Abstract: Objective To construct and validate a risk prediction model for motoric cognitive risk syndrome (MCRS) in the elderly in rural areas. Methods From October 2022 to May 2023, 752 rural elderly people were surveyed using General Information Questionnaire, Pittsburgh Sleep Quality Index Scale, Social Support Rating Scale, Simplified Geriatric Depression Scale-15(GDS-15), Mini-Mental State Examination(MMSE) and 4-meter walk test. According to the occurrence of MCRS, they were divided into MCRS group and non-MCRS group. The relevant variables of MCRS were screened by Lasso regression, and then the nomogram prediction model of MCRS in the elderly in rural areas was constructed by multi-factor Logistic regression. The ROC curve and calibration curve were drawn to evaluate the model's discrimination and calibration,and a bootstrap was further conducted to internally validate the model. Results The incidence rate of MCRS in 752 rural elderly people was 14.89% (112/752). Age, sedentary behavior, polypharmacy, poor sleep quality, social support and depression were the influencing factors of MCRS in the elderly in rural areas (P＜0.05). The area under the ROC curve of the nomogram prediction model was 0.844 (95%CI: 0.804-0.883). Bootstrap internal verification results showed that the average absolute error was 0.009, and the model performance was in good agreement with the ideal model. Conclusions The nomogram model of MCRS constructed in this study has a good predictive effect, which provides a reference for early identification of high-risk groups of MCRS.

Key words: rural, aged, motoric cognitive risk syndrome, influencing factor, nomogram