Yan Wu, Peng Luting, Shi Yanan, Cao Mengyao, Zheng Qingqing, Gao Shenghu, Liu Qianqi, Li Xiaonan
Department of Children Health Care, Children's Hospital of Nanjing Medical University, Nanjing, 210008, China.
Institute of Pediatric Research, Nanjing Medical University, Nanjing, 210029, China.
J Transl Med. 2025 Jun 17;23(1):664. doi: 10.1186/s12967-025-06182-2.
Body 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.
The 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.
A 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 (R = 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).
Physiological 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.
体重指数z评分（BMI-Z）和腰高比（WHtR）被广泛用于评估儿童的营养和代谢状况。颈高比（NHtR）、甘油三酯-葡萄糖指数（TyG）、内脏脂肪指数（VAI）和中国内脏脂肪指数（CVAI）最近被用于评估心血管和脑血管疾病风险的发展。然而，它们在评估心血管代谢危险因素聚集（CCRF）方面的有效性尚不清楚。本研究旨在探讨生理参数对CCRF的预测能力，为儿童心血管代谢风险的早期识别提供依据。
纳入接受健康检查的儿童，计算BMI-Z、体脂百分比（PBF）、WHtR、NHtR、VAI、CVAI和TyG。采用Spearman相关性分析探讨生理参数与代谢指标之间的关系。采用二元逻辑回归分析评估生理参数与代谢危险因素之间的关联。采用受试者工作特征（ROC）分析评估生理参数对CCRF的预测能力。采用Delong检验比较差异并确定预测优势。
共纳入9039名儿童和青少年，其中37.9%超重或肥胖。生理参数与代谢参数之间存在显著相关性。所有七个生理参数均显著增加CCRF，其中CVAI模型在调整年龄和性别后效果最佳（R = 0.398，AIC = 7738）。ROC曲线显示，WHtR预测CCRF的准确性在男孩中最高（曲线下面积（AUC）= 0.837）。CVAI预测女孩CCRF的准确性最高（AUC = 0.826）。
生理参数可用于评估儿童和青少年的CCRF，其中WHtR在男孩中的预测效率最高，CVAI和WHtR在女孩中具有较强的可靠性。
