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Maternal Exposure to Air Pollutions and Risk of Autism in Children: A Systematic Review and Meta-analysis

2019· review· en· W2981786751 on OpenAlexaffabout
HeeKyoung Chun, Cheryl Leung, Wen Su, Judy McDonald, Hyeong‐Moo Shin

Bibliographic record

VenueEnvironmental Epidemiology · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth CanadaUniversity of Ottawa
Fundersnot available
KeywordsMeta-analysisFrequentist inferenceConfidence intervalOdds ratioMedicineRandom effects modelPublication biasAutism spectrum disorderEnvironmental healthDemographyBayesian probabilityAutismStatisticsPsychiatryInternal medicineBayesian inferenceMathematics

Abstract

fetched live from OpenAlex

TPS 731: Neurological effects in children, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background: The number of children diagnosed with autism spectrum disorder (ASD) has increased. This systematic review and meta-analysis aimed to summarize the association between maternal exposure to outdoor air pollution and ASD in children. Methods: A systematic literature search in three databases (Medline, Embase, and Web of Science) was performed using subject headings related to ASD and maternal exposure to air pollution. Eligible studies were screened based on predetermined criteria, and risk of bias was assessed by the Newcastle-Ottawa Scale. For meta-analyses, the studies were grouped by air pollutant and exposure time (prenatal period and trimesters). Within-group studies were standardized by log odds ratio (OR) and then combined by three meta-analysis methods: frequentist fixed and random effects models, and Bayesian random effects model due to the small number of studies. Results: The initial search identified 1,302 papers, of which 20 studies remained for final analysis after duplicates and ineligible studies were removed. Of the 20 studies, 9, 11, 10, and 6 studies, respectively, investigated the association of ASD with PM2.5, PM10, NO2, and ozone. The frequentist and Bayesian random effects models resulted in different statistical significance. For prenatal period, frequentist meta-analysis returned significant pooled ORs for PM2.5 (1.073 with 95% confidence interval (1.008, 1.142)) and ozone (1.010: (1.002, 1.017)), but Bayesian meta-analysis showed ORs with wider uncertainty for PM2.5 (1.075 with 95% posterior interval (0.966, 1.222)) and ozone (1.010: (0.907, 1.133)). Trimester 3 appeared to have higher pooled ORs for PM2.5, PM10, NO2, and ozone. Patterns in the time-varying associations over the trimester were inconsistent, as between-study differences were apparent. Conclusions: There is marginal evidence for positive associations between maternal exposure to PM2.5, but not PM10, NO2, and ozone, and ASD development in children during pregnancy. However, trends in associations over trimesters were inconsistent between studies and between air pollutants.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.373
Teacher spread0.268 · 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 designMeta-analysis
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

Citations2
Published2019
Admission routes2
Has abstractyes

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