Alcohol Consumption Per Capita and Suicide
Bibliographic record
Abstract
Importance: At the individual level, alcohol use is an established risk factor for suicide; however, it is unclear whether this is reflected at the population level. If alcohol consumption per capita (APC), a population-level metric of total alcohol consumption used in international frameworks to measure progress in reducing the harmful use of alcohol, is associated with suicide, it could prove to be a useful target for suicide prevention initiatives. Objective: To examine whether there is an association between APC and suicide mortality, and if there is, to evaluate whether it differs by sex. Data Sources: Embase, Medline, PsycINFO, and Web of Science were searched from database inception to February 24, 2025, for original quantitative studies that measured the association between APC and suicide. Study Selection: Included studies consisted of (1) original quantitative studies with a longitudinal observational or cross-sectional ecological design, including pre-post designs; and (2) studies that provided a measure of association. A total of 304 records were initially identified. Data Extraction and Synthesis: Data extraction was completed by 1 reviewer and cross-checked by a second review. Risk of bias was assessed using the Risk of Bias in Nonrandomized Studies of Exposure tool, and evidence quality was assessed using Grading of Recommendations, Assessment, Development, and Evaluations. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was followed. A random-effects meta-analysis was conducted to obtain a pooled estimate of the association between APC and suicide mortality. The presence of a sex difference was assessed using a random-effects meta-regression. Main Outcomes and Measures: The association between APC, measured as alcohol consumed in liters per person, and the suicide mortality rate. Results: A total of 13 studies were included in the main analysis. It was found that, on the population level, every 1-L increase in APC was associated with an increase of 3.59% (95% CI, 2.38%-4.79%) in the suicide mortality rate. There was no evidence of a sex difference in the association of interest. Conclusions and Relevance: In this systematic review and meta-analysis, an increase in APC was associated with an increase in the suicide mortality rate at the population level and that the association was similar across sexes. As such, APC may be a useful target to consider within comprehensive national suicide prevention strategies.
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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 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".