Dynamic Intergenerational Support and Anxiety-Depression in Aging: Insights from Latent Transitions to Symptom Networks

Intergenerational support plays a vital role in mitigating anxiety and depression among the elderly; however, the dynamic transition patterns of intergenerational support and the varying interactions between anxiety and depressive symptoms across these patterns remain underexplored. This study examined transition patterns in intergenerational support and their predictors, and characterized the network structure of anxiety–depression comorbidity across different patterns using a network analysis approach. Data were drawn from 1,826 individuals aged 65 and above in the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2014–2018). Intergenerational support was assessed using relevant CLHLS items, while depressive and anxiety symptoms were measured with the Center for Epidemiologic Studies Depression Scale and the Generalized Anxiety Disorder Questionnaire, respectively. Latent transition analysis identified support trajectories, and logistic regression tested their predictors. Bridge expected influence was computed to identify key symptoms in the comorbidity networks, and network comparison tests assessed structural differences across patterns. Four distinct transition patterns of intergenerational support were identified, with persistent high emotional support and consistently low overall support being most prevalent. Gender, marital status, smoking, and physical exercise significantly predicted these transitions. GAD1 emerged as a common bridge symptom in both Patterns 1 and 4, while CESD6 and GAD3 were unique to Pattern 4. The comorbidity networks exhibited significant differences in global strength. These findings highlight key intervention targets for alleviating anxiety and depression in elderly populations and offer a theoretical framework for understanding the link between intergenerational support and mental health in later life.