Developing and validating a nomogram for cognitive impairment in the older people based on the NHANES

Xiaoming Ma; Wendie Huang; Lijuan Lu; Hanqing Li; Jiahao Ding; Shiying Sheng; Meng Liu; Jie Yuan

doi:10.3389/fnins.2023.1195570

Developing and validating a nomogram for cognitive impairment in the older people based on the NHANES

Front Neurosci. 2023 Aug 17:17:1195570. doi: 10.3389/fnins.2023.1195570. eCollection 2023.

Authors

Xiaoming Ma¹, Wendie Huang², Lijuan Lu², Hanqing Li², Jiahao Ding¹, Shiying Sheng², Meng Liu², Jie Yuan^{3

4}

Affiliations

¹ North China University of Science and Technology, Tangshan, Hebei, China.
² Department of Neurology, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China.
³ Jitang College, North China University of Science and Technology, Tangshan, Hebei, China.
⁴ Institution of Mental Health, North China University of Science and Technology, Tangshan, Hebei, China.

Abstract

Objective: To use the United States National Health and Nutrition Examination Study (NHANES) to develop and validate a risk-prediction nomogram for cognitive impairment in people aged over 60 years.

Methods: A total of 2,802 participants (aged ≥ 60 years) from NHANES were analyzed. The least absolute shrinkage and selection operator (LASSO) regression model and multivariable logistic regression analysis were used for variable selection and model development. ROC-AUC, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram's performance.

Results: The nomogram included five predictors, namely sex, moderate activity, taste problem, age, and education. It demonstrated satisfying discrimination with a AUC of 0.744 (95% confidence interval, 0.696-0.791). The nomogram was well-calibrated according to the calibration curve. The DCA demonstrated that the nomogram was clinically useful.

Conclusion: The risk-prediction nomogram for cognitive impairment in people aged over 60 years was effective. All predictors included in this nomogram can be easily accessed from its' user.

Keywords: NHANES; ROC; aging; cognition disorders; prediction model.