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人体测量指标预测代谢综合征发病风险的能力:一项横断面研究。

Predictive ability of anthropometric indices for risk of developing metabolic syndrome: a cross-sectional study.

机构信息

Research Group in Public Nutrition and Nutritional Food Security, Universidad San Ignacio de Loyola, Lima, Peru.

Department of Nutrition, Food Sciences and Physiology, Faculty of Pharmacy and Nutrition, Universidad de Navarra, Pamplona, Spain.

出版信息

J Int Med Res. 2024 Nov;52(11):3000605241300017. doi: 10.1177/03000605241300017.

DOI:10.1177/03000605241300017
PMID:39578935
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11585023/
Abstract

OBJECTIVE

To determine the discriminatory ability of different anthropometric indicators of body fat percentage for diagnosing metabolic syndrome (MetS) in a Peruvian sample.

METHODS

This was a cross-sectional, non-experimental, diagnostic accuracy study. Anthropometric and biochemical data for 948 participants were analyzed. Waist circumference (WC), body mass index, relative fat mass (RFM), conicity index, body roundness index (BRI), waist-to-height ratio (WHtR), and A Body Shape Index were assessed for their MetS discriminatory ability. The National Cholesterol Education Program's Adult Treatment Panel III criteria were used to diagnose MetS. Receiver operating characteristic curves and area under the curve (AUC) were used to determine the predictive power of each anthropometric measurement to diagnose MetS.

RESULTS

In both sexes, RFM, BRI, and WHtR showed the same predictive ability to diagnose MetS. In women, indicators incorporating WC showed high discriminatory ability: RFM, BRI, and WHtR (all AUC: 0.869, 95% confidence interval [CI]: 0.828-0.910). In men, WC had the highest AUC (0.829, 95% CI: 0.793-0.866).

CONCLUSIONS

In both sexes, RFM, WC, BRI, and WHtR were the best predictors of MetS diagnosis. This is the first study to identify RFM as a potentially useful clinical predictor of MetS in a Peruvian sample of educational workers.

摘要

目的

确定不同体脂百分比人体测量指标在秘鲁人群中诊断代谢综合征(MetS)的鉴别能力。

方法

这是一项横断面、非实验性、诊断准确性研究。对 948 名参与者的人体测量学和生化数据进行了分析。评估了腰围(WC)、体重指数、相对脂肪量(RFM)、锥形指数、体圆度指数(BRI)、腰高比(WHtR)和 A 体型指数对 MetS 的鉴别能力。采用美国国家胆固醇教育计划成人治疗专家组 III 标准诊断 MetS。使用受试者工作特征曲线和曲线下面积(AUC)来确定每种人体测量指标诊断 MetS 的预测能力。

结果

在男女中,RFM、BRI 和 WHtR 对诊断 MetS 的预测能力相同。在女性中,纳入 WC 的指标显示出较高的鉴别能力:RFM、BRI 和 WHtR(AUC 均为 0.869,95%置信区间[CI]:0.828-0.910)。在男性中,WC 的 AUC 最高(0.829,95%CI:0.793-0.866)。

结论

在男女中,RFM、WC、BRI 和 WHtR 是 MetS 诊断的最佳预测指标。这是第一项在秘鲁教育工作者样本中发现 RFM 可能是 MetS 有用的临床预测指标的研究。

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