A nomogram incorporating subjective health status and vascular risk factors for stroke prediction in korean adults

Abstract

Objectives: To develop and validate a questionnaire-based nomogram for predicting individual stroke risk, providing a practical, non-clinical tool for community-level stroke risk assessment without requiring clinical measurements. Methods: Data were derived from the 2024 Korea National Health and Nutrition Examination Survey. Of 6,998 participants, 364 (91 with stroke; 273 without) were included after excluding missing data and applying 1:3 propensity score matching. Logistic regression analyses identified independent predictors, which were incorporated into a nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and predictive values. Results: Age, poor subjective health status, physician-diagnosed hypertension, and physician-diagnosed dyslipidemia were independently associated with stroke. Stroke risk increased with age, and poor subjective health was associated with substantially higher odds compared with good health. Hypertension and dyslipidemia were also significant predictors. The nomogram demonstrated acceptable discrimination (AUC = 0.706), with a sensitivity of 73.63% and a specificity of 63.74%. Conclusions: In addition to established factors such as age, hypertension, and dyslipidemia, subjective health status may serve as a meaningful indicator of stroke risk. This questionnaire-based nomogram offers a practical, non-invasive approach for risk estimation in community settings and may support early identification and population-level prevention strategies.