Construction and validation of a nomogram prediction model for risk of depression in elderly patients with hypertension

Objective To explore the influencing factors of depression risk in elderly patients with hypertension and construct and validate a nomogram prediction model.

Methods A total of 869 elderly patients with hypertension were selected from national survey database of the China Health and Retirement Longitudinal Study (CHARLS) in 2018.Multivariate Logistic regression analysis was used to identify the risk factors for depression in elderly patients with hypertension, and a nomogram prediction model was constructed.The accuracy and effectiveness of the model were validated by the Hosmer-Lemeshow (H-L) goodness-of-fit test, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and the calibration curve.

Results The incidence of depression in elderly patients with hypertension was 47.18%.Factors influencing the risk of depression included rural residence (OR=2.191, P < 0.05), impaired basic activities of daily living (BADL)(OR=2.338, P < 0.05), impaired instrumental activitiesofdaily living (IADL)(OR=1.674, P < 0.05), poor life satisfaction (OR=7.348, P < 0.05), fair self-rated health (OR=0.441, P < 0.05), good self-rated health (OR=0.259, P < 0.05), and sleep duration of 6 to 9 hours (OR=0.510, P < 0.05).The AUC of the ROC curve was 0.795, the slope of the calibration curve was close to 1, and the H-L goodness-of-fit test yielded χ²=5.074.The validation set showed an AUC of 0.703.

Conclusion The prediction model established in this study has high accuracy and discriminative ability.Healthcare professionals can take effective preventive measures based on individual patient factors.