Racial and Ethnic Differences in All-Cause Mortality Risk According to Alcohol Consumption Patterns in the National Alcohol Surveys
Bibliographic record
Abstract
Previous studies have found J-shaped relations between volume of alcohol consumed and mortality risk in white Americans but not in African Americans, suggesting the need for studies in which race/ethnicity-defined subgroups are analyzed in separate comparable models. In the present study, the authors utilized mortality follow-up data (through 2006) on respondents from the 1984 and 1995 National Alcohol Surveys, including similar numbers of black, white, and Hispanic respondents by oversampling the minority groups. Cox proportional hazards models controlling for demographic, socioeconomic, mental health, and drug- and tobacco-use measures were used to estimate mortality risk from all causes. Findings indicated a protective effect of moderate alcohol drinking (2-30 drinks/month for women and 2-60 drinks/month for men) with no monthly ≥5-drink days) relative to lifetime abstention for whites only. Elevated mortality risk relative to moderate drinking was found in former drinkers with lifetime alcohol problems. Moderate drinkers who consumed ≥5 drinks in 1 day at least monthly were also found to have increased risk, suggesting the importance of identifying heavy-occasion drinking for mortality analyses. These differential results regarding lifetime abstainers may suggest bias from differential unmeasured confounding or unmeasured aspects of alcohol consumption pattern or may be due to genetic differences in the health impact of alcohol metabolism.
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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 | 0.017 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".