Re-examining the pain-depression vicious cycle in knee osteoarthritis: a random-intercept cross-lagged panel analysis

Pain and depression frequently co-occur in knee osteoarthritis (OA), traditionally viewed as a vicious cycle in which each worsens the other over time. However, conventional cross-lagged models cannot separate stable differences between individuals from real year-to-year changes within a person. We therefore used a random-intercept cross-lagged panel model (RI-CLPM) in the Osteoarthritis Initiative (OAI).

Of 4,796 enrolled OAI participants with, or at risk of, knee OA, 4,638 contributed data across four annual waves from months 12 to 48. The RI-CLPM was applied to knee pain (WOMAC scale, worse knee) and depressive symptoms (CES-D scale), using full-information maximum likelihood. We contrasted it with a traditional model (CLPM), replicated it in a later six-wave window (months 36 to 96), and tested moderation by sex, arthritis severity, baseline pain and baseline depression, alongside covariate-adjusted and sensitivity analyses. Sensitivity analyses used a cognitive-affective CES-D subscale excluding somatic items, alternative model constraints and an alternative standardisation.

The RI-CLPM fitted well and the between-person trait correlation was substantial (standardised r = 0.39, p < 0.001), whereas within-person cross-lagged paths were small and non-significant in both directions (pain to depression standardised beta = 0.019, 95% CI -0.010 to 0.048; depression to pain beta = 0.009, 95% CI -0.019 to 0.036). A classical CLPM on identical data showed significant reciprocal paths (both beta approximately 0.08) but fitted poorly; separating the random intercepts reduced the cross-lagged coefficients by roughly 77-89%. The pattern was reproduced in the second window, unchanged by covariates, and no moderator test survived correction for multiple testing. Using a cognitive-affective CES-D subscale reduced both cross-lagged paths further (0.014 and - 0.001) and the trait correlation to 0.34.

In knee OA, the link between pain and depression was mainly explained by stable differences between individuals. At annual intervals we found limited evidence for reciprocal within-person effects, which is not evidence that none exist; shorter-term dynamics were not estimable. Depressive symptoms should still be assessed, but the findings do not support an automatic year-to-year feedback loop, and do not show whether treating one symptom improves the other.