, however the specific timing of critical windows during development is not fully understood. OBJECTIVES: We evaluated air pollution exposures during the prenatal and early-life period in association with lung function at ages 6-9, in an effort to identify potentially influential windows of exposure for lung development. METHODS: Our study population consisted of 222 children aged 6-9 from the Fresno-Clovis metro area in California with spirometry data collected between May 2015 and May 2017. We used distributed-lag non-linear models to flexibly model the exposure-lag-response for monthly average exposure to fine particulate matter (PM2.5) and ozone (O3) during the prenatal months and first three years of life in association with forced vital capacity (FVC), and forced expiratory volume in the first second (FEV1), adjusted for covariates. RESULTS: PM2.5 exposure during the prenatal period and the first 3-years of life was associated with lower FVC and FEV1 assessed at ages 6-9. Specifically, an increase from the 5th percentile of the observed monthly average exposure (7.55 µg/m3) to the median observed exposure (12.69 µg/m3) for the duration of the window was associated with 0.42 L lower FVC (95% confidence interval (CI): -0.82, -0.03) and 0.38 L lower FEV1 (95% CI: -0.75, -0.02). The shape of the lag-response indicated that the second half of pregnancy may be a particularly influential window of exposure. Associations for ozone were not as strong and typically CIs included the null. CONCLUSIONS: Our findings indicate that prenatal and early-life exposures to PM2.5 are associated with decreased lung function later in childhood. Exposures during the latter months of pregnancy may be especially influential.

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.

Identifying pre-conception and pre-natal periods in which ambient air pollution exposure affects fetal growth in the predominately Hispanic MADRES cohort.

BACKGROUND: It is well documented that persons of color experience disproportionate exposure to environmental contaminants, including air pollution, and have poorer pregnancy outcomes. This study assessed the critical windows of exposure to ambient air pollution on in utero fetal growth among structurally marginalized populations in urban Los Angeles. METHODS: Participants (N = 281) from the larger ongoing MADRES pregnancy cohort study were included in this analysis. Fetal growth outcomes were measured on average at 32 [Formula: see text] 2 weeks of gestation by a certified sonographer and included estimated fetal weight, abdominal circumference, head circumference, biparietal diameter and femur length. Daily ambient air pollutant concentrations were estimated for four pollutants (particulate matter less than 2.5 µm (PM2.5) and less than 10 µm (PM10) in aerodynamic diameter, nitrogen dioxide (NO2), and 8-h maximum ozone (O3)) at participant residences using inverse-distance squared spatial interpolation from ambient monitoring data. Weekly gestational averages were calculated from 12 weeks prior to conception to 32 weeks of gestation (44 total weeks), and their associations with growth outcomes were modeled using adjusted distributed lag models (DLMs). RESULTS: Participants were on average 29 years [Formula: see text] 6 old and predominately Hispanic (82%). We identified a significant sensitive window of PM2.5 exposure (per IQR increase of 6 [Formula: see text]3) between gestational weeks 4-16 for lower estimated fetal weight [Formula: see text] averaged4-16 = -8.7 g; 95% CI -16.7, -0.8). Exposure to PM2.5 during gestational weeks 1-23 was also significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged1-23 = -0.6 mm; 95% CI -1.1, -0.2). Additionally, prenatal exposure to PM10 (per IQR increase of 13 [Formula: see text]3) between weeks 6-15 of pregnancy was significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged6-15 = -0.4 mm; 95% CI -0.8, -0.1). DISCUSSION: These results suggest that exposure to particulate matter in early to mid-pregnancy, but not preconception or late pregnancy, may have critical implications on fetal growth.

Association Between Ambient Air Pollution and Birth Weight by Maternal Individual- and Neighborhood-Level Stressors.

