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体质量指数诊断肥胖与体脂定义肥胖的诊断性能:系统评价和荟萃分析。

Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis.

机构信息

University of Missouri School of Medicine, Columbia, MO, USA.

出版信息

Int J Obes (Lond). 2010 May;34(5):791-9. doi: 10.1038/ijo.2010.5. Epub 2010 Feb 2.

Abstract

OBJECTIVE

We performed a systematic review and meta-analysis of studies that assessed the performance of body mass index (BMI) to detect body adiposity.

DESIGN

Data sources were MEDLINE, EMBASE, Cochrane, Database of Systematic Reviews, Cochrane CENTRAL, Web of Science, and SCOPUS. To be included, studies must have assessed the performance of BMI to measure body adiposity, provided standard values of diagnostic performance, and used a body composition technique as the reference standard for body fat percent (BF%) measurement. We obtained pooled summary statistics for sensitivity, specificity, positive and negative likelihood ratios (LRs), and diagnostic odds ratio (DOR). The inconsistency statistic (I2) assessed potential heterogeneity.

RESULTS

The search strategy yielded 3341 potentially relevant abstracts, and 25 articles met our predefined inclusion criteria. These studies evaluated 32 different samples totaling 31 968 patients. Commonly used BMI cutoffs to diagnose obesity showed a pooled sensitivity to detect high adiposity of 0.50 (95% confidence interval (CI): 0.43-0.57) and a pooled specificity of 0.90 (CI: 0.86-0.94). Positive LR was 5.88 (CI: 4.24-8.15), I (2)=97.8%; the negative LR was 0.43 (CI: 0.37-0.50), I (2)=98.5%; and the DOR was 17.91 (CI: 12.56-25.53), I (2)=91.7%. Analysis of studies that used BMI cutoffs >or=30 had a pooled sensitivity of 0.42 (CI: 0.31-0.43) and a pooled specificity of 0.97 (CI: 0.96-0.97). Cutoff values and regional origin of the studies can only partially explain the heterogeneity seen in pooled DOR estimates.

CONCLUSION

Commonly used BMI cutoff values to diagnose obesity have high specificity, but low sensitivity to identify adiposity, as they fail to identify half of the people with excess BF%.

摘要

目的

我们对评估体重指数(BMI)检测体脂含量的表现的研究进行了系统评价和荟萃分析。

设计

数据来源为 MEDLINE、EMBASE、Cochrane、系统评价数据库、Cochrane 中心、Web of Science 和 SCOPUS。纳入的研究必须评估 BMI 测量体脂含量的性能,提供诊断性能的标准值,并使用身体成分技术作为体脂肪百分比(BF%)测量的参考标准。我们获得了敏感性、特异性、阳性和阴性似然比(LR)以及诊断比值比(DOR)的汇总汇总统计数据。不一致性统计量(I2)评估了潜在的异质性。

结果

搜索策略产生了 3341 篇潜在相关的摘要,有 25 篇文章符合我们预先设定的纳入标准。这些研究评估了 32 个不同的样本,共 31968 名患者。常用的 BMI 截断值来诊断肥胖的敏感性汇总为 0.50(95%置信区间[CI]:0.43-0.57),特异性汇总为 0.90(CI:0.86-0.94)。阳性 LR 为 5.88(CI:4.24-8.15),I2=97.8%;阴性 LR 为 0.43(CI:0.37-0.50),I2=98.5%;DOR 为 17.91(CI:12.56-25.53),I2=91.7%。使用 BMI 截断值>或=30 的研究的敏感性汇总为 0.42(CI:0.31-0.43),特异性汇总为 0.97(CI:0.96-0.97)。研究的 BMI 截断值和地域来源只能部分解释汇总 DOR 估计中的异质性。

结论

常用的 BMI 截断值用于诊断肥胖具有高特异性,但对识别肥胖的敏感性较低,因为它们无法识别一半的 BF%过多的人。

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