Background: Suicide is a major public health concern, and short-term meteorological conditions may contribute to acute suicide risk. However, the independent and joint effects of temperature, solar radiation, and precipitation, and their modification by large-scale climate variability, remain incompletely understood. Methods: We conducted a bi-directional, time-stratified case-crossover study of 7,546 suicide deaths in Utah, USA from 2000-2016. Daily precipitation (mm), solar radiation (W/m2), and maximum temperature (◦C) were assigned to geocoded residential locations at time of death. Conditional logistic regression estimated odds ratios (ORs) per interquartile-range increases for same-day, single-day and cumulative day lags (CL0-6) exposures, adjusting for relative humidity and holidays. Effect modification by season, PM2.5, NO2, and El Niño-Southern Oscillation (ENSO) phase was evaluated. Quantile g-computation assessed joint effects of pairwise and three-way meteorological mixtures. Findings: In spring, solar radiation was positively associated with suicide at CL0-6 (OR 1·29, 95% CI 1·08-1·53). In summer, temperature showed the strongest positive association at CL0-6 (OR 1·22, 95% CI 1·10-1·35), and solar radiation was also positively associated at CL0-6 (OR 1·19, 95% CI 1·03-1·37). Joint effects were season-specific. Solar radiation-temperature mixture was positively associated with suicide in spring at CL0-6 (OR 1·01, 95% CI 1·00-1·01). Positive temperature and solar radiation associations were larger during El Niño periods, and temperature associations were amplified under higher NO2 concentrations. Interpretation: Short-term weather patterns may influence suicide risk in a seasonally specific manner. Findings suggest that large-scale climate variability and co-occurring air pollution may modify meteorological associations with suicide, with implications for climate-sensitive mental health surveillance and prevention.

Ambient air pollutant levels during pregnancy are known to impact the offspring’s health. DNA Methylation (DNAm) may be sensitive to air pollutants throughout pregnancy. This study estimated the effect of ambient air pollution (PM2.5, PM10, NO2, O3) mixture levels in early and late pregnancy on paired maternal prenatal DNAm (N = 116) levels. The impact of average prenatal pollutant mixture on neonatal cord blood DNAm signatures was also evaluated (N = 114). Lastly, the association of pollutant-related maternal DNAm profiles (N = 78 maternal-child dyads) with neonatal DNAm profiles was investigated. Quantile g-computation was applied to maternal and neonatal datasets to test the effect of the pollutant mixture on DNAm signatures. To test the correlation of pollutant associated alteration in maternal DNAm with cord blood DNAm signatures, independent cord blood epigenome wide association studies (EWASs) were applied within the subset of significant maternal CpGs identified in the mixture model. Sex was explored as a modifying variable. We identified 18 maternal prenatal CpGs whose methylation levels were associated with ambient air pollution mixtures in pregnancy on average. 1 CpG, cg00723044, displayed significance in models for the neonatal mixtures analysis only among male neonates. Neonatal CpGs were not associated with maternal CpGs identified in the maternal mixtures analysis. Ambient air pollution mixtures were associated with maternal methylation levels in 18 CpGs (q < 0.1) in pregnancy, and there was some evidence that air pollutant mixture levels in pregnancy affected cord blood DNAm in 1 CpG in male neonates.

Despite the recent increase in the intensity and frequency of wildland fires in the United States, there is limited investigation into the impact of wildland fires on pregnancy-related mortality and morbidity. This study examined associations between maternal exposure to wildland fire smoke and severe maternal morbidity (SMM), or potentially life-threatening complications related to pregnancy or delivery, in a population-based cohort of California birthing people between 2007 and 2018. We measured pregnancy smoke-day burden using the Hazard Mapping System smoke product and wildland fire-specific fine particulate matter (PM2.5, particles ≤2.5 μm) using bias-corrected Community Multiscale Air Quality Model results, linked to birthing people's residential locations. Logistic regression models estimated severe maternal morbidity risk associated with pregnancy smoke-day burden and average wildland fire-specific PM2.5, during the whole pregnancy and within each trimester, adjusting for individual-level sociodemographic and health covariates. To investigate whether the impact of wildland fire smoke was more pronounced among racially marginalized populations, we conducted stratified analysis by race and ethnicity. In a sample of 4,584,110 individuals with singleton births, exposure to high pregnancy smoke-day burden and average wildland fire-specific PM2.5, compared to low exposure, was associated with elevated risk of SMM (OR = 1.16, 95% CI: 1.13-1.19; OR = 1.12, 95% CI 1.09-1.14, respectively). Exposure during the second and third trimesters was more strongly associated with SMM, compared to first trimester exposure. Exposure to pregnancy smoke-day burden was most strongly associated with SMM among births to Asian and Pacific Islander individuals, and exposure to wildland fire-specific PM2.5 was more strongly associated with SMM among births to Asian and Pacific Islander and Black individuals. Results demonstrate the urgency to understand how wildland fire smoke affects maternal health, as well as its role in shaping racial and ethnic inequities in SMM.

