Age, period and cohort effects of heavy episodic drinking by sex/gender and socioeconomic position in Canada, 2000–2021
Bibliographic record
Abstract
BACKGROUND AND AIMS: Heavy episodic drinking (HED) trends have not been comprehensively examined in Canada. We measured age, period and birth cohort trends in HED in Canada by sex/gender and socioeconomic position. DESIGN AND SETTING: We analyzed repeat cross-sectional data from the 10 provinces in the Canadian Community Health Surveys from 2000 to 2021 using hierarchical cross-classified random effects logistic regression. PARTICIPANTS: 1 167 831 respondents aged 12+ . MEASUREMENTS: HED was defined as 4+ standard drinks for women or 5+ for men at least monthly in the past 12 months. Socioeconomic position was measured using household income and education. FINDINGS: We observed steeper HED decreases in young adult men (aged 18-29) than women (by 14.4% and 8.7%, respectively, from 2015 to 2021) and HED increases in middle adult women (ages 50-64) (by 8.0% from 2000 to 2014). Sex/gender-specific age-period-cohort models revealed strong age and birth cohort effects. In women and men, respectively, HED peaked in young adulthood (18.2% and 33.8%) and decreased with age, and HED was greatest in the 1980-1989 cohort (20.7% and 35.8%) and decreased in the most recent cohort born in 1990-2009 (15.6% and 19.8%), particularly in men. Higher household incomes had greater HED across age, periods and cohorts, while trends varied by education. Compared with lower education groups, people with a bachelor's degree or above had the lowest HED in middle adulthood. People with a bachelor's degree or above had low HED in earlier cohorts, which converged with other education groups in recent cohorts due to a pronounced HED increase, particularly in women. CONCLUSION: The sex/gender gap in heavy episodic drinking (HED) appears to be converging in Canada: current young adult men are reducing HED, while high-risk cohorts of women are aging into middle adulthood with greater HED. Recent birth cohorts with a bachelor's degree or above experienced pronounced HED increases, which among women suggests greater educational attainment contributes to the converging gender gap in HED.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".