Synergism between Female Gender and High Levels of Daily Stress Associated with Migraine Headaches in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Migraines affect women more than men and originate from interactions of genetic and environmental factors. This study assessed the prevalence of migraines in Ontario, Canada and the effect of gender and stress on migraines. METHODS: Our analysis was based on data from 42,282 persons 12 years or older who participated in the 2013-2014 Canadian Community Health Survey. Multivariate log-binomial model was used to calculate adjusted prevalence ratios for migraines associated with individual and joint exposures of female gender and stress. We used relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S index) to measure additive interaction. RESULTS: The prevalence of migraines was 10.7%. The adjusted prevalence ratios were 2.37 (95% CI 2.13-2.63) for female versus male, 1.63 (95% CI 1.39-1.90) for persons with high versus low levels of stress, and 3.38 (95% CI 3.00-3.80) for women with high stress versus men with low stress. The RERI estimate was 0.38 (95% CI 0.04-0.73), the AP estimate was 0.11 (95% CI 0.02-0.21), and the S index was 1.19 (95% CI 1.01-1.41). CONCLUSION: We report 10.7% prevalence of migraines and synergism between female gender and stress on risk of migraine, suggesting health interventions targeting women under stress may be beneficial.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".