Daily changes in ambient air pollution concentrations and temperature and suicide mortality in Canada: Findings from a national time-stratified case-crossover study
Bibliographic record
Abstract
Worldwide, approximately 1900 people die by suicide daily. Daily elevations in air pollution and temperature have previously been linked to a higher risk of death from suicide. To date, there have been relatively few studies of air pollution and suicide, particularly at a national level. National analyses play an important role in shaping health policy to mitigate against adverse health outcomes. We used a time-stratified case-crossover study design to investigate the influence of short-term (i.e., day to day) interquartile range (IQR) increases in air pollutants (nitrogen dioxide [NO2], ozone [O3], and fine particulate matter [PM2.5]) and temperature on suicide mortality in Canada between 2002 and 2015. For air pollution models, odds ratios (ORs) derived from conditional logistic regression models were adjusted for average daily temperature, and holidays. For temperature models, ORs were adjusted for holidays. Stratified analyses were undertaken by suicide type (non-violent and violent), sex, age, and season. Analyses are based on 50,800 suicide deaths. Overall, temperature effects were stronger than those for air pollution. A same day IQR increase in temperature (9.6 °C) was associated with a 10.1% increase (95% confidence interval (CI): 9.0%–11.2%) of death from suicide. For 3-day average increase of O3 (IQR = 14.1 ppb), PM2.5 (IQR = 5.6 μg/m3) and NO2 (IQR = 9.7 ppb) the corresponding risks were 4.7% (95% CI: 3.9, 5.6), 3.4% (95% CI: 3.0, 3.8), and 2.0% (95% CI: 1.1, 2.8), respectively. All pollutants showed stronger associations with suicide during the warmer season (April–September). Stratified analyses revealed stronger associations for both temperature and air pollution in women. Daily increases in air pollution and temperature were found to increase the risk of death from suicide. Females, particularly during warmer season, were most vulnerable to these exposures. Policy decisions related to air pollution and climate change should consider effects on mental health.
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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) | 0.001 | 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".