The efficacy of physiological parameters in assessing the clustering of cardiovascular risk factors (CCRF) among children and adolescents

BackgroundBody mass index z-score (BMI-Z) and waist-to-height ratio (WHtR) are widely used to assess children's nutrition and metabolic status. Neck-to-height ratio (NHtR), triglyceride-glucose index (TyG), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI) have recently been used to assess the development of cardiovascular and cerebrovascular risks. However, their effectiveness in assessing the clustering of cardiometabolic risk factors (CCRF) is not yet clear. This study aims to explore the predictive ability of physiological parameters for CCRF, which could provide evidence for the early identification of cardiometabolic risks in children.MethodsThe children who underwent health examinations were included, and BMI-Z, percentage of body fat (PBF), WHtR, NHtR, VAI, CVAI, and TyG were calculated. Spearman correlation analysis was applied to explore the relationship between physiological parameters and metabolic indices. Binary logistic regression analysis was employed to assess the association between physiological parameters and metabolic risk factors. The receiver operating characteristic (ROC) analysis was utilized to estimate the ability of physiological parameters to CCRF. The Delong tests were utilized to compare the differences and determine predictive superiority.ResultsA total of 9039 children and adolescents were included, among whom 37.9% were overweight or obese. Significant correlation between physiological parameters and metabolic parameters. All the seven physiological parameters significantly increased the CCRF, among which the CVAI model had the best effect after adjusting for age and gender (R2 = 0.398, AIC = 7738). The ROC curve showed that the accuracy of WHtR in predicting CCRF was the highest in boys (area under curve (AUC) = 0.837). The accuracy of CVAI in predicting CCRF in girls was the highest (AUC = 0.826).ConclusionPhysiological parameters could be used to assess CCRF among children and adolescents, among which WHtR has the highest prediction efficiency in boys, and CVAI and WHtR have strong reliability in girls.