Patients with migraine are right about their perception of temperature as a trigger: time series analysis of headache diary data

Yang, Albert C.; Fuh, Jong Ling; Huang, Norden E.; Shia, Ben‐Chang; Wang, Shuu Jiun

doi:10.1186/s10194-015-0533-5

Cited by 29 publications

(26 citation statements)

References 29 publications

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“…The contributions of individual trigger factors were similar, and the proportion of patients who reported any trigger(s) was higher in the SHD for 3 months. The frequent trigger factors in this analysis were in line with previous studies [ 2 , 3 , 10 , 29 – 30 ]. Several studies have suggested that stress is related to hormones, including cortisol and thyroid hormone, and may have a role in migraine pathogenesis [ 2 , 29 ].…”

Section: Discussionsupporting

confidence: 89%

Analysis of Trigger Factors in Episodic Migraineurs Using a Smartphone Headache Diary Applications

et al. 2016

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BackgroundVarious stimuli can trigger migraines in susceptible individuals. We examined migraine trigger factors by using a smartphone headache diary application.MethodEpisodic migraineurs who agreed to participate in our study downloaded smartphone headache diary application, which was designed to capture the details regarding headache trigger factors and characteristics for 3 months. The participants were asked to access the smartphone headache diary application daily and to confirm the presence of a headache and input the types of trigger factors.ResultsSixty-two participants kept diary entries until the end of the study. The diary data for 4,579 days were analyzed. In this data set, 1,099 headache days (336 migraines, 763 non-migraine headaches) were recorded; of these, 772 headache events had with trigger factors, and 327 events did not have trigger factors. The common trigger factors that were present on headache days included stress, fatigue, sleep deprivation, hormonal changes, and weather changes. The likelihood of a headache trigger was 57.7% for stress, 55.1% for sleep deprivation, 48.5% for fatigue, and 46.5% for any trigger. The headaches with trigger factors were associated with greater pain intensity (p<0.001), headache-related disability (p<0.001), abortive medication use (p = 0.02), and the proportion of migraine (p < 0.001), relative to those without trigger factors. Traveling (odd ratios [OR]: 6.4), hormonal changes (OR: 3.5), noise (OR: 2.8), alcohol (OR: 2.5), overeating (OR: 2.4), and stress (OR:1.8) were significantly associated with migraines compared to non-migraine headaches. The headaches that were associated with hormonal changes or noise were more often migraines, regardless of the preventive medication. The headaches due to stress, overeating, alcohol, and traveling were more often migraines without preventive medication, but it was not evident with preventive medication.ConclusionSmartphone headache diary application is an effective tool to assess migraine trigger factors. The headaches with trigger factors had greater severity or migraine features. The type of triggers and the presence of preventive medication influenced the headache characteristics; hence, an investigation of trigger factors would be helpful in understanding migraine occurrences.

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Section: Discussionsupporting

confidence: 89%

Analysis of Trigger Factors in Episodic Migraineurs Using a Smartphone Headache Diary Applications

et al. 2016

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“…It is unclear what portion of these headaches were thunderclap‐like, but these meteorological parameters were quite different from those associated with RCVS onset in our study. One study conducted in Taiwan showed that there were higher migraine attack incidence rates when the weather was cool, conditions more similar to those we found to be associated with RCVS occurrence.…”

Section: Discussionsupporting

confidence: 85%

Influence of Climate on the Incidence of RCVS – A Retrospective Study From Taiwan

et al. 2019

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Background Cold weather is reportedly a precipitator of reversible cerebral vasoconstriction syndrome (RCVS) in a few cases. We systematically investigated whether meteorological factors correlate with the occurrence of RCVS. Methods We conducted a retrospective analysis of a cohort of patients diagnosed with RCVS or probable RCVS, based on International Classification of Headache Disorders, third edition (ICHD‐3) criteria, in a hospital‐based headache center from March 2005 to February 2014. Monthly averages of local weather data measured in Taipei were obtained from the Central Weather Bureau in Taiwan. Primary weather variables were compared with the number of monthly new‐onset cases of RCVS. Results We recruited 226 patients with established RCVS and 72 patients with probable RCVS during a 108‐month study period. Incidence of RCVS was higher in winter than summer months (3.3 persons/month [SD: 2.0] vs 2.1 persons/month [SD: 1.5], P = .013). The monthly incidence of RCVS correlated negatively with mean daily temperature (r = −0.231, P = .016) and average precipitation (r = −0.269, P = .005), but positively with barometric pressure (r = 0.274, P = .004). These 3 correlated meteorological factors together explained about 10% of the variance in RCVS monthly incidence (R2 = 0.095, P = .015). Conclusion RCVS was found to be more common in winter months and to be associated with weather variables in Taiwan. Further studies are needed to explore the underlying mechanisms of these associations.

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“…The majority of Google users live in the northern hemisphere; thus, seasonal variations in the time series mainly reflected this population. The peaks of interest in pain-related topics reflected previously reported relationships of pain location and the season for Headaches [51], viral infection of the upper airways (Ear pain, Sore throat), heartburn [52] or angina pectoris (Chest pain) [53], Abdominal pain [54,55], Low back pain [56], sexual activity (Dyspareunia) [57], and injuries (limb pain) [58]. Interestingly, the lowest RSVs for most of the topics were observed in December, which may be associated with the seasonal holidays, when people's attention could be away from the Internet.…”

Section: Time Coursesupporting

confidence: 59%

“Dr. Google, I am in Pain”—Global Internet Searches Associated with Pain: A Retrospective Analysis of Google Trends Data

Kamińśki

Łoniewski

Marlicz

2020

IJERPH

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We aimed to rank the most common locations of pain among Google users globally and locally and analyze secular and seasonal trends in pain-related searches in the years 2004–2019. We used data generated by Google Trends (GT) to identify and analyze global interest in topics (n = 24) related to locations of pain and how these progressed over time. We analyzed secular trends and time series decomposition to identify seasonal variations. We also calculated the interest in all topics with reference to the relative search volume (RSV) of “Abdominal pain”. Google users were most commonly interested in “Headache” (1.30 [times more frequently than “Abdominal pain”]), “Abdominal pain” (1.00), and “Back pain” (0.84). “Headache” was the most frequent search term in n = 41 countries, while “Abdominal pain” was the most frequent term in n = 27 countries. The interest in all pain-related topics except “Dyspareunia” increased over time. The sharpest increase was observed for “Abdominal pain” (5.67 RSV/year), and “Toothache” (5.52 RSV/year). Most of the topics revealed seasonal variations. Among pain-related topics, “Headache,” “Abdominal pain,” and “Back pain” interested most Google users. GT is a novel tool that allows retrospective investigation of complaints among Internet users.

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Patients with migraine are right about their perception of temperature as a trigger: time series analysis of headache diary data

Cited by 29 publications

References 29 publications

Analysis of Trigger Factors in Episodic Migraineurs Using a Smartphone Headache Diary Applications

Analysis of Trigger Factors in Episodic Migraineurs Using a Smartphone Headache Diary Applications

Influence of Climate on the Incidence of RCVS – A Retrospective Study From Taiwan

“Dr. Google, I am in Pain”—Global Internet Searches Associated with Pain: A Retrospective Analysis of Google Trends Data

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