Trajectories of Depressive Symptoms in Middle-Aged and Older Adults with Arthritis: A Longitudinal Analysis Using the Korean Longitudinal Study of Aging (2006–2022)

Abstract

This study aimed to examine the trajectories of depressive symptoms among patients newly diagnosed with arthritis, using data from the Korean Longitudinal Study of Aging (2006–2022). Depressive symptoms were assessed with the 10-item Center for Epidemiologic Studies Depression Scale. Latent growth modeling was applied to examine linear and quadratic trajectories of depressive symptoms and to identify sociodemographic and health-related predictors influencing these trajectories. Model fit was evaluated using chi-square test, CFI, RMSEA, SRMR indices. Data from 769 participants diagnosed between 2008 and 2014 were analyzed. The quadratic growth model provided a superior fit (χ²= 41.26, df=12, CFI=0.978, RMSEA=0.056, SRMR=0.044) compared to the linear model, indicating a nonlinear trajectory characterized by an initial rise in depressive symptoms around diagnosis followed by gradual stabilization to near pre-diagnosis levels. Age (β= 0.102, p<.001), number of diseases (β=0.551, p=.005), and marital status (β=–0.922, p=.040) had significant effects on the initial level of depressive symptoms. For the linear rate of change of depressive symptoms, final education (beta=-0.339, p=.041) and the number of diseases (beta= 0.161, p=.040) had a significant impact. Regarding the quadratic rate of change in depressive symptoms, final education (beta=0.034, p=.042) and the number of diseases (beta=-0.020, p=.012) had a significant effect. These findings underscore the dynamic nature of depressive symptoms in arthritis and the need for timely, tailored mental health interventions.