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亚洲人群代谢综合征严重程度评分的制定及其与新发糖尿病的关系——来自新加坡纵向队列研究的结果。

Development of a metabolic syndrome severity score and its association with incident diabetes in an Asian population-results from a longitudinal cohort in Singapore.

机构信息

Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore.

Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore.

出版信息

Endocrine. 2019 Jul;65(1):73-80. doi: 10.1007/s12020-019-01970-5. Epub 2019 Jun 3.

Abstract

PURPOSE

Metabolic syndrome (MetS) is a constellation of clinical factors that indicates elevated risk of diabetes. It is diagnosed based on three or more abnormalities in its components. This does not take into account that MetS can likely present as a continuum of risk. We aim to develop a MetS severity score and assess its association with incident diabetes.

METHODS

In total, 4149 subjects without baseline diabetes participated in a community screening programme in 2013-2017. MetS was defined according to International Diabetes Federation criteria. A MetS severity z-score was derived from standardised loading coefficients of a confirmatory factor analysis for waist circumference, triglycerides, HDL-cholesterol, blood pressure and fasting plasma glucose (FPG). Multivariable cox proportional hazards regression model was used to assess the risk of diabetes by the score with adjustment for demographics and MetS components.

RESULTS

Diabetes occurred in 130 subjects. Quintile 5 of the baseline MetS severity z-score was significantly associated with development of diabetes even in fully adjusted model with HR 2.63 (95% CI: 1.04-6.64; p = 0.040). The relationship between MetS and incident diabetes became attenuated and non-significant in fully adjusted model with HR 0.67 (95% CI: 0.34-1.29; p = 0.228). Mediation analysis showed that MetS severity z-score accounted 61.0% of the association between increasing body mass index and development of diabetes (p < 0.001).

CONCLUSIONS

The MetS severity z-score is an inexpensive and clinically-available continuous measure of MetS to identify individuals at high risk of diabetes.

摘要

目的

代谢综合征(MetS)是一组临床因素,表明糖尿病风险升高。它是根据其成分中的三种或更多异常来诊断的。这并没有考虑到 MetS 可能表现为风险的连续体。我们旨在开发一种 MetS 严重程度评分,并评估其与糖尿病发病的关系。

方法

共有 4149 名基线无糖尿病的受试者参加了 2013-2017 年的社区筛查计划。MetS 根据国际糖尿病联合会的标准定义。MetS 严重程度 z 评分是通过对腰围、甘油三酯、高密度脂蛋白胆固醇、血压和空腹血糖(FPG)的验证性因素分析的标准化加载系数得出的。多变量 Cox 比例风险回归模型用于评估评分的糖尿病风险,调整了人口统计学和 MetS 成分。

结果

共有 130 名受试者发生了糖尿病。即使在完全调整后的模型中,基线 MetS 严重程度 z 评分的五分位 5 与糖尿病发病显著相关,HR 为 2.63(95%CI:1.04-6.64;p=0.040)。在完全调整后的模型中,MetS 与新发糖尿病之间的关系减弱且无统计学意义,HR 为 0.67(95%CI:0.34-1.29;p=0.228)。中介分析表明,MetS 严重程度 z 评分解释了 BMI 升高与糖尿病发病之间关系的 61.0%(p<0.001)。

结论

MetS 严重程度 z 评分是一种廉价且临床可用的 MetS 连续测量方法,可用于识别糖尿病高危个体。

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