AI Article Synopsis

  • The study evaluated different parameters, such as BMI and the TyG index, to determine their effectiveness in detecting insulin resistance (IR) among nondiabetic Chinese individuals.
  • Researchers analyzed data from 1,067 participants, using tests like glucose tolerance and blood lipid measurements to compare correlations and predictive efficacy of these parameters.
  • Findings revealed that BMI and the TyG-BMI combination were the most reliable indicators for IR, with a recommended optimal BMI cut-off point of 27 kg/m² for effective detection across various glucose categories.

Article Abstract

In the present study, the performance of anthropometric parameters, lipid and glucose indexes, and the combination of anthropometric parameters with the TyG (triglycerides × fasting plasma glucose) metabolic index, was compared in detecting insulin resistance (IR) to evaluate the optimal cut-off points in nondiabetic Chinese individuals. A total of 1067 nondiabetics underwent oral glucose tolerance test, blood lipid, and fasting insulin measurements. The clinical usefulness of various parameters- body mass index (BMI), waist circumference (WC), TyG, triglycerides/ high density lipoprotein cholesterol ratio, and TyG with adiposity status (TyG-BMI [TyG × BMI] and TyG-WC)-was analyzed to identify IR. Spearman correlation and receiver-operating characteristic curve analyses were used to compare the predictive efficacy of different indicators. All indicators showed a positive correlation with IR in both normal glucose and all subjects. However, the correlation between BMI and homeostasis model assessment of IR index was higher than other indicators as assessed by Spearman correlation test (P < .05). Furthermore, BMI and TyG-BMI were better indicators than others as determined by comparing the area under the receiver-operating characteristics curves (P < .05) in detecting IR. BMI is a simple and accurate measure for detecting IR in Chinese subjects. The 27 kg/m threshold was the optimal BMI cut-off point for detecting IR in both normal glucose and all glucose categories subjects.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004598PMC
http://dx.doi.org/10.1097/MD.0000000000019023DOI Listing

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