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Record W4398780482 · doi:10.3389/fpubh.2024.1396251

Association of prenatal and postnatal exposure to air pollution with clinically diagnosed attention deficit hyperactivity disorder: a systematic review

2024· review· en· W4398780482 on OpenAlexaboutno aff
Jinzhu Zhao, Tianyi He, Feng Wang, Wei Liu

Bibliographic record

VenueFrontiers in Public Health · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAttention deficit hyperactivity disorderPrenatal exposureMedicinePsychiatryPediatricsPregnancyEnvironmental healthGestation

Abstract

fetched live from OpenAlex

Attention deficit hyperactivity disorder (ADHD), a prevalent neurodevelopmental disorder in children, originates from a multifaceted interplay of genetic, neurological, and environmental factors. Recent studies have increasingly concentrated on environmental determinants, notably air pollution, and their impact on the risk of developing ADHD. Additionally, previous research has often conflated clinically diagnosed ADHD cases with instances of mere ADHD-like symptoms, a methodology that can introduce bias and obscure the true relationship between environmental factors and ADHD. To address this oversight, our systematic review meticulously investigates the relationship between both prenatal and postnatal exposures to particular air pollutants and strictly clinically diagnosed ADHD. Our comprehensive review encompassed 801 studies from PubMed, Cochrane Library, Web of Science, and Embase databases, out of which eight met our rigorous inclusion criteria. The Newcastle-Ottawa Scale (NOS) was utilized to gauge quality and bias. Our review found substantiated the connection between prenatal exposure to PM 2.5 and NO x and a heightened risk of ADHD, while exposure to PM 10 during the prenatal stage was not associated with ADHD. These findings hint at varied health impacts from different particulate matters and the prospect of gender-specific susceptibilities to such exposures. We also identified an association between postnatal exposure to PM 2.5 , PM 10 , and NO 2 and an increased ADHD risk, underlining the potential neurodevelopmental harms from early exposure to these pollutants. These relationships, seemingly intricate and potentially dose-dependent, underscore the need for more detailed scrutiny. The unique value of our review is in its detailed exploration of the association between specific air pollution exposures and clinically diagnosed ADHD. Our findings offer much-needed clarity in this complex domain and emphasize the importance of future research to standardize exposure and outcome metrics, probe potential mechanisms, and reduce bias and heterogeneity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.181
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.345
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2024
Admission routes1
Has abstractyes

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