The association between alcohol retail access and health care visits attributable to alcohol for individuals with and without a history of alcohol‐related health‐care use
Bibliographic record
Abstract
BACKGROUND AND AIMS: Alcohol retail access is associated with alcohol use and related harms. This study measured whether this association differs for people with and without heavy and disordered patterns of alcohol use. DESIGN: The study used a repeated cross-sectional analysis of health administrative databases. SETTING, PARTICIPANTS/CASES: All residents of Ontario, Canada aged 10-105 years with universal health coverage (n = 10 677 604 in 2013) were included in the analysis. MEASUREMENTS: Quarterly rates of emergency department (ED) and outpatient visits attributable to alcohol in 464 geographic regions between 2013 and 2019 were measured. Quarterly off-premises alcohol retail access scores were calculated (average drive to the closest seven stores) for each geographic region. Mixed-effect linear regression models adjusted for area-level socio-demographic covariates were used to examine associations between deciles of alcohol retail access and health-care visits attributable to alcohol. Stratified analyses were run for individuals with and without prior alcohol-attributable health-care use in the past 2 years. FINDINGS: We included 437 707 ED visits and 505 271 outpatient visits attributable to alcohol. After adjustment, rates of ED visits were 39% higher [rate ratio (RR) = 1.39, 95% confidence interval (CI) = 1.20-1.61] and rates of outpatient visits were 49% higher (RR = 1.49, 95% CI = 1.26-1.75) in the highest versus lowest decile of alcohol access. There was a positive association between alcohol access and outpatient visits attributable to alcohol for individuals without prior health-care attributable to alcohol (RR = 1.65, 95% CI = 1.39-1.95 for the highest to lowest decile of alcohol access) but not for individuals with prior health-care attributable to alcohol (RR = 1.08, 95% CI = 0.90-1.30). There was a positive association between alcohol access and ED visits attributable to alcohol for individuals with and without prior health-care for alcohol for ED visits. CONCLUSION: In Ontario, Canada, greater alcohol retail access appears to be associated with higher rates of emergency department (ED) and outpatient health-care visits attributable to alcohol. Individuals without prior health-care for alcohol may be more susceptible to greater alcohol retail access for outpatient but not ED visits attributable to alcohol.
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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 | 0.000 | 0.000 |
| 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".