Front Public Health. 2026 Sep 15;14:1890897. doi: 10.3389/fpubh.2026.1890897. eCollection 2026.
ABSTRACT
BACKGROUND: Older adults with hypertension commonly experience poor sleep quality and reduced health-related quality of life (HRQoL). Previous studies have mainly examined these associations using total scores, providing limited insight into interactions between specific symptom dimensions. This study aimed to construct a component- and dimension-level network linking sleep quality and HRQoL and to compare network differences across depressive-symptom status.
METHODS: This study included 2,257 older adults. Sleep quality, HRQoL, and depressive symptoms were assessed using the B-PSQI, EQ-5D-5L, and PHQ-9, respectively. We estimated a component- and dimension-level network based on the EBICGlasso-regularized Gaussian graph model, calculated centrality and bridge centrality metrics, validated stability using the bootstrap method, and compared network differences between the depressive and non-depressive-symptom groups.
RESULTS: The final network included 10 nodes and 32 non-zero edges among 45 possible edges, with a density of 0.711. The strongest associations were between sleep efficiency and sleep duration (SE-ST, 0.793), sleep interruption and subjective sleep quality (SW-SQ, 0.583), and self-care and usual activities (SC-UA, 0.560). Usual activities (UA) showed the highest strength centrality and expected influence, followed by subjective sleep quality (SQ), self-care (SC), and sleep efficiency (SE). Sleep efficiency had the highest bridge expected influence, followed by subjective sleep quality. Centrality indices demonstrated good stability (CS = 0.75). No significant differences were found in network structure (M = 0.224, P > 0.05) or global strength (S = 0.119, P > 0.05); repeated 1:1 subsampling broadly supported these findings.
CONCLUSION: Sleep components and HRQoL dimensions formed a closely connected network in older adults with hypertension. Usual activities showed the highest centrality, while sleep efficiency and subjective sleep quality showed prominent cross-community. These domains may be useful for screening or hypothesis generation but should not be interpreted as confirmed intervention targets.
PMID:42763455 | PMC:PMC13588788 | DOI:10.3389/fpubh.2026.1890897