The contribution of stress to the comorbidity of migraine and major depression: results from a prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: To assess how much the association between migraine and depression may be explained by various measures of stress. DESIGN: National Population Health Survey is a prospective cohort study representative of the Canadian population. Eight years of follow-up time were used in the present analyses. SETTING: Canadian adult population ages 18-64. PARTICIPANTS: 9288 participants. OUTCOME: Incident migraine and major depression. RESULTS: Adjusting for sex and age, depression was predictive of incident migraine (HR: 1.62; 95% CI 1.03 to 2.53) and migraine was predictive of incident depression (HR: 1.55; 95% CI 1.15 to 2.08). However, adjusting for each assessed stressor (childhood trauma, recent marital problems, recent unemployment, recent household financial problems, work stress, chronic stress and change in social support) decreased this association, with chronic stress being a particularly strong predictor of outcomes. When adjusting for all stressors simultaneously, both associations were largely attenuated (depression-migraine HR: 1.30; 95% CI 0.80 to 2.10; migraine-depression HR: 1.19; 95% CI 0.86 to 1.66). CONCLUSIONS: Much of the apparent association between migraine and depression may be explained by stress.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".