Association of hemoglobin glycation index and glycation gap with cardiovascular disease among US adults. (August 2022)

• Record Type: Journal Article
• Authors: Wang, Sibo; Gu, Lingfeng; Chen, Jiawen; Jiang, Qiqi; Sun, Jiateng; Wang, Hao; Wang, Liansheng
• Is Part Of: Diabetes research and clinical practice. Volume 190(2022)
• Publication Date: 2022-08
• Subjects: Hemoglobin glycation index -- Glycation gap -- Glycated hemoglobin A1c -- Cardiovascular disease -- National Health and Nutrition Examination Survey; HGI hemoglobin glycation index -- GGap glycation gap -- HbA1c glycated hemoglobin A1c -- CVD cardiovascular disease -- NHANES National Health and Nutrition Examination Survey -- FPG fasting plasma glucose -- GA glycated albumin -- T2D type 2 diabetes -- PIR the ratio of family income to poverty -- LDL-C low-density lipoprotein cholesterol -- HDL-C high-density lipoprotein cholesterol -- CRP C-reactive protein -- WBC white blood cell count -- Hb hemoglobin -- SBP systolic blood pressure -- DBP diastolic blood pressure -- eGFR estimated glomerular filtration rate -- BMI body mass index -- WC waist circumference -- AGEs advanced glycation end products; Diabetes -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462
• DOI: 10.1016/j.diabres.2022.109990
• Languages: English
• ISSNs: 0168-8227

Abstract

Abstract: Aims: To investigate the association of hemoglobin glycation index (HGI) and glycation gap (GGap), reflecting mismatches between HbA1c and other measures of glycemia, with cardiovascular disease (CVD) in the general population. Methods: 5966 US adult (age ≥ 20 years) participants were included from the National Health and Nutrition Examination Survey (NHANES) (1999–2004). In this cross-sectional study, predicted HbA1c was calculated based on fasting plasma glucose (FPG) and glycated albumin (GA), respectively. Multivariable binary logistic regression analysis was performed to explore the association of HGI and GGap with CVD prevalence. Results: Compared to the lowest tertile, the ORs with 95% CIs for CVD across the tertiles were 1.41 (1.01, 1.96) and 0.87 (0.58, 1.31) for HGI ( P for trend = 0.535) and 1.06 (0.77, 1.47) and 1.60 (1.18, 2.17) for GGap ( P for trend = 0.002) in the fully-adjusted model. Besides, the discordantly high GGap/low HbA1c group was associated with higher CVD prevalence compared with the low GGap/high HbA1c group (OR = 1.50, 95% CI, 1.04–2.16, P = 0.030). Conclusions: GGap derived from GA is associated with CVD independent of traditional risk factors, even HbA1c, in US general adults. Considering the potential limitations of HbA1c, the introduction of GGap is warranted.