Objectives: This study aimed to identify and characterize homogeneous subgroups of individuals with distinct trajectories of physical functioning (PF) and to examine prognostic indicators of deterioration in PF in a highly heterogeneous population of older adults with joint pain and comorbidity.
Study design: A prospective cohort study among 407 older adults with joint pain and comorbidity provided data over a period of 18 months, with 6 month time-intervals. We used latent class growth modelling (LCGM) to identify underlying subgroups (clusters) with distinct trajectories of PF. Next, we characterized these subgroups and applied multivariable logistic regression analysis to identify prognostic indicators for deterioration in PF.
Main outcome measures: We measures PF with the RAND-36 PF subscale and several potential sociodemographic, physical and psychosocial prognostic indicators.
Results: LCGM identified three clusters. Cluster 1 'good PF' contained 140 participants with good baseline PF and small improvements over time. Cluster 2 'moderate PF' contained 130 participants with moderate baseline PF and deterioration over time. Cluster 3 'poor PF' contained 137 participants with poor baseline PF and deterioration over time. After backward selection, the final model that could best distinguish between improved participants (cluster 1) and deteriorated participants (cluster 2-3) included the following prognostic indicators: higher age, more depressive symptoms, less perceived self-efficacy and more activity avoidance.
Conclusions: Older adults with joint pain and comorbidity either improved or deteriorated in PF over time. The prognostic model facilitates the classification of patients, the provision of more accurate information about prognosis and helps to narrow the focus to the high risk group of poor PF.
Keywords: Elderly; Functioning; Joint pain; Longitudinal; Primary care; Prognostic.
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