Does the Path From Cigarette Smoking to Suicide Death Go Through the Hospital? A Causal Mediation Analysis in a National Canadian Sample
Bibliographic record
Abstract
Background: Although many epidemiological studies show an association of cigarette smoking with suicide the path to the latter is not well understood. Objective: Using causal inference methodology with observational data, to examine if smoking leads indirectly to suicide through mental health hospitalization. Design: The study used 11 waves of a cross-sectional national health survey that was linked with hospitalization and death registers. Methods: The data came from Canadian Community Health Survey respondents (n = 723 665) between the years 2000 and 2014. These respondents agreed to link their data with hospitalization and death registers and were followed for an average of 9.18 (SD: 4.42; range: 3 to 17) years. Mediation models, one each for men and women, were created in which lifetime daily smoking was the exposure, mental health hospitalization was the mediator, and death by suicide was the outcome, adjusting for 11 covariates reported at survey participation. Results: In both men and women, the direct effect of daily smoking was larger than the indirect effect through hospitalization for mental conditions. The direct effect of smoking was 1.76 (95% CI: 1.47-2.10) for men and 2.60 (95% CI: 1.90-3.57) for women. The indirect effect through mental health hospitalization was 1.07 (95% CI: 1.05-1.09) for men and 1.04 (95% CI: 0.99-1.09) for women. Conclusion: A relatively smaller proportion of the daily smoking-suicide association is transmitted indirectly through mental health hospitalizations compared to a direct effect. Suicide interventions focusing on people hospitalized for mental disorders may miss many suicidal people, so primary prevention and secondary prevention of smoking are crucial.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".