Growing alcohol use preceding death by suicide among women compared with men: age‐specific temporal trends, 2003–18
Bibliographic record
Abstract
BACKGROUND AND AIMS: In the United States, until 2018 both the prevalence of heavy alcohol use and the suicide mortality rate increased among men and women; however, women had experienced a notably higher increase in both. As heavy alcohol use may have contributed to the observed sex disparity in the suicide mortality rate increase, the aim of the current study was to estimate the temporal trend of the sex- and age-group-specific proportion of suicides that were alcohol-involved in the United States. DESIGN: Using restricted-access data from the National Violent Death Reporting System, we performed joinpoint regression analyses to investigate temporal trends in the sex- and age-group (young adults = 18-34 years; middle-aged adults = 35-64 years; and older adults = 65+ years)-specific proportion of suicides that were alcohol-involved. SETTING: United States. PARTICIPANTS: A total of 115 202 suicide decedents 18+ years of age from 2003 to 2018. MEASUREMENTS: The sex- and age-group-specific proportion of suicides that were alcohol-involved, among all suicide decedent, for which the decedent had a blood alcohol concentration (BAC) (a) ≥ 0.04 g/dl and (b) ≥ 0.08 g/dl. FINDINGS: For 2003-18, the proportion of suicides that were alcohol-involved wherein the decedent had a BAC ≥ 0.08 g/day significantly increased on average annually for women of all age groups [young women: 2.80%, 95% confidence interval (CI) = 1.86%, 3.75%; middle-aged women: 2.20%, 95% CI = 1.20%, 3.21%; older women: 10.48%, 95% CI = 1.17%, 20.65%], while only middle-aged men experienced a significant average annual percentage increase (0.81%, 95% CI = 0.003%, 1.62%). CONCLUSION: In the United States between 2003 and 2018, alcohol use preceding death by suicide increased among women compared with men.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".