The association between hot days and substance-related suicides: a time-stratified case-crossover analysis in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Hot weather can negatively impact mental health and increase the risk of suicide. The relationship between heat and risk of suicide is not fully understood, and varies geographically across regions with differing climates, cultures, and socio-economic factors. The objective of this study was to investigate the relationship between hot summer days and suicides in British Columbia, Canada (BC). METHODS: A time-stratified case-crossover design was used to estimate the relationship between hot days (exposure) and suicide (outcome), considering same-day and two-day mean temperature. Conditional logistic regression was used to estimate the odds ratio (OR) for the association between hot days and suicides for three outcomes including: (1) suicide attempts by self-poisoning extracted from BC Drug and Poison Information Centre (DPIC) database (2012-2023); (2) completed suicides by self-poisoning extracted from BC vital statistics (2004-2023); and (3) completed suicides by violent methods extracted from BC vital statistics (2004-2023). Analyses were stratified by sex, age, ecological region, substance types used in self-poisonings, and by methods of violent suicide. RESULTS: There were 9,599 suicide attempts via self-poisoning and 2,571 suicide deaths included in this study. Overall, hot days were associated with increased odds of self-poisoning suicide attempts and deaths, but not with suicide deaths via violent methods. The odds ratio [95% confidence interval] for suicide attempts via self-poisoning on hot days was 1.19 [1.11, 1.29], and 1.48 [1.12, 1.95] for suicide deaths. There was no effect of hot days on suicide deaths by violent methods. The associations varied by day of exposure, sex, age groups, and geography. The effect of hot days was greatest for suicide attempts and deaths involving opioids and elevated for suicide attempts involving opioid and analgesia combinations, analgesics alone, and alcohol. CONCLUSIONS: The risk of suicide via self-poisoning was increased on hot summer days in BC, Canada. However, the relationship was influenced by other factors that vary among individuals and geographies. Policy decisions and future research for suicide-prevention during hot weather should consider sub-population susceptibility.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".