Dataset Information

The predictive value of anthropometric indices for cardiometabolic risk factors in Chinese children and adolescents: A national multicenter school-based study.

ABSTRACT: OBJECTIVES:This study aimed to assess the accuracy of body mass index (BMI) percentile, waist circumference (WC) percentile, waist-height ratio, and waist-hip ratio for identifying cardiometabolic risk factors in Chinese children and adolescents stratified by sex and BMI categories. METHODS:We measured anthropometric indices, fasting plasma glucose, lipid profile and blood pressure for 15698 participants aged 6-17 in a national survey between September and December 2013. The predictive accuracy of anthropometric indices for cardiometabolic risk factors was examined using receiver operating characteristic (ROC) analyses. The DeLong test and Z test were used for the comparisons of areas under ROC curves (AUCs). RESULTS:The prevalence of impaired fasting glucose, dyslipidemia, hypertension and cluster of risk factors were 2.9%, 27.3%, 10.5% and 5.7% respectively. The four anthropometric indices showed poor to fair discriminatory ability for cardiometabolic risk factors with the AUCs ranging from 0.53-0.72. Each index performed significantly better AUCs for dyslipidemia (0.59-0.63 vs. 0.56-0.59), hypertension (0.62-0.70 vs. 0.55-0.65) and clustered risk factors (0.70-0.73 vs. 0.60-0.64) in boys than that in girls. BMI percentile performed the best accuracy for hypertension in both sexes; WC percentile had the highest AUC for dyslipidemia and BMI percentile and waist-height ratio performed similarly the best AUCs for clustered risk factors in boys while BMI percentile, WC percentile and waist-height ratio performed similar and better AUCs for dyslipidemia and clustered risk factors in girls; whereas waist-hip ratio was consistently the poorest predictor for them regardless of sex. Though the anthropometric indices were more predictive of dyslipidemia, hypertension and clustered risk factors in overweight/obese group compared to their normal BMI peers, the AUCs in overweight/obese group remained in the poor range below 0.70. CONCLUSIONS:Anthropometric indices are not effective screening tools for pediatric cardiometabolic risk factors, even in overweight/obese children.

SUBMITTER: Li Y

PROVIDER: S-EPMC6974264 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The predictive value of anthropometric indices for cardiometabolic risk factors in Chinese children and adolescents: A national multicenter school-based study.

Li Yamei Y Zou Zhiyong Z Luo Jiayou J Ma Jun J Ma Yinghua Y Jing Jin J Zhang Xin X Luo Chunyan C Wang Hong H Zhao Haiping H Pan Dehong D Jia Peng P

PloS one 20200121 1

<h4>Objectives</h4>This study aimed to assess the accuracy of body mass index (BMI) percentile, waist circumference (WC) percentile, waist-height ratio, and waist-hip ratio for identifying cardiometabolic risk factors in Chinese children and adolescents stratified by sex and BMI categories.<h4>Methods</h4>We measured anthropometric indices, fasting plasma glucose, lipid profile and blood pressure for 15698 participants aged 6-17 in a national survey between September and December 2013. The predi ...[more]

PMID: 31961891

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Project description:Background The predictive value of adiposity indices and the newly developed index for cardiometabolic risk factors and cardiovascular diseases (CVDs) remains unclear in the Chinese population. This study aimed to compare the predictive value of A Body Shape Index with other 5 conventional obesity-related anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio) in Chinese population. Methods and Results A total of 44 048 participants in the study were derived from the baseline data of the PURE-China (Prospective Urban and Rural Epidemiology) study in China. All participants' anthropometric parameters, CVDs, and risk factors (dyslipidemia, abnormal blood pressure, and hyperglycemia) were collected by standard procedures. Multivariable logistic regression models and receiver operator characteristic curve analysis were used to evaluate the predictive values of obesity-related anthropometric indices to the cardiometabolic risk factors and CVDs. A positive association was observed between each anthropometric index and cardiometabolic risk factors and CVDs in all models (P<0.001). Compared with other anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, and A Body Shape Index), waist-to-height ratio had significantly higher areas under the curve (AUCs) for predicting dyslipidemia (AUCs: 0.646, sensitivity: 65%, specificity: 44%), hyperglycemia (AUCs: 0.595, sensitivity: 60%, specificity: 45%), and CVDs (AUCs: 0.619, sensitivity: 59%, specificity: 41%). Waist circumference showed the best prediction for abnormal blood pressure (AUCs: 0.671, sensitivity: 66%, specificity: 40%) compared with other anthropometric indices. However, the new body shape index did not show a better prediction to either cardiometabolic risk factors or CVDs than that of any other traditional obesity-related indices. Conclusions Waist-to-height ratio appeared to be the best indicator for dyslipidemia, hyperglycemia, and CVDs, while waist circumference had a better prediction for abnormal blood pressure.

Project description:Background: Unhealthy dietary and lifestyle behaviors are associated with a higher prevalence of non-communicable chronic diseases and higher mortality in adults. However, there remains some uncertainty about the magnitude of the associations between lifestyle behaviors and cardiovascular factors in adolescents. Methods: We conducted a school-based cross-sectional study of 895 Chinese adolescents aged 15-19 years. They participated in a questionnaire survey, physical examination, and blood sample collection. Latent class analysis (LCA) was used to identify heterogeneous subgroups of lifestyle behaviors. A set of 12 latent class indicators, which reflected lifestyle behaviors including dietary habits, physical activity, sleep duration, screen time, and pressure perception, were included in the analysis. Logistic regression analysis was performed to determine whether the derived classes were related to a cardiometabolic risk. Results: In total, 13.7 and 5.6% of the participants were overweight and obese, respectively, and 8.4 and 14.1% reported having pre-hypertension and hypertension, respectively. A two-class model provided the best fit with a healthy lifestyle pattern (65.8%) and a sub-healthy lifestyle pattern (34.2%). There were more female participants with a healthy lifestyle (56.2 vs. 43.8%), whereas there were more males with a sub-healthy lifestyle (45.4 vs. 54.6%), (all P = 0.002). Increased risk of cardiometabolic abnormality (BMI categories, blood pressure and lipids) was not significant across lifestyle patterns, except for waist circumference (70.5 vs 69.1 cm, P = 0.044). There was no significant difference in physical activity and intake of fruit and vegetable between the two patterns. Conclusion: Primary prevention based on lifestyle modification should target patterns of behaviors at high risk in adolescents. Due to the complex effect of lifestyle clusters on cardiometabolic risks, well-designed and prospective studies in adolescents are needed in the future.

Dataset Information

The predictive value of anthropometric indices for cardiometabolic risk factors in Chinese children and adolescents: A national multicenter school-based study.

Publications

The predictive value of anthropometric indices for cardiometabolic risk factors in Chinese children and adolescents: A national multicenter school-based study.

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