Are the 1976–1985 birth cohorts heavier drinkers? Age‐period‐cohort analyses of the <scp>N</scp>ational <scp>A</scp>lcohol <scp>S</scp>urveys 1979–2010
Bibliographic record
Abstract
AIMS: To estimate age-period-cohort models predicting alcohol volume, heavy drinking and beverage-specific alcohol volume in order to evaluate whether the 1976-1985 birth cohorts drink relatively heavily. DESIGN: Data from seven cross-sectional surveys of the USA conducted between 1979 and 2010 were utilized in negative binomial generalized linear models of age, period and cohort effects predicting alcohol measures. SETTING: General population surveys of the USA. PARTICIPANTS: Thirty-six thousand four hundred and thirty-two US adults (aged 18 years or older). MEASUREMENTS: Monthly number of alcohol drinks, beer, wine and spirits drinks, and days drinking five or more drinks in the past year derived from beverage-specific graduated frequency questions. FINDINGS: Relative to the reference 1956-60 birth cohort, men in the 1976-1980 cohort for were found to consume more alcohol [incidence rate ratio (IRR) = 1.222: confidence interval (CI) 1.07-1.39) and to have more 5+ days (the number of days having five or more drinks) (IRR = 1.365: CI 1.09-1.71) as were men in the 1980-85 cohort for volume (IRR = 1.284: CI 1.10-1.50) and 5+ days (IRR = 1.437: CI 1.09-1.89). For women, those in the 1980-85 cohort were found to have higher alcohol volume (IRR = 1.299: CI 1.07-1.58) and more 5+ days (IRR = 1.547: CI 1.01-2.36). Beverage-specific models found different age patterns of volume by beverage with a flat age pattern for both genders' spirits and women's wine, an increasing age pattern for men's wine and a declining age pattern from those in their early 20s for beer. CONCLUSIONS: In the USA, men born between 1976 and 1985, and women born between 1981 and 1985 have higher alcohol consumption than in earlier or later years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".