TY - JOUR
T1 - Establishment of hypertension risk nomograms based on physical fitness parameters for men and women
T2 - a cross-sectional study
AU - Xu, Yining
AU - Shi, Zhiyong
AU - Sun, Dong
AU - Munivrana, Goran
AU - Liang, Minjun
AU - István, Bíró
AU - Radak, Zsolt
AU - Baker, Julien S.
AU - Gu, Yaodong
N1 - This study was sponsored by the Major Program of the National Natural Science Foundation of China (19ZDA352), Zhejiang Provincial Key Research and Development Program of China (2021C03130), Zhejiang Provincial Natural Science Foundation of China for Distinguished Young Scholars (LR22A020002), Philosophy and Social Sciences Project of Zhejiang Province, China (22QNYC10ZD, 22NDQN223YB), Educational science planning project of Zhejiang Province (2021SCG083), Fundamental Research Funds for the Provincial Universities of Zhejiang (SJWY2022014), Ningbo Natural Science Foundation (20221JCGY010532; 20221JCGY010607), Public Welfare Science & Technology Project of Ningbo, China (2021S134), Teaching research project of Ningbo University (JYXMXZD2022008) and K. C. Wong Magna Fund in Ningbo University.
Publisher Copyright:
2023 Xu, Shi, Sun, Munivrana, Liang, István, Radak, Baker and Gu.
PY - 2023/9/12
Y1 - 2023/9/12
N2 - Objective: This study aims to establish hypertension risk nomograms for Chinese male and female adults, respectively.Method: A series of questionnaire surveys, physical assessments, and biochemical indicator tests were performed on 18,367 adult participants in China. The optimization of variable selection was conducted by running cyclic coordinate descent with 10-fold cross-validation through the least absolute shrinkage and selection operator (LASSO) regression. The nomograms were built by including the predictors selected through multivariable logistic regression. Calibration plots, receiver operating characteristic curves (ROC), decision curve analysis (DCA), clinical impact curves (CIC), and net reduction curve plots (NRC) were used to validate the models.Results: Out of a total of 18 variables, 5 predictors—namely age, body mass index, waistline, hipline, and resting heart rate—were identified for the hypertension risk predictive model for men with an area under the ROC of 0.693 in the training set and 0.707 in the validation set. Seven predictors—namely age, body mass index, body weight, cardiovascular disease history, waistline, resting heart rate, and daily activity level—were identified for the hypertension risk predictive model for women with an area under the ROC of 0.720 in the training set and 0.748 in the validation set. The nomograms for both men and women were externally well-validated.Conclusion: Gender differences may induce heterogeneity in hypertension risk prediction between men and women. Besides basic demographic and anthropometric parameters, information related to the functional status of the cardiovascular system and physical activity appears to be necessary.
AB - Objective: This study aims to establish hypertension risk nomograms for Chinese male and female adults, respectively.Method: A series of questionnaire surveys, physical assessments, and biochemical indicator tests were performed on 18,367 adult participants in China. The optimization of variable selection was conducted by running cyclic coordinate descent with 10-fold cross-validation through the least absolute shrinkage and selection operator (LASSO) regression. The nomograms were built by including the predictors selected through multivariable logistic regression. Calibration plots, receiver operating characteristic curves (ROC), decision curve analysis (DCA), clinical impact curves (CIC), and net reduction curve plots (NRC) were used to validate the models.Results: Out of a total of 18 variables, 5 predictors—namely age, body mass index, waistline, hipline, and resting heart rate—were identified for the hypertension risk predictive model for men with an area under the ROC of 0.693 in the training set and 0.707 in the validation set. Seven predictors—namely age, body mass index, body weight, cardiovascular disease history, waistline, resting heart rate, and daily activity level—were identified for the hypertension risk predictive model for women with an area under the ROC of 0.720 in the training set and 0.748 in the validation set. The nomograms for both men and women were externally well-validated.Conclusion: Gender differences may induce heterogeneity in hypertension risk prediction between men and women. Besides basic demographic and anthropometric parameters, information related to the functional status of the cardiovascular system and physical activity appears to be necessary.
KW - hypertension
KW - LASSO
KW - nomogram
KW - physical fitness
KW - predictive model
KW - risk factor
UR - http://www.scopus.com/inward/record.url?scp=85173075596&partnerID=8YFLogxK
UR - https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1152240/full
U2 - 10.3389/fcvm.2023.1152240
DO - 10.3389/fcvm.2023.1152240
M3 - Journal article
AN - SCOPUS:85173075596
SN - 2297-055X
VL - 10
JO - Frontiers in Cardiovascular Medicine
JF - Frontiers in Cardiovascular Medicine
M1 - 1152240
ER -