Abstract
Background
Pain is the primary symptom of knee osteoarthritis (KOA), significantly associated
with depressive symptoms. Whether the early pain intensity could distinguish different
trajectories of depressive symptoms is not well understood among patients with KOA.
Aims
To identify heterogeneous depressive symptoms trajectories among patients with KOA,
and investigate the association between depressive symptoms subgroups and pain intensity.
Design
Secondary analysis of a cohort sample.
Setting
Three waves of data from the China Health and Retirement Longitudinal Study was collected
in 28 provinces across China.
Participants
702 patients with KOA aged ≥ 45 years completed the Center for Epidemiologic Studies
Depression Scale biennially from 2011 to 2015.
Methods
Latent class growth analysis was performed to identify the optimal trajectory shape
and number of classes. Multinomial logistic regression analysis was conducted to compare
pain intensity across the trajectories.
Results
Four distinct trajectories were identified as follows: no depressive symptoms, highly
stable, decreasing, and increasing. In multivariate analysis, compared with the “no
depressive symptoms” class, patients in the “highly stable” class and “increasing”
class were more likely to report moderate pain (p < 0.05) and severe pain (p < 0.05). In addition, there was no significant difference in pain intensity between
“no depressive symptoms” class and “decreasing” class (p > 0.05).
Conclusions
These results suggest important heterogeneity in depressive symptom trajectories among
patients with KOA. Pain intensity could predict different depressive symptom trajectories
in patients with KOA. Efforts to improve the depressive symptoms in patients with
KOA must incorporate strategies to address pain.
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Article info
Publication history
Published online: November 24, 2022
Accepted:
October 24,
2022
Received in revised form:
October 23,
2022
Received:
May 8,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2022 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.
