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

OBJECTIVE

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.

DESIGN

a cross-sectional study using data from the 2024 baseline survey of the Active Aging Cohort in Rural Areas, Shandong Province, China.

SUBJECTS: 1,049 rural older adults aged ≥ 60 years with MCI.

METHODS

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.

RESULTS

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.