TY - JOUR
T1 - Investigating the relationship between sleep and migraine in a global sample
T2 - a Bayesian cross-sectional approach
AU - Stanyer, Emily C.
AU - Brookes, Jack
AU - Pang, Jia Rong
AU - Urani, Alexandre
AU - Holland, Philip R.
AU - Hoffmann, Jan
N1 - Funding Information:
J.H. received honoraria for consulting activities and/or serving on advisory boards and/or as a speaker from Allergan, Abbvie, Autonomic Technologies Inc., Cannovex BV, Chordate Medical AB, Eli Lilly, Hormosan Pharma, Lundbeck, MD-Horizonte, Novartis, Sanofi and Teva. He received personal fees for Medico-Legal work as well as from NEJM Journal Watch, Oxford University Press, Quintessence Publishing, Sage Publishing and Springer Healthcare. He holds stock options from Chordate Medical AB. He also reports a research grant from Bristol Myers Squibb. Jan Hoffmann serves as Associate Editor for Cephalalgia, Cephalalgia Reports, Journal of Headache and Facial Pain, Journal of Oral & Facial Pain and Headache as well as for Frontiers in Pain Research. He is an elected member of the Board of Trustees as well as the Science and Research Committee of the International Headache Society (IHS) and serves as a Council Member and Treasurer of the British Association for the Study of Headache (BASH). None of the reported activities is directly related to the submitted work.
Funding Information:
This work has been supported by a Medical Research Council PhD studentship (E.C.S.; MR/N013700/1).
Publisher Copyright:
© 2023, Springer-Verlag Italia S.r.l., part of Springer Nature.
PY - 2023/12
Y1 - 2023/12
N2 - 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: 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: 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: 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.
AB - 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: 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: 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: 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.
KW - Bayesian
KW - Headache
KW - Migraine
KW - Modelling
KW - Pain
KW - Sleep
KW - Sleep deprivation
UR - http://www.scopus.com/inward/record.url?scp=85170195512&partnerID=8YFLogxK
U2 - 10.1186/s10194-023-01638-6
DO - 10.1186/s10194-023-01638-6
M3 - Article
C2 - 37679693
AN - SCOPUS:85170195512
SN - 1129-2369
VL - 24
JO - Journal of Headache and Pain
JF - Journal of Headache and Pain
IS - 1
M1 - 123
ER -