While family income and neighborhood disadvantage have been associated with adolescent mental health, less is known about their independent associations with distinct, group-based patterns of change. Moreover, little is known about how school environments are associated with such mental health trajectory patterns, and if they serve as independent promotive factors or are protective factors that mitigate risk. Data come from the Adolescent Brain Cognitive Development StudySM(ABCD study®; n = 9769; baseline through year 2; ages 9-13). Internalizing and externalizing behaviors were measured with the Child Behavior Checklist. Growth mixture modeling was utilized to identify subgroups with distinct mental health trajectories, and logistic regression was used to examine the association between family income, neighborhood environment and trajectory group membership, and moderation by baseline school and school district characteristics, controlling for age, sex, race/ethnicity, and parental education. Two trajectory classes were identified for internalizing (91%; low-decreasing, 9%; high-increasing) and externalizing behaviors (92%; low-decreasing, 8%; high-stable). Lower family income was associated with a high-increasing trajectory pattern of internalizing and a high-stable pattern of externalizing behaviors. A more positive school climate predicted belonging to the low-decreasing trajectory group for internalizing and externalizing behaviors, though there was no evidence of moderation. Low family income, but not neighborhood disadvantage, was a risk factor for trajectories of internalizing and externalizing behavior elevated within a clinical range that persisted from age 9 through early adolescence. However, a positive school climate was a promotive, rather than a protective, factor for internalizing and externalizing trajectories. Supporting families with resources and enhancing the school context may improve adolescent mental health.

Background:Minority and socioeconomically disadvantaged children face disproportionate air pollution burdens, yet the geographic heterogeneity and intersectional structure of these disparities remain poorly characterized in pediatric populations. Methods:Using baseline data (2016-2018) from the Adolescent Brain Cognitive Development Study, the largest longitudinal study of child brain development in the United States, we estimated residential fine particulate matter (PM2.5) and nitrogen dioxide (NO2) among 9- to 10-year-olds across 21 sites spanning 19 metropolitan areas. We employed an intersectional analytic approach to examine race/ethnicity and socioeconomic effects jointly, and a two-stage meta-analytic design to explicitly model between-site heterogeneity. Results:Hispanic/Latinx and Black children experienced higher average PM2.5 and NO2 than white peers overall, but intersectional analyses revealed that Hispanic/Latinx preadolescents from the lowest income households bore the greatest PM2.5 burden, and higher educated Black families showed increased NO2 exposure relative to those with high school diplomas. Site-specific analyses revealed substantial geographic heterogeneity in disparity magnitude, challenging the assumption of homogeneous national patterns. Conclusion:These findings underscore the need for locally targeted interventions. Nearly all participants exceeded World Health Organization air quality guidelines despite meeting Environmental Protection Agency thresholds, highlighting a regulatory gap with particular relevance to children's developing neurological systems.

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.

Ambient air pollution poses significant risks to brain health. The hippocampus may be particularly vulnerable, yet the extent to which it is impacted in children remains unclear. Using partial least squares correlation, we cross-sectionally analyzed air pollution, brain, and cognitive data from the Adolescent Brain Cognitive Development Study to examine how multi-pollutant exposure influences hippocampal structure and memory in 9–11-year-olds (n = 7,940). Annual average air pollution exposures included PM2.5 (total mass, 15 components, and 6 source factors), NO2, and 8-hour maximum O3. Hippocampal outcomes included microstructure measured using Restriction Spectrum Imaging and hippocampus longitudinal-axis (i.e., head, body, tail) volumes. We examined hippocampal-dependent list-learning using the Rey Auditory Verbal Learning Test. Models were adjusted for demographic, socioeconomic, and neuroimaging factors. PM2.5 total mass was associated with hippocampal microstructure, but not long-axis volume or list-learning ability. Component and source analyses provided greater specificity: higher bromine, sulfate, and vanadium exposure was related to microstructure (72

