Acute alcohol use among suicide decedents in 14 <scp>US</scp> states: impacts of off‐premise and on‐premise alcohol outlet density
Bibliographic record
Abstract
AIMS: To estimate the association between per capita alcohol retail outlet density and blood alcohol concentration (BAC) from 51 547 suicide decedents and to analyse the relationship between alcohol outlet density and socio-demographic characteristics among alcohol-positive suicide decedents in the United States by racial/ethnic groups and method of suicide. DESIGN: Analysis of US data, 2003-11, National Violent Death Reporting System. SETTING: Suicide decedents from 14 US states. PARTICIPANTS: A total of 51 347 suicide decedents tested for BAC. MEASUREMENTS: BAC and levels were derived from coroner/medical examiner reports. Densities of county level on-premises and off-premises alcohol retail outlets were calculated using the 2010 Census. FINDINGS: Multi-level logistic regression models suggested that higher off-premises alcohol outlet densities were associated with greater proportions of alcohol-related suicides among men-for suicides with alcohol present [BAC >0; adjusted odds ratio (AOR) = 1.08, 95% confidence interval (CI) = 1.03-1.13]. Interactions between outlet density and decedents' characteristics were also tested. There was an interaction between off-premises alcohol availability and American Indian/Alaska Native race (AOR = 1.36; 95% CI = 1.10-1.69) such that this subgroup had highest BAC positivity. On-premises density was also associated with BAC >0 (AOR = 1.07; 95% CI = 1.03-1.11) and BAC ≥0.08 (AOR = 1.05; 95% CI = 1.02-1.09) among male decedents. CONCLUSIONS: In the United States, the density of both on- and off-premises alcohol outlets in a county is associated positively with alcohol-related suicide, especially among American Indians/Alaska Natives.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".