Importance: Fetal growth is precisely programmed and could be interrupted by environmental exposures during specific times during pregnancy. Insights on potential sensitive windows of air pollution exposure in association with birth weight are needed. Objective: To examine the association of sensitive windows of ambient air pollution exposure with birth weight and heterogeneity by individual- and neighborhood-level stressors. Design, Setting, and Participants: Data on a cohort of low-income Hispanic women with singleton term pregnancy were collected from 2015 to 2021 in the ongoing Maternal and Developmental Risks from Environmental and Social Stressors cohort in Los Angeles, California. Exposures: Daily ambient particulate matter with aerodynamic diameter less than 10 µm (PM10) and aerodynamic diameter less than 2.5 µm (PM2.5), nitrogen dioxide (NO2), and 8-hour maximum ozone were assigned to residential locations. Weekly averages from 12 weeks before conception to 36 gestational weeks were calculated. Individual-level psychological stressor was measured by the Perceived Stress Scale. Neighborhood-level stressor was measured by the CalEnviroScreen 4.0. Main Outcomes and Measures: Sex-specific birth weight for gestational age z score (BWZ). The associations between air pollutant and BWZ were estimated using distributed lag models to identify sensitive windows of exposure, adjusting for maternal and meteorologic factors. We stratified the analyses by Perceived Stress Scale and CalEnviroScreen 4.0. We converted the effect size estimation in BWZ to grams to facilitate interpretation. Results: The study included 628 pregnant women (mean [SD] age, 22.18 [5.92] years) and their newborns (mean [SD] BWZ, -0.08 [1.03]). On average, an interquartile range (IQR) increase in PM2.5 exposure during 4 to 22 gestational weeks was associated with a -9.5 g (95% CI, -10.4 to -8.6 g) change in birth weight. In stratified models, PM2.5 from 4 to 24 gestational weeks was associated with a -34.0 g (95% CI, -35.7 to -32.4 g) change in birth weight and PM10 from 9 to 14 gestational weeks was associated with a -39.4 g (95% CI, -45.4 to -33.4) change in birth weight in the subgroup with high Perceived Stress Scale and high CalEnviroScreen 4.0 scores. In this same group, NO2 from 9 to 14 gestational weeks was associated with a -40.4 g (95% CI, -47.4 to -33.3 g) change in birth weight and, from 33 to 36 gestational weeks, a -117.6 g (95% CI, -125.3 to -83.7 g) change in birth weight. Generally, there were no significant preconception windows for any air pollutants or ozone exposure with birth weight. Conclusions and Relevance: In this cohort study, early pregnancy to midpregnancy exposures to PM2.5, PM10, and NO2 were associated with lower birth weight, particularly for mothers experiencing higher perceived stress and living in a neighborhood with a high level of stressors from environmental pollution.

Independent associations of short- and long-term air pollution exposure with COVID-19 mortality among Californians.

The growing literature demonstrating air pollution associations on COVID-19 mortality contains studies predominantly examining long-term exposure, with few on short-term exposure, and rarely both together to estimate independent associations. Because mechanisms by which air pollution may impact COVID-19 mortality risk function over timescales ranging from years to days, and given correlation among exposure time windows, consideration of both short- and long-term exposure is of importance. We assessed the independent associations between COVID-19 mortality rates with short- and long-term air pollution exposure by modeling both concurrently. Using California death certificate data COVID-19-related deaths were identified, and decedent residential information used to assess short- (4-week mean) and long-term (6-year mean) exposure to particulate matter <2.5µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3). Negative binomial mixed models were fitted on weekly census tract COVID-19 mortality adjusting for potential confounders with random effects for county and census tract and an offset for population. Data were evaluated separately for two time periods March 16, 2020-October 18, 2020 and October 19, 2020-April 25, 2021, representing the Spring/Summer surges and Winter surge. Independent positive associations with COVID-19 mortality were observed for short- and long-term PM2.5 in both study periods, with strongest associations observed in the first study period: COVID-19 mortality rate ratio for a 2-µg/m3 increase in long-term PM2.5 was 1.13 (95%CI:1.09,1.17) and for a 4.7-µg/m3 increase in short-term PM2.5 was 1.05 (95%CI:1.02,1.08). Statistically significant positive associations were seen for both short- and long-term NO2 in study period 1, but short-term NO2 was not statistically significant in study period 2. Results for long-term O3 indicate positive associations, however, only marginal significance is achieved in study period 1. These findings support an adverse effect of long-term PM2.5 and NO2 exposure on COVID-19 mortality risk, independent of short-term exposure, and a possible independent effect of short-term PM2.5.

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.

Increases in ambient air pollutants during pregnancy are linked to increases in methylation of IL4, IL10, and IFNγ.

