Do Demographic and Clinical Variables Predict Change in Physical Activity over Time in Persons with Relapsing-Remitting Multiple Sclerosis?
Objectives: This study involved a secondary analysis of existing data and examined demographic and clinical variables as predictors of initial status and rate of change in physical activity over a 2.5 year period of time in people with relapsing-remitting multiple sclerosis (RRMS).
Methods: On 6 occasions separated by 6 months over 2.5 years, 269 persons with RRMS completed a battery of questionnaires and wore an accelerometer (ActiGraph model 7164) for 7 days. The battery of questionnaires included information on disease duration, disability, sex, age, race, BMI, education and income. The data were analyzed with unconditional and conditional latent growth curve modeling (LGM) using the robust maximum likelihood estimator and the Mplussoftware package.
Results: The unconditional LGM indicated a statistically significant linear reduction in average counts per day from the accelerometer over the 2.5-year period of time. The conditional LGM indicated that education (p < .01), disability (p < .001), and BMI (p < .005) predicted initial status for physical activity. The conditional LGM further indicated that BMI predicted the rate of change in physical activity over time (p < .005); those who were more overweight had a greater reduction in physical activity over the 2.5-year period.
Conclusions: Researchers should consider designing behavioral interventions for increasing physical activity among those persons with MS who have higher BMI as this demographic appears susceptible to reductions in physical activity over time. This might further explain the association between BMI and other disease outcomes in RRMS.