Alcohol Consumption and the Physical Availability of Take-Away Alcohol: Systematic Reviews and Meta-Analyses of the Days and Hours of Sale and Outlet Density
Bibliographic record
Abstract
Objective: Systematic reviews and meta-analyses were completed studying the effect of changes in the physical availability of take-away alcohol on per capita alcohol consumption. Previous reviews examining this topic have not focused on off-premise outlets where take-away alcohol is sold and have not completed meta-analyses. Method: Systematic reviews were conducted separately for policies affecting the temporal availability (days and hours of sale) and spatial availability (outlet density) of take-away alcohol. Studies were included up to December 2015. Quality criteria were used to select articles that studied the effect of changes in these policies on alcohol consumption with a focus on natural experiments. Random-effects meta-analyses were applied to produce the estimated effect of an additional day of sale on total and beverage-specific consumption. Results: Separate systematic reviews identified seven studies regarding days and hours of sale and four studies regarding density. The majority of articles included in these systematic reviews, for days/hours of sale (7/7) and outlet density (3/4), concluded that restricting the physical availability of take-away alcohol reduces per capita alcohol consumption. Meta-analyses studying the effect of adding one additional day of sale found that this was associated with per capita consumption increases of 3.4% (95% CI [2.7, 4.1]) for total alcohol, 5.3% (95% CI [3.2, 7.4]) for beer, 2.6% (95% CI [1.8, 3.5]) for wine, and 2.6% (95% CI [2.1, 3.2]) for spirits. The small number of included studies regarding hours of sale and density precluded meta-analysis. Conclusions: The results of this study suggest that decreasing the physical availability of take-away alcohol will decrease per capita consumption. As decreasing per capita consumption has been shown to reduce alcohol-related harm, restricting the physical availability of take-away alcohol would be expected to result in improvements to public health.
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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 | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.040 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".