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. Implications for Rehabilitation Sedentary behaviour is highly prevalent in multiple sclerosis and may be associated with comorbid conditions. The majority of research on sedentary behaviour in multiple sclerosis has been derived from self-report instruments that only measure the volume of sitting time per day. This study indicates that persons with multiple sclerosis spend a significant amount of time sedentary, and those who are older, have progressive multiple sclerosis, and have higher disability status spend prolonged, uninterrupted periods of time sedentary. Such results highlight the need for targeted behavioural interventions in these sub-populations of multiple sclerosis to reduce time spent sedentary and break the pattern of sedentary behaviour to manage its consequences.
Keywords: Multiple sclerosis; accelerometry; health behaviour; lifestyle factors; sedentary behaviour.