Parental Stress Increases the Detrimental Effect of Traffic Exposure on Children's Lung Function
Bibliographic record
Abstract
RATIONALE: Emerging evidence indicates that psychosocial stress enhances the effect of traffic exposure on the development of asthma. OBJECTIVES: We hypothesized that psychosocial stress would also modify the effect of traffic exposure on lung function deficits. METHODS: We studied 1,399 participants in the Southern California Children's Health Study undergoing lung function testing (mean age, 11.2 yr). We used hierarchical mixed models to assess the joint effect of traffic-related air pollution and stress on lung function. MEASUREMENTS AND MAIN RESULTS: Psychosocial stress in each child's household was assessed based on parental response to the perceived stress scale (range, 0-16) at study entry. Exposures to nitric oxide, nitrogen dioxide, and total oxides of nitrogen (NOx), surrogates of the traffic-related pollution mixture, were estimated at schools and residences based on a land-use regression model. Among children from high-stress households (parental perceived stress scale > 4) deficits in FEV1 of 4.5 (95% confidence interval, -6.5 to -2.4) and of 2.8% (-5.7 to 0.3) were associated with each 21.8 ppb increase in NOx at homes and schools, respectively. These pollutant effects were significantly larger in the high-stress compared with lower-stress households (interaction P value 0.007 and 0.05 for residential and school NOx, respectively). No significant NOx effects were observed in children from low-stress households. A similar pattern of association was observed for FVC. The observed associations for FEV1 and FVC remained after adjusting for sociodemographic factors and after restricting the analysis to children who do not have asthma. CONCLUSIONS: A high-stress home environment is associated with increased susceptibility to lung function effects of air pollution both at home and at school.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".