A predictive nomogram among hypertension old population from the community: A cross-sectional study.

Background: Frailty presents a significant challenge for aging adults, with a multitude of factors needing consideration. Despite this, there is a lack of research on predicting frailty in the old population with hypertension.

Aim: This study aims to create and validate a nomogram model for the old population with hypertension, to predict frailty and gain valuable insights into its prevalence and determinants.

Method: Data for this study were extracted from the "Psychology and Behavior Investigation of Chinese Residents (PBICR) in 2022 (PBICR-2022)", with information on frailty and related factors obtained through self-reported questionnaires. Frailty was assessed using the Fatigue, Resistance, Ambulation, Illnesses, and Loss of Weight (FRAIL) scale. The independent variables encompassed sociodemographic, physiological, psychological, and family health factors. A total of 1135 participants aged over 60 with hypertension were included in the study. Univariate and stepwise binary logistic regression analyses were conducted to identify the relationship between frailty and multiple risk factors and to establish the frailty risk prediction nomogram.

Results: The prevalence of social frailty was found to be 30.91%. The final model included the degree of hypertension, history of falling in the past 3 months, Brief Illness Perception Questionnaire score, depression levels, and Family Health Scale score. The model exhibited good accuracy in the testing set, with an area under the ROC curve of 0.984 (95% CI: 0.978, 0.990).

Conclusion: These findings suggest that the prediction model effectively estimated the prevalence of frailty in the older population with hypertension from community and identified associated factors. The model demonstrated good performance and holds potential for further study on the management of frailty.