BACKGROUND: Ambient air pollutant (AAP) exposure is associated with adverse pregnancy outcomes, such as preeclampsia, preterm labor, and low birth weight. Previous studies have shown methylation of immune genes associate with exposure to air pollutants in pregnant women, but the cell-mediated response in the context of typical pregnancy cell alterations has not been investigated. Pregnancy causes attenuation in cell-mediated immunity with alterations in the Th1/Th2/Th17/Treg environment, contributing to maternal susceptibility. We recruited women (n = 186) who were 20 weeks pregnant from Fresno, CA, an area with chronically elevated AAP levels. Associations of average pollution concentration estimates for 1 week, 1 month, 3 months, and 6 months prior to blood draw were associated with Th cell subset (Th1, Th2, Th17, and Treg) percentages and methylation of CpG sites (IL4, IL10, IFNγ, and FoxP3). Linear regression models were adjusted for weight, age, season, race, and asthma, using a Q value as the false-discovery-rate-adjusted p-value across all genes. RESULTS: Short-term and mid-term AAP exposures to fine particulate matter (PM2.5), nitrogen dioxide (NO2) carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAH456) were associated with percentages of immune cells. A decrease in Th1 cell percentage was negatively associated with PM2.5 (1 mo/3 mo: Q < 0.05), NO2 (1 mo/3 mo/6 mo: Q < 0.05), and PAH456 (1 week/1 mo/3 mo: Q < 0.05). Th2 cell percentages were negatively associated with PM2.5 (1 week/1 mo/3 mo/6 mo: Q < 0.06), and NO2 (1 week/1 mo/3 mo/6 mo: Q < 0.06). Th17 cell percentage was negatively associated with NO2 (3 mo/6 mo: Q < 0.01), CO (1 week/1 mo: Q < 0.1), PM2.5 (3 mo/6 mo: Q < 0.05), and PAH456 (1 mo/3 mo/6 mo: Q < 0.08). Methylation of the IL10 gene was positively associated with CO (1 week/1 mo/3 mo: Q < 0.01), NO2 (1 mo/3 mo/6 mo: Q < 0.08), PAH456 (1 week/1 mo/3 mo: Q < 0.01), and PM2.5 (3 mo: Q = 0.06) while IL4 gene methylation was positively associated with concentrations of CO (1 week/1 mo/3 mo/6 mo: Q < 0.09). Also, IFNγ gene methylation was positively associated with CO (1 week/1 mo/3 mo: Q < 0.05) and PAH456 (1 week/1 mo/3 mo: Q < 0.06). CONCLUSION: Exposure to several AAPs was negatively associated with T-helper subsets involved in pro-inflammatory and anti-inflammatory responses during pregnancy. Methylation of IL4, IL10, and IFNγ genes with pollution exposure confirms previous research. These results offer insights into the detrimental effects of air pollution during pregnancy, the demand for more epigenetic studies, and mitigation strategies to decrease pollution exposure during pregnancy.

Transcriptomic and metabolomic associations with exposures to air pollutants among young adults with childhood asthma history.

Ambient air pollutants are well-known risk factors for childhood asthma and asthma exacerbation. It is unknown whether different air pollutants individually or jointly affect pathophysiological mechanisms of asthma. In this study, we aim to integrate transcriptome and untargeted metabolome to identify dysregulated genetic and metabolic pathways that are associated with exposures to a mixture of ambient and traffic-related air pollutants among adults with asthma history. In this cross-sectional study, 102 young adults with childhood asthma history were enrolled from southern California in 2012. Whole blood transcriptome was measured with 20,869 expression signatures, and serum untargeted metabolomics including 937 metabolites were analyzed by Metabolon, Inc. Participants' exposures to regional air pollutants (NO2, O3, PM10, PM2.5) and near-roadway air pollutants averaged at one month and one year before study visit were estimated based on residential addresses. xMWAS network analysis and joint-pathway analysis were performed to identify subnetworks and genetic and metabolic pathways that were associated with exposure to air pollutants adjusted for socio-characteristic covariates. Network analysis found that exposures to air pollutants mixture were connected to 357 gene markers and 92 metabolites. One-year and one-month averaged PM2.5 and NO2 were associated with several amino acids related to serine, glycine, and beta-alanine metabolism. Lower serum levels of carnosine and aspartate, which are involved in the beta-alanine metabolic pathway, as well as choline were also associated with worse asthma control (p < 0.05). One-year and one-month averaged PM10 and one-month averaged O3 were associated with higher gene expression levels of HSPA5, LGMN, CTSL and HLA-DPB1, which are involved in antigen processing and presentation. These results indicate that exposures to various air pollutants are associated with altered genetic and metabolic pathways that affect anti-oxidative capacity and immune response and can potentially contribute to asthma-related pathophysiology.

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.

Traffic-related air pollution, biomarkers of metabolic dysfunction, oxidative stress, and CC16 in children.

