An observational study of self-reported migraine triggers and prospective evaluation of the relationships with occurrence of attacks enabled by a smartphone application (App).

Objective: To investigate the relationship between self-reported triggers and the occurrence of migraine attacks using a smartphone application.

Background: One of several issues around the study of migraine attack triggers is that limited available evidence supports whether self-reported triggers can induce a headache on a particular subject.

Methods: This is an observational longitudinal cohort study of individuals with migraine registered to track their headaches prospectively using a smartphone application. For 90 days, participants entered daily data about triggers (potential triggers and premonitory symptoms) that may be associated with attack risk, as well as migraine symptoms. The statistical significance of univariate associations between each trigger and migraine recurrent events was determined for each individual. Statistically identified triggers were then compared to self-reported triggers.

Results: In 328 individuals (290/328 [88.4%] female; mean [standard deviation] 4.2 [1.5] migraine attacks/month) the mean (standard deviation) number of triggers moderately or highly endorsed per individual was 28.0 (7.7) in individuals presented with up to 38 possible triggers. Of these, an average (standard deviation) of 2.2 (2.1) triggers per individual were statistically associated with increased risk of attacks. Even the most commonly endorsed triggers (sleep quality, stress, tiredness/fatigue, sleep duration, dehydration, neck pain, missed meals, eyestrain, mean barometric pressure, and anxiety) were statistically associated in fewer than one third of individuals suspecting each, with the exception of neck pain (117/302 [38.7%]).

Conclusions: Individuals with episodic migraine believe that many triggers contribute to their attacks; however, few of these withstand statistical testing at the individual level. Improved personal knowledge of potential triggers and premonitory symptoms may help individuals adopt behavioral changes to mitigate attack risk.