| 肖培,程红,郁兆仓,王莲革,王宏健,高爱钰,赵小元,洪伟,侯冬青,王文鹏,米杰.基于体脂肪的肥胖评估指标在学龄儿童持续性血脂异常筛查中的应用[J].中华流行病学杂志,2020,41(12):2066-2071 |
| 基于体脂肪的肥胖评估指标在学龄儿童持续性血脂异常筛查中的应用 |
| Application of obesity indicators based on body fat in the screening of persistent dyslipidemia among school-aged children |
| 收稿日期:2020-08-05 出版日期:2020-12-25 |
| DOI：10.3760/cma.j.cn112338-20200805-01024 |
| 中文关键词: 儿童 肥胖 血脂异常 队列研究 |
| 英文关键词: Children Obesity Dyslipidemia Cohort study |
| 基金项目:国家自然科学基金（81973110） |
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| 摘要点击次数: 2063 |
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| 中文摘要: |
| 目的 探讨基于体脂肪量指标评估的肥胖对儿童持续性血脂异常的筛查效果。方法 对“儿童青少年心血管与骨健康促进项目”的基线和随访调查数据进行分析。采用BMI、脂肪质量指数（FMI）和体脂率（FMP）指标分别对肥胖进行定义，将基线和随访调查中均发生血脂异常定义为持续性血脂异常状态。通过受试者工作特征曲线下面积（AUC）比较不同指标定义的肥胖对持续性血脂异常的预测效果。结果 共纳入10 783名儿童（男童占49.6%）进行分析，年龄（10.9±3.3）岁。持续性高TC、高LDL-C、低HDL-C、高TG和高非HDL-C的检出率分别为1.3%、1.2%、4.3%、1.3%和0.8%。男童中FMI和FMP定义的肥胖预测持续性高LDL-C［FMI：AUC=0.626（95% CI：0.558~0.694），P=0.024；FMP：AUC=0.642（95% CI：0.574~0.710），P=0.004］和高非HDL-C ［FMI：AUC=0.637（95% CI：0.584~0.689），P=0.017；FMP：AUC=0.641（95% CI：0.588~0.693），P=0.018］的效果均优于BMI。此外，FMI定义的肥胖男童预测持续性低HDL-C的效果优于BMI［AUC=0.784（95% CI：0.742~0.826）vs.0.750（95% CI：0.726~0.773），P=0.047］。在女童中，FMI和FMP定义的肥胖预测各项持续性血脂异常的能力与BMI相比差异无统计学意义。结论 男童中基于体脂肪定义的肥胖预测持续性高LDL-C、低HDL-C和高非HDL-C的能力优于BMI指标，可进一步推广肥胖精准评估指标在心血管疾病预防中的应用。 |
| 英文摘要: |
| Objective To explore the screening effect of obesity assessed by body fat indicators on persistent dyslipidemia among children. Methods Data were obtained from the baseline and follow-up survey of ‘School-based Cardiovascular and Bone Health Promotion Program.’ BMI, fat mass index (FMI), and fat mass percentage (FMP) were used to define obesity. Dyslipidemia, diagnosed both in the baseline and a follow-up survey, was defined as persistent dyslipidemia. The area under the receiver operating characteristic curve (AUC) was used to compare the predictive capabilities of obesity defined by different indicators on persistent dyslipidemia. Results A total of 10 783 children (boys accounted for 49.6%) were included in the analysis, with the average age as (10.9±3.3) years old. The detection rates of persistent high TC, high LDL-C, low HDL-C, high TG, and high non-HDL-C were 1.3%, 1.2%, 4.3%, 1.3%, and 0.8%, respectively. In boys, the capabilities of FMI-and FMP-defined obesity in the prediction of persistent high LDL-C[FMI:AUC=0.626 (95% CI:0.558-0.694), P=0.024; FMP:AUC=0.642 (95% CI:0.574-0.710), P=0.004] and high non-HDL-C[FMI:AUC=0.637 (95% CI:0.584-0.689), P=0.017; FMP:AUC=0.641 (95% CI:0.588-0.693), P=0.018] were significantly higher than BMI-defined obesity. Besides, obese boys defined by FMI had the stronger capability in predicting persistent low HDL-C than that defined by BMI[AUC=0.784 (95% CI:0.742-0.826) vs. 0.750 (95% CI:0.726-0.773), P=0.047]. In girls, the capabilities of FMI-and FMP-defined obesity in the prediction of persistent dyslipidemia were not statistically different from BMI. Conclusions The obesity assessed by body fat performed better in predicting persistent high LDL-C, low HDL-C, and high non-HDL-C than that assessed by BMI among boys, which can be further applied to cardiovascular disease prevention. |
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