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Record W4409644511 · doi:10.1101/2025.04.19.25325915

Phthalates, Bisphenols, and Childhood Allergic Phenotypes: Findings from Two Birth Cohort Studies

2025· preprint· en· W4409644511 on OpenAlexafffundabout
Thomas Boissiere-O’Neill, Nina Lazarevic, Anne‐Louise Ponsonby, Peter D. Sly, Aimin Chen, Tamara Blake, Jeffrey R. Brook, Cassidy Du Berry, Louise King, Theo J. Moraes, Elinor Simons, Padmaja Subbarao, Dwan Vilcins

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsChildren's Hospital Research Institute of ManitobaHospital for Sick ChildrenUniversity of AlbertaPublic Health OntarioUniversity of Toronto
FundersNational Health and Medical Research CouncilCanadian Institutes of Health ResearchBarwon Health FoundationPercy Baxter Charitable TrustAustralian GovernmentState Government of VictoriaShepherd FoundationDeakin UniversityMurdoch Children's Research InstituteJack Brockhoff FoundationMedical Research CouncilChildren’s Hospital of Wisconsin Research Institute
KeywordsCohortPhenotypeMedicineCohort studyGeneticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Background Phthalates and bisphenols may contribute to childhood allergic outcomes, but whether these are differentially associated with atopic or non-atopic phenotypes is uncertain. We investigated whether early-life exposure to these chemicals differentially impacts atopic and non-atopic allergic outcomes. Methods We used two prospective birth cohorts to investigate distinct exposure windows. The Barwon Infant Study (n = 797) measured urinary phthalate and bisphenol metabolites at 36 weeks’ gestation. The Canadian Healthy Infant Longitudinal Development Study (n = 993) measured phthalate metabolites at 3, 12, and 36 months. Atopy was assessed via skin prick tests at 4-5 years. Outcomes included asthma, wheeze, eczema, and rhinitis at 4-5 years. Models were stratified by atopy. We modelled exposure mixtures using quantile G-computation and Bayesian kernel machine regression. Results Phthalate mixtures were associated with increased asthma risk in both exposure windows. Prenatal phthalate mixtures were more strongly associated with non-atopic asthma (adjusted risk ratio [aRR] = 1.83; 95% confidence interval [CI]: 1.10-3.04), with evidence of effect modification by atopy (p = 0.02 for interaction). Postnatal phthalate mixtures were associated with non-atopic asthma (aRR = 1.82, 95% CI: 1.19-2.78), though the association did not differ by phenotype (p = 0.45 for interaction). Phthalate mixtures showed U-shaped (prenatal) and inverse U-shaped (postnatal) associations with atopic asthma, and linear associations with non-atopic asthma. There was little evidence of associations for other allergic outcomes. Conclusion Early-life exposure to phthalates may differentially influence the risk of childhood atopic and non-atopic asthma. Future studies are needed to confirm these associations. HIGHLIGHTS We used two birth cohorts to examine distinct exposure windows to phthalates. Pre-and postnatal phthalate exposure was associated with increased asthma risk. Pre-and postnatal associations with asthma differed by atopic status. There was little evidence of association with other allergic outcomes.

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)0.009
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.327
Teacher spread0.313 · 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 designObservational
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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

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