Background: Outdoor air pollution exposure is associated with structural and functional brain differences and an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering brain regions implicated in psychopathology, such as the amygdala. Here, we examined the association between ambient air pollution exposure and amygdala subregion volumes in 9- to 10-year-olds. Methods: Cross-sectional data from 4473 (55.4% male) Adolescent Brain Cognitive Development (ABCD) Study participants were leveraged. Air pollution exposure was estimated based on each participant’s primary residential address. Using the CIT168 atlas, we quantified total amygdala and 9 subregion volumes from T1- and T2-weighted images. We investigated associations between criteria pollutants (i.e., fine particulate matter [PM2.5], nitrogen dioxide, and ground-level ozone), 15 PM2.5 components, and amygdala subregion volumes and relative volume fractions using both single-pollutant linear mixed-effects regression and partial least squares correlation (PLSC) co-exposure modeling approaches. Results: No significant associations were detected using single-pollutant models. Rather, in examining mixtures of exposures with PLSC, 1 latent dimension (52% variance explained) captured a positive association between calcium and several basolateral subregions. Latent dimensions were also identified for amygdala relative volume fractions (ranging from 30% to 82% variance explained), with PM2.5 and component co-exposure being associated with increases in lateral, but decreases in medial and central, relative volume fractions. Conclusions: PM2.5 and its components are associated with distinct amygdala differences, potentially playing a role in risk for adolescent mental health problems.

Ambient fine particulate matter (PM2.5) pollution is a heterogeneous mixture of chemicals with documented neurotoxic effects. Developmental neuroimaging literature has linked childhood PM2.5 exposure to alterations in brain morphology, microarchitecture, and function, with implications for cognition and psychopathology. However, the extant literature remains largely cross-sectional and often considers PM2.5 a single pollutant, rather than a heterogeneous mixture of chemicals from different sources. This work addresses these gaps by leveraging estimates of exposure to six PM2.5 sources derived from positive matrix factorization, and longitudinal neuroimaging data from a large, geographically-diverse sample of Adolescent Brain Cognitive Development Study youth (N = 6,291) from across the United States (U.S.). To identify exposure-related differences in brain function and assess their geographical generalizability, we used a predictive modeling approach to assess both differences in functional brain network connectivity during childhood (9-11 years of age) and changes in functional brain network connectivity during the transition to adolescence (9-13 years of age) related to PM2.5 exposure. Childhood PM2.5 exposure from traffic emissions and industrial/residual fuel burning were linked to mixed patterns of both stronger and weaker connectivity of sensorimotor networks at ages 9-11 years. Conversely, childhood exposures to secondary pollutants (i.e., ammonium sulfates, nitrates) were linked to largely stronger connectivity of brain networks underlying higher-order cognition that decreased over the following two years. However, these patterns of exposure-related functional connectivity identified in youth across the U.S. better represented youth living in the northeast as compared to youth living in the west. Altogether, this work provides insights into the neurotoxicity of outdoor air pollution exposure in developing sensory and motor systems and potential for biomarkers of eventual psychopathology.

Air pollution is an emerging novel neurotoxicant during childhood and adolescence. However, little is known regarding how fine particulate matter (PM2.5) components and its sources impact brain morphology. We investigated air pollution exposure-related differences in brain morphology using cross-sectional magnetic resonance imaging data from 10,095 children ages 9-11 years-old enrolled in the United States' Adolescent Brain Cognitive Development Study [2016-2018]. Air pollution estimates included fifteen PM2.5 constituent chemicals and metals, and six major sources of PM2.5 (e.g., crustal materials, biomass burning, traffic) identified from prior source apportionment, as well as nitrogen dioxide (NO2) and ozone (O3). After adjusting for demographic, socioeconomic, and neuroimaging covariates, we used partial least squares analyses to identify associations between simultaneous co-exposures and morphological differences in cortical thickness, surface area, and subcortical volumes. We found that greater exposure to PM2.5 and NO2 was associated with decreases in frontal and increases in inferior temporal surface area. PM2.5 component and source analyses linked cortical surface area and thickness to biomass burning (e.g., organic carbon, potassium), crustal material (e.g., calcium, silicon), and traffic (e.g., copper, iron) exposures, while smaller subcortical volumes were linked to greater potassium exposure. This is the first study to show differential effects of several air pollution sources on development of children's brains. Significant associations were found in brain structures involved in several cognitive and social processes, including lower- and higher-order sensory processing, socioemotional behaviors, and executive functioning. These findings highlight differential effects of several air pollution sources on brain structure in preadolescents across the U.S.