BACKGROUND: Previous research has revealed links between air pollution exposure and metabolic syndrome in adults; however, these associations are less explored in children. OBJECTIVE: This study aims to investigate the association between traffic-related air pollutants (TRAP) and biomarkers of metabolic dysregulation, oxidative stress, and lung epithelial damage in children. METHODS: We conducted cross-sectional analyses in a sample of predominantly Latinx, low-income children (n = 218) to examine associations between air pollutants (nitrogen dioxide (NO2), nitrogen oxides (NOx), elemental carbon, polycyclic aromatic hydrocarbons, carbon monoxide (CO), fine particulates (PM2.5)) and biomarkers of metabolic function (high-density lipoprotein (HDL), hemoglobin A1c (HbA1c), oxidative stress (8-isoprostane), and lung epithelial damage (club cell protein 16 (CC16)). RESULTS: HDL cholesterol showed an inverse association with NO2 and NOx, with the strongest relationship between HDL and 3-month exposure to NO2 (-15.4 mg/dL per IQR increase in 3-month NO2, 95% CI = -27.4, -3.4). 8-isoprostane showed a consistent pattern of increasing values with 1-day and 1-week exposure across all pollutants. Non-significant increases in % HbA1c were found during 1-month time frames and decreasing CC16 in 3-month exposure time frames. CONCLUSION: Our results suggest that TRAP is significantly associated with decreased HDL cholesterol in longer-term time frames and elevated 8-isoprostane in shorter-term time frames. TRAP could have the potential to influence lifelong metabolic patterns, through metabolic effects in childhood.

Long-term air pollution and COVID-19 mortality rates in California: Findings from the Spring/Summer and Winter surges of COVID-19.

A growing number of studies report associations between air pollution and COVID-19 mortality. Most were ecological studies at the county or regional level which disregard important local variability and relied on data from only the first few months of the pandemic. Using COVID-19 deaths identified from death certificates in California, we evaluated whether long-term ambient air pollution was related to weekly COVID-19 mortality at the census tract-level during the first ∼12 months of the pandemic. Weekly COVID-19 mortality for each census tract was calculated based on geocoded death certificate data. Annual average concentrations of ambient particulate matter <2.5 µm (PM2.5) and <10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) over 2014-2019 were assessed for all census tracts using inverse distance-squared weighting based on data from the ambient air quality monitoring system. Negative binomial mixed models related weekly census tract COVID-19 mortality counts to a natural cubic spline for calendar week. We included adjustments for potential confounders (census tract demographic and socioeconomic factors), random effects for census tract and county, and an offset for census tract population. Data were analyzed as two study periods: Spring/Summer (March 16-October 18, 2020) and Winter (October 19, 2020-March 7, 2021). Mean (standard deviation) concentrations were 10.3 (2.1) µg/m3 for PM2.5, 25.5 (7.1) µg/m3 for PM10, 11.3 (4.0) ppb for NO2, and 42.8 (6.9) ppb for O3. For Spring/Summer, adjusted rate ratios per standard deviation increase were 1.13 (95% confidence interval: 1.09, 1.17) for PM2.5, 1.16 (1.11, 1.21) for PM10, 1.06 (1.02, 1.10) for NO2, and 1.09 (1.04, 1.14) for O3. Associations were replicated in Winter, although they were attenuated for PM2.5 and PM10. Study findings support a relation between long-term ambient air pollution exposure and COVID-19 mortality. Communities with historically high pollution levels might be at higher risk of COVID-19 mortality.

Racial/Ethnic Disparities in Alzheimer's Disease Risk: Role of Exposure to Ambient Fine Particles.

BACKGROUND: Whether racial/ethnic disparities in Alzheimer's disease (AD) risk may be explained by ambient fine particles (PM2.5) has not been studied. METHOD: We conducted a prospective, population-based study on a cohort of Black (n = 481) and White (n = 6 004) older women (aged 65-79) without dementia at enrollment (1995-1998). Cox models accounting for competing risk were used to estimate the hazard ratio (HR) for racial/ethnic disparities in AD (1996-2010) defined by Diagnostic and Statistical Manual of Mental Disorders, 4th edition and the association with time-varying annual average PM2.5 (1999-2010) estimated by spatiotemporal model. RESULTS: Over an average follow-up of 8.3 (±3.5) years with 158 incident cases (21 in Black women), the racial disparities in AD risk (range of adjusted HRBlack women = 1.85-2.41) observed in various models could not be explained by geographic region, age, socioeconomic characteristics, lifestyle factors, cardiovascular risk factors, and hormone therapy assignment. Estimated PM2.5 exposure was higher in Black (14.38 ± 2.21 µg/m3) than in White (12.55 ± 2.76 µg/m3) women, and further adjustment for the association between PM2.5 and AD (adjusted HRPM2.5 = 1.18-1.28) slightly reduced the racial disparities by 2%-6% (HRBlack women = 1.81-2.26). The observed association between PM2.5 and AD risk was ~2 times greater in Black (HRPM2.5 = 2.10-2.60) than in White (HRPM2.5 = 1.07-1.15) women (range of interaction ps: <.01-.01). We found similar results after further adjusting for social engagement (social strain, social support, social activity, living alone), stressful life events, Women's Health Initiative's clinic sites, and neighborhood socioeconomic characteristics. CONCLUSIONS: PM2.5 may contribute to racial/ethnic disparities in AD risk and its associated increase in AD risk was stronger among Black women.