A dose-response meta-analysis on the relationship between average amount of alcohol consumed and death by suicide
Bibliographic record
Abstract
BACKGROUND: To determine whether sub-clinical levels of drinking may contribute to suicide risk, and whether the risk differs by sex, we aimed to evaluate the relationship between average amount of alcohol consumed per day and death by suicide. METHODS: A systematic literature search was performed in Embase, Medline, PsycINFO, PubMed, and Web of Science from database inception up to April 27, 2022. The search strategies incorporated a combination of medical subject headings and keywords for "alcohol use" and "suicide". One-stage dose-response meta-analyses using a restricted maximum likelihood random-effect estimator were conducted to explore the relationship between average alcohol volume consumed and suicide, by sex. Three different shapes of the dose-response relationship-linear (on the log-scale), quadratic, and restrictive cubic splines-were tested. RESULTS: A total of eight studies were included (three studies for females (n=781,205), and eight studies for males (n=1,215,772)). A linear dose-response relationship between average alcohol volume consumed and the log-risk of suicide was identified for both males and females. For males and females, a relative risk (RR) of 1.11 (95% CI: 1.05, 1.18) and 1.64 (95% CI: 1.07, 2.51) for suicide when consuming an average of 10 g of pure alcohol per day compared to lifetime abstention, 1.38 (95% CI: 1.14, 1.66) and 4.39 (95% CI: 1.21, 15.88) for 30g/day, and 1.71 (95% CI: 1.25, 2.33) and 11.75 (95% CI: 1.38, 100.33) for 50g/day, respectively. CONCLUSIONS: As consumption increases, the risk of suicide increases proportionally. The risk of suicide associated with average daily alcohol consumption may be elevated for females, compared with males. Albeit, more research is needed, particularly among females.
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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 | 0.021 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.057 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".