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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".