Why the study?
Predicting potential risk factors for high blood pressure among children and adolescents remains a knowledge gap.
Does a nomogram-based model composed of demographic, early life, and lifestyle factors accurately predict the risk of high blood pressure in children and adolescents?
Does a nomogram-based model composed of demographic, early life, and lifestyle factors accurately predict the risk of high blood pressure in children and adolescents?
A nomogram incorporating 9 clinical and lifestyle factors can accurately predict the risk of high blood pressure in children and adolescents, aiding in early identification in primary care.
Background Predicting the potential risk factors of High blood pressure(HBP) among children and adolescents is still a knowledge gap. Our study aimed to establish and validate a nomogram-based model for identifying children and adolescents at risk of developing HBP based on a population-based prospective study. Methods Hypertension was defined as systolic blood pressure or diastolic blood pressure above 95 th percentile, using age, gender and height-specific cut-points. Penalized regression with Lasso was used to identify the strongest predictors of hypertension. Internal validation was conducted by 5-fold cross-validation and bootstrapping approach. The predictive variables were identified along with the advanced nomogram plot by conducting univariate and multivariate logistic regression analyses. A nomogram was constructed by training group comprised of 239,546(69.89%)participants and subsequently validated by externally group with 103,190(30.11%)participants. Results Of 342,736 children and adolescents, a total of 55,480(16.19%) youths were identified with HBP with mean age 11.51±1.45 year and 183,487 were boys(53.5%). Nine significant relevant predictors were identified including: age, gender, weight status, birthweight, breastfeeding, gestational hypertension, family history of obesity, family history of hypertension and physical activity. An acceptable discrimination[Area under the receiver operating characteristic curve(AUC):0.742(Development group), 0.740(Validation group)] and good calibration(Hosmer and Lemeshow statistics, P > 0.05) were observed in our models. An available web-based nomogram was built online. Conclusions This model composed of age, gender, early life factors, family history of disease, and lifestyle factors may predict the risk of HBP among children and adolescents, which has developed a promising nomogram that may aid in more accurately for identifying the HBP among youths in primary care. Funding Sources The work was supported by the National Natural Science Foundation of China (No. 81673193).
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Liang et al. (2021) studied this question.
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