Co-occurring mood, anxiety, and substance use disorders in Canada 2022: Prevalence, patterns, correlates, and changes over time
Bibliographic record
Abstract
Abstract Objective: This study examines: (1) the 2022 prevalence and co-occurrence of past 12 month mood, anxiety, and substance use disorders (SUD)among Canadian’s aged 15+; and (2) changes in the prevalence of co-occurring disorders from 2012 to 2022. Methods: Data from the 2022 Mental Health and Access to Care Survey (MHACS; n=9,861) and the 2012 Canadian Community Health Survey’s Mental Health Component (CCHS-MH; n=25,113) were analyzed. Diagnoses for past 12 month mood (major depressive episode, bipolar), anxiety (generalized anxiety, social phobia), and substance use (alcohol, cannabis, and drug) disorders were assessed using the World Health Organization Composite International Diagnostic Interview. Multivariable multinomial regression examined demographic and clinical correlates, as well as changes over time, of mood/anxiety disorder(s) alone, SUD(s) alone, and concurrent disorders (mood/anxiety+SUD). Age (youth aged 15-24 vs adults 26+) and sex (females vs males) differences were explored through stratified analyses and interactions. Results: In 2022, 16.4% of Canadians met criteria for a mood (8.4%), anxiety (9.9%), or SUD (3.5%). Of those with at least one disorder, co-occurrence was common: 39.5% had 2+ disorders with 10.6% experiencing concurrent SUD and mood/anxiety disorders. Among those with an SUD, 48.9% had a concurrent mood/anxiety disorder, while 15.2% and 9.6% of those with a mood and anxiety disorders respectively had a concurrent SUD. Youth, unemployed individuals, and those with high distress or suicidality had elevated odds of concurrent disorders. Males had higher overall concurrent disorder prevalences, but among those with SUDs, concurrent disorders were higher among females. While the odds of SUD-alone declined, mood/anxiety disorders and concurrent disorders doubled from 2012 to 2022. Conclusions: Findings highlight the urgent need for integrated mental health and substance use services in Canada, particularly for youth and females, who are disproportionately affected.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".