Cross‐country comparison of proportion of alcohol consumed in harmful drinking occasions using the International Alcohol Control Study
Bibliographic record
Abstract
INTRODUCTION AND AIMS: This study examines the proportion of alcohol markets consumed in harmful drinking occasions in a range of high-, middle-income countries and assesses the implications of these findings for conflict of interest between alcohol producers and public health and the appropriate role of the alcohol industry in alcohol policy space. DESIGN AND METHODS: Cross-sectional surveys were conducted in 10 countries as part of the International Alcohol Control study. Alcohol consumption was measured using location- and beverage-specific measures. A level of consumption defined as harmful use of alcohol was chosen and the proportion of the total market consumed in these drinking occasions was calculated for both commercial and informal alcohol. RESULTS: In all countries, sizeable proportions of the alcohol market were consumed during harmful drinking occasions. In general, a higher proportion of alcohol was consumed in harmful drinking occasions by respondents in the middle-income countries than respondents in the high-income countries. The proportion of informal alcohol consumed in harmful drinking occasions was lower than commercial alcohol. DISCUSSION AND CONCLUSIONS: Informal alcohol is less likely to be consumed in harmful drinking occasions compared with commercial alcohol. The proportion of commercial alcohol consumed in harmful drinking occasions in a range of alcohol markets shows the reliance of the transnational alcohol corporations on harmful alcohol use. This reliance underpins industry lobbying against effective policy and support for ineffective approaches. The conflict of interest between the alcohol industry and public health requires their exclusion from the alcohol policy space.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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".