Zhang Fang, Li Yufeng, Zhao Yingxi, Zhou Xianghai, Ji Linong
Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China.
Department of Endocrinology and Metabolism, Beijing Pinggu Hospital, Beijing, China.
J Diabetes Investig. 2020 Jul;11(4):888-895. doi: 10.1111/jdi.13217. Epub 2020 Feb 23.
AIMS/INTRODUCTION: The aim of the present study was to analyze the strength of association between fasting plasma glucose (FPG), 2-h postprandial glucose (2h PPG), hemoglobin A1c (HbA1c), disposition index (DI) and nine anthropometrics measures, to explore the best indicator for hyperglycemia.
Analyses were based on the cross-sectional data of 3,572 adults from the Pinggu Metabolic Disease Study. Anthropometrics were measured, visceral fat area (VFA) and subcutaneous fat area were calculated using an abdominal computed tomography scan. Linear regression was used to analyze the association between FPG, 2h PPG, HbA1c, DI and nine anthropometrics measures (height, weight, waist circumference [WC], body mass index and waist-to-hip ratio [WHR], waist-to-height ratio, VFA, subcutaneous fat area, and visceral-to-subcutaneous ratio). Logistic regression was further carried out to understand the association between per standard increase and risk for hyperglycemia.
Higher VFA and subcutaneous fat area were associated with higher FPG, 2h PPG, HbA1c and DI after adjusting for other covariates. The strongest association observed after adjustment was WC for FPG, with one standard deviation greater WC being associated with 1.70 increased odds; WHR for 2h PPG, with one standard deviation greater WHR being associated with 1.83 increased odds. The strength of the association between VFA and FPG, 2h PPG, HbA1c, and DI was less than WHR and WC, but slightly stronger than body mass index. Stratified analyses showed that VFA performs better as an anthropometrics indicator in predicting hyperglycemic risk in women than men.
WHR and WC remain the best indicators for hyperglycemic risk among ahealthy Chinese population.
目的/引言：本研究旨在分析空腹血糖（FPG）、餐后2小时血糖（2h PPG）、糖化血红蛋白（HbA1c）、处置指数（DI）与九项人体测量指标之间的关联强度，以探寻高血糖的最佳指标。
分析基于平谷代谢病研究中3572名成年人的横断面数据。测量人体测量指标，使用腹部计算机断层扫描计算内脏脂肪面积（VFA）和皮下脂肪面积。采用线性回归分析FPG、2h PPG、HbA1c、DI与九项人体测量指标（身高、体重、腰围[WC]、体重指数和腰臀比[WHR]、腰高比、VFA、皮下脂肪面积以及内脏与皮下脂肪比）之间的关联。进一步进行逻辑回归以了解每单位标准增加与高血糖风险之间的关联。
在调整其他协变量后，较高的VFA和皮下脂肪面积与较高的FPG、2h PPG、HbA1c和DI相关。调整后观察到的最强关联是FPG与WC，WC每增加一个标准差，高血糖几率增加1.70；2h PPG与WHR，WHR每增加一个标准差，高血糖几率增加1.83。VFA与FPG、2h PPG、HbA1c和DI之间的关联强度小于WHR和WC，但略强于体重指数。分层分析表明，在预测女性高血糖风险方面，VFA作为人体测量指标的表现优于男性。
在健康中国人群中，WHR和WC仍然是高血糖风险的最佳指标。
