The association between social engagement and depressive symptoms in middle-aged and elderly Chinese: A longitudinal subgroup identification analysis under causal inference frame

BackgroundStudies have suggested that there is a significant association between social engagement and depression symptoms. However, this association may differ in people with different features such as different sociodemographic characteristics and health conditions. MethodsResearch data were obtained from the CHARLS database. The causal inference was performed with the propensity score. We used the linear mixed-effects model tree algorithm under the causal inference frame for subgroup identification analysis. ResultsWe included 13,521 participants, and the median follow-up time is 4 years. Under the casual inference frame, the association between social engagement and depression symptoms is confirmed for all included individuals (OR = 0.957, P = 0.016; 95%CI: 0.923-0.992). Using the linear mixed-effects model tree, we found two subgroups, including middle-aged and elderly residents who live in rural areas with <6 h of sleep and those living in urban areas, could benefit more from social engagement. After using the propensity score method, all the two subgroups selected are statistically significant (P = 0.007; P = 0.013) and have a larger effect size (OR = 0.897, 95%CI: 0.830-0.971; OR = 0.916, 95%CI: 0.854-0.981) than the whole participants. As for sex difference, this associations are statistically significant in male (OR: 0.935, P = 0.011, 95%CI: 0.888-0.985) but not in female (OR: 0.979, P = 0.399, 95%CI: 0.931-1.029). ConclusionsOur findings indicate that social engagement may reduce the risks of depressive symptoms among all individuals. The identified subgroups of middle-aged and elderly residents who live in rural areas with <6 h of sleep and those who live in urban areas may benefit more from the social engagement than the whole participants.