Clinical and social burden of migraine in Japanese males: a cross-sectional comparison with females without menstrual migraine
Abstract
BACKGROUND: Migraine is globally more prevalent in females; however, the clinical and social burden among males remains insufficiently characterized. This study aimed to describe the clinical features and social burden of migraine in Japanese males to identify sex-specific migraine profiles.
METHODS: A cross-sectional, population-based web survey was conducted among Japanese adults aged ≥ 18 years diagnosed with migraine according to modified criteria from the International Classification of Headache Disorders, Third Edition (ICHD-3). Participants were grouped by sex; females diagnosed with menstrual migraine (MM) were excluded to minimize hormonal confounding. Key outcomes included pain intensity (Visual Analog Scale [VAS]), pain duration, and social burden assessed using validated instruments: Migraine Interictal Burden Scale (MIBS-4), Migraine Disability Assessment (MIDAS), Migraine-Specific Quality of Life Questionnaire (MSQ), and Work Productivity and Activity Impairment for Migraine (WPAI-M) scores.
RESULTS: Of 266,392 individuals screened, 18,750 completed the survey; 4,161 males and 9,997 females (excluding those with MM) were included in the analysis. Males were older (mean± standard deviation age: 43.9 ± 12.4 vs. 40.9 ± 12.2 years) and reported more lifestyle-related triggers (e.g., alcohol, irregular eating, and overexercise). Males, compared to females, experienced greater pain intensity (VAS: 57.1 ± 16.7 vs. 54.9 ± 19.6; p < 0.001) but shorter pain duration (6.3…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 266,392 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.