Core symptoms and potential pathways of multidimensional frailty: a nationwide population-based study integrating network analysis and directed acyclic graphs

BACKGROUND: Frailty in older adults is a multidimensional syndrome that includes physical, cognitive, psychological, and social aspects and is associated with adverse health outcomes. This study used network analysis and directed acyclic graphs (DAGs) to figure out the core symptoms and potential directional relationships of multidimensional frailty in older adults. METHODS: The study included 5211 participants from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The frailty network was estimated using mixed graphical model with centrality indices identifying key symptoms. A Bayesian hill-climbing algorithm constructed a DAG to explore potential causal relationships across domains. Analyses were conducted in R version 4.5.1. RESULTS: In the symptom network, "social support," "low muscle strength," and "feeling sad or depressed" emerged as central symptoms of multidimensional frailty. DAG analysis indicated that "feeling sad or depressed" and "unintentional weight loss" occupied prominent positions within the network, suggesting their potential importance in frailty symptom patterns. CONCLUSION: This study identifies key symptoms and potential pathways underlying multidimensional frailty. Early screening and intervention strategies targeting these core symptoms should be considered in the assessment and management of multidimensional frailty. Future longitudinal studies are required to validate these findings and clarify temporal relationships.