INTRODUCTION:Numerous studies have linked wildfire exposure to adverse physical and mental health outcomes and symptoms. However, few studies incorporate both outdoor wildfire smoke-related PM2.5 concentration and indoor air quality measurements. Understanding the mechanisms by which objectively measured and perceived wildfire smoke impact people's health could facilitate interventions to mitigate adverse health effects. METHODS:Survey data were obtained from N = 849 adult residents in the Los Angeles area 2-3 months after the 2025 wildfires. A latent class analysis identified subgroups of people with similar symptom experiences. Associations between wildfire smoke-related PM2.5 concentration and indoor air quality with likely class membership were examined. RESULTS:We identified three latent subgroups: Physical and Mental Health Symptoms, Physical Health Symptoms, and Low Symptoms. Higher outdoor wildfire smoke-related PM2.5 levels were associated with a higher likelihood of belonging to the symptomatic classes, and indoor air quality statistically explained most of this association. DISCUSSION:Indoor exposure may be an important mechanism by which people are exposed to wildfire smoke, which can cause adverse health symptoms. While outdoor PM2.5 concentration is commonly used in wildfire exposure research, our findings suggest that perceived indoor air quality provides additional explanatory information about who experiences more severe symptom profiles, particularly for wildland-urban interface fires where many residents are sheltering in place. Protective behaviors and interventions to maintain clean indoor air during WUI fire events should be promoted.

The increase in the frequency, duration, and intensity of wildland fires is a significant source of air pollution that can impact perinatal outcomes. This study assessed associations between wildfire fine particulate matter <2.5 μm (PM2.5) and adverse birth weight outcomes among singleton term births in California for 2007-2018. Exposure was assessed using bias-corrected Community Multiscale Air Quality Model, linked to residence at delivery. Logistic and linear regression models estimated associations between average daily wildfire PM2.5 and birth weight outcomes, adjusting for individual-level sociodemographic covariates and seasonality. We conducted race/ethnicity-stratified analyses to assess whether the influence of wildfire PM2.5 differed among racially marginalized populations. In a sample of 4,537,418 term births, a 1 μg/m3 increase in wildfire PM2.5 during pregnancy was associated with increased odds of large for gestational age and an increase in birth weight, as well as moderately decreased odds of low birth weight and small for gestational age. These associations were more pronounced among Hispanic individuals and those in the Other race category. Conversely, among American Indian and Alaska Native births, exposure to wildfire PM2.5 was associated with decreased odds of large for gestational age. Results underscore the importance of understanding how wildfire PM2.5 impacts fetal growth, especially among marginalized groups.

Particulate air pollution is associated with autism spectrum disorder (ASD), with disadvantaged neighborhoods potentially increasing vulnerability due to stress or other social determinants of health. Understanding the impact of air pollution interventions on ASD incidence across neighborhood disadvantage levels can guide policies to protect vulnerable populations. We examined 2 sets of hypothetical particulate matter (PM)2.5 interventions: percentage reduction and regulatory standards as thresholds, to assess their potential effects on ASD cumulative incidence. Using G-computation under a counterfactual framework, we estimated changes in the cumulative incidence of ASD by age 5 under hypothetical interventions compared to observed exposures. Our study involved a birth cohort of 318 298 children born between 2001-2014 in Southern California, with 4548 diagnosed with ASD by age 5. Pregnancy average PM2.5 and neighborhood disadvantage were assigned to residential addresses. Adjusted Cox regression models were applied to estimate ASD cumulative incidence. Reducing pregnancy average PM2.5 by 30% or below 9 μg/m3 would have prevented 10.6 (95% CI, 3.6-19.2) and 12.5 (2.7-23.6) ASD cases per 10 000 children, respectively. The decreases in ASD cumulative incidence under hypothetical interventions were similar across neighborhood disadvantage levels. These findings suggest that reducing ambient PM2.5 levels to meet or surpass current standards could help prevent ASD.

