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Association of accelerometer-derived sleep and idiopathic dystonia: A UK Biobank cohort study

G. Bailey, M. Wadon, S. Komarzynski, C. Matthews, EH. Davies, K. Peall (Cardiff, United Kingdom)

Meeting: 2022 International Congress

Abstract Number: 555

Keywords: Dystonia: Clinical features, Sleep disorders. See also Restless legs syndrome: Clinical features

Category: Dystonia: Epidemiology, Genetics, Phenomenology

Objective: To assess the rate and nature of sleep disturbances in dystonia, and to examine the extent to which disturbance to sleep is associated with other non-motor symptoms, using data from the UK Biobank (UKBB).

Background: Sleep disturbance is an increasingly recognised co-morbid trait in dystonia.      Although wrist-worn accelerometers enable objective measures of sleep at scale, no previous studies have investigated the accuracy of wrist-worn accelerometers in delineating the nature of these changes. Here, we examine sleep using self-reported and accelerometer-derived measures from a cohort of patients diagnosed with dystonia in the UKBB.

Method: A previously validated algorithm using ICD-10 and Read codes from hospital and primary care records was used to identify a cohort of individuals diagnosed with dystonia. Within this cohort, those who had also participated in an accelerometer study were selected[1]. An age- and sex-matched control cohort was determined from the remaining UKBB cohort. Sleep measures were derived from a wrist-worn triaxial accelerometer (Axivity AX3) worn over seven days and compared to the control cohort. Linear regression was used to analyse data relating to physical activity, pain and psychiatric disorders.

Results: 241 individuals with a clinically confirmed dystonia diagnosis and accelerometer recordings were identified. Mann Whitney-U tests found those with dystonia to have later sleep times (p<0.001), reduced time in bed (p<0.001) and shorter sleep duration (p=0.001) and reduced daytime acceleration (p<0.001) compared to controls. Accelerometer-derived sleep measures were concordant with their respective self-reported sleep variables (p<0.001) and were associated with measures of physical activity (p<0.001). Interestingly, there were limited associations with pain and psychiatric diagnoses, only psychiatric disorders were associated with increased number and duration of daytime naps (p=0.001, p<0.001).

Conclusion: Wrist-worn accelerometers are a useful tool in identifying and exploring sleep disturbances in dystonia at scale. Monitoring of sleep also has important implications for the treatment of other non-motor symptoms in dystonia, particularly as inactivity worsened sleep quality. Our findings provide a platform for future investigations and support the integration of sleep assessment into dystonia clinical care pathways.

References: Doherty A, Jackson D, Hammerla N, Plötz T, Olivier P, et al. (2017) Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLOS ONE 12(2): e0169649. https://doi.org/10.1371/journal.pone.0169649

To cite this abstract in AMA style:

G. Bailey, M. Wadon, S. Komarzynski, C. Matthews, EH. Davies, K. Peall. Association of accelerometer-derived sleep and idiopathic dystonia: A UK Biobank cohort study [abstract]. Mov Disord. 2022; 37 (suppl 2). https://www.mdsabstracts.org/abstract/association-of-accelerometer-derived-sleep-and-idiopathic-dystonia-a-uk-biobank-cohort-study/. Accessed June 14, 2025.
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