Comorbidity of migraine and depression
Abstract
BACKGROUND: An association between migraine and major depression has been observed in clinical and community samples. The factors that contribute to this association and their implications remain unclear. OBJECTIVE: To determine the factors contributing to the association of migraine and major depression. METHODS: A cohort study of persons aged 25 to 55 years with migraine (n = 496) or with other headaches of comparable severity (n = 151) and control subjects with no history of severe headaches (n = 539) randomly selected from the general community were interviewed first in 1997 and then reinterviewed in 1999. RESULTS: Major depression at baseline predicted the first-onset migraine during the 2-year follow-up period (odds ratio [OR] = 3.4; 95% CI = 1.4, 8.7) but not other severe headaches (OR = 0.6; 95% CI = 0.1, 4.6). Migraine at baseline predicted the first-onset major depression during follow-up (OR = 5.8; 95% CI = 2.7, 12.3); the prospective association from severe headaches to major depression was not significant (OR = 2.7; 95% CI = 0.9, 8.1). Comorbid major depression did not influence the frequency of migraine attacks, their persistence, or the progression of migraine-related disability over time. CONCLUSIONS: Major depression increased the risk for migraine, and migraine increased the risk for major depression. This bidirectional association, with each disorder increasing the risk for first onset of the other, was not observed in relation to other severe headaches.…
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: 539 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.