Increased risk of multiple sclerosis among women with migraine in the Nurses' Health Study II

Mult Scler. 2012 Jan;18(1):90-7. doi: 10.1177/1352458511416487. Epub 2011 Aug 3.


Background: The prospective Nurses' Health Study II (NHS-II), which enrolled over 116,000 female nurses, provides a unique opportunity to test the hypothesis of whether migraine is associated with multiple sclerosis (MS) and to explore the temporal aspects of the interrelationship.

Objectives: To calculate relative risk of MS among NHS-II participants with and without migraine and to estimate odds ratio (OR) of being diagnosed with migraine in women with and without pre-existing MS.

Methods: Cox proportional hazards regression was used to estimate rate ratios and 95% confidence intervals (CIs) of being diagnosed with MS in women with and without pre-existing migraine adjusted for potential confounders. Multivariate adjusted ORs of being diagnosed with migraine in women with and without pre-existing MS were estimated using logistic regression.

Results: The prevalence of migraine in women with MS at baseline (26%, p = 0.11) and those diagnosed with MS after enrolment (29%, p < 0.0001) was higher than in the non-MS cases (21%). The relative risk of developing MS in migraineurs was 1.39 times higher than in non-migraineurs (95% CI 1.10-1.77, p = 0.008). The absolute risk of developing MS in women migraineurs over a 15-year follow-up was 0.47% and among non-migraineurs 0.32%. The odds of being diagnosed with migraine was higher in women with pre-existing MS compared with those without MS, but did not reach statistical significance (OR = 1.57, 95% CI 0.97-2.52; p = 0.06).

Conclusions: Using a large, cohort of women-nurses, history of migraine was associated with an increased risk of MS. However, the difference in absolute risk of MS in migraineurs and non-migraineurs was small.

MeSH terms

  • Adult
  • Cohort Studies
  • Female
  • Humans
  • Migraine Disorders / complications*
  • Multiple Sclerosis / complications
  • Multiple Sclerosis / epidemiology*
  • Nurses
  • Prevalence
  • Proportional Hazards Models
  • Risk Factors