Depression in older adults: longitudinal study findings from a national survey in China.

Background: Late-life depression (LLD) is a significant global public health challenge among older adults. Identifying predictive/influential symptoms based on longitudinal data can contribute to early prevention, detection, and intervention of LLD. This study examined significant influential symptoms of LLD using cross-lagged panel network (CLPN) analysis based on a longitudinal national survey.

Methods: Data from the 2018 and 2020 waves of the China Health and Retirement Longitudinal Study (CHARLS) were used to construct a longitudinal depressive symptom network. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). In expected influence (in-EI) and out expected influence (out-EI) were used as centrality indices to characterize interactions within the depressive symptom network. Network stability was assessed using the case-dropping bootstrap method.

Results: A total of 6533 older adults were assessed (Model 1). The most predictive/influential symptoms were "Everything was an effort" (CESD4), "Felt depressed" (CESD3) and "Felt lonely" (CESD9), all of which predicted increased risk for other depressive symptoms two years later. Additionally, when examining older adults with depression at baseline (Model 2), "Bothered by things" (CESD1), "Everything was an effort" (CESD4) and "Felt unhappy" (CESD8) emerged as the most predictive/influential symptoms of other depressive symptoms in the future.

Conclusions: Considering difficulties in treating LLD and its negative consequences on daily life in older adults, timely interventions targeting identified most influential symptoms may be conducive to the prevention and mitigation of future depression.