机构地区:[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
出 处:《中国循证儿科杂志》2024年第5期341-347,共7页Chinese Journal of Evidence Based Pediatrics
基 金:国家自然科学基金项目:82373589;深圳市“医疗卫生三名工程”项目:SZSM 202311020。
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10603人纳入本文分析,基线时年龄(10.9±3.3)岁,男童5242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[AUC_(FMI+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P_(75)~P_(95)之间,TLR的最佳切点位于P_(75)~P 90。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P_(75)和P_(95)分别作为体脂肪轻中�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 measures The best combination and optimal cutoffs of body fat indices for detecting persistent hyperglycemia and dyslipidemia.Results A total of 10603(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
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