Temporal associations between weather and headache: analysis by empirical mode decomposition.

Area of Science:

• Environmental Health
• Epidemiology
• Biometeorology

Background:

• Headache patients often report weather changes as triggers or exacerbating factors.
• Empirical Mode Decomposition (EMD) is a technique for analyzing temporal relationships in disease data.

Purpose of the Study:

• To apply EMD to identify intrinsic weather components associated with headache incidence.
• To analyze headache data from a large-scale epidemiological survey in the Greater Taipei area.

Main Methods:

• Detrending weather time-series parameters using EMD into intrinsic mode functions (IMFs).
• Utilizing multiple linear regression with forward stepwise methods to assess temporal associations.
• Analyzing data from 52 randomly selected headache patients.

Main Results:

• No associations were found between raw weather variables and headache incidence.
• Intrinsic weather components (temperature, sunshine, humidity, pressure, wind speed) were linked to headaches during the cold period.
• Maximal wind speed was associated with headaches during the warm period.
• EMD-derived temperature and sunshine IMFs explained up to 33.3% of headache variance in the cold period, coinciding with cold fronts.

Conclusions:

• EMD analysis revealed significant associations between headache and intrinsic weather components, missed by direct comparisons.
• Key weather parameters influencing headaches may differ by geographic region and season.