BACKGROUND:Individual components of the ambient environment, such as temperature and air pollution, exist as part of a complex mixture and have been associated with suicide; however, their interactive effects remain poorly understood. This study examined the independent and interactive effects of wet bulb globe temperature (WBGT), nitrogen dioxide (NO2), and fine particulate matter (PM2.5) on suicide mortality. METHODS:We identified 7,551 suicide cases in Utah, USA, from 2000 to 2016 and assigned exposure to daily maximum WBGT (sourced from the European Center for Medium-Range Weather Forecasts) and PM2.5 and NO2 concentrations (sourced from a national spatiotemporal ensemble model) using decedent's residential address at the time of death. A case-crossover design with conditional logistic regression was used to estimate the independent and interactive effects of WBGTmax, PM2.5, and NO2 on suicide. For exposure windows, we considered single days preceding suicide (lag 0 to 6) and their averages across preceding days (lag 0-1, 0-3, and 0-6). Analyses were stratified by season. RESULTS:We identified a significant association between WBGTmax and suicide across all seasons (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.01, 1.10; per 5 °C increase on lag 0-3 days). The associations were stronger in the warm season (March 22 to September 21), with ORs and 95% CIs ranging from 1.08 (1.02, 1.15) to 1.20 (1.10, 1.30) per 5 °C increase depending on the lag periods. We observed synergistic interactions between WBGTmax and PM2.5 and NO2 in the warm season, associated with higher odds of suicide. The associations of WBGTmax with suicide were most pronounced at high NO2 levels. CONCLUSIONS:We found evidence of synergistic interactions between WBGTmax and PM2.5 and NO2 on suicide in the warm season, emphasizing the need for considering the combined effects of heat stress and air pollution in suicide prevention strategies.

Prenatal depression shows diverse patterns in severity and progression. While air pollution has been linked to depression risk, its impact on the course of prenatal depression remains understudied. The study objectives were to (1) identify distinct trajectories of depressive symptoms across pregnancy, and (2) to evaluate whether preconception and early-pregnancy air pollution exposure impacts membership in trajectory groups. This study followed 542 predominantly low-income Hispanic/Latina participants in the MADRES cohort. We assessed depressive symptoms using the Center for Epidemiologic Studies-Depression (CES-D) scale at 1st, 2nd, and 3rd trimester visits. Daily residential concentrations of PM2.5, PM10, NO2, and O3 were estimated using inverse-distance squared spatial interpolation from monitoring data. We used latent growth mixture modeling (LGMM) to identify trajectory classes and multinomial logistic regression to estimate adjusted relative risk ratios (RRRs) of membership in each class relative to the lowest group with averaged air pollution levels over preconception and early pregnancy. We identified four distinct trajectories: moderate-to-high symptoms (7.4

PNPLA3-I148M genotype is the strongest predictive single-nucleotide polymorphism for liver fat. We examine whether PNPLA3-I148M modifies associations between oxidative gaseous air pollutant exposure (O-x(wt)) with i) liver fat and ii) multi-omics profiles of miRNAs and metabolites linked to liver fat. Participants were 69 young adults (17-22 years) from the Meta-AIR cohort. Prior-month residential O-x(wt) exposure (redox-weighted oxidative capacity of nitrogen dioxide and ozone) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Liver fat fraction was assessed by MRI. Serum miRNAs and metabolites were assayed via NanoString nCounter and LC-HRMS, respectively. Multi-omics factor analysis (MOFA) was used to identify latent factors with shared variance across omics layers. Multivariable linear regression models adjusted for age, sex, body mass index, and genotype with liver fat or MOFA factors as an outcome and examined PNPLA3 (rs738409; CC/CG vs. GG) as a multiplicative interaction term. Overall, a standard deviation difference in O-x(wt) exposure was associated with 8.9% relative increase in liver fat (p = 0.04) and this relationship differed by PNPLA3 genotype (p-value for interaction term: p(intx)<0.001), whereby relative increases in liver fat for GG and CC/CG participants were 71.8% and 2.4%, respectively. There was no main effect of O-x(wt) on MOFA Factor 1 expression (p = 0.85), but there was an interaction with PNPLA3 genotype (p(intx) = 0.01), whereby marginal slopes were 0.211 and -0.017 for GG and CC/CG participants, respectively. MOFA Factor 1 in turn was associated with liver fat (p = 0.006). MOFA Factor 1 miRNAs targeted genes in Fatty Acid Biosynthesis and Metabolism and Lysine Degradation pathways. MOFA Factor 9 was also associated with liver fat and was comprised of branched-chain keto acid and amino acid metabolites. The effects of O-x(wt) exposure on liver fat is exacerbated in young adults with two PNPLA3 risk alleles, potentially through differential effects on miRNA and/or metabolite profiles.

