Alcohol accounts for a high proportion of premature mortality in central and eastern Europe
Bibliographic record
Abstract
BACKGROUND: There is a west-east mortality gradient in Europe, more pronounced in men. The objective of this article was to quantify the contribution of alcohol use to the gap in premature adult mortality between three old (France, Sweden and United Kingdom) and four new (Czech Republic, Hungary, Lithuania and Poland) European Union (EU) member states for the year 2002. Russia was added as an external comparator. METHODS: Exposure data were taken from surveys and per capita consumption records from the World Health Organization (WHO) Global Alcohol Database. Mortality data were taken from the WHO databank. The risk relationships were taken from published meta-analyses and from the WHO Comparative Risk Assessment project. Alcohol exposure and relative risk information was combined to derive alcohol-attributable fractions for relevant causes of premature mortality. RESULTS: Alcohol consumption was responsible for 14.6% of all premature adult mortality in the eight countries, 17.3% in men and 8.0% in women. This proportion was clearly higher in the new EU member states and Russia compared with the comparison countries from the old EU. For men, Russia with 29.0 alcohol-attributable premature deaths per 10,000 population had a more than 10-fold higher rate compared with Sweden (2.7 deaths/10,000). For women, the ratio between Hungary (5.0 alcohol-attributable deaths/10,000) and Russia (4.7 deaths/10,000) compared with Sweden (0.5 deaths/10,000) was almost as high, but the rates were much lower. The Czech Republic and Poland showed proportionally less alcohol-attributable premature mortality than the other new EU member states or Russia for both genders, which, however, was still higher than in any of the old EU member states. CONCLUSIONS: Alcohol is a strong contributor to the health gap between western and central and eastern Europe, with both average volume of consumption and patterns of drinking contributing to burden of disease and injury. Alcohol also contributes substantially to male-female differences in mortality and life expectancy. However, there are feasible and cost-effective measures to reduce alcohol-related burden that should be implemented in central and eastern Europe.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".