Construction and validation of a predictive model for sleep disorders among rural older adults with mild cognitive impairment.

Authors

Teng Yang, Jiajing Chi, Jia Song, Luyao Yan, Wen Li, Ziting Xu, Haoyuan Li, Chunhao Dai, Minmin Leng

Published in

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology. Volume 47. Issue 11. Oct 20, 2026. Epub Oct 20, 2026.

Abstract

to construct and validate a risk assessment model for sleep disturbance among rural older adults with mild cognitive impairment (MCI), to support early screening and targeted intervention.
a cross-sectional study using data from the 2024 baseline survey of the Active Aging Cohort in Rural Areas, Shandong Province, China.
1,049 rural older adults aged ≥ 60 years with MCI.
demographic, lifestyle, disease history, and psychological factors were collected through face-to-face survey questionnaires and health examinations. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Logistic regression identified independent predictors, which were used to build a nomogram. Model performance was evaluated with ROC curve, calibration curve, decision curve analysis, and bootstrap validation.
the prevalence of sleep disturbance was 54.2%. Sex, hypertension, self-rated health, and depression were identified as independent predictors. The nomogram demonstrated good discrimination (AUC = 0.759, 95%CI: 0.731-0.778) and calibration, with internal validation confirming robustness.

PMID:
42897358
Bibliographic data and abstract were imported from PubMed on 20 Oct 2026.

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