Effect of Smoking on the Development of Migraine in Women: Nationwide Cohort Study in South Korea
Bibliographic record
Abstract
Background: Smoking is known to be a significant risk factor for various diseases. Migraine, a condition requiring careful lifestyle management, currently lacks specific guidelines advocating for smoking cessation as a preventive measure. Although cross-sectional studies have suggested a potential link between smoking and an increased risk of migraine, the findings have been inconsistent and conflicting. To date, there has been no longitudinal study which investigated the effect of smoking on the risk of migraine in a prospective setting. Objective: This longitudinal study aimed to investigate the impact of smoking on the incidence of migraine in women and examine the modifying effect of menopausal status. Methods: Using nationally representative National Health Insurance Service (NHIS) data, women aged ≥40 years who participated in national breast cancer screening in 2009 were followed-up until the end of 2019. Baseline data on smoking status (non-, ex-, and current smoker) as well as the duration and amount of cigarette smoking were collected. A Cox proportional hazards regression model was used to examine the independent effect of smoking on the risk of incident migraine after adjusting for demographics, comorbidities, and female reproductive factors. The results were stratified by menopausal status, and an interaction analysis (smoking × menopause) was performed. Results: In total, 1,827,129 women were included in the analysis. Women with a history of smoking exhibited a higher risk of developing migraine, compared with nonsmokers. Specifically, a higher risk of migraine was observed in women with past (adjusted hazard ratio [HR] 1.044, 95% CI 1.000-1.089) and current cigarette use (adjusted HR 1.050, 95% CI, 1.023-1.079) than in nonsmokers. The effect was greater in premenopausal women (adjusted HR 1.140, 95% CI, 1.108-1.172) than in postmenopausal women (adjusted HR 1.045, 95% CI 1.018-1.073; P<.001). The risk increased with an increased amount of smoking, with a greater association in premenopausal women (P<.001). Conclusions: Smoking increases the risk of migraine in women, with a dose-dependent relationship. Menopause modifies this effect. Our findings suggest that smoking is an important modifiable risk factor of migraine, with a higher impact in premenopausal women. The interaction between smoking and estrogen may increase the vulnerability of the migraine brain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".