Motor dysfunction in Parkinson's patients: depression differences in a latent growth model.

Objective: This study aims to utilize latent growth model (LGM) to explore the developmental trajectory of motor dysfunction in Parkinson's disease (PD) patients and investigate the relationship between depression and motor dysfunction. Methods: Four-year follow-up data from 389 PD patients were collected through the Parkinson's Progression Marker Initiative (PPMI). Firstly, a univariate LGM was employed to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, depression levels were introduced as covariates into the model, and depression was further treated as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression. Results: In the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ2 = 7.419, df = 6, CFI = 0.998, TLI = 0.997, SRMR = 0.019, and RMSEA = 0.025, indicating that the growth trend of motor dysfunction follows a quadratic curve rather than a simple linear pattern. Introducing depression symptoms as time-varying covariates to explore their effect on motor dysfunction revealed significant positive correlations (β = 0.383, Conclusion: This study indicates a quadratic growth trajectory for motor dysfunction in PD, suggesting a continuous increase in severity with a gradual deceleration in growth rate. The relationship between depression and motor dysfunction is complex, involving initial associations, evolving trends over time, and potential quadratic effects. Exacerbation of depressive symptoms may coincide with motor function deterioration.