Migraine and Stroke Risk in Postmenopausal Women in the Women's Health Initiative
Abstract
Background and objectives: Migraine is a known risk factor for stroke in women of reproductive age, although its relationship with stroke among postmenopausal women remains unclear. We assessed the association between migraine history and incident stroke in a sample of postmenopausal women.
Methods: We included women enrolled in the Women's Health Initiative, a large US longitudinal cohort study of postmenopausal women, and excluded those with previous stroke or those with missing data on key variables. The primary exposure was self-reported, physician-diagnosed migraine at baseline, and the primary outcome was incident stroke (total, ischemic, or hemorrhagic). Multivariable Cox proportional hazards models were used to test the cause-specific hazard ratios (HRs) between migraine history and total, ischemic (overall and by subtype), and hemorrhagic stroke, sequentially adjusted for age, traditional cardiovascular risk factors, and female-specific risk factors (age at menopause, age at menarche, menstrual irregularity, presence of vasomotor symptoms, parity, breastfeeding, and use of menopausal hormone therapy). We then quantified the association between a history of migraine and total stroke by age at baseline (in 5-year age groups) using multivariable models. Data on the presence of aura and migraine frequency were not available.
Results: Participants (N = 130,277) had a median age of 63 years (interquartile range [IQR] 57-69). A total of 5,743 incident stroke events…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 130,277 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.