Longitudinal Associations Between Depression Symptoms and Cognitive Functions in Chinese Older Adults: A Cross-Lagged Panel Network Analysis.

With rapid population aging in China, understanding the relationship between depression symptoms and cognitive function is crucial for improving the mental health of older adults. This study investigates these dynamics using data from the China Health and Retirement Longitudinal Study (CHARLS). We analyzed data from the 2015, 2018, and 2020 waves of CHARLS, including 5203 participants aged 60 and above. Depression symptoms were measured using the Centre for Epidemiological Studies Depression-10 (CESD-10) scale, while cognitive function was assessed via the Mini-Mental State Examination (MMSE) scale. Cross-sectional network analysis was utilized for constructing the contemporaneous network, and cross-lagged panel network (CLPN) analysis was subsequently employed for longitudinal analysis. In all three cross-sectional networks, "Hope" was identified as a key bridge symptom connecting the depression symptom community and the cognitive function community, while "Depressed mood" was found to be the central symptom of the entire network. In temporal networks, higher drawing ability at wave 1 was associated with greater "Hope" at wave 2, whereas higher "Fear" at wave 1 was related to lower recall ability at wave 2. Moreover, lower memory ability at wave 2 was associated with lower "Bothered" at wave 3. This study uncovered the dynamic interplay between specific depression symptoms and cognitive functions among Chinese older adults, thereby providing further validation for the scar theory and the cognitive vulnerability model. Additionally, it provides a critical theoretical foundation for developing intervention strategies targeting mental health and cognitive function in the aging population, as well as a scientific basis for related policy formulation. Future research should integrate quantitative and qualitative data for stronger causal validation.