On-Premise Alcohol Establishments and Ambulance Calls for Trauma, Assault, and Intoxication
Bibliographic record
Abstract
Alcohol contributes to intentional and unintentional injury. We explored on-premise licensed alcohol establishments (LAEs) and emergency medical service (EMS) ambulance calls.We completed a retrospective population-based study in the Region of Peel, Ontario, 2005 to 2014, where alcohol sales are tightly regulated and healthcare is universally available. We included participants age ≥ 19 years. Longitude-latitude coordinates of all 696 LAEs and all 267,477 EMS ambulance calls were ascertained, and then assigned to 1 of 1568 dissemination areas (DA) in Peel. Relative risks (RRs) described the association between density of on-premise LAEs (by DA deciles) and the rate of EMS calls, adjusted for material deprivation, and density of beer/liquor stores in each DA.There was a curvilinear relation between LAE density and EMS calls for trauma, rising from 45.3 per 1000 in DAs with no LAEs to 381.0 per 1000 in decile-10 (adjusted RR 7.83, 95% confidence interval [CI] 6.15-9.97). This relation was more pronounced for alcohol-focused LAEs, and highest among younger males. Calls for assault (RR 2.67, 95% CI 1.26-5.65) and intoxication (RR 4.00, 95% CI 1.41-11.38) were more likely on the last day of the month and the day thereafter, compared to 1 week prior. At 02:00 hours, when LAEs must stop selling alcohol, there was a considerable rise in assault-related calls in DAs with LAE but not in DAs without LAEs.On-premise LAEs contribute to EMS calls for trauma and assault, especially among young males, around last call, and when monthly pay cheques are cashed.
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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".