Suicide, Alcohol Intoxication, and Age Among Whites and American Indians/Alaskan Natives
Bibliographic record
Abstract
BACKGROUND: Among American Indians/Alaskan Natives (AI/ANs), suicides are disproportionately high among those younger than 40 years of age. This paper examines suicide and alcohol intoxication (postmortem BAC ≥ 0.08 g/dl) by age among Whites and AI/ANs to better understand the reasons for the high rate of suicide among AI/ANs for those younger than 40. METHODS: Data come from the restricted 2003 to 2016 National Violent Death Reporting System (NVDRS), with postmortem information on 79,150 White and AI/AN suicide decedents of both genders who had a BAC test in 32 states of the United States. RESULTS: Among Whites, 39.3% of decedents legally intoxicated are younger than 40 years of age, while among AI/ANs the proportion is 72.9% (p < 0.001). Multivariable logistic regression with data divided by age shows that in the 18 to 39 age group, AI/ANs are about 2 times more likely than Whites to have a postmortem BAC ≥ 0.08. Veteran status compared to nonveteran, and history of alcohol problems prior to suicide were also associated with BAC ≥ 0.08. Suicide methods other than by firearm and a report of the presence of 2 or more suicide precipitating circumstances were protective against BAC ≥ 0.08. Results for the age group 40 years of age and older mirror those for the younger group with 1 exception: Race/ethnicity was not associated with BAC level. CONCLUSIONS: The proportion of suicide decedents with a BAC ≥ 0.08 is higher among AI/ANs than Whites, especially among those 18 to 39 years of age. However, acute alcohol intoxication does not fully explain differences in suicide age structure between AI/ANs and Whites.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".