Chinese General Practice ›› 2025, Vol. 28 ›› Issue (21): 2595-2603.DOI: 10.12114/j.issn.1007-9572.2024.0559

• Original Research • Previous Articles     Next Articles

Study on the Effect and Predictive Value of Obesity and Lipid-related Indices on Metabolic Syndrome in Adults

  

  1. 1. School of Nursing, Anhui Medical University, Hefei 230032, China
    2. Health Management Center, Bozhou People's Hospital, Bozhou 236800, China
  • Received:2025-01-10 Revised:2025-04-15 Published:2025-07-20 Online:2025-06-05
  • Contact: LIU Annuo

成年人肥胖和脂质相关指标对代谢综合征的影响及预测价值研究

  

  1. 1.230032 安徽省合肥市,安徽医科大学护理学院
    2.236800 安徽省亳州市人民医院健康管理中心
  • 通讯作者: 刘安诺
  • 作者简介:

    作者贡献:

    李春贤负责文章的构思与设计、数据收集与整理、统计学处理、论文撰写;李春贤、刘安诺负责研究的实施与可行性分析、结果的分析与解释、论文的修订;刘安诺负责文章的质量控制及审校,并对文章整体负责,监督管理。

  • 基金资助:
    安徽省高校自然科学研究重大项目(2023AH040085)

Abstract:

Background

Metabolic Syndrome (MetS) is an important risk factor for cardiovascular complications and kidney damage. Obesity and lipid-related markers are closely associated with MetS, and the predictive ability of different markers for MetS is still controversial.

Objective

The aim of this study was to evaluate the effect of 12 obesity and lipid-related indices, including lipid accumulation products, body mass index, visceral adiposity index, Chinese visceral adiposity index (CAVI) , abdominal volume index (AVI) , body fat index, BMI, body size index (ABSI) , triacylglycerol-glucose index (TyG) and its combined index TyG-BMI, TyG-waist circumference (TyG-WC) , and TyG-waist-height ratio (TyG-WHtR) , on the optimal cutoff values for MetS screening and prediction and to identify the most appropriate predictors.

Methods

The health checkup data of a state-owned enterprise in Anhui Province in 2023 were selected, and the correlation between 12 obesity and lipid-related indexes and MetS was analyzed by binary logistic regression. The work characteristics (ROC) curves of subjects with different obesity and lipid-related indexes assessing MetS were plotted, and the area under the ROC curve (AUC) was calculated and compared with its predictive value.

Results

A total of 4 028 employees of a state-owned enterprise were included in this study, and the overall prevalence of MetS in the study population was 23.43% (944/4 028) , with a prevalence of MetS of 26.53% (816/3 075) in males and 13.43% (128/953) in females.The results of the logistic model showed that the TyG-WHtR was associated with an OR (95%CI) of the total population =7.170 (5.411-9.500) , gender subgroup [male OR (95%CI) =16.277 (11.554-22.930) ; female OR (95%CI) =13.422 (5.388-33.435) ] , age subgroup of males >50 years old OR (95%CI) =31.411 (18.868-52.292) and 36~50 years old women OR (95%CI) =95.154 (22.610-400.465) had the strongest association with the odds of developing MetS. The predictive ability of CVAI for MetS showed the best predictive effect in the total population, males and age subgroups of males ≤35 years old group and 36~50 years old group, with AUCs of 0.926 (95%CI=0.917-0.936, P<0.001) , 0.941 (95%CI=0.933-0.949, P<0.001) , 0.931 (95%CI=0.917-0.946, P<0.001) , 0.947 (95%CI=0.934-0.961, P<0.001) ; the predictive ability of AVI for MetS was higher in women and the age subgroups of women ≤35 and >50 years old, and in the group of men >50 years old, with a higher discrimination ability, with AUCs of 0.951 (95%CI=0.938~0.963, P<0.001) , 0.961 [95%CI=0.943-0.978, P<0.001) , 0.909 (95%CI=0.857-0.961, P<0.001) , 0.962 (95%CI=0.951-0.974, P<0.001) ; TyG-WC in the age subgroup female 36-50 years group performed better in predicting MetS with an AUC of 0.949 (95%CI=0.925~0.972, P<0.001) .

