The association between alcohol access and alcohol‐attributable emergency department visits in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND AND AIMS: The availability of alcohol through retail outlets is associated with alcohol-related harms, but few studies have demonstrated a causal relationship. We investigated the association between alcohol availability and alcohol-attributable emergency department (ED) visits in the province of Ontario during a period of deregulation of controls on the number of alcohol outlets. DESIGN: Cross-sectional and pre-post design SETTING AND PARTICIPANTS: The study used data from two time-periods: pre-deregulation (2013-14) and post-deregulation (2016-17), to compare rates of ED visits for 513 defined geographic regions in Ontario Canada, called Forward Sortation Areas (FSAs). MEASUREMENTS: The primary outcome was the age-standardized rates of alcohol-attributable ED visits. We compiled a list of all alcohol retail outlets in Ontario during 2014 and 2017 and matched them to their corresponding FSA. We fitted mixed-effects Poisson regression models to assess: (a) the cross-sectional association between number of outlets and hours of operation and ED visits; and (b) the impact of deregulation on ED visits using a difference-in-difference approach. FINDINGS: Alcohol-attributed ED visits increased 17.8% over the study period: more than twice the rate of increase for all ED visits. Increased hours of operation and numbers of alcohol outlets within an FSA were positively associated with higher rates of alcohol-attributable ED visits. The increase in ED visits attributable to alcohol was 6% (incident rate ratio = 1.06; 95% confidence interval = 1.04-1.08) greater in FSAs that introduced alcohol sales in grocery stores following deregulation compared with FSAs that did not. CONCLUSIONS: Deregulation of alcohol sales in Ontario, Canada in 2015 was associated with increased emergency department visits attributable to alcohol.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".