Air pollution and daily emergency department visits for depression
Bibliographic record
Abstract
OBJECTIVES: To investigate the potential correlation between ambient air pollution exposure and emergency department (ED) visits for depression. MATERIALS AND METHODS: A hierarchical clusters design was used to study 27 047 ED visits for depression in six cities in Canada. The data used in the analysis contain the dates of visits, daily numbers of diagnosed visits, and daily mean concentrations of air pollutants as well as the meteorological factors. The generalized linear mixed models technique was applied to data analysis. Poisson models were fitted to the clustered counts of ED visits with a single air pollutant, temperature and relative humidity. RESULTS: Statistically significant positive correlations were observed between the number of ED visits for depression and the air concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2) and particulate matter (PM10). The percentage increase in daily ED visits was 15.5% (95% CI: 8.0-23.5) for CO per 0.8 ppm and 20.0% (95% CI: 13.3-27.2) for NO2 per 20.1 ppb, for same day exposure in the warm weather period (April-September). For PM10, the largest increase, 7.2% (95% CI: 3.0-11.6) per 19.4 ug/m3, was observed for the cold weather period (October-March). CONCLUSIONS: The results support the hypothesis that ED visits for depressive disorder correlate with ambient air pollution, and that a large majority of this pollution results from combustion of fossil fuels (e.g. in motor vehicles).
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".