{"doi":"10.1101/2023.04.28.538763","title":"Neighborhood air pollution is negatively associated with neurocognitive maturation in early adolescence","abstract":"Abstract Adolescence is a key period of neurocognitive maturation. Exposure to high levels of air pollutants have been associated with brain differences in youth, though the relevance of these brain findings to behavioral outcomes such as cognitive development is less clear. In this study, we used the US Environmental Protection Agency’s thresholds for unhealthy levels of fine particulate matter (PM 2.5 ), Ozone (O 3 ), and NO 2 pollutants to compare youth exclusively exposed to high levels of each pollutant to their respective socioeconomically-matched low-pollution peers over a two-year period in the Adolescent Brain Cognitive Development (ABCD) Study. No youth in ABCD study were found to be at or above the unhealthy threshold for NO 2 . Separate multivariate analyses for PM 2.5 ( N High =348; N control =279) and O 3 ( N High =355; N control =324) resulted in two very similar neurocognitive latent variables loading positively on cortical functional maturation and task performance, and negatively on cortical grey matter thickness. We found a significant difference in this neurocognitive maturation latent variable over time between the high-pollution and control groups from 9-10 to 11-12 years of age, such that maturation of cortical networks, increase in task performance, and cortical thinning were significantly higher in the control groups. These results were adjusted for parental income and education and youth’s age, sex, race/ethnicity, site, head-motion, scanner, general factor of psychopathology, pubertal status, and area deprivation index, in addition to the matching between high-pollution and control groups. In conclusion, exposure to high levels of PM 2.5 and O 3 is associated with lags in normative neurocognitive maturation in early adolescence.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":391787,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9586,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1164966,"name":"Chacriya Sereeyothin","orcid":null,"position":1,"is_corresponding":false},{"id":809397,"name":"Kathryn E. Schertz","orcid":"0000-0003-1104-0801","position":2,"is_corresponding":false},{"id":304985,"name":"Mike Angstadt","orcid":"0000-0003-4870-7649","position":3,"is_corresponding":false},{"id":361170,"name":"Alexander Weigard","orcid":"0000-0003-3820-6461","position":4,"is_corresponding":false},{"id":305562,"name":"Marc G. Berman","orcid":"0000-0002-7087-3697","position":5,"is_corresponding":false},{"id":434521,"name":"Mary M. Heitzeg","orcid":"0000-0002-6737-2971","position":6,"is_corresponding":false},{"id":264247,"name":"Monica D. Rosenberg","orcid":"0000-0001-6179-4025","position":7,"is_corresponding":false},{"id":305558,"name":"Omid Kardan","orcid":"0000-0003-4187-5228","position":0,"is_corresponding":true}],"reference_count":63,"raw_metadata":null,"created_at":"2026-07-19T01:18:47.408273Z","pmid":"37205398","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}