Objective: This article provided an updated quantitative synthesis of physical activity levels in persons with multiple sclerosis compared with controls and other clinical populations. Design: A systematic search through PubMed, Scopus, and PsycINFO was conducted for articles published between August 2016 and July 2022. Articles that included a group comparison of at least one measurement of physical activity between adults with multiple sclerosis and controls or other clinical populations were included in the meta-analysis. Results: Twenty-four studies met the inclusion criteria and yielded a total of 119 comparisons. There was a moderate difference in physical activity levels between persons with multiple sclerosis and controls (effect size = −0.56, P < 0.01), but no significant difference between persons with multiple sclerosis and other clinical populations (effect size = 0.01, P = 0.90). The pooled effect sizes comparing multiple sclerosis with controls (Q ₁₀₄ = 457.9, P < 0.01) as well as with clinical populations (Q ₁₃ = 108.4, P < 0.01) were heterogeneous. Moderating variables included sex, disability status, measurement method, outcome, intensity, and application of a multiple sclerosis–specific cut-point. Conclusions: Physical activity levels remain significantly lower in persons with multiple sclerosis compared with controls, but the magnitude of difference has become smaller over the past decade. There is a need for continued development of effective physical activity programs that can reach the greater community with multiple sclerosis.

Background: Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD. Objective: This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD. Methods: A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (–0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking. Conclusions: The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

Purpose: This study examined sociodemographic and clinical variables as correlates of device-measured volume and pattern of sedentary behaviour in persons with multiple sclerosis (MS). Materials and methods: Participants were recruited through a standardised invitation letter distributed among 1000 persons randomly selected from the North American Research Committee on MS registry. Those who volunteered wore an accelerometer for 7 d and provided sociodemographic and clinical information. Results: There were 233 persons with MS who were included in the analyses. Linear regression analyses indicated that age and MS type explained significant variance in total sedentary time per day as well as number of breaks in sedentary time. Only disability status explained significant variance in sedentary bout length, whereas age explained significant variance in both number of long sedentary bouts per day. Both age and disability status explained significant variance total time spent in long sedentary bouts per day. Conclusions: Persons of older age, progressive MS, and higher disability status spend prolonged, uninterrupted periods of time sedentary. Such results highlight the need for targeted interventions in sub-populations of MS that reduce time spent sedentary and break up the pattern of sedentary behaviour.

Objective: This study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson’s disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD. Methods: The sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2–3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual’s self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system. Results: Our results indicated a strong association between activity counts and energy expenditure for persons with PD (R² = 0.87) and controls (R² = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min^-1 for persons with PD than the cut-point of 2,010 counts·min^-1 for controls. Conclusion: Our results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD.