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Record W4367396248 · doi:10.1016/j.envres.2023.115991

Who benefits most from a prenatal HEPA filter air cleaner intervention on childhood cognitive development? The UGAAR randomized controlled trial

2023· article· en· W4367396248 on OpenAlexafffund
Battsetseg Ulziikhuu, Enkhjargal Gombojav, Chimeglkham Banzrai, Sarangerel Batsukh, Enkhtuul Enkhtuya, Buyantushig Boldbaatar, David C. Bellinger, Bruce P. Lanphear, Lawrence C. McCandless, Pablo A. Nepomnaschy, Katrina G. Salvante, Joanne Weinberg, Ryan W. Allen

Bibliographic record

VenueEnvironmental Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsWechsler Adult Intelligence ScaleRandomized controlled trialPregnancyIntervention (counseling)MedicineSocioeconomic statusEnvironmental healthPsychologyCognitionPopulationPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Air pollution exposure during pregnancy affects children's brain function. Maternal stress and nutrition, socioeconomic status, and the child's sex may modify this relationship. OBJECTIVE: To identify characteristics of children with the largest increases in full-scale IQ (FSIQ) after their mothers used HEPA filter air cleaners during pregnancy. METHODS: In this randomized controlled trial we randomly assigned women to receive 1-2 air cleaners or no air cleaners during pregnancy. We analyzed maternal hair samples for cortisol and dehydroepiandrosterone (DHEA). When the children were 48 months old, we measured FSIQ with the Wechsler Preschool and Primary Scale of Intelligence. We evaluated ten potential modifiers of the intervention-FSIQ relationship using interaction terms in separate regression models. To account for correlations between modifiers, we also used a single regression model containing main effects and intervention x modifier terms for all potential modifiers. RESULTS: Among 242 mother-child dyads with complete data, the intervention was associated with a 2.3-point increase (95% CI: -1.5, 6.0 points) in mean FSIQ. The intervention improved mean FSIQ among children of mothers in the bottom (5.4 points; 95% CI: -0.8, 11.5) and top (6.1 points; 95% CI: 0.5, 11.8) cortisol tertiles, but not among those whose mothers were in the middle tertile. The largest between-group difference in the intervention's effect was a 7.5-point (95% CI: -0.7, 15.7) larger increase in mean FSIQ among children whose mothers did not take vitamins than among children whose mothers did take vitamins (interaction p-value = 0.07). We also observed larger benefits among children whose mothers did not complete university, and those with lower hair DHEA concentrations, hair cortisol concentrations outside the middle tertile, or more perceived stress. CONCLUSION: The benefits of reducing air pollution during pregnancy on brain development may be greatest for children whose mothers who do not take vitamins, experience more stress, or have less education.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.057
GPT teacher head0.348
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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

Citations4
Published2023
Admission routes2
Has abstractyes

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