Evaluation of the risk relationship between average alcohol volume consumed and suicide in the USA: an analysis of mortality linked cohort data
Bibliographic record
Abstract
OBJECTIVE: Alcohol use disorder is an established risk factor for suicide; however, it is largely unknown whether subclinical levels of drinking may also contribute to the risk of suicide. The objective was to evaluate the relationship between average alcohol volume consumed per day and suicide. METHODS: Data from the annual, cross-sectional National Health Interview Survey, 1997-2018 in the USA, was obtained and linked to the 2019 National Death Index. The association between average alcohol volume consumed in grams per day (g/day) and suicide was quantified using Cox proportional hazards model (multiplicative) and Aalen's additive hazard model. All analyses were stratified by sex, and adjusted for education, marital status, psychological distress, race and ethnicity, and survey year. RESULTS: On the multiplicative scale, for males, former drinkers and those who consumed on average >40-60 g/day had about 43% (HR=1.43, 95% CI 1.03, 2.01) and 72% (HR=1.72, 95% CI 1.14, 2.60) greater risk of dying by suicide, compared with lifetime abstainers, respectively. There was no significant association found for former or current drinkers among females, on the multiplicative scale. On the additive scale, for males, drinking >40-60 g/day on average was associated with 22.7 (95% CI 6.0, 39.4) additional deaths per 100 000 person-years, while for females, being a former drinker and drinking >0-20 g/day on average was associated with 5.5 (95% CI 0.7, 10.4) and 1.9 (95% CI 0.2, 3.5) additional deaths per 100 000 person-years, compared with lifetime abstainers. The level of education was not found to modify the focal relationship for males or females. CONCLUSIONS: The findings suggest that the relationship between average alcohol volume consumed per day and suicide is nuanced. Additional research on the respective relationship is needed, including repeated measures of average alcohol consumption over time.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".