Life‐time risk of mortality due to different levels of alcohol consumption in seven European countries: implications for low‐risk drinking guidelines
Bibliographic record
Abstract
BACKGROUND AND AIMS: Low-risk alcohol drinking guidelines require a scientific basis that extends beyond individual or group judgements of risk. Life-time mortality risks, judged against established thresholds for acceptable risk, may provide such a basis for guidelines. Therefore, the aim of this study was to estimate alcohol mortality risks for seven European countries based on different average daily alcohol consumption amounts. METHODS: The maximum acceptable voluntary premature mortality risk was determined to be one in 1000, with sensitivity analyses of one in 100. Life-time mortality risks for different alcohol consumption levels were estimated by combining disease-specific relative risk and mortality data for seven European countries with different drinking patterns (Estonia, Finland, Germany, Hungary, Ireland, Italy and Poland). Alcohol consumption data were obtained from the Global Information System on Alcohol and Health, relative risk data from meta-analyses and mortality information from the World Health Organization. RESULTS: The variation in the life-time mortality risk at drinking levels relevant for setting guidelines was less than that observed at high drinking levels. In Europe, the percentage of adults consuming above a risk threshold of one in 1000 ranged from 20.6 to 32.9% for women and from 35.4 to 54.0% for men. Life-time risk of premature mortality under current guideline maximums ranged from 2.5 to 44.8 deaths per 1000 women in Finland and Estonia, respectively, and from 2.9 to 35.8 deaths per 1000 men in Finland and Estonia, respectively. If based upon an acceptable risk of one in 1000, guideline maximums for Europe should be 8-10 g/day for women and 15-20 g/day for men. CONCLUSIONS: If low-risk alcohol guidelines were based on an acceptable risk of one in 1000 premature deaths, then maximums for Europe should be 8-10 g/day for women and 15-20 g/day for men, and some of the current European guidelines would require downward revision.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".