Mortality and population drinking: a review of the literature
Bibliographic record
Abstract
The aim of this review was to review research addressing the relationship between population drinking and health, particularly mortality. The review is based primarily on articles published in international journals after 1994 to February 2005, identified via Medline. The method used in most studies is time-series analysis based on autoregressive intergrated moving average (ARIMA) modelling. The outcome measures covered included the following mortality indicators: mortality from liver cirrhosis and other alcohol-related diseases, accident mortality, suicide, homicide, ischaemic heart disease (IHD) mortality and all-cause mortality. The study countries included most of the EU member states as of 1995 (14 countries), Canada and the United States. For Eastern Europe there was only scanty evidence. The study period was in most cases the post-war period. There was a statistically significant relationship between per capita consumption and mortality from liver cirrhosis and other alcohol-related diseases in all countries. In about half the countries, there was a significant relationship between consumption, on one hand, and mortality from accidents and homicide as well as all-cause mortality on the other hand. A link between alcohol and suicide was found in all regions except for mid- and southern Europe. There was no systematic link between consumption and IHD mortality. Overall, a 1-litre increase in per capita consumption was associated with a stronger effect in northern Europe and Canada than in mid- and southern Europe. Research during the past decade has strengthened the notion of a relationship between population drinking and alcohol-related harm. At the same time, the marked regional variation in the magnitude of this relationship suggests the importance of drinking patterns for modifying the impact of alcohol. By and large, there was little evidence for any cardioprotective effect at the population level. It is a challenge for future research to reconcile this outcome with the findings from observational studies, most of which suggest a protective effect of moderate drinking.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".