Investigating the relationship between sleep and migraine in a global sample: a Bayesian cross-sectional approach.
Bayesian
Headache
Migraine
Modelling
Pain
Sleep
Sleep deprivation
Journal
The journal of headache and pain
ISSN: 1129-2377
Titre abrégé: J Headache Pain
Pays: England
ID NLM: 100940562
Informations de publication
Date de publication:
08 Sep 2023
08 Sep 2023
Historique:
received:
24
05
2023
accepted:
24
07
2023
medline:
11
9
2023
pubmed:
8
9
2023
entrez:
7
9
2023
Statut:
epublish
Résumé
There is a bidirectional link between sleep and migraine, however causality is difficult to determine. This study aimed to investigate this relationship using data collected from a smartphone application. Self-reported data from 11,166 global users (aged 18-81 years, mean: 41.21, standard deviation: 11.49) were collected from the Migraine Buddy application (Healint Pte. Ltd.). Measures included: start and end times of sleep and migraine attacks, and pain intensity. Bayesian regression models were used to predict occurrence of a migraine attack the next day based on users' deviations from average sleep, number of sleep interruptions, and hours slept the night before in those reporting ≥ 8 and < 25 migraine attacks on average per month. Conversely, we modelled whether attack occurrence and pain intensity predicted hours slept that night. There were 724 users (129 males, 412 females, 183 unknown, mean age = 41.88 years, SD = 11.63), with a mean monthly attack frequency of 9.94. More sleep interruptions (95% Highest Density Interval (95%HDI [0.11 - 0.21]) and deviation from a user's mean sleep (95%HDI [0.04 - 0.08]) were significant predictors of a next day attack. Total hours slept was not a significant predictor (95%HDI [-0.04 - 0.04]). Pain intensity, but not attack occurrence was a positive predictor of hours slept. Sleep fragmentation and deviation from typical sleep are the main drivers of the relationship between sleep and migraine. Having a migraine attack does not predict sleep duration, yet the pain associated with it does. This study highlights sleep as crucial in migraine management.
Sections du résumé
BACKGROUND
BACKGROUND
There is a bidirectional link between sleep and migraine, however causality is difficult to determine. This study aimed to investigate this relationship using data collected from a smartphone application.
METHODS
METHODS
Self-reported data from 11,166 global users (aged 18-81 years, mean: 41.21, standard deviation: 11.49) were collected from the Migraine Buddy application (Healint Pte. Ltd.). Measures included: start and end times of sleep and migraine attacks, and pain intensity. Bayesian regression models were used to predict occurrence of a migraine attack the next day based on users' deviations from average sleep, number of sleep interruptions, and hours slept the night before in those reporting ≥ 8 and < 25 migraine attacks on average per month. Conversely, we modelled whether attack occurrence and pain intensity predicted hours slept that night.
RESULTS
RESULTS
There were 724 users (129 males, 412 females, 183 unknown, mean age = 41.88 years, SD = 11.63), with a mean monthly attack frequency of 9.94. More sleep interruptions (95% Highest Density Interval (95%HDI [0.11 - 0.21]) and deviation from a user's mean sleep (95%HDI [0.04 - 0.08]) were significant predictors of a next day attack. Total hours slept was not a significant predictor (95%HDI [-0.04 - 0.04]). Pain intensity, but not attack occurrence was a positive predictor of hours slept.
CONCLUSIONS
CONCLUSIONS
Sleep fragmentation and deviation from typical sleep are the main drivers of the relationship between sleep and migraine. Having a migraine attack does not predict sleep duration, yet the pain associated with it does. This study highlights sleep as crucial in migraine management.
Identifiants
pubmed: 37679693
doi: 10.1186/s10194-023-01638-6
pii: 10.1186/s10194-023-01638-6
pmc: PMC10486047
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
123Subventions
Organisme : Medical Research Council
ID : MR/N013700/1
Pays : United Kingdom
Informations de copyright
© 2023. Springer-Verlag Italia S.r.l., part of Springer Nature.
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