To explore the impact of dynamic changes in depressive states on activity of daily living (ADL) limitations among middle-aged and older adults.

Based on data from the China Health and Retirement Longitudinal Study from 2011 to 2020, 8 617 individuals aged 45 and above were included. The transition characteristics of depressive states were analyzed using a Markov chain model. Latent class analysis was used to identify patterns of depressive changes, and the impact of different depressive trajectories on ADL limitations was assessed using multivariate logistic regression.

The transition probabilities of depressive states showed that the stability of no depression (0.76) and severe depression (0.37) was the highest. However, the transition probabilities from no depression to moderate and severe depression were 0.32 and 0.2,respectively. Latent class analysis identified three types of depressive trajectories: low-stable (1 007 cases with ADL limitations), gradually increasing (1 526 cases), and highly fluctuating (665 cases). Multivariate logistic regression showed that compared with the low-stable group, the risk of ADL limitations was significantly higher in the highly fluctuating group (OR=7.75, 95%CI: 6.54-9.17, P<0.05), followed by the gradually increasing group (OR=2.86; 95%CI: 2.58-3.18, P<0.05).

Dynamic changes in depressive states significantly affect ADL limitations. The group with highly fluctuating depressive trajectories has the highest risk. Clinically, it is necessary to strengthen the monitoring of depressive trajectories and design enhanced interventions for individuals with fluctuating depression to improve functional outcomes.