BACKGROUND:Ambient air pollutants such as particulate matter (PM), ozone (O3), and nitrogen dioxide (NO2) have been associated with lower lung function among children. However, the reported associations could be due to correlation with other pollutants. OBJECTIVE:We investigate the relationships between exposures to eight ambient air pollutants and children's lung function and apply mixture analysis to identify key contributors to health effects. METHODS:The Children's Health and Air Pollution Study (CHAPS) in Fresno, California, is a prospective cohort study that recruited 299 children and assessed their lung function at two visits, at approximately 7 and 9 years of age. The children's forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio were standardized using the Global Lung Function Initiative (GLI) race-neutral calculators. We assessed the children's average daily residential exposures to PM2.5, PM10, nitrogen oxides (NOx), NO2, O3, carbon monoxide (CO), elemental carbon (EC), and polycyclic aromatic hydrocarbons (PAHs), during the 1-week, 1-month, 3-month, 6-month, and 12-month periods before each visit, and the 2 years between visits. We applied linear mixed-effect models and quantile-based g-computation (q-gcomp) for statistical analysis. RESULTS:The children's exposures to the eight ambient air pollutants exhibited high intercorrelation: Seven air pollutants were positively correlated, while O3 exposures were negatively correlated with the other pollutants. Higher PM10 was associated with lower FEV1 and FEV1/FVC ratio, and the associations were strongest for the 3-month exposure timeframe. Q-gcomp also identified PM10 as the key pollutant associated with lower FEV1 and FEV1/FVC ratio. CONCLUSION:Among the eight ambient air pollutants, PM10 was the strongest risk factor for impaired lung function among children in Fresno. Ambient air pollution levels in this community exceed regulatory standards and are harmful to children's lung function.

Objectives: To assess long term trends in outdoor heat and wildfire smoke exposure at 410 correctional facilities in California from 2000 to 2023. Methods: We used ERA5 Land data to calculate daily wet bulb globe temperature (WBGT) and identified days exceeding the NIOSH exposure limits for heat stress. Wildfire smoke exposure was estimated using the NOAA Hazard Mapping System (HMS). Temporal trends in daily heat and smoke exposure were modeled using linear regression for each facility. Results: Smoke affected days rose statewide from 4.9% (2006 to 2010) to 12.5% (2019 to 2023), with Northern California experiencing the highest burden and steepest increases. Days above 28 degrees Celsius WBGT increased from 27.3% to 29.8% statewide, with the Central Valley and desert regions showing the highest current burden and coastal areas experiencing the steepest increases. Coastal facilities show emerging heat risks, and some regions especially the Central Valley and Sierra foothills face dual exposure to both hazards. Conclusions: Correctional officers and incarcerated workers face rising environmental risks, with regional variation in exposure. Facilities with concurrent heat and smoke burdens must balance cooling and filtration needs. Resilience planning and occupational protections must evolve to meet facility and region-specific challenges. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by the California Fifth Climate Change Assessment Core Climate Research Program. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Select data produced in the present study are available upon reasonable request to the authors.

Long-term exposure to air pollutants may be harmful to the brain, potentially through inducing oxidative stress or inflammation. Few studies of air pollution and depression have been conducted in the United States where this mental health disorder is prevalent among adults. We investigated associations between ambient air pollutants (O3, PM2.5 and NO2) and depression symptoms in middle-aged and older adults (n = 1496) without cardiovascular disease or cognitive impairment in Los Angeles, California. Air pollution exposures were assigned to residential addresses using a geographic information system with air quality monitoring data. The Center for Epidemiological Studies-Depression scale (CES-D) assessed depression symptoms at study entry. Carotid artery intima-media thickness (CIMT) was obtained as a measure of subclinical atherosclerosis. Linear and Poisson regression models estimated cross-sectional associations between air pollutants and total CES-D score and suspected clinical depression (CES-D score ≥ 16) adjusting for potential confounders and examined effect modification by CIMT. Higher exposure to O3, PM2.5 and NO2 overall were not cross-sectionally associated with higher CES-D total scores or CES-D score ≥ 16. However, the interaction between CIMT and PM2.5 was statistically significant (β-interaction term = 1.01, 95

