Objective To analyze the influencing factors of hypertension among healthcare workers in the Xizang region, and to construct a nomogram, providing a reference for formulating targeted hypertension prevention and control interventions.
Methods A total of 2 262 healthcare workers from the medical personnel component of the Seventh Xizang Autonomous Region Health Service Survey were included. LASSO regression was used to select the best predictive variables, and a logistic regression model was used to analyze the influencing factors of hypertension among healthcare workers and to construct a nomogram. The predictive performance of the nomogram was evaluated using the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test, calibration curves, and decision curve analysis, and internal validation of the model was performed using the Bootstrap method.
Results A total of 2 262 healthcare workers were included, among whom 352 (15.6%) had hypertension. Six variables, smoking status, drinking status, subhealth status, baseline self-reported hyperlipidemia, baseline self-reported diabetes, and baseline self-reported depression, were included in the model. The area under the ROC curve of the prediction model in the validation set was 0.838; the Hosmer-Lemeshow test yielded a P value of 0.565; the calibration curve showed a good consistency between the predicted values and the actual hypertension prevalence. Decision curve analysis showed that the model had good net benefit and accuracy across different threshold ranges.
Conclusion The nomogram prediction model constructed based on LASSO regression has good predictive performance and can serve as a convenient and effective tool for medical institutions and relevant departments in Xizang to assess the risk of hypertension among healthcare workers.
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