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基于体脂分布和腰围的新型肥胖表型系统进行心脏代谢风险分层。

Cardiometabolic risk stratification using a novel obesity phenotyping system based on body adiposity and waist circumference.

机构信息

Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Spain.

Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Spain.

出版信息

Eur J Intern Med. 2024 Jun;124:54-60. doi: 10.1016/j.ejim.2024.02.027. Epub 2024 Mar 6.

Abstract

BACKGROUND

The estimation of obesity-associated cardiometabolic risk does not usually take into account body composition or the distribution of adiposity. The aim of the present study was to assess the clinical usefulness of a novel obesity phenotyping system based on the combination of actual body fat percentage (BF%) and waist circumference (WC) according to the cardiometabolic risk estimation.

METHODS

A classification matrix combining BF% and WC as measures of both amount and distribution of adiposity establishing nine body phenotypes (3 BF% x 3 WC) was developed. Individuals were grouped in five different cardiometabolic risk phenotypes. We conducted a validation study in a large cohort of White subjects from both genders representing a wide range of ages and adiposity (n = 12,754; 65 % females, aged 18-88 years).

RESULTS

The five risk groups using the matrix combination of BF% and WC exhibited a robust linear distribution regarding cardiometabolic risk, estimated by the Metabolic Syndrome Severity Score, showing a continuous increase between groups with significant differences (P < 0.001) among them, as well as in other cardiometabolic risk factors. An additional 24 % of patients at very high risk was detected with the new classification system proposed (P < 0.001) as compared to an equivalent matrix using BMI and WC instead of BF% and WC.

CONCLUSIONS

A more detailed phenotyping should be a priority in the diagnosis and management of patients with obesity. Our classification system allows to gradually estimate the cardiometabolic risk according to BF% and WC, thus representing a novel and useful tool for both research and clinical practice.

摘要

背景

评估肥胖相关的心血管代谢风险通常不考虑身体成分或体脂分布。本研究旨在评估一种新的肥胖表型系统的临床实用性,该系统基于实际体脂肪百分比(BF%)和腰围(WC)的组合,根据心血管代谢风险评估来评估肥胖表型。

方法

建立了一个分类矩阵,将 BF%和 WC 作为脂肪量和分布的衡量标准,将肥胖表型分为 9 种(3 BF% x 3 WC)。将个体分为五种不同的心血管代谢风险表型。我们在一个由来自不同年龄段和不同肥胖程度的白种人组成的大型队列中进行了验证研究(n = 12754;65%为女性,年龄 18-88 岁)。

结果

使用 BF%和 WC 的矩阵组合的五个风险组在心血管代谢风险方面表现出稳健的线性分布,通过代谢综合征严重程度评分来估计,各组之间存在显著差异(P <0.001),以及其他心血管代谢风险因素。与使用 BMI 和 WC 代替 BF%和 WC 的等效矩阵相比,新的分类系统(P <0.001)检测到了额外的 24%的极高风险患者。

结论

更详细的表型分析应该是肥胖患者诊断和管理的优先事项。我们的分类系统允许根据 BF%和 WC 逐渐评估心血管代谢风险,因此代表了一种新的有用的研究和临床实践工具。

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