Air pollution and age-dependent changes in emotional behavior across early adolescence in the U.S

A systematic review of air pollution exposure and brain structure and function during development

OBJECTIVES

Air pollutants are known neurotoxicants. In this updated systematic review, we evaluate new evidence since our 2019 systematic review on the effect of outdoor air pollution exposure on childhood and adolescent brain structure and function as measured by magnetic resonance imaging (MRI).

METHODS

Using PubMed, Web of Science, and Scopus we conducted an updated literature search and systematic review of articles published through January 2025, using key terms for air pollution and functional and/or structural MRI. Two raters independently screened all articles using Covidence and implemented the risk of bias instrument for systematic reviews used to inform the World Health Organization Global Air Quality Guidelines.

RESULTS

We identified 29 relevant papers, and 20 new studies met our inclusion criteria. Including six studies from our 2019 review, the 26 publications to date include study populations from the United States, Netherlands, Spain, and United Kingdom. Studies investigated exposure periods spanning pregnancy through early adolescence, and estimated air pollutant exposure levels via personal monitoring, geospatial residential estimates, or school courtyard monitors. Brain MRI occurred when children were on average 6-14.7 years old; however, one study assessed newborns. Several MRI modalities were leveraged, including structural morphology, diffusion tensor imaging, restriction spectrum imaging, arterial spin labeling, magnetic resonance spectroscopy, as well as resting-state and task-based functional MRI. Air pollutants were associated with widespread brain differences, although the magnitude and direction of findings are largely inconsistent, making it difficult to draw strong conclusions.

CONCLUSION

Prenatal and childhood exposure to outdoor air pollution is associated with structural and functional brain variations. Compared to our initial 2019 review comprised of only cross-sectional studies, the current literature now includes longitudinal studies and more advanced neuroimaging methods. Further research is needed to clarify the effects of developmental timing, along with the downstream implications of outdoor air pollution exposure on children's cognitive and mental health.

Associations between air pollution and surrounding greenness with internalizing and externalizing behaviors among schoolchildren

BACKGROUND

Air pollution and greenness are emerging as modifiable risk and protective factors, respectively, in child psychopathology. However, research shows inconsistencies. Here, we examined associations between air pollution and surrounding greenness with internalizing and externalizing behaviors. In addition, the potential modifying role of the genetic susceptibility for these traits and socioeconomic status (SES) was explored.

METHODS

This population-based study included 4485 schoolchildren aged 5-18 years from Spain. Internalizing and externalizing behaviors were assessed using the Child Behavior Checklist (CBCL). Average air pollution (NO2, PM2.5, PM10, PMcoarse, and PM2.5 absorbance) and surrounding greenness (NDVI within 100-m, 300-m, and 500-m buffers) school exposure were estimated for 12 months before outcome assessment. Genetic liability was assessed by computing polygenic risk scores (PRS) and SES was calculated using the Hollingshead Four-Factor Index. Associations were analyzed using negative binomial mixed-effects models.

RESULTS

Although no associations survived multiple testing, we found that increases of 5.48 μg/m3 in PM10 and 2.93 μg/m3 in PMcoarse were associated with a 6% (Mean Ratio (MR) = 1.06; 95% CI: 1.01-1.12) and a 4% (MR = 1.04; 95% CI: 1.00-1.09) increase in internalizing behavior scores. A 0.1 increase in NDVI within a 100-m buffer was associated with a 6% decrease in externalizing behavior (MR = 0.94; 95% CI: 0.89-0.99). Neither differences by sex or age, or moderation effects by PRS or SES, were observed.

CONCLUSIONS

We found preliminary evidence of detrimental effects of air pollution on internalizing behavior and protective effects of greenness on externalizing behavior, which were not modified by sex, age, SES, or genetic liability. If confirmed, these results reinforce the need for improving air quality, especially around schools, as part of preventive strategies focused on childhood psychopathology.

Study on the impact of air pollution on residents' health expenditures in Guangdong, Hong Kong, and Macao Greater Bay Area

The Guangdong, Hong Kong, and Macao Greater Bay Area (GHMA) has experienced economic development and rapid growth of transportation infrastructure in recent years. However, the economic advancement is also accompanied by serious atmospheric pollution, which threatens the health of the residents, thus, it is of great significance to explore the impact of atmospheric pollution on the health expenditures of residents in the GHMA. The article establishes a spatial econometric model to study the impact of atmospheric pollution on residents' health expenditure in the GHMA based on panel data from 2014 to 2021, using nine prefectures in the GHMA as research objects. The results show that: (1) Atmospheric pollution in the GHMA has an obvious spatial agglomeration phenomenon and spatial spillover effect, and the impact of atmospheric pollution on the health of the residents is still very serious; (2) PM2.5 emissions are positively and significantly related to the actual health care cost per person, and the rise in air pollution is the main reason for the rise in public health spending; (3) Other factors also have different impacts on residents' health expenditures. Based on the above research, the article puts forward corresponding policy recommendations.

Exposure to multiple ambient air pollutants changes white matter microstructure during early adolescence with sex-specific differences

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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 from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.