TY - JOUR
T1 - Fragmentation, circadian amplitude, and fractal pattern of daily-living physical activity in people with multiple sclerosis
T2 - Is there relevant information beyond the total amount of physical activity?
AU - Salomon, Amit
AU - Galperin, Irina
AU - Buzaglo, David
AU - Mirelman, Anat
AU - Regev, Keren
AU - Karni, Arnon
AU - Schmitz-Hübsch, Tanja
AU - Paul, Friedemann
AU - Devos, Hannes
AU - Sosnoff, Jacob J.
AU - Gazit, Eran
AU - Tamir, Raz
AU - Shimoni, Nathaniel
AU - Hausdorff, Jeffrey M.
N1 - Publisher Copyright:
© 2022
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Background: Physical activity is lower in people with multiple sclerosis (pwMS) compared to healthy controls. Previous work focused on studying activity levels or activity volume, but studies of daily-living rest-activity fragmentation patterns, circadian rhythms, and fractal regulation in pwMS are limited. Based on findings in other cohorts, one could suggest that these aspects of daily-living physical activity will provide additional information about the health and well-being of pwMS. Therefore, here, we aimed to (1) identify which fragmentation, fractal, and circadian amplitude measures differ between pwMS and healthy controls, (2) evaluate the relationship between fragmentation, fractal, and circadian amplitude measures and disease severity, and (3) begin to evaluate the added value of those measures, as compared to more conventional measures of physical activity (e.g., mean signal vector magnitude (SVM). A global measure of the overall volume of physical activity). Methods: 132 people with relapsing-remitting MS (47±11 yrs, 69.7% female, Expanded Disability Status Scale, EDSS, median (IQR): 3 (2–4)) and 90 healthy controls (46±11 yrs, 47.8% female) were asked to wear a 3D accelerometer on their lower back for 7 days. Rest-activity fragmentation, circadian amplitude, fractal regulation, and mean SVM metrics were extracted. PwMS and healthy controls were compared using independent samples t-tests and linear regression, including comparisons adjusted for mean SVM to control for the effect of physical activity volume. Spearman correlations between measures and logistic regressions were used to identify the clinical condition based on the measures that differed significantly after adjusting for SVM. All analyses included adjustments for demographic and clinical parameters (e.g., age, sex). Results: Multiple measures of activity fragmentation significantly differed between pwMS and healthy controls, reflecting a more fragmented active behavior in pwMS. PwMS had a lower circadian rhythm amplitude, indicating a smaller amplitude in the circadian changes of daily activity, and weaker temporal correlations as based on the fractal analysis. When taking into account physical activity volume, one circadian amplitude measure and one fractal measure remained significantly different in pwMS and controls. Fragmentation measures and circadian amplitude measures were significantly associated with disability level as measured by the EDSS; the association with circadian amplitude remained significant, even after adjusting for the mean SVM. Conclusion: The physical activity patterns of pwMS differ from those of healthy individuals in rest-activity fragmentation, the amplitude of the circadian rhythm, and fractal regulation. Measures describing these aspects of activity provide information that is not captured in the total volume of physical activity and could, perhaps, augment the monitoring of disease progression and evaluation of the response to interventions.
AB - Background: Physical activity is lower in people with multiple sclerosis (pwMS) compared to healthy controls. Previous work focused on studying activity levels or activity volume, but studies of daily-living rest-activity fragmentation patterns, circadian rhythms, and fractal regulation in pwMS are limited. Based on findings in other cohorts, one could suggest that these aspects of daily-living physical activity will provide additional information about the health and well-being of pwMS. Therefore, here, we aimed to (1) identify which fragmentation, fractal, and circadian amplitude measures differ between pwMS and healthy controls, (2) evaluate the relationship between fragmentation, fractal, and circadian amplitude measures and disease severity, and (3) begin to evaluate the added value of those measures, as compared to more conventional measures of physical activity (e.g., mean signal vector magnitude (SVM). A global measure of the overall volume of physical activity). Methods: 132 people with relapsing-remitting MS (47±11 yrs, 69.7% female, Expanded Disability Status Scale, EDSS, median (IQR): 3 (2–4)) and 90 healthy controls (46±11 yrs, 47.8% female) were asked to wear a 3D accelerometer on their lower back for 7 days. Rest-activity fragmentation, circadian amplitude, fractal regulation, and mean SVM metrics were extracted. PwMS and healthy controls were compared using independent samples t-tests and linear regression, including comparisons adjusted for mean SVM to control for the effect of physical activity volume. Spearman correlations between measures and logistic regressions were used to identify the clinical condition based on the measures that differed significantly after adjusting for SVM. All analyses included adjustments for demographic and clinical parameters (e.g., age, sex). Results: Multiple measures of activity fragmentation significantly differed between pwMS and healthy controls, reflecting a more fragmented active behavior in pwMS. PwMS had a lower circadian rhythm amplitude, indicating a smaller amplitude in the circadian changes of daily activity, and weaker temporal correlations as based on the fractal analysis. When taking into account physical activity volume, one circadian amplitude measure and one fractal measure remained significantly different in pwMS and controls. Fragmentation measures and circadian amplitude measures were significantly associated with disability level as measured by the EDSS; the association with circadian amplitude remained significant, even after adjusting for the mean SVM. Conclusion: The physical activity patterns of pwMS differ from those of healthy individuals in rest-activity fragmentation, the amplitude of the circadian rhythm, and fractal regulation. Measures describing these aspects of activity provide information that is not captured in the total volume of physical activity and could, perhaps, augment the monitoring of disease progression and evaluation of the response to interventions.
KW - Accelerometer
KW - Activity fragmentation
KW - Circadian amplitude
KW - Daily living
KW - Fractal regulation
KW - Multiple sclerosis
UR - http://www.scopus.com/inward/record.url?scp=85137300870&partnerID=8YFLogxK
U2 - 10.1016/j.msard.2022.104108
DO - 10.1016/j.msard.2022.104108
M3 - Article
C2 - 36063732
AN - SCOPUS:85137300870
SN - 2211-0348
VL - 68
JO - Multiple Sclerosis and Related Disorders
JF - Multiple Sclerosis and Related Disorders
M1 - 104108
ER -