Social disparities in alcohol consumption among Canadian emerging adults
Bibliographic record
Abstract
INTRODUCTION: Young adult drinking is a public health priority, but knowledge of socioeconomic status (SES) indicators and alcohol use among emerging adults (EAs; aged 18-29 years) is primarily informed by college samples, populations in their late teens and early twenties and non-Canadian data. We compared the association of three different SES indicators with monthly heavy episodic drinking (HED), less-than-monthly HED, no HED, and no drinking among Canadian EAs. METHODS: We pooled the 2015 to 2019 waves of the Canadian Community Health Survey to include participants aged 18 to 29 years (n = 29 598). Using multinomial regression, we calculated weighted estimates of alcohol use by education, household income and area-level disadvantage, adjusting for adult roles and sociodemographic characteristics. RESULTS: Approximately 30% of EAs engaged in monthly HED, whereas 16% did not drink at all in the past year. Compared to those in the lowest household incomes, being in the top income quintile was significantly associated with increased relative odds of monthly HED (e.g. in combined SES model, RRR = 1.21, 95% CI: 1.04-1.39). Higher levels of education, being in higher income quintiles and living in less disadvantaged areas were significantly associated with reduced relative odds of no HED and not drinking. Adjusting for adult roles did not substantially change the associations between SES and alcohol use. CONCLUSION: Higher SES was associated with HED among EAs, although the magnitude of association was small. Universal prevention measures addressing the affordability, availability and marketing of alcohol could be complemented by interventions targeting EA populations at higher risk of HED.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".