The COVID-19 pandemic and school closures adversely affected adolescents' mental health and well-being, with the weight of evidence indicating worse outcomes for students attending school remotely or in a hybrid modality compared to fully in person. We leverage survey data from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) collected from 6,245 adolescents (mean age = 13.2) during the 2020-2021 school year to investigate the moderating effects of race/ethnicity, household income, and neighborhood disadvantage on the relationship between 2020-2021 school modality and outcomes including perceived stress, sadness, and positive affect. For relatively advantaged students, our results corroborate prior findings that students in remote or hybrid schooling report worse mental health outcomes than students who attended fully in person. However, this pattern between schooling modality and mental health disappears or reverses for relatively disadvantaged students. Given substantial within-group variation, these findings underscore the importance of considering varied student needs in developing mental health supports.

Background:Air pollution is a ubiquitous neurotoxicant associated with alterations in structural connectivity. Good habitual sleep may be an important protective lifestyle factor due to its involvement in the brain waste clearance and its bidirectional relationship with immune function. Wearable multisensory devices may provide more objective measures of sleep quantity and quality. We investigated whether sleep duration and efficiency moderated the relationship between prenatal and childhood pollutant exposure and whole-brain white matter microstructural integrity at ages 10-13 years. Methods:We used multi-shell diffusion-weighted imaging data collected on 3T MRI scanners and objective sleep data collected with Fitbit Charge 2 from the 2-year follow-up visit for 2178 subjects in the Adolescent Brain Cognitive Development Study®. White matter tracts were identified using a probabilistic atlas. Restriction spectrum imaging was performed to extract restricted normalized isotropic (RNI) and directional (RND) signal fraction parameters for all white matter tracts, then averaged to calculate global measures. Sleep duration was calculated by summing the time spent in each sleep stage; sleep efficiency was calculated by dividing sleep duration by time spent in bed. Using an ensemble-based modeling approach, air pollution concentrations of PM2.5, NO2, and O3 were assigned to each child's residential addresses during the prenatal period (9-month average before birthdate) as well as at ages 9-10 years. Multi-pollutant linear mixed effects models assessed the associations between global RNI and RND and sleep-by-pollutant interactions, adjusting for appropriate covariates. Results:Sleep duration interacted with childhood NO2 exposure and sleep efficiency interacted with prenatal O3 exposure to affect RND at ages 10-13 years. Longer sleep duration and higher sleep efficiency in the context of higher pollutant exposure was associated with lower RND compared to those with similar pollutant exposure but shorter sleep duration and lower sleep efficiency. Conclusions:Low-level air pollution poses a risk to brain health in youth, and healthy sleep duration and efficiency may increase resilience to its harmful effects on white matter microstructural integrity. Future studies should evaluate the generalizability of these results in more diverse cohorts as well as utilize longitudinal data to understand how sleep may impact brain health trajectories in the context of pollution over time.

