Does Drinking Within Low-Risk Guidelines Prevent Harm? Implications for High-Income Countries Using the International Model of Alcohol Harms and Policies
Bibliographic record
Abstract
OBJECTIVE: Many countries propose low-risk drinking guidelines (LRDGs) to mitigate alcohol-related harms. North American LRDGs are high by international standards. We applied the International Model of Alcohol Harms and Policies (InterMAHP) to quantify the alcohol-caused harms experienced by those drinking within and above these guidelines. We customized a recent Global Burden of Disease (GBD) analysis to inform guidelines in high-income countries. METHOD: Record-level death and hospital stay data for Canada were accessed. Alcohol exposure data were from the Canadian Substance Use Exposure Database. InterMAHP was used to estimate alcohol-attributable deaths and hospital stays experienced by people drinking within LRDGs, people drinking above LRDGs, and former drinkers. GBD relative risk functions were acquired and weighted by the distribution of Canadian mortality. RESULTS: More men (18%) than women (7%) drank above weekly guidelines. Adherence to guidelines did not eliminate alcohol-caused harm: those drinking within guidelines nonetheless experienced 140 more deaths and 3,663 more hospital stays than if they had chosen to abstain from alcohol. A weighted relative risk analysis found that, for both women and men, the risk was lowest at a consumption level of 10 g per day. For all levels of consumption, men were found to experience a higher weighted relative risk than women. CONCLUSIONS: Drinkers following weekly LRDGs are not insulated from harm. Greater than 50% of alcohol-caused cancer deaths are experienced by those drinking within weekly limits. Findings suggest that guidelines of around one drink per day may be appropriate for high-income countries.
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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 | 0.001 | 0.001 |
| 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".