The Longitudinal Relationships Between Cognitive Impairment and Depression in Older Adults: A Cross-Lagged Panel Network Analysis.

Authors

Hui-Hui Zhou, Yu Sun, Yang-Zi-Ye Guo, Feng Guo, Shuang Li, Ya Wang, Xuan Zhou, Fu-Qin Mu, Yi Qiao, Min Liu, Yan Liu

Published in

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry. Jul 31, 2026. Epub Jul 31, 2026.

Abstract

To investigate the prospective associations and network characteristics between cognitive impairment and depression among individuals aged 60 years or older.
A longitudinal study employing a cross-lagged panel network (CLPN) analysis.
Community-based setting in China.
A total of 6,297 older adults participated, recruited via cluster sampling.
Cognitive function was assessed using the Ascertain Dementia eight-item questionnaire (AD-8). Depressive symptoms were measured using the Patient Health Questionnaire-nine (PHQ-9). A CLPN analysis was employed to establish the symptom network spanning time-point T1 to T2. Centrality metrics-including out-strength, in-strength, betweenness, and closeness-were quantified.
The results show that cognitive impairment (particularly AD-8 item 5: time disorientation and item 1: impaired judgment) was identified as the strongest prospective predictor of depressive symptoms, whereas the reverse influence of depressive symptoms on cognition was comparatively weak. Impaired judgment showed high out-predictability, suggesting its potential as a candidate target for early intervention; conversely, the high in-predictability of fatigue indicates it may be a sensitive marker of upstream network changes.
This study provides evidence that cognitive impairment prospectively predicts depression in an asymmetric manner and offers a conceptual cascade model. These findings support further research into a public health shift toward staged interventions, from early screening to targeted strategies, to alleviate the population burden of this comorbidity.

PMID:
42624702
Bibliographic data and abstract were imported from PubMed on 21 Aug 2026.

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