Air pollution is a ubiquitous neurotoxicant linked to altered structural brain connectivity. Sleep may offer neuroprotection through its roles in brain waste clearance and immune regulation. Using Fitbit-derived sleep data and multi-shell diffusion MRI from 2178 children (ages 10-13) in the ABCD Study®, we examined whether sleep moderated associations between prenatal and childhood exposure to PM2.5, NO2, and O3 and white matter microstructure. Restriction spectrum imaging yielded restricted normalized isotropic (RNI) and directional (RND) metrics, averaged across tracts. Pollution exposure was estimated at prenatal and childhood (ages 9-10) residences. Linear mixed-effects models tested sleep-by-pollution interactions on RNI/RND. Childhood NO2 and prenatal O3 interacted with sleep duration and efficiency, respectively, to influence RND. Among children with similar pollutant exposure, those with longer sleep duration and higher sleep efficiency had lower RND than peers with poorer sleep. This suggests that healthy sleep may buffer adverse effects of air pollution on white matter integrity.

The adolescent brain is vulnerable to ambient air pollution. Importantly, community-level factors - such as neighborhood disadvantage - that co-occur with air pollution may further enhance this vulnerability and impact brain development. The current study investigated if neighborhood disadvantage moderates the association between residential fine particulate matter (PM2.5) pollution and adolescent brain development, including longitudinal changes in cortical thickness, surface area, and subcortical/white matter volume from ages 9-13 years (n = 8321 participants from the ABCD Study®; 12,634 observations). We found that, in more disadvantaged neighborhoods, higher PM2.5 levels were associated with greater age-related cortical thinning in temporal areas and in most regions of the occipital lobe. Furthermore, independent of neighborhood disadvantage, higher PM2.5 exposure was associated with larger age-related surface area decreases in parietal, occipital, and temporal regions, but smaller age-related increases in right cerebral white matter volume and frontal and temporal region surface area. Similarly, higher PM2.5 exposure was independently associated with greater age-related cortical thinning in the frontal regions, cingulate, and insula, but smaller age-related cortical thickening in temporal regions. Findings have policy implications for air quality improvements alongside investment in disadvantaged neighborhoods to bolster adolescent brain development.

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.

BACKGROUND:Emerging literature suggests that fine particulate matter [with aerodynamic diameter ≤2.5μm (PM2.5)] air pollution and its components are linked to various neurodevelopmental outcomes. However, few studies have evaluated how PM2.5 component mixtures from distinct sources relate to cognitive outcomes in children. OBJECTIVES:This cross-sectional study investigated how ambient concentrations of PM2.5 component mixtures relate to neurocognitive performance in 9- to 10-year-old children, as well as explored potential source-specific effects of these associations, across the US. METHODS:Using spatiotemporal hybrid models, annual concentrations of 15 chemical components of PM2.5 were estimated based on the residential address of child participants from the Adolescent Brain Cognitive Development (ABCD) Study. General cognitive ability, executive function, and learning/memory scores were derived from the NIH Toolbox. We applied positive matrix factorization to identify six major PM2.5 sources based on the 15 components, which included crustal, ammonium sulfate, biomass burning, traffic, ammonium nitrate, and industrial/residual fuel burning. We then utilized weighted quantile sum (WQS) and linear regression models to investigate associations between PM2.5 components' mixture, their potential sources, and children's cognitive scores. RESULTS:Mixture modeling revealed associations between cumulative exposure and worse cognitive performance across all three outcome domains, including shared overlap in detrimental effects driven by ammonium nitrates, silicon, and calcium. Using the identified six sources of exposure, source-specific negative associations were identified between ammonium nitrates and learning & memory, traffic and executive function, and crustal and industrial mixtures and general cognitive ability. Unexpected positive associations were also seen between traffic and general ability as well as biomass burning and executive function. DISCUSSION:This work suggests nuanced associations between outdoor PM2.5 exposure and childhood cognitive performance, including important differences in cognition related both to individual chemicals as well as to specific sources of these exposures. https://doi.org/10.1289/EHP14418.

Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex. We investigate sex-stratified effects of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) at ages 9–10 years on longitudinal patterns of white matter microstructure over a 2-year period. Diffusion-weighted imaging was collected on 3T MRI scanners for 8182 participants (1–2 scans per subject; 45% with two scans) from the Adolescent Brain Cognitive Development (ABCD) Study®. Restriction spectrum imaging was performed to quantify intracellular isotropic (RNI) and directional (RND) diffusion. Ensemble-based air pollution concentrations were assigned to each child’s primary residential address. Multi-pollutant, sex-stratified linear mixed-effect models assessed associations between pollutants and RNI/RND with age over time, adjusting for sociodemographic factors. Here we show higher PM2.5 exposure is associated with higher RND at age 9 in both sexes, with no significant effects of PM2.5 on RNI/RND change over time. Higher NO2 exposure is associated with higher RNI at age 9 in both sexes, as well as attenuating RNI over time in females. Higher O3 exposure is associated with differences in RND and RNI at age 9, as well as changes in RND and RNI over time in both sexes. Criteria air pollutants influence patterns of white matter maturation between 9–13 years old, with some sex-specific differences in the magnitude and anatomical locations of affected tracts. This occurs at concentrations that are below current U.S. standards, suggesting exposure to low-level pollution during adolescence may have long-term consequences. Air pollution is known to affect health, but it is unclear whether it affects the growing human brain. We investigated whether there were differences in the development of white matter connections, which allow for faster communication between different brain regions, in children aged 9-13 years living in areas with relatively low or high air pollution in the USA. In a large group of U.S. teens, we find that polluted air is linked to differences in white matter at ages 9-10 years old and over the next two years. In some cases, males and females showed differences in the part of the brain showing changes and the amount of white matter change. Our study suggests that air pollution levels that are deemed acceptable under current regulations in the USA could have long-term effects on how a child’s brain grows. Further studies are needed to better understand the impact of these changes. Cotter et al. investigate associations between low levels of ambient pollutant exposure and white matter microstructural development during the transition from childhood to adolescence. There are sex-stratified associations, with NO2 primarily affecting females and O3 affecting both sexes over time.

Doctoral social work education is challenged to revisit how we mentor the next generation of social work scholars to decolonize and de-center whiteness in social work research, education, and practice. Building on the existing literature and adopting the Delphi technique with four Delphi rounds that were based on a dialogue with 100 participants at a webinar on anti-racist and inclusive mentoring, an expert panel including members representing doctoral program directors, deans and directors, the Social Work Grand Challenges board on Eliminating Racism, BIPOC scholars, and a doctoral student collaboratively developed this model. This mentoring model included three interconnected components. An explicit definition of Anti-racist & Inclusive Mentoring provides a useful frame to clearly articulate the second component that focuses on action, steps, and strategies of this mentoring process. Effective anti-racist & inclusive mentoring is understood as a parallel process operating at multi-levels including the individual, interpersonal, institutional, and society level. Coordinated anti-racist and inclusive mentoring process efforts will lead to outcomes that include long-term and sustainable system changes and institutional changes. The Anti-Racist & Inclusive Mentoring Model highlights the importance of an interconnected and coordinated effort at multi-levels to create sustainable and impactful mentorship embedded in individual, interpersonal and system changes at school and institutional levels. In addition to doctoral education, the mentoring model will have useful implications for mentoring social work students at undergraduate and graduate levels.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study examines how annual average PM2.5 and NO2 exposure at ages 9-10 years relates to internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at baseline and annually for two follow-up sessions for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Overall, the pollution effects moderated the main effects of age with higher levels of PM2.5 and NO2 leading to an even greater likelihood of having no behavioral problems (i.e., score of zero) with age over time, as well as fewer problems when problems are present as the child ages. Albeit this was on the order equal to or less than a 1-point change. Thus, one year of annual exposure at 9-10 years is linked with very small change in emotional behaviors in early adolescence, which may be of little clinical relevance.

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.

Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM2.5), daily nitrogen dioxide (NO2), and 8-h maximum ozone (O3) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Study℠. Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence – a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9–10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.