Distinct trajectories and state-trait decomposition of depressive symptoms in the pre-dementia stage: data from two large cohorts in China and England.

OBJECTIVES

This study examines the trajectories of depressive symptoms and decompose depressive symptoms into stable versus situational components among older adults in the pre-dementia stage.

METHODS

Using the data from the China Health and Retirement Longitudinal Study (CHARLS, N = 2926) and the English Longitudinal Study of Aging (ELSA, N =1641), latent class growth analysis grouped participants into distinct depressive symptom trajectories and regression model explored the predictors contributing to heterogeneous depressive symptom trajectories. The Stable Trait, Autoregressive Trait, and State (STARTS) model was conducted to distinguish the stable and situational components of depressive symptoms.

RESULTS

The results revealed four distinct depressive symptom trajectories: 'low symptoms, then worsening', 'persistent low symptoms', 'high symptoms, then improving' and 'persistent high symptoms'. Predictors of heterogeneous depressive symptom trajectories include age, gender, marital status, educational level, social isolation, pain, visual impairment and hypertension. The STARTS model decomposition indicated that the CHARLS sample accounted for 48% state variance and 52% autoregressive trait variance, whereas the ELSA sample had 52% state variance and 48% autoregressive trait variance.

CONCLUSIONS

Depressive symptom trajectories among older adults in the pre-dementia stage are heterogeneous. Predictors, emotional states, and long-term cumulative burden collectively shape the variability of trajectories. This study provides the evidence base for interrupting depressive symptoms and cognitive decline.