Statistical model of trajectories of reduced mobility in older people with locomotive disorders: a prospective cohort study with group-based trajectory model

Abstract

Abstract Background Today we experience “Super-aged society”, and a drastic increase in the number of older people needing assistance is an urgent matter for everyone from medical and socio-economical standpoints. Locomotive organ dysfunction due to musculoskeletal disorders is one of the main problems in these patients. Although the concepts of frailty and sarcopenia have been proposed for functional decline, pain remains the main and non-negligible complaint in these of such disorders. This prospective cohort study aimed to observe the changes of reduced mobility in patients with locomotive disorders and to determine the risk factors for functional deterioration of those patients using statistical modeling. Methods A cohort of older adults with locomotive disorders who were followed up every 6 months for up to 18 months was organized. Pain, physical findings related to the lower extremities, locomotive function in performing daily tasks, and Geriatric Locomotive Function Scale-25 (GLFS-25) score were collected to predict the progress of deterioration. Group-based trajectory analysis was used to identify subgroups of changes of GLFS-25 scores, and multinomial logistic regression analysis was performed to investigate potential predictors of the GLFS-25 trajectories. Results Overall, 314 participants aged between 65 and 93 years were included. The participants were treated with various combinations of orthopedic conservative treatments on an outpatient basis. The in-group trajectory model analysis revealed a clear differentiation between the four groups. The mild and severe groups generally maintained their GLFD-25 scores, while the moderate group included a fluctuating group and a no change group.　This study showed that comorbidity of osteoporosis was related to GLFS-25 score over 18 months. Age was a weak factor to be moderate or severe group, but gender was not. In addition, the number of pain locations, number of weak muscles, one-leg standing time, grip strength and BMI significantly contributed to the change in GLFS-25 score. Conclusions This study proposes an effective statistical model to monitor locomotive functions and related findings. Pain and comorbid osteoporosis are significant factors that related to functional deterioration of activities. In addition, the study shows a patient group recovers from the progression and their possible contributing factors.