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Depressive symptom trajectories and new-onset arthritis in a middle-aged and elderly Chinese population. | LitMetric

Depressive symptom trajectories and new-onset arthritis in a middle-aged and elderly Chinese population.

J Psychosom Res

Department of Clinical Nutrition, Yancheng Third People's Hospital, The Sixth Affiliated Hospital of Nantong University, Yancheng, 224001, PR China. Electronic address:

Published: September 2023

Objective: Previous studies reported that depression was associated with a high risk of arthritis. However, the effect of different long-term depressive symptom trajectory patterns on the risk of arthritis has not been evaluated. Our study aimed to explore the association between depressive symptom trajectories and the risk of arthritis.

Methods: A total of 5583 participants from the China Health and Retirement Longitudinal Study from 2011 to 2018 were included in this analysis. Group-based trajectory modeling was used to identify depressive symptom trajectories, and a multivariable competitive Cox regression model was used to examine the association of depressive symptom trajectories with arthritis during follow-up.

Results: Five depressive symptom trajectories were identified in our research: stable-high, decreasing, increasing, stable-moderate and stable-low. Compared with participants in the stable-low trajectory group, those in the stable-moderate, increasing, decreasing and stable-high trajectory groups had a higher cumulative risk of arthritis, with HRs (95% CIs) for arthritis of 1.64 (1.30, 2.07), 1.86 (1.30, 2.66), 1.99 (1.41, 2.80) and 2.19 (1.38, 3.48), respectively. Participants with the stable-high symptoms trajectory had the highest cumulative risk of arthritis. There was still a high risk of arthritis, although the depression state was reduced and remained at a level that is generally considered reasonable.

Conclusions: The higher depressive symptoms trajectories were significantly associated with the increased risk of arthritis, and the long-term depressive symptoms trajectories may be a strong predictor of having arthritis.

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Source
http://dx.doi.org/10.1016/j.jpsychores.2023.111422DOI Listing

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