Association of Marijuana, Mental Health, and Tobacco in Colorado
Bibliographic record
Abstract
OBJECTIVES: Marijuana's evolving legality may change marijuana use patterns in adults. Co-use of marijuana and tobacco are strongly associated, and populations with mental health disorders are disproportionately likely to use either substance, but neither association has been assessed in the context of legal recreational marijuana. We assessed the associations of tobacco smoking with marijuana use and with mental health disorders in Colorado in 2015. METHODS: Data came from a population-based survey of adults (n = 8023). Multiple logistic regressions were used with current tobacco smoking as the primary outcome. Past 30-day marijuana use and mental health status were the independent variables of interest. Covariates included age, sex, ethnicity, poverty level, and education. RESULTS: Adults who used marijuana in the past 30 days had 3.4 (95% confidence interval [CI] 2.7, 4.2) greater odds of currently smoking tobacco compared to adults who had not recently used marijuana, after adjusting for sociodemographic and economic factors. A mental health disorder was independently associated with tobacco smoking (adjusted odds ratio [OR] 1.7, 95% CI 1.4, 2.1). Prevalence of co-use among adults self-reporting a mental health disorder was significantly higher compared those without a mental health disorder (11.1% vs 4.3%; P < 0.0001). CONCLUSIONS: This study examined the associations between mental health, marijuana use, and tobacco smoking after the legalization of recreational marijuana in Colorado. Adults using marijuana and/or self-reporting a mental health disorder were more likely to smoke tobacco and should be targeted for cessation interventions.
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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 | 0.000 | 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 | 0.000 |
| 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".