ArticleJournal of oral & facial pain and headache2026
Climatic sensitivity of migraine: a 14-year time series analysis of primary care consultations in Spain.
Article in Journal of oral & facial pain and headache, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- Medication Overuse Headache and Health-Related Quality of Life for Adults with Migraine in Saudi Arabia.Journal of clinical medicine · 2026Article
- Case Report: Glossopharyngeal neuralgia secondary to syncope: insights into microvascular decompression treatment.Frontiers in surgery · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClimatic variability has been proposed as a trigger for migraine; however, evidence from long-term primary care datasets remains scarce. Understanding how atmospheric conditions influence healthcare utilization may improve migraine prediction and management. This study aimed to analyze the association between climatic variables and weekly migraine consultations over a 14-year period in Spanish primary care and to identify the most accurate predictive time-series model.
methodsWeekly migraine consultations from 2010 to 2023 were extracted from electronic medical records using the International Classification of Primary Care, Second Edition (ICPC-2) code N89.01. Meteorological variables-temperature, diurnal variability, day-to-day change, wind direction and speed, barometric pressure, and sunshine hours-were obtained from the Spanish State Meteorological Agency (AEMET). Time-series analyses used exponential smoothing state-space models with external regressors (ETSX) and AutoRegressive Integrated Moving Average models with eXogenous regressors (ARIMAX). Model performance was assessed using Root Mean Squared Error (RMSE), Symmetric Mean Absolute Percentage Error (SMAPE), and Mean Absolute Scaled Error (MASE).
resultsA total of 3176 migraine consultations were identified (mean age 47.6 ± 15.3 years; 81.7% female). The ARIMAX model showed the best predictive performance (RMSE = 3.485, SMAPE = 73.840, MASE = 0.875). Stationarity was confirmed using the Augmented Dickey-Fuller test (
conclusionsThis long-term time-series analysis showed that female sex was the only variable independently associated with weekly migraine consultations in primary care. Although most atmospheric indicators did not retain significance, climate-informed ARIMAX modeling improved prediction accuracy and may support personalized, weather-adapted preventive strategies.
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