Associations between diet quality and migraine headaches: a cross-sectional study
Abstract
ABSTRACT Aims We evaluated associations between diet quality and migraine outcomes. Methods The current work represented a cross-sectional study on 262 patients with migraine (20–50 y). Diet quality was assessed using the standard healthy eating index 2015 (HEI-2015) and alternative healthy eating index 2010 (AHEI-2010). A validated 168-item food frequency questionnaire was used to assess dietary intake. Migraine outcomes included clinical factors (severity, duration, frequency, and disability related to migraine) and serum nitric oxide (NO). Associations between diet quality indices and migraine outcomes were evaluated using linear regressions, and β and 95% corresponding confidence interval (CI) were reported. Results HEI-2015 was inversely associated with migraine frequency (β = −4.75, 95% CI: −6.73, −2.76) in patients with the highest HEI scores (third tertile) vs. those with the lowest scores (first tertile) after adjusting for relevant confounders. AHEI-2010 was inversely associated with migraine frequency (β = −3.67, 95% CI: −5.65, −1.69) and migraine-related disability (β = −2.74, 95% CI: −4.79, −0.68) in adjusted models. Also, AHEI-2010 was inversely associated with migraine severity in patients in the second vs. first tertile (β = −0.56; 95% CI: −1.08, −0.05). We detected no associations between diet quality and NO levels (All P > 0.14). Conclusions Improved diet quality may be associated with favorable migraine outcomes (lower headache frequency, severity, and…
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: 262 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.