Age–period–cohort analysis of trends in tobacco smoking, cannabis use, and their co‐use in the Australian population
Bibliographic record
Abstract
BACKGROUND AND AIM: The prevalence of tobacco smoking has declined in most high-income countries, while cannabis use has been rising. Moreover, cannabis use has been found to have increased among cigarette smokers in recent years in jurisdictions where it has been either decriminalized or legalized. This study measured trends in cannabis, tobacco and the co-use of cannabis and tobacco in Australia. DESIGN: Age-period-cohort analysis. SETTING AND PARTICIPANTS: Participants were n = 143 344 individuals aged 18-80 years who participated in Australia's National Drug Strategy Household Surveys (NDSHS) between 2001 and 2019. MEASUREMENTS: Regular (weekly/more frequently): (1) tobacco smoking only, (2) cannabis use only and (3) the co-use of cannabis and tobacco. FINDINGS: Prevalence of only smoking tobacco decreased in all age groups (P < 0.001) and birth cohorts between 2001 and 2019, but the co-use of cannabis and tobacco did not. Younger cohorts were much less likely to co-use tobacco and cannabis (P = 0.02). Period trends showed that both cannabis use only and the co-use of cannabis and tobacco have increased since 2013. CONCLUSION: There has been a consistent decrease in exclusive tobacco smoking across age, period and birth cohorts between 2001 and 2019 in Australia, although there is a recent increasing period trend in cannabis use with or without tobacco. The non-decreasing trend of co-use may reflect the strong tobacco control policies introduced over the period and changing attitudes towards cannabis use in Australia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".