MétaCan
Menu
Back to cohort
Record W2889237026 · doi:10.1016/j.envint.2018.08.040

A population-based birth cohort study of the association between childhood-onset asthma and exposure to industrial air pollutant emissions

2018· article· en· W2889237026 on OpenAlexafffundabout
Stéphane Buteau, Louis-François Tétreault, Philippe Gamache, Michel Fournier, Allan Brand, Tom Kosatsky, Audrey Smargiassi

Bibliographic record

VenueEnvironment International · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversité de MontréalBC Centre for Disease ControlMcGill UniversityUniversité LavalInstitut National de Santé Publique du Québec
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsPollutantAir pollutantsAsthmaEnvironmental healthCohortCohort studyMedicineAir pollutionPopulationPediatricsEnvironmental scienceImmunologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Studies of the association between air pollution and asthma onset have mostly focused on urban and traffic-related air pollution. We investigated the associations between exposure to industrial emissions and childhood-onset asthma in a population-based birth cohort in Quebec, Canada, 2002–2011. The cohort was built from administrative health databases. We developed separately for PM2.5 and SO2 different metrics representing children's time-varying residential exposure to industrial emissions: 1) yearly number of tons of air pollutant emitted by industries located within 2.5 km of the residence; 2) distance to the nearest “major emitter” (≥100 tons) of either PM2.5 and SO2 within 7.5 km of the residence, and; 3) tons of air pollutant emitted by the nearest “major emitter” within 7.5 km, weighted by the inverse of the distance and the percentage of time that the residence was downwind. To handle the large number of zeros (i.e., children unexposed) we decomposed the exposure variable into two covariates simultaneously included in the regression model: a binary indicator of exposure and a continuous exposure variable centered at the mean value among exposed children. We performed Cox models using age as the time axis, adjusted for gender, material and social deprivation and calendar year. We indirectly adjusted for unmeasured secondhand smoke. The cohort included 722,667 children and 66,559 incident cases of asthma. Across the different exposure metrics, mean percentage changes in the risk of asthma onset in children exposed to the mean relative to those unexposed ranged from 4.5% (95% CI: 2.8, 6.3%) to 10.6% (95% CI: 6.2, 15.2%) for PM2.5 and, from 1.1% (95% CI: −0.1, 3.3%) to 8.9% (95% CI: 7.1, 11.1%) for SO2. Indirect adjustment for secondhand smoke did not substantially affect the associations. In children exposed, the risk of asthma onset increased with the magnitude of the exposure for all metrics, except the distance to the nearest major emitter of SO2. In this population-based birth cohort, residential exposure to industrial air pollutant emissions was associated with childhood-onset asthma. Additional studies with improved models for estimating exposure to industrial point-sources are needed to further support the observed associations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 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

Citations58
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueEnvironment InternationalSame topicAir Quality and Health ImpactsFrench-language works237,207