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Association between seasons with substantial atmospheric pressure change and migraine occurrence: a retrospective
Muneto Tatsumoto1,2, Koichi Hirata2, Takeo Nakayama3
1Canon Marketing Japan Inc., Tokyo, Japan.
Background:
This study investigated the impact of seasons with substantial atmospheric pressure change on the occurrence of migraine using large-scale data from a Japanese health insurance claims database matched with meteorological data.
Methods:
This retrospective cohort study used JMDC Claims Data and national meteorological data from Japan. Patients with a diagnostic record of migraine were included and categorized into eight regional subgroups based on the location of the healthcare facility at which they were initially diagnosed with migraine. The time to migraine occurrence, defined as the duration from the first day of each season to the prescription of triptans, was compared between the seasons with the highest and lowest atmospheric pressure change.
Results:
A total of 26,777 individuals were included in this study. Summer showed the lowest atmospheric pressure change across all eight regions. Conversely, winter showed the highest atmospheric pressure change in seven regions, while autumn showed the highest change in one region. No differences were observed in survival curves between the seasons with the highest and lowest atmospheric pressure change in any region. In Cox regression analysis, hazard ratio for the season with the highest atmospheric pressure change was 0.970 (95% CI: 0.951-0.989) in the minimally adjusted model, which included sex and age. Conversely, the fully adjusted model, which incorporated eight covariates, indicated a hazard ratio of 1.294 (95% CI: 1.007-1.663) for the season with the highest atmospheric pressure change.
Conclusion:
This study, using a large Japanese administrative claims database, did not identify a significant association between seasons with substantial atmospheric pressure change and migraine occurrence. Future research should consider examining more granular residential data, beyond the prefecture level, for a more detailed analysis.
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