Trends in self-reported past alcoholic beverage consumption and ethanol intake from 1950 to 1995 observed in eight European countries participating in the European Investigation into Cancer and Nutrition (EPIC)
Bibliographic record
Abstract
OBJECTIVE: To describe the trends of self-reported past consumption of alcoholic beverages and ethanol intake from 1950 to 1995 within the European Prospective Investigation into Cancer and Nutrition (EPIC). DESIGN: Data on consumption of beer/cider, wine and liqueur/spirits were obtained retrospectively at age 20, 30 and 40 years to calculate average consumption and ethanol intake for the time periods 1950-1975 (at age 20), 1960-1985 (at age 30) and 1970-1995 (at age 40). Regression analysis was conducted with the time period data to assess trends in past alcoholic beverage consumption and ethanol intake with time. SETTING: The EPIC project. SUBJECTS: In total, 392 064 EPIC participants (275 249 women and 116 815 men) from 21 study centres in eight European countries. RESULTS: Generally, increases in beer/cider consumption were observed for most EPIC centres for 1950-1975, 1960-1985 and 1970-1995. Trends in wine consumption differed according to geographical location: downward trends with time were observed for men in southern European EPIC centres, upward trends for those in middle/northern European study centres. For women, similar but less pronounced trends were observed. Because wine consumption was the major contributor to ethanol intake for both men and women in most study centres, time trends for ethanol intake showed a similar geographical pattern to that of wine consumption. CONCLUSION: The different trends in alcoholic beverage consumption and ethanol intake suggest that information depicting lifetime history of ethanol intake should be included in analyses of the relationship between ethanol and chronic diseases, particularly in multi-centre studies such as EPIC.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".