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AuthorAbedalaziz, Wlla
AuthorAl-Sharman, Alham
AuthorAburub, Aseel
AuthorLatrous, Mariem Syrine
AuthorEsser, Patrick
AuthorDawes, Helen
AuthorEl-Salem, Khalid
AuthorKhalil, Hanan
Available date2024-07-22T09:20:00Z
Publication Date2023
Publication NameHong Kong Physiotherapy Journal
Identifierhttp://dx.doi.org/10.1142/S1013702523500129
ISSN1013-7025
URIhttp://hdl.handle.net/10576/56919
AbstractBackground: Gait deficits are common among people with multiple sclerosis (PwMS). Therefore, investigating factors that may influence walking in PwMS is important. Previous studies in older adults and other neurological populations demonstrated the relationship between sleep quality and gait performance. Despite the fact that the prevalence of poor sleep quality is very high among PwMS, little is known about the effect of sleep quality on gait among PwMS. Objective: This study aimed to explore the relationship between sleep quality and gait performance in PwMS. Methods: Forty-one PwMS participated in the study between February 2019 and December 2019. Participants were asked to walk at a self-selected speed over 10m with an inertial measurement unit (IMU) attached over the back. Walking speed, step length (left and right), and step time were calculated. Sleep was estimated objectively using a wrist-worn triaxle-accelerometer; the derived parameters were sleep efficiency (SE) and the number of awakening after sleep onset (NASO). Results: SE significantly correlated with step length (p=0.02). Furthermore, the NASO significantly correlated with gait speed (p=0.03), and step-time (p=0.02). These correlations remained significant even after adjusting for age and disease duration. Conclusion: We observed that when corrected for disease duration and age there were relationships between NASO and SE to gait parameters; these observations warrant further investigations. AB - Background: Gait deficits are common among people with multiple sclerosis (PwMS). Therefore, investigating factors that may influence walking in PwMS is important. Previous studies in older adults and other neurological populations demonstrated the relationship between sleep quality and gait performance. Despite the fact that the prevalence of poor sleep quality is very high among PwMS, little is known about the effect of sleep quality on gait among PwMS. Objective: This study aimed to explore the relationship between sleep quality and gait performance in PwMS. Methods: Forty-one PwMS participated in the study between February 2019 and December 2019. Participants were asked to walk at a self-selected speed over 10m with an inertial measurement unit (IMU) attached over the back. Walking speed, step length (left and right), and step time were calculated. Sleep was estimated objectively using a wrist-worn triaxle-accelerometer; the derived parameters were sleep efficiency (SE) and the number of awakening after sleep onset (NASO). Results: SE significantly correlated with step length (p=0.02). Furthermore, the NASO significantly correlated with gait speed (p=0.03), and step-time (p=0.02). These correlations remained significant even after adjusting for age and disease duration. Conclusion: We observed that when corrected for disease duration and age there were relationships between NASO and SE to gait parameters; these observations warrant further investigations.
SponsorFunding support from the Jordan University of Science and Technology (Grant number-AA/31/2019) is acknowledged. Helen Dawes research is supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. This manuscript has not previously been presented in a scientific meeting or publication.
Languageen
PublisherWorld Scientific Publishing Co.
SubjectMultiple sclerosis
gait
sleep quality
TitleThe relationship between sleep quality and gait in people with multiple sclerosis: A pilot study
TypeArticle
Pagination11-19
Issue Number1
Volume Number44
dc.accessType Open Access


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