Development and validation of a nomogram for predicting anorexia of aging in older people

Background: Anorexia of aging (AA) is a common geriatric syndrome that seriously endangers the health of older adults. Early identification of populations at risk of AAand the implementation of appropriate intervention measures hold significant public health importance. This study aimed to develop a nomogram for predicting the risk of AA among older people. Methods: We conducted a cross-sectional study involving 2144 community-dwelling older adults to evaluate the AA using the Simplified Nutritional Appetite Questionnaire. We utilized the Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis to select variables and develop a nomogram prediction model. The predictive performance of the nomogram was evaluated using the Receiver Operating Characteristic (ROC) curves, calibration curves, Decision Curve Analysis (DCA), and internal validation. Results: The prevalence of AA among Chinese older adults was 21.7% (95%CI: 20.0%-23.5%). Age, sex, family economic level, smoking status, dysphagia, loneliness, depressive symptoms, living alone, health literacy, life satisfaction, and body mass index have been identified as predictive factors for AA among older people. The nomogram constructed based on these predictive factors showed an area under the curve (AUC) of 0.766 (95%CI: 0.742-0.791), indicating good calibration and discrimination ability. Additionally, the results obtained from the 10-fold cross-validation process confirmed the nomogram's good predictive capabilities. Furthermore, the DCA results showed that the nomogram has clinical utility. Conclusion: The nomogram constructed in this study serves as an effective tool for predicting anorexia of aging among community-dwelling older adults. Its implementation can help community healthcare workers evaluate the risk of AA in this population and identify high-risk groups.