腰围身高比对代谢综合征的筛检能力分析及界值确定

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目的分析腰围身高比(WHtR)对代谢综合征(MS)的筛检能力并确定界值,以期获得简单、准确、经济、家庭化的MS筛检方法。方法采用随机整群抽样的方法,以河南省某县为研究现场对成年常住居民进行问卷调查、体格检查和生化检查。进而通过MedCalc软件对WHtR与腰围预测MS各代谢异常组分的ROC曲线下面积进行比较;计算WHtR筛检MS的界值并分析假阳性和假阴性人群的特征。结果WHtR与WC相比,除对MS少数组分预测能力无统计学差异外;对其余各组分的预测能力均较强;WHtR筛检MS的界值为男性0.51,女性0.52,不考虑性别差异的界值为0.52。对假阳性和假阴性人群进行特征分析显示:假阳性组人群的体重、BMI、腰围等指标高于假阴性组,其余指标低于假阴性组。假阳性组中存在任意一个组分异常者的人数占80.78%;存在任意两个组分异常者人数占8.59%。结论WHtR对MS单组分及复合组分异常的预测效力均较强,适合作为MS的筛检指标,其诊断界值可定为0.52。 Objective To analyze the screening ability of WHtR for metabolic syndrome (MS) and to determine the cut - off value in order to obtain a simple, accurate, economical and home - based MS screening method. Methods A random cluster sampling method was used to conduct a questionnaire survey, physical examination and biochemical examination on adult residents living in a county in Henan Province. Further, the area under the ROC curve of WHtR and waist circumference prediction MS metabolic abnormalities components was compared by MedCalc software; the cutoff value of WHtR screening MS was calculated and the characteristics of the false positive and false negative populations were analyzed. Results Compared with WC, WHtR showed no significant difference in predicting ability of MS, except for the ability of predicting the other components. The predictive value of WHtR for MS was 0.51 for males and 0.52 for females, regardless of sex The cut-off value is 0.52. False-positive and false-negative population characteristics analysis showed that: false-positive group of weight, BMI, waist circumference and other indicators higher than the false-negative group, the remaining indicators were lower than the false-negative group. In the false positive group, there were 80.78% of the patients with any component abnormalities, and 8.59% of the patients with any two component abnormalities. CONCLUSION: The predictive power of WHtR for MS single component and composite component abnormalities is high, which is suitable as a screening index for MS. The diagnostic cutoff value of WHtR can be set as 0.52.
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