Migraine and Mental Health in a Population-Based Sample of Adolescents
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between migraine and anxiety disorders, mood disorders and perceived mental health in a population-based sample of adolescents. METHODS: The Canadian Community Health Survey (CCHS) is a cross-sectional health survey sampling a nationally representative group of Canadians. In this observational study, data on all 61,375 participants aged 12-19 years from six survey cycles were analyzed. The relationships between self-reported migraine, perceived mental health, and mood/anxiety disorders were modeled using univariate and multivariate logistic regression. The migraine-depression association was also explored in a subset of participants using the Composite International Diagnostic Interview-Short Form (CIDI-SF) depression scale. RESULTS: The odds of migraine were higher among those with mood disorders, with the strongest association in 2011-2 (adjusted odds ratio [aOR]=4.59; 95% confidence interval [CI 95%]=3.44-6.12), and the weakest in 2009-10 (aOR=3.06, CI 95%=2.06-4.55). The migraine-mood disorders association was also significant throughout all cycles, other than 2011-2, when the CIDI-SF depression scale was employed. The odds of migraine were higher among those with anxiety disorders, with the strongest association in 2011-2 (aOR=4.21, CI 95%=3.31-5.35) and the weakest in 2010 (aOR=1.87, CI 95%=1.10-3.37). The inverse association between high perceived mental health and the odds of migraine was observed in all CCHS cycles, with the strongest association in 2011-2 (aOR=0.58, CI 95%=0.48-0.69) and the weakest in 2003-4 (aOR=0.75, CI 95%=0.62-0.91). CONCLUSIONS: This study provides evidence, derived from a large population-based sample of adolescents, for a link between migraine and mood/anxiety disorders.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| 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".