Conclusion

TyG-WHtR had the strongest association with MetS. Except for ABSI, which had poor predictive ability for MetS, CVAI showed better predictive ability for MetS in the total population, males and age subgroups males ≤35 years old group and 36~50 years old group, AVI had higher discriminatory ability for MetS in females and age subgroups females ≤35 years old and >50 years old, and males >50 years old group, and TyG-WC showed better predictive ability for MetS in the age subgroup females 36-50 years old group. MetS predictive ability performed better.

Key words: Metabolic syndrome, Adult, Obesity, Lipid-related indexes, ROC curve

摘要:

背景

代谢综合征(MetS)是心血管并发症和肾损害的重要危险因素。肥胖和脂质相关指标与MetS密切相关,目前不同指标对MetS的预测价值尚有争议。

目的

本研究旨在评估脂质积累指数、BMI、内脏脂肪指数、中国内脏脂肪指数(CVAI)、腹容积指数(AVI)、体脂肪指数、体圆度指数、体型指数(ABSI)、三酰甘油葡萄糖指数(TyG)及其联合指数TyG-BMI、TyG-腰围(TyG-WC)、TyG-腰高比(TyG-WHtR)12项肥胖和脂质相关指标对MetS筛查和预测的最佳截断值,并确定最合适的预测因子。

方法

选取2023年安徽省某国企成年人健康体检资料,采用二元Logistic回归分析12项肥胖和脂质相关指标与MetS的相关性。绘制不同肥胖和脂质相关指标评估MetS的受试者工作特征(ROC)曲线,计算ROC曲线下面积(AUC)并比较其预测价值。

结果

本研究共纳入4 028名某国企成年人健康体检者的数据,研究人群MetS总体患病率为23.43%(944/4 028),男性MetS患病率为26.53%(816/3 075),女性MetS患病率为13.43%(128/953)。二元Logistic回归分析结果显示,TyG-WHtR与总人群[OR(95%CI)=7.170(5.411~9.500)]、性别亚组[男性OR(95%CI)=16.277(11.554~22.930);女性OR(95%CI)=13.422(5.388~33.435)]、年龄亚组[>50岁男性,OR(95%CI)=31.411(18.868~52.292)与36~50岁女性,OR(95%CI)=95.154(22.610~400.465)]MetS患病风险相关(P<0.05)。CVAI预测总人群、男性及年龄亚组男性≤35岁组和36~50岁组发生MetS的AUC分别为0.926(95%CI=0.917~0.936,P<0.001)、0.941(95%CI=0.933~0.949,P<0.001)、0.931(95%CI=0.917~0.946,P<0.001)、0.947(95%CI=0.934~0.961,P<0.001);AVI预测女性及年龄亚组女性≤35岁和>50岁、男性>50岁组发生MetS的AUC分别为0.951(95%CI=0.938~0.963,P<0.001)、0.961(95%CI=0.943~0.978,P<0.001)、0.909(95%CI=0.857~0.961,P<0.001)、0.962(95%CI=0.951~0.974,P<0.001);TyG-WC预测年龄亚组女性36~50岁组发生MetS的AUC为0.949(95%CI=0.925~0.972,P<0.001)。

结论

TyG-WHtR与成年人MetS关联性最强。除ABSI对MetS预测能力欠佳外,CVAI在总人群、男性及年龄亚组男性≤35岁组和36~50岁组对MetS预测能力均较佳,AVI对女性及年龄亚组女性≤35岁和>50岁、男性>50岁组对MetS均具有较高预测价值,TyG-WC对年龄亚组女性36~50岁组MetS的预测能力表现更优。

关键词: 代谢综合征, 成年人, 肥胖症, 脂质相关指标, ROC曲线