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老年男性心血管危险因素聚集适宜指标和切点
引用本文:范宇慧,蔡威,陶晔璇,汤庆娅.老年男性心血管危险因素聚集适宜指标和切点[J].上海交通大学学报(医学版),2009,29(8):982.
作者姓名:范宇慧  蔡威  陶晔璇  汤庆娅
作者单位:上海交通大学,医学院新华医院临床营养中心,上海200092
摘    要:目的 探讨老年男性心血管危险因素聚集的适宜体质量指数(BMI)、体脂百分比(PBF)和体脂指数(BFMI)切点。 方法 收集2007年1 052例上海市老年男性健康体检资料,分析不同BMI、PBF和BFMI水平与心血管危险因素聚集的关系;采用受试者工作特征(ROC)曲线分析BMI、PBF和BFMI最适切点;通过曲线下面积(AUC)分析BMI、PBF和BFMI的诊断价值;计算各切点检出危险因素聚集的人群归因危险度百分比(PARP)。 结果 随BMI、PBF和BFMI增加,危险因素聚集的比值比(OR)呈升高趋势。ROC曲线分析显示,BMI≥24 kg/m2、PBF≥21%和BFMI≥5 kg/m2为敏感性和特异性较均衡、和(或)ROC曲线距离最短的切点;三项指标AUC均>0.5。PARP分析显示,BMI、PBF和BFMI分别控制于24 kg/m2、21%和5 kg/m2以下,能分别防止人群中27.1%、37.44%和36.63%的危险因素聚集。 结论 反映老年男性心血管危险因素聚集的适宜BMI、PBF和BFMI切点分别为24 kg/m2、21%和5 kg/m2。

关 键 词:老年  心血管危险因素聚集  体质量指数  体脂百分比  体脂指数  切点

Optimal variables and corresponding cut-off points for identification of cardiovascular risk factors clustering among elderly males
FAN Yu-hui,CAI Wei,TAO Ye-xuan,TANG Qing-ya.Optimal variables and corresponding cut-off points for identification of cardiovascular risk factors clustering among elderly males[J].Journal of Shanghai Jiaotong University:Medical Science,2009,29(8):982.
Authors:FAN Yu-hui  CAI Wei  TAO Ye-xuan  TANG Qing-ya
Institution:Clinical Nutrition Center, Xinhua Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200092, China
Abstract:Objective To explore the optimal cut-off points of body mass index (BMI), percentage of body fat (PBF) and body fat mass index (BFMI) for identification of cardiovascular risk factors clustering among elderly males. Methods The data of physical examinations from 1 052 Shanghai elderly males in 2007 were collected. The relationship between cardiovascular risk factors clustering and different strata of BMI, PBF and BFMI was analyzed. Receiver Operator Characteristic (ROC) curve analysis was employed to determine the optimal cut-points for identification of cardiovascular risk factors clustering, and area under curve (AUC) was worked out. The population attributable risk proportion (PARP) of risk factors clustering was calculated. Results Odds ratios of risk factors clustering tended to increase with BMI, PBF and BFMI. BMI≥24 kg/m2, PBF≥21% and BFMI≥5 kg/m2 were the cut-off points that had approximate sensitivity and specificity, and/or had the shortest distance in ROC curve. AUC of all the three indexes was larger than 0.5. Analysis of PARP indicated that BMI under 24 kg/m2,  PBF under 21% and BFMI under 5 kg/m2 could prevent 27.1%, 37.44% and 36.63% risk factors clustering, respectively. Conclusion BMI≥24 kg/m2, PBF≥21% and BFMI≥5 kg/m2 can well reflect the cardiovascular risk factors clustering among elderly males.
Keywords:elderly  cardiovascular risk factors clustering  body mass index  percentage of body fat  body fat mass index  cut off point
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