Air Pollution and Emergency Department Visits for Depression in Edmonton, Canada
Bibliographic record
Abstract
OBJECTIVE: Depression is a common cause of morbidity. Sufferers are very sensitive to many external factors. Emergency department (ED) visits for this condition can be associated with the concentration of ambient air pollutants. The study objective was to examine and assess the associations between ED visits for depression and ambient air pollution. DESIGN AND METHODS: The present study analyzed 15,556 ED visits for depression (ICD-9: 311) at Edmonton hospitals between 1992 and 2002. The data were clustered based on the triplet {year, month, day of the week}. The generalized linear mixed models (GLMM) technique was used to regress the logarithm of the clustered counts for ED visits for depression on the levels of air pollutants (CO, NO2, SO2, O3, PM10 and PM2.5) and the meteorological variables. The number of ED visits for depression was analyzed separately for all patients, and males and females. An analysis by season was also conducted: for the whole year (I-XII), warm season (IV-IX), and cold season (X-III). RESULTS: After adjusting for temperature and relative humidity, the following increments in daily depression-related ED visits could be noted: 6.9% (95% CI: 1.3, 12.9) for carbon monoxide (CO) for all patients in warm season; 7.4% (95% CI: 0.5, 14.8) for nitrogen dioxide (NO2) for female patients in warm season; 4.5% (95% CI: 0.1, 9.1) for sulphur dioxide (SO2) for female patients in warm season; 6.9% (95% CI: 0.6, 13.6) for ground level ozone (O3, 1-day lagged) for female patients in warm season; 7.2% (95% CI: 2.7, 12.0) for particulate matter (PM10) for females in cold season; and 7.2% (95% CI: 2.0, 12.8) for particulate matter (PM2.5) for females in cold season. CONCLUSIONS: The findings provide support for the hypothesis that ED visits for depression are associated with exposure to ambient air pollution.
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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".