biostudies-literatureFan LNational Outstanding Youth Science Fund Project of National Natural Science Foundation of China404https://www.ebi.ac.uk/biostudies/studies/S-EPMC12632084biostudies-literatureUnknown44(1)<h4>Background</h4>Frailty is emerging as a determinant of adverse health outcomes in older adults; identifying high-risk groups early and taking effective interventions can improve the quality of life and prognosis for the elderly. The aim of this study was to build and test a model to predict frailty among the older Chinese person, facilitating early intervention.<h4>Methods</h4>This cross-sectional study used data from the Psychology and Behavior Investigation of Chinese Residents (PBICR), the set was split into a training set and a validation set at a 70:30 ratio. Logistic regression analyzed frailty factors, and a nomogram was developed to predict frailty, with calibration curves and decision curve analysis (DCA) assessing accuracy.<h4>Results</h4>4,367 people above 60 years of age frJournal of health, population, and nutritionDevelopment and validation of a risk prediction nomogram for frailty in older Chinese adults.PMC1263208471804125Liu YFan LZhu HYu ZWang LfalseDevelopment and validation of a risk prediction nomogram for frailty in older Chinese adults.<h4>Background</h4>Frailty is emerging as a determinant of adverse health outcomes in older adults; identifying high-risk groups early and taking effective interventions can improve the quality of life and prognosis for the elderly. The aim of this study was to build and test a model to predict frailty among the older Chinese person, facilitating early intervention.<h4>Methods</h4>This cross-sectional study used data from the Psychology and Behavior Investigation of Chinese Residents (PBICR), the set was split into a training set and a validation set at a 70:30 ratio. Logistic regression analyzed frailty factors, and a nomogram was developed to predict frailty, with calibration curves and decision curve analysis (DCA) assessing accuracy.<h4>Results</h4>4,367 people above 60 years of age fr2025-01-01T00:00:00Z2025 Nov2026-06-05T18:43:22.204Z2026-05-20T03:13:57.989ZS-EPMC126320844126711010.1186/s41043-025-01148-y