Alcohol Consumption, Alcoholics Anonymous Membership, and Suicide Mortality Rates, Ontario, 1968-1991
Bibliographic record
Abstract
OBJECTIVE: The goal of this study is to identify alcohol-related factors that influence mortality rates from suicide. Specifically, we examine the impact of per capita consumption of total alcohol, distilled spirits, and beer and wine; unemployment rate; and Alcoholics Anonymous (AA) membership rate on total and male and female suicide mortality rates in Ontario between 1968 and 1991. METHOD: We studied the impact of alcohol consumption levels, AA membership rates, and unemployment rates on suicide mortality rates in Ontario from 1968 to 1991. Time series analyses with Auto Regressive Integrated Moving Average (ARIMA) modeling were applied to total and male and female suicide rates. The analyses performed included total alcohol consumption, distilled spirits consumption, beer consumption, and wine consumption. Missing AA membership data were interpolated with cubic splines. RESULTS: Total alcohol consumption and consumption of each of beer, distilled spirits, and wine were significantly and positively related to total and female suicide mortality rates. AA membership rates were negatively related to total and female suicide rates. Although data for males did not reach significance (except for the relationship between wine consumption and suicide rate), the direction of effects was consistent with that observed for female and total suicide rates. Unemployment rates were positively related to male and total suicide rates in some models. CONCLUSIONS: These data confirm the important relationships between per capita consumption measures and suicide mortality rates seen by previous investigators. Additionally, the results for AA membership rates are consistent with the hypothesis that AA membership and treatment for misuse of alcohol can exert beneficial effects observable at the population level.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".