Lifestyle Behavior and Mental Health in Early Adolescence
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Mental illnesses affect >15% of Canadian adolescents. New preventive strategies are critically needed. We examined the associations of meeting established recommendations for diet, physical activity, sleep, and sedentary behavior in childhood with mental illness in adolescence. METHODS: = 3436) linking 2011 health behavior survey data of 10- to 11-year-olds with administrative health data from 2011 to 2014. Lifestyle behaviors were measured with the Harvard Food Frequency Questionnaire and self- and parental-proxy reports, expressed as meeting recommendations for vegetables and fruit, grain products, milk and alternatives, meat and alternatives, added sugar, saturated fat, sleep, screen time, and physical activity. Mental illness was defined by physician-diagnosed internalizing, externalizing, and other psychiatric conditions. Negative binomial regression was used to determine the independent and cumulative associations of meeting lifestyle recommendations with physician visits for mental illnesses. RESULTS: Of all participants, 12%, 67%, and 21% met 1 to 3, 4 to 6, and 7 to 9 recommendations, respectively, and 15% had a mental illness diagnosis during follow-up. Compared with meeting 1 to 3 recommendations, meeting 7 to 9 recommendations was associated with 56% (95% confidence interval: 38%-69%) fewer physician visits for mental illness during follow-up. Every additional recommendation met was associated with 15% fewer physician visits for mental illnesses (95% confidence interval: 9%-21%). CONCLUSIONS: Mental illness in adolescence is associated with compliance to lifestyle recommendations in childhood, with stronger associations seen when more recommendations are met. Emphasizing lifestyle recommendations in pediatric practice may reduce the future burden of mental illness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".