Independent Association of Chronic Smoking and Abstinence With Suicide
Bibliographic record
Abstract
OBJECTIVE: The study examined whether chronic exposure to nicotine is independently associated with suicide. METHODS: Data from the 1993 National Mortality Followback Survey in the United States were analyzed by using a case-control design. Data for 989 suicide decedents were compared with data for 3,125 accident and homicide decedents. Inclusion criteria were ever smoking 100 cigarettes and white or black race. The exclusion criterion was death from natural or undetermined causes. Three smoking parameters were compared: lifetime smoking duration, ever quitting, and abstinence duration. Covariates were the manner of death, which was derived from coroners' death certificates, and data pertaining to the last year of life, which was reported by next of kin, on depressive symptoms, alcohol and drug use, veteran status, having a firearm in the home, and living alone. RESULTS: In multivariate, fully adjusted analyses, longer lifetime smoking (≥ 41 versus ≤ 10 years) was associated with higher odds of suicide (odds ratio [OR]=2.26, 95% confidence interval [CI]=1.30-3.93). Quitting smoking was associated with lower odds of suicide (OR=.37, CI=.25-.55), as was longer abstinence duration (≥ 11 versus <5 years) (OR=.33, CI=.21-.52). These associations were observed only among males. CONCLUSIONS: Findings indicated a probable independent association between suicide and current smoking and longer lifetime smoking duration. The findings are additional grounds to investigate smoking as a possible independent cause of suicide.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".