Parental stress increases the effect of traffic-related air pollution on childhood asthma incidence
Bibliographic record
Abstract
Exposure to traffic-related pollution (TRP) and tobacco smoke have been associated with new onset asthma in children. Psychosocial stress-related susceptibility has been proposed to explain social disparities in asthma. We investigated whether low socioeconomic status (SES) or high parental stress modified the effect of TRP and in utero tobacco smoke exposure on new onset asthma. We identified 2,497 children aged 5-9 years with no history of asthma or wheeze at study entry (2002-2003) into the Children's Health Study, a prospective cohort study in southern California. The primary outcome was parental report of doctor-diagnosed new onset asthma during 3 years of follow-up. Residential exposure to TRP was assessed using a line source dispersion model. Information about maternal smoking during pregnancy, parental education (a proxy for SES), and parental stress were collected in the study baseline questionnaire. The risk of asthma attributable to TRP was significantly higher for subjects with high parental stress (HR 1.51 across the interquartile range for TRP; 95% CI 1.16-1.96) than for subjects with low parental stress (HR 1.05, 95% CI 0.74-1.49; interaction P value 0.05). Stress also was associated with larger effects of in utero tobacco smoke. A similar pattern of increased risk of asthma was observed among children from low SES families who also were exposed to either TRP or in utero tobacco smoke. These results suggest that children from stressful households are more susceptible to the effects of TRP and in utero tobacco smoke on the development of asthma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".