The impact of 12 modifiable lifestyle behaviours on depressive and anxiety symptoms in middle adolescence: prospective analyses of the Canadian longitudinal COMPASS study
Bibliographic record
Abstract
BACKGROUND: Unhealthy lifestyle behaviours are becoming increasingly common and might contribute to the growing burden of mental disorders in adolescence. We examined the associations between a comprehensive set of lifestyle behaviours and depression and anxiety in middle adolescents. METHODS: School-based survey responses were collected from 24,274 Canadian high school students at baseline and 1-year follow-up (average age 14.8 and 15.8 years, respectively). Using linear mixed-effects models, we examined prospective associations of adherence to recommendations for vegetables and fruit, grains, milk and alternatives, meat and alternatives, sugar-sweetened beverages [SSB], physical activity, screen time, sleep, and no use of tobacco, e-cigarettes, cannabis, and binge drinking at baseline with the depressive and anxiety symptoms (measured by CESD-R-10 and GAD-7 scales, respectively) at follow-up. RESULTS: Adherence to recommendations was low overall, particularly for vegetables and fruit (3.9%), grains (4.5%), and screen time (4.9%). Students adhering to individual recommendations, particularly for meat and alternatives, SSB, screen time, sleep, and no cannabis use, at baseline had lower CESD-R-10 and GAD-7 scores at follow-up. Adhering to every additional recommendation was associated with lower CESD-R-10 (β=-0.15, 95% CI -0.18, -0.11) and GAD-7 scores (β=-0.10, 95% CI -0.14, -0.07) at follow-up. Assuming cumulative impact, this might translate into 7.2- and 4.8-point lower CESD-R-10 and GAD-7 scores, respectively, among students adhering to 12 vs. 0 recommendations over four years of high school. CONCLUSIONS: The results highlight the preventive potential of population-based approaches promoting healthy lifestyle behaviours, particularly those with the lowest prevalence, as a strategy to improve mental health in adolescence.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".