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Record W2791856972 · doi:10.1183/13993003.01884-2017

Effect modification of perinatal exposure to air pollution and childhood asthma incidence

2018· article· en· W2791856972 on OpenAlexafffundabout
Éric Lavigne, Marc‐André Bélair, Daniel Rodriguez Duque, T. Minh, David M. Stieb, Perry Hystad, Aaron van Donkelaar, Randall V. Martin, Dan L. Crouse, Eric Crighton, Hong Chen, Richard T. Burnett, Scott Weichenthal, Paul J. Villeneuve, Teresa To, Jeffrey R. Brook, Markey Johnson, Sabit Cakmak, Abdool S. Yasseen, Mark Walker

Bibliographic record

VenueEuropean Respiratory Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsOntario Stroke NetworkChildren's Hospital of Eastern OntarioEnvironment and Climate Change CanadaSickKids FoundationOttawa HospitalCarleton UniversityUniversity of New BrunswickHospital for Sick ChildrenPublic Health OntarioUniversity of OttawaPublic Health Agency of CanadaMcGill UniversityInstitute for Clinical Evaluative SciencesUniversity of TorontoDalhousie UniversityHealth Canada
FundersHealth CanadaClean Air Regulatory AgendaOntario Ministry of Health and Long-Term CarePublic Health AgencyInstitute for Clinical Evaluative SciencesPublic Health Agency of Canada
KeywordsMedicineIncidence (geometry)AsthmaEnvironmental healthAir pollutionPollutionPediatricsImmunology

Abstract

fetched live from OpenAlex

Perinatal exposure to ambient air pollution has been associated with childhood asthma incidence; however, less is known regarding the potential effect modifiers in this association. We examined whether maternal and infant characteristics modified the association between perinatal exposure to air pollution and development of childhood asthma.761 172 births occurring between 2006 and 2012 were identified in the province of Ontario, Canada. Associations between exposure to ambient air pollutants and childhood asthma incidence (up to age 6 years) were estimated using Cox regression models.110 981 children with asthma were identified. In models adjusted for postnatal exposures, second-trimester exposures to particulate matter with a 50% cut-off aerodynamic diameter ≤2.5 μm (hazard ratio (HR) per interquartile range (IQR) increase 1.07, 95% CI 1.06-1.09) and nitrogen dioxide (HR per IQR increase 1.06, 95% CI 1.03-1.08) were associated with childhood asthma development. Enhanced impacts were found among children born to mothers with asthma, who smoked during pregnancy or lived in urban areas during pregnancy, males and children born preterm or of low birthweight.Prenatal exposure to air pollution may have a differential impact on the risk of asthma development, according to maternal and infant characteristics.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.295
Teacher spread0.272 · 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.

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

Citations89
Published2018
Admission routes3
Has abstractyes

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