Background: The natural distributions of ambient air pollutants are often correlated. Existing studies have found that exposures to various air pollutants are associated with elevated risks of asthma symptoms among children. However, most studies applied single-pollutant models, which cannot distinguish between causal effects and associations due to correlations with other measured or unmeasured pollutants. Objective: We sought to investigate air pollutant mixtures and child asthma symptoms and identify key risk factors. Methods: The Children’s Health and Air Pollution Study recruited 299 children in Fresno, California, 63 of whom had ever-diagnosed asthma. We assessed the children’s prior 12-month exposures to 8 ambient air pollutants, namely, particulate matter with aerodynamic diameter of 2.5 μm, particulate matter with aerodynamic diameter of 10 μm, nitrogen oxides, nitrogen dioxide, ozone, carbon monoxide, elemental carbon, and polycyclic aromatic hydrocarbons, and asthmatic symptoms (wheeze and cough) at 2 visits, at age approximately 7 and 9 years. We conducted repeated-measures analysis with mixture analysis methods, including principal-component analysis and quantile-based g-computation (q-gcomp). Results: The 8 air pollutants exhibited strong intercorrelation. In single-pollutant models, exposure to ozone was associated with higher risk of cough (odds ratio, 1.39; 95% CI, 1.06-1.82). Using principal-component analysis and q-gcomp, exposures to nitrogen oxides, elemental carbon, and ozone had relatively high contributions to cough and wheeze. The association between ozone and cough was consistently positive from single-pollutant models, double-pollutant models, principal-component analysis, and quantile-based g-computation with negative control. Conclusion: Ozone stands out among the 8 air pollutants and may be a driving risk factor for persistent cough among children with asthma.

We investigated associations between preconception and prenatal heat stress and wildfire (WF) smoke exposures on adverse birth outcomes and whether neighborhood climate vulnerability is an effect modifier in the Maternal And Developmental Risks from Environmental and Social stressors cohort (N = 713). Generalized linear models were fit to test the association between exposures and small-for-gestational-age (SGA), low birthweight (LBW), and Fenton growth z-score outcomes, adjusting for confounders. Living in a high climate vulnerability index neighborhood was tested as an effect modifier. During preconception, increases in heat stress and WF measures were associated with higher odds of SGA. Living in the most climate-vulnerable neighborhoods during preconception significantly modified and nearly doubled the odds of SGA with exposure to heat stress. Similarly, heat stress and WF exposure in trimester-specific time periods were associated with adverse birth outcomes. Conversely, third-trimester exposures were associated with lower odds of LBW. Throughout pregnancy, two measures of infant size (SGA and Fenton z-scores) were lower among those with greater exposure to multiple WF exposures. This study highlights how living in more climate-vulnerable neighborhoods significantly modifies the effect of heat stress on SGA, suggesting that the increasing adaptation capacity of communities may strengthen climate change resilience.

Prenatal exposure to air pollution has been associated with an increased risk of low birth weight. Disrupted metabolism may serve as an underlying mechanism, but the specific metabolic pathways involved remain unclear. In the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) study, 382 third-trimester maternal serum samples were analyzed for untargeted metabolomics using liquid chromatography with Fourier transform high-resolution mass spectrometry. Ambient concentrations of fine particulate matter (PM2.5), particulate matter ≤ 10 μm in diameter (PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated using inverse-distance-squared weighted spatial interpolation based on daily residential histories. Birth weight was retrieved from medical records. Linear regression identified metabolomic features associated with air pollution exposure or birth weight, followed by Mummichog pathway enrichment and mediation analyses for the selected features. Second-trimester PM2.5 exposure was associated with lower birth weight. Fourteen metabolic pathways were significantly associated with second-trimester PM2.5 exposure, with C21-steroid hormone biosynthesis and metabolism showing the most significant association. Sixteen metabolic pathways were significantly associated with birth weight, with vitamin A (retinol) metabolism being the most significantly enriched pathway. Seven pathways were associated with both PM2.5 exposure and birth weight, including C21-steroid hormone biosynthesis and metabolism, bile acid biosynthesis, tyrosine metabolism, ascorbate (vitamin C) and aldarate metabolism, vitamin D3 (cholecalciferol) metabolism, vitamin A (retinol) metabolism, and pyrimidine metabolism. Overweight or obese women exhibited more metabolomic features and metabolic pathways associated with PM2.5 exposure compared to underweight or normal-weight women. No associations were observed between PM10, NO2, or O3 and birth weight. Maternal metabolic pathways involving steroid metabolism, oxidative stress and inflammation, vitamin metabolism, and DNA damage may link prenatal PM2.5 exposure to lower birth weight, with overweight or obese women potentially more susceptible to these metabolic disruptions.

