Traffic-related air pollution and incident asthma in a high-risk birth cohort
Bibliographic record
Abstract
Abstract \nOBJECTIVES: \nThe risk of incident asthma and bronchial hyper-reactivity associated with early life exposure to traffic-related air pollution has not been fully elucidated. We aimed to evaluate the hypothesis that the risk of new onset asthma is positively associated with early exposure to traffic-related air pollution in a well-characterised high-risk birth cohort. \nMETHODS: \nInfants at high-risk for asthma were recruited for an intervention study. Birth year exposures to NO, NO(2), black carbon and PM(2.5) were estimated by land use regression. At 7 years of age, asthma was assessed by a paediatric allergist and bronchial hyper-reactivity was measured by methacholine challenge. Associations between exposures and outcomes were analysed by stepwise multiple logistic regression, adjusted for potential confounding variables. \nRESULTS: \nExposure estimates were available for 184 children; 23 were diagnosed with asthma and 68 with bronchial hyper-reactivity. The IQR (4.1 μg/m(3)) of birth year PM(2.5) was associated with a significantly increased risk of asthma (OR 3.1, 95% CI 1.3 to 7.4) and with a trend to increased risk of bronchial hyper-reactivity. Similar findings were noted in association with NO and NO(2), while black carbon did not appear to confer increased risk. \nCONCLUSION: \nModest elevations in exposure to some traffic-related air pollutants during the year of birth are associated with new onset asthma assessed at age 7. That significant associations were revealed in spite of a limited sample size emphasises the strengths of a high-risk birth cohort model, along with individual air pollution exposure estimates and well-characterised data on covariates and outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".