Combining multiaspect factors to predict the risk of childhood hypertension incidence

Childhood hypertension has become a global public health issue due to its increasing prevalence and association with cerebral‐cardiovascular disease in adults. In this study, we developed a predictive model for childhood hypertension based on environmental and genetic factors to identify at‐risk individuals. Eighty children diagnosed with childhood hypertension and 84 children in the control group matched by sex and age from an established cohort were included in a nested case–control study. We constructed a multiple logistic regression model to analyze the factors associated with hypertension and applied the 10‐fold cross‐validation method to verify the prediction stability of the model. Childhood hypertension was found positively correlated with triglyceride level ≥150 mg/dL; low‐density lipoprotein cholesterol level ≥110 mg/dL; body mass index Z score; waist‐to‐height ratio Z score; and red blood cell count (all P < .01) and negatively correlated with the relative expression level of retinol acyltransferase; relative expression level of vitamin D receptor; and dietary intake of fiber, vitamin C and copper (all P < .05) in this study. BMI Z score, triglyceride ≥150 mg/dL, RBC count, VDR/β‐actin and LRAT/β‐actin ratios were used to construct the predictive model. The area under the receiver operating characteristic curve was 94.45% (95% CI = 89.35%∼98.65%, P < .001). The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were all above 80% in both the training and validation sets. In conclusion, this model can predict the risk of childhood hypertension and could provide a theoretical basis for early prevention and intervention to improve the cardiovascular health of children.