<![CDATA[Background: Multidimensional frailty is highly prevalent among older adults residing in long-term care facilities (LTCFs). However, the structural interrelationships among physical, psychological, social, cognitive, and functional health domains remain insufficiently understood. Objective: To characterize the network structure of multidimensional frailty domains and related health indicators among institutionalized older adults. Methods: This cross-sectional study included 272 LTCF residents from Liaoning, China. Eleven theoretically selected health indicators were modeled using a Mixed Graphical Model with ℓ1-regularized neighborhood regression and model selection based on the Extended Bayesian Information Criterion (γ = 0.25). This approach estimates sparse conditional dependence structures among mixed data types. Strength centrality was used as the primary descriptive metric. Network accuracy and stability were evaluated using non-parametric and case-dropping bootstrap procedures. Results: The strongest conditional association emerged between age and cognitive impairment (edge weight = 0.68). Substantial associations were also observed between physical frailty and ADL dependency (edge weight = 0.43), and between psychological frailty and depressive symptoms (edge weight = 0.45). Physical frailty, ADL dependency, and depression exhibited relatively high strength centrality values; however, bootstrap difference tests indicated that these nodes were not statistically more central than several other highly connected indicators. The correlation stability coefficient for strength centrality was 0.75, indicating good stability of strength centrality estimates within this sample. Conclusion: The network revealed an interconnected pattern linking functional dependency, physical frailty, and psychosocial health among LTCF residents. Because the data were cross-sectional, the observed conditional associations should not be interpreted as causal or temporal pathways. These findings highlight the potential value of multidomain nursing assessment in long-term care settings and may inform hypothesis generation for future longitudinal or interventional nursing studies.]]>