As individuals are exposed to a myriad of potentially harmful pollutants every day, it is important to determine which actors have the greatest influence on health outcomes. However, jointly modeling the associations of multiple pollutant exposures is often hindered by the presence of highly correlated chemicals originating from a common source. A popular approach to analyzing associations between a disease outcome and several highly correlated exposures is Weighted Quantile Sum Regression (WQSR) modeling. WQSR provides increased stability in estimating model parameters but requires data splitting to estimate individual and group effects of chemicals, which reduces the power of the approach. A recent Bayesian implementation of WQSR regression provides a model fitting procedure that avoids data splitting at the cost of high computational expense on large data. In this paper, we introduce a Frequentist Grouped Weighted Quantile Sum Regression (FGWQSR) model that can be fitted efficiently to large datasets without requiring data splitting. FGWQSR produces estimates of the joint effect of mixture groups and of individual chemicals, and likelihood-ratio-based tests that account for FGWQSR's non-standard asymptotics. We demonstrate that FGWQSR is well calibrated for type-I errors while outperforming both Bayesian Grouped Weighted Quantile Sum Regression and Quantile Logistic Regression in terms of statistical power to detect the effects of mixture groups and individual chemicals. In addition, we show that FGWQSR is robust to model misspecification and can be fitted on large datasets in a fraction of the time required for BGWQSR. We apply FGWQSR to a dataset of 317 767 mother-child pairs with exposure profiles generated by chemical transport models to study the associations between several components found in particulate matter with an aerodynamic diameter smaller than 2.5 μ m $$ \mu \mathrm{m} $$ (PM   2 . 5 $$ {}_{2.5} $$ ) and child Autism Spectrum Disorder (ASD) diagnosis before age 5. PM   2 . 5 $$ {}_{2.5} $$ copper and PM   2 . 5 $$ {}_{2.5} $$ crustal material are found to be statistically significantly associated with ASD diagnosis by five years of age.

Exposure to air pollution during pregnancy that disrupts thyroid function can lead to adverse health outcomes in mother and child. We evaluated the overall effect and critical exposure window of residential ambient air pollution exposures on thyroid function in the MADRES pregnancy cohort. We also investigated whether these associations varied by iodine deficiency status and neighborhood deprivation. Early pregnancy (6-20 weeks) serum thyroid stimulating hormone (TSH) and free thyroxine (FT4) were measured for 217 mothers. Daily residential ambient air pollution exposures (PM2.5, PM10, NO2 and O3 8hr max) were estimated using inverse-distance squared spatial interpolation from regulatory monitors. We used linear regression to assess effects of single ambient air pollutants on thyroid function, including exploration of effect modification by iodine deficiency and neighborhood deprivation (Area Deprivation Index and Gini Index of income inequality, dichotomized at the median). Distributed lag models (DLM) were used to assess critical windows of exposure for ambient air pollutants from 12 weeks preconception to first trimester. We found that one SD increase in PM2.5 (2.4 μg/m3) and PM10 (5.8 μg/m3) were associated with 18.9 % (95 % CI: 2.7, 37.8 %) and 16.8 % (95 % CI: 0.7, 35.6 %) higher TSH levels, respectively, with significant windows of susceptibility in the first trimester (GW 5-8 or 6-8). These associations were also modified by neighborhood deprivation, and iodine status. Our findings indicate that relatively low levels of PM exposures in early pregnancy are associated with increased TSH levels particularly among women with replete iodine levels and women living in neighborhoods with greater deprivation.

