文章摘要
颜欢畅,郝宇婷,郭仰峰,韦远欢,张家华,黄高培,毛丽梅,张喆庆.广州市6~9岁儿童体脂率与不同肥胖指标关系的研究[J].中华流行病学杂志,2017,38(11):1471-1475
广州市6~9岁儿童体脂率与不同肥胖指标关系的研究
Correlation between percentage of body fat and simple anthropometric parameters in children aged 6-9 years in Guangzhou
收稿日期:2017-03-07  出版日期:2017-11-11
DOI:10.3760/cma.j.issn.0254-6450.2017.11.006
中文关键词: 肥胖,儿童期  体质指数  全身脂肪百分比
英文关键词: Pediatric obesity  Body mass index  Body fat percentage
基金项目:合生元母婴营养与护理研究基金(BINCMYF15006)
作者单位E-mail
颜欢畅 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
郝宇婷 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
郭仰峰 510180 广州市中小学卫生健康促进中心常见病防治室  
韦远欢 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
张家华 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
黄高培 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
毛丽梅 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系  
张喆庆 510515 广州, 广东省南方医科大学公共卫生学院营养与食品卫生学系 zzqaa501@163.com 
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中文摘要:
      目的 分析不同肥胖指标与广州市6~9岁儿童体脂率的关系及对儿童肥胖的诊断价值。方法 对广州市465例6~9岁儿童应用双能X线进行全身脂肪百分比(BF%)的测定,同时测量腰围,计算BMI、腰臀围比(WHR)和腰围身高比(WHtR)。各项指标经年龄校正后,利用多元线性回归分析其与BF%的关联,并以受试者工作特性(ROC)曲线评价各项简易指标对肥胖的诊断价值,计算曲线下面积(AUC)。结果 多元线性回归分析显示,BMI与BF%关联最强,BMI每增加1个标准差,男女童BF%分别约增加5.3%(t=23.104,P<0.01)和4.6%(t=17.509,P<0.01);ROC曲线分析显示,BMI诊断肥胖的AUC值最大,男女童分别为0.908和0.895,特异度和灵敏度均>80%;WHtR以及腰围诊断肥胖的效果次之,但AUC值均>0.8;WHR诊断肥胖的效果最差。结论 BMI能较好地预测BF%,是广州市6~9岁儿童肥胖诊断的最佳简易指标。
英文摘要:
      Objective To evaluate the accuracy of simple anthropometric parameters in diagnosing obesity in children in Guangzhou. Methods A cross-sectional study, including 465 children aged 6-9 years, was carried out in Guangzhou. Their body height and weight, waist circumference (WC) and hip circumference were measured according to standard procedure. Body mass index (BMI), waist to hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BF%)was determined by dual-energy X-ray absorptiometry. Multiple regression analysis was applied to evaluate the correlations between age-adjusted physical indicators and BF%, after the adjustment for age. Obesity was defined by BF%. Receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic accuracy of the indicators for childhood obesity. Area under-ROC curves (AUCs) were calculated and the best cut-off point that maximizing ‘sensitivity + specificity-1’ was determined. Results BMI showed the strongest association with BF% through multiple regression analysis. For ‘per-standard deviation increase’ of BMI, BF% increased by 5.3% (t=23.1, P<0.01) in boys and 4.6% (t=17.5, P<0.01) in girls, respectively. The ROC curve analysis indicated that BMI exhibited the largest AUC in both boys (AUC=0.908) and girls (AUC=0.895). The sensitivity was 80.8% in boys and 81.8% in girls, and the specificity was 88.2% in boys and 87.1% in girls. Both the AUCs for WHtR and WC were less than 0.8 in boys and girls. WHR had the smallest AUCs (<0.8) in both boys and girls. Conclusion BMI appeared to be a good predicator for BF% in children aged 6-9 years in Guangzhou.
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