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中国循证儿科杂志

中国循证儿科杂志 ›› 2024, Vol. 19 ›› Issue (5): 341-147.DOI: 10.3969/j.issn.1673-5501.2024.05.005

• 论著 • 上一篇    下一篇

基于持续性糖脂代谢异常风险预测的儿童青少年真实肥胖诊断切点的前瞻性队列研究

董虹孛1， 程红2，熊静帆3，肖培1，单馨影2，米杰1    

  1.  1 国家儿童医学中心，首都医科大学附属北京儿童医院，儿童慢病管理中心北京，100045；2 首都儿科研究所，流行病学研究室北京，100020；3 深圳市慢性病防治中心，儿童青少年慢性病防控科深圳，518020

  • 收稿日期:2024-12-23 修回日期:2024-12-23 出版日期:2024-10-25 发布日期:2024-10-25
  • 通讯作者: 米杰

Overfat cutoffs for detecting persistent hyperglycemia and dyslipidemia among children and adolescents: A prospective cohort study

 DONG Hongbo1, CHENG Hong2, XIONG Jingfan3, XIAO Pei1, SHAN Xinying2, MI Jie1   

  1. 1 Center for Noncommunicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China;2 Department of Epidemiology, Capital Institute of Pediatrics, Beijing 100020, China;  3 Child and Adolescent Chronic Diseases Prevention and Control Department, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China
  • Received:2024-12-23 Revised:2024-12-23 Online:2024-10-25 Published:2024-10-25
  • Contact: MI Jie, email:jiemi12@vip.sina.com

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摘要： 背景：体成分测量的体脂肪总量与分布水平是诊断真实肥胖与准确筛查相关代谢性疾病的基础。然而，目前尚缺乏基于适用于儿童的相关诊断切点。 目的：通过比较不同体脂肪指标对儿童持续性糖脂代谢异常的预测能力，探讨评估儿童真实肥胖的诊断切点。 设计：前瞻性队列研究。 方法：在儿童青少年心血管与骨健康促进项目（SCVBH）的队列中，以基线（2017年）和随访（2019年）中均完成血糖、血脂和体成分检测者为研究对象，基线和随访血糖和血脂［空腹血糖受损（IFG）、总胆固醇（TC）、甘油三酯（TG）、低密度脂蛋白胆固醇（LDLC）、高密度脂蛋白胆固醇（HDLC）、非高密度脂蛋白胆固醇（NonHDLC）］均异常为金标准，以BMI和生物电阻抗法测量获得体脂肪指标［全身脂肪质量指数（FMI）、全身脂肪质量（FMP）、躯干脂肪/下肢脂肪（TLR）］为预测因子，通过受试者工作特征曲线（ROC）下面积（AUC）比较BMI与不同体脂肪指标组合对持续性糖脂代谢异常的筛查效能与诊断切点。 主要结局指标：体成分指标筛查糖脂代谢异常的组合界值。 结果：共10 603人纳入本文分析，基线时年龄（10.9±3.3）岁，男童5 244人（49.4%），研究人群中，持续IFG 371(3.5%)人，持续高 TC 131(1.2%)人，持续高 TG 128(1.2%)人，持续高 LDLC 118(1.1%)人，持续低 HDLC 448(4.2%)人，持续高NonHDLC 212(2.0%)人。经ROC曲线分析及Delong检验，在所有体脂肪指标的组合中， FMI和 TLR 的联合应用对男女童持续 IFG、高 TC、高 LDLC 的筛查效果均优于BMI(P均<0.05)，女童对持续高 NonHDLC筛查效果优于 BMI［AUCFMI+TLR：0.664 (95%CI：0.615~0.713) vs AUC BMI：0.617 (95%CI：0.557~0.677), P<0.001］。ROC曲线结果显示，对于预测各项持续糖脂代谢异常，FMI的最佳界值点位于P75~P95之间，TLR的最佳切点位于P75~P90。 结论：FMI和TLR组合指标筛查较BMI筛查持续性糖脂代谢异常效果更佳。建议以FMI 性别别、年龄别P75和P95分别作为体脂肪轻中度过量和重度过量的诊断切点，以TLR的性别别、年龄别 P75和P90分别作为体脂肪轻中度异位和重度异位的诊断切点。

关键词: 生物电阻抗法, 体脂肪量, 体脂肪分布, 持续性糖脂代谢异常, 真实肥胖诊断切点

Abstract: Background：The diagnosis of true obesity was recommended to be based on body fat quantity and distribution by body composition measurement. However, the riskbased overfat cutoffs were scarce for pediatric population. Objective：To develop cutoffs and the optimal combination for body fat indices for screening persistent hyperglycemia and dyslipidemia among the pediatric population. Design：Prospective cohort study. Methods：Subjects who participated in the 2017 baseline and 2019 followup survey of Schoolbased Cardiovascular and Bone Health (SCVBH) Promotion Program with complete data of body composition and blood test, were selected as the study population. The gold standard was persistent hyperglycemia and dyslipidemia in both baseline and followup surveys, including persistent impaired fasting glucose (IFG), persistent high total cholesterol (TC), persistent high TG, persistent high low density lipoprotein cholesterol (LDLC), persistent low high density lipoprotein cholesterol (HDLC) and persistent high NonHDLC. The predictors included body mass index (BMI) and body fat indices derived from bioelectrical impedance analysis, including fat mass index (FMI), fat mass percentage (FMP), trunk to leg fat ratio (TLR).The area under the receiver operating characteristic curve was used to determine the best combination and optimal cutoffs of body fat indices for detecting persistent hyperglycemia and dyslipidemia. Main outcome measuresThe best combination and optimal cutoffs of body fat indices for detecting persistent hyperglycemia and dyslipidemia. Results：A total of 10 603 (mean age at baseline: 10.9 ± 3.3 years, 49.4% males) children and adolescents aged 618years were included for analysis. Among, 371 (3.5%) were diagnosed as persistent lFG,131 (1.2%) as persistent high TC, 128 (1.2%) as persistent high TG, 118 (1.1%) as persistent high LDLC, 448 (4.2%) as persistent low HDLC, and 212 (2.0%) as persistent high nonHDLC. According to the results for ROC analyses and Delong tests, the capability of FMI+TLR combination for detecting persistent IFG, persistent high TC and persistent high LDLC were statistically higher than BMI in both sexes (All P<0.05). Moreover, the combined use of FMI+TLR presented higher capability for detecting persistent high NonHDLC ［AUCFMI+TLR：0.664 (0.6150.713) vs AUCBMI：0.617 (0.5570.677), P<0.001］ than BMI in girls. According to the ROC analysis, the optimal overfat cutoffs of FMI were determined at the range of 75th percentile to 95th percentile, and TLR were determined at the range of 75th percentile to 90th percentile, varied by indicators for persistent hyperglycemia and dyslipidemia. Conclusion：The FMI + TLR combination presented higher predictability for discriminating persistent hyperglycemia and dyslipidemia among children and adolescents. We suggest the 75th percentile of FMI to be the cutoff for mild general overfat, the 90th percentile of FMI to be the cutoff for severe general overfat, the75th percentile of TLR to be the cutoff for mild central overfat, the 90th percentile of TLR to be the cutoff for severe central overfat.

Key words: Bioelectrical impedance analysis, Body fat quantity, Body fat distribution, Persistent hyperglycemia and dyslipidemia, Overfat cutoffs