AUTHOR=Zhang Yi , Jiang Tian , Liu Chao , Hu Honglin , Dai Fang , Xia Li , Zhang Qiu 

TITLE=Effectiveness of Early Advanced Glycation End Product Accumulation Testing in the Diagnosis of Diabetes: A Health Risk Factor Analysis Using the Body Mass Index as a Moderator

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2021.766778

DOI=10.3389/fendo.2021.766778

ISSN=1664-2392

ABSTRACT=Objective To evaluate the value of noninvasive detection of advanced glycation end products (AGEs) in the early screening of diabetes mellitus in the community of China.  Methods From January 2018 to January 2019, a total of 912 patients with community health physical examination and no history of diabetes were selected. Finally, 906 samples were included in the study, with an effective rate of 99.3%. Noninvasive diabetic detection technology was used to detect AGEs in upper arm skin of all participants, AGE accumulations were classified as ≤P25, P25～P50, P50～P75 and > P75; and HbA1c, insulin, C-peptide, total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL⁃C), creatinine, urea and other indicators were measured at the same time. Univariate analysis of variance was used to compare the differences in general data, biochemical indexes, skin AGEs levels and blood glucose among groups, and logistic regression analysis and latent category analysis were performed.  Results In univariate analysis, SBP, FBG, HbA1c, age were correlated with higher AGE (P < 0.01); TG, TC, HDL, UA and gender were not positively correlated with AGE. After controlling for covariates (waist circumference, hip circumference), AGE accumulation was interacted with other variables. The results of latent category analysis (LCA) showed that the health risk factors, including age, systolic blood pressure, HbA1c, FBG, triglyceride, total cholesterol, HDL⁃C, uric acid were divided as three groups, and AGE is divided into four categories according to the quartile method, which were low risk (≤P25), low to medium risk (P25～P50), medium to high (P50～P75) and high risk (> P75), respectively. In association between the quartile AGE and risk factors of the OR values were 1.09, 2.61 , 5.41, respectively. The PROCESS program was used to analyze whether BMI moderated the link between risk factors and AGE accumulation. There was also significant three-way interaction among HFRs, BMI, and gender for AGE accumulation in the total sample (β = -0.30) Conclusion Noninvasive skin detection of AGEs has certain application value for the assessment of diabetes risk, and is related to a variety of risk factors, but may not be fully applicable for early screening of diabetes.