Trajectories of Physical Function and Disability Over 12 Months in Older Adults With Chronic Low Back Pain

Background and Purpose:Understanding prognosis is critical for clinical care and health policy initiatives. The purpose of this study was to determine whether distinct prognostic trajectories of physical function and disability exist in a cohort of 245 community-dwelling older adults with chronic low back pain (LBP), and to characterize the demographic, health, and pain-related profiles of each trajectory subgroup.Methods:All participants underwent standard clinic examinations at baseline, 3 months, 6 months, and 12 months. At each time point, the Late Life Function & Disability Instrument (LLFDI) was used to measure general physical function (LLFDI Function) and disability (LLFDI Disability-Limitation); the Quebec LBP Disability Questionnaire was used to measure disability due to pain. Growth mixture modeling (GMM) was performed on each outcome to identify distinct trajectory classes/subgroups; baseline demographic (eg, age and sex), health (eg, comorbidities, depressive symptoms, and physical activity level), and pain-related (eg, LBP intensity, pain-related fear, and pain catastrophizing) characteristic profiles were compared across subgroups.Results:GMM statistics revealed an optimal number of 3 to 4 trajectory subgroups, depending on the outcome examined. Subgroups differed across demographic, health, and pain-related characteristics; the classes with the most favorable prognoses had consistent profile patterns: fewer depressive symptoms, fewer comorbidities, higher physical activity levels, lower LBP intensities, less pain-related fear, and less pain catastrophizing.Conclusion:Our findings indicate that several distinct trajectory subgroups exist that would have been masked by observing mean cohort change alone. Furthermore, subgroup characteristic profiles may help clinicians identify likely prognostic trajectories for their patients. Future research should focus on identifying modifiable risk factors that best predict group membership, and tailoring interventions to mitigate the risk of poor prognosis.