The November 2018 Camp fire was the most destructive wildfire in California history, but its effects on reproductive health are not known. We linked California birth records from 2017-2019 to daily smoke levels using US EPA Air Quality System (AQS) PM2.5 data and NOAA Hazard Mapping System smoke plume polygons during the Camp fire. In the main analysis, pregnancies were considered exposed if they had median AQS PM2.5 levels above 50 μg/m3 for at least 7 days during November 8-22, 2018. We calculated rates of preterm birth and the infant sex ratio based on week of conception and used the generalized synthetic control method to estimate the average treatment effect on the treated and to propose a novel approach to identify potential critical weeks of exposure during pregnancy. We found associations between Camp fire-related smoke exposure and rates of preterm birth, with a risk difference (RD) of 0.005 and a 95% confidence interval (CI) of 0.001-0.010. Exposure during week 10 of pregnancy was consistently associated with increased preterm birth (RD, 0.030; 95% CI, 0.004-0.056). We did not observe differences in the infant sex ratio. Camp fire smoke exposure was associated with increased rates of preterm birth, with sensitive windows in the first trimester. This article is part of a Special Collection on Environmental Epidemiology.

Importance:Emerging evidence suggests that exposure to air pollution affects children's glucose metabolism. However, the underlying mechanisms are not fully understood. Objective:To investigate whether body mass index (BMI; calculated as the weight in kilograms divided by the height in meters squared) growth trajectories mediate the association between traffic-related air pollution (TRAP) and insulin resistance. Design, Setting, and Participants:As part of the Southern California Children's Health Study, the ongoing Meta-Air2 cohort substudy followed up participants from pregnancy to 24 years of age and examined the mediation role of BMI. Cardiometabolic follow-up was initiated as participants transitioned into adulthood. Data from the Meta-Air2 substudy were collected from November 27, 2018, to May 31, 2023. Exposures:The California Line Source Dispersion Model was used to calculate mean childhood exposure to traffic-related total nitrogen oxides (NOx) from pregnancy to 13 years of age by calculating mean monthly estimates. Traffic density within a 300-m buffer around participants' residence was calculated as a secondary outcome. Main Outcomes and Measures:Insulin resistance markers were assessed during the recent visit in young adulthood, including the homeostatic model assessment of insulin resistance (HOMA-IR; calculated from fasting glucose and insulin levels) and glycated hemoglobin (HbA1c) level. Participants' BMI growth trajectories, including BMI at 13 years of age and accelerated BMI growth, were analyzed as potential mediators. Using fully adjusted PROCESS macro mediation models, their role in mediating the association between traffic-related total NOx exposure and insulin resistance was examined with adjustment for demographic characteristics, smoking status, and parental history of diabetes. Results:Among the 282 participants (mean [SD] age, 24.0 [1.7] years), each 1-SD increase in childhood exposure to traffic-related total NOx was associated with a BMI increase of 0.71 (95% CI, 0.29-1.13) at 13 years of age and adult HOMA-IR increase of 0.55 (95% CI, 0.23-0.87). An estimated mediation effect identified BMI at 13 years of age combined with accelerated BMI growth as accounting for 41.8% of the estimated total effect (β, 0.23; 95% bootstrap CI, 0.01-0.52) between total NOx and HOMA-IR. Similar patterns were observed when exploring traffic density as an exposure or HbA1c level as an outcome. Conclusions and Relevance:In this cohort study of young adults, the long-term association between TRAP and insulin resistance may be partially explained by higher BMI and accelerated BMI growth from early adolescence into young adulthood. These findings highlight the importance of weight management in children, particularly those residing in highly polluted areas.

Autism spectrum disorder (ASD) is a developmental disorder with symptoms that range from social and communication impairments to restricted interests and repetitive behavior and is the 4th most disabling condition for children aged 5-14. Risk factors of ASD are not fully understood. Environmental risk factors are believed to play a significant role in the ASD epidemic.Research focusing on air pollution exposure as an early-life risk factor of autism is growing, with numerous studies finding associations of traffic and industrial emissions with an increased risk of ASD. One of the possible mechanisms linking autism and air pollution exposure is metabolic dysfunction. However, there were no consensus about the key metabolic pathways and corresponding metabolite signatures in mothers and children that are altered by air pollution exposure and cause the ASD. Therefore, we performed a review of published papers examining the metabolomic signatures and metabolic pathways that are associated with either air pollution exposure or ASD risk in human studies.In conclusion, we found that dysregulated lipid, fatty acid, amino acid, neurotransmitter, and microbiome metabolisms are associated with both short-term and long-term air pollution exposure and the risk of ASD. These dysregulated metabolisms may provide insights into ASD etiology related to air pollution exposure, particularly during the perinatal period in which neurodevelopment is highly susceptible to damage from oxidative stress and inflammation.