Does Mental Health Status Influence Susceptibility to the Physiologic Effects of Air Pollution? A Population Based Study of Canadian Children
Bibliographic record
Abstract
BACKGROUND: Both air pollution exposure and the presence of mental illness are associated with an increased risk of physical illness. OBJECTIVE: To determine whether or not children with less favourable mental health are more susceptible to pulmonary and cardiovascular effects of ambient air pollution, compared to those who are mentally healthy. METHODS: We carried out a cross-sectional study of 1,883 children between the ages of 6 and 17 years of age who participated in the Canadian Health Measures population survey between 2007 and 2009. Subjects were assigned the air pollution values obtained from the National Air Pollution monitor closest to their neighborhood. Lung function, heart rate and blood pressure were stratified by indicators of mental health. The latter were ascertained by questions about feelings of happiness, a diagnosed mood disorder, and the emotional symptom subscale of the Strengths and Difficulties Questionnaire. RESULTS: Among those who reported a mood disorder, an interquartile increase in ozone was associated with increases in systolic and diastolic pressures of 3.8 mmHg (95% CI 1.6, 5.9) and 3.0mmHg (95%CI 0.9, 5.2) respectively, and a decreases in FVC of 7.6% (95% CI 2.9, 12.3). No significant changes in these variables were observed in those who did not report a mood disorder. Among those with unfavourable emotional symptoms, ozone was associated with a 6.4% (95% CI 1.7, 11.3) increase in heart rate, a 4.1% (95%CI 1.2, 7.1) increase in systolic blood pressure, and a 6.0% (95% CI 1.4, 10.6) decrease in FEVl. No significant effect was seen in these variables among those with no emotional symptoms. CONCLUSIONS: In the Canadian population, children who report mood disorders or unfavourable emotional symptoms appear to be more vulnerable to the adverse physiologic effects of air pollution.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".