The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans

Abstract

BackgroundScreening for risk of type 2 diabetes mellitus (T2DM) is an important public health issue. Previous studies report that fasting plasma glucose (FPG) and triglyceride (TG)-related indices, such as lipid accumulation product (LAP) and the product of fasting glucose and triglyceride (TyG index), are associated with incident T2DM. We aimed to evaluate whether FPG or TG-related indices can improve the predictive ability of a diabetes risk model for middle-aged Koreans.Methods7708 Koreans aged 40–69 years without diabetes at baseline were eligible from the Korean Genome and Epidemiology Study. The overall cumulative incidence of T2DM was 21.1% (766 cases) in men and 19.6% (797 cases) in women. Therefore, the overall cumulative incidence of T2DM was 20.3% (1563 cases). Multiple logistic regression analysis was conducted to compare the odds ratios (ORs) for incident T2DM for each index. The area under the receiver operating characteristic curve (AROC), continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI) were calculated when each measure was added to the basic risk model for diabetes.ResultsAll the TG-related indices and FPG were more strongly associated with incident T2DM than WC in our study population. The adjusted ORs for the highest quartiles of WC, TG, FPG, LAP, and TyG index compared to the lowest, were 1.64 (95% CI, 1.13–2.38), 2.03 (1.59–2.61), 3.85 (2.99–4.97), 2.47 (1.82–3.34), and 2.79 (2.16–3.60) in men, and 1.17 (0.83–1.65), 2.42 (1.90–3.08), 2.15 (1.71–2.71), 2.44 (1.82–3.26), and 2.85 (2.22–3.66) in women, respectively. The addition of TG-related parameters or FPG, but not WC, to the basic risk model for T2DM (including age, body mass index, family history of diabetes, hypertension, current smoking, current drinking, and regular exercise) significantly increased cNRI, IDI, and AROC in both sexes.ConclusionsAdding either TyG index or FPG into the basic risk model for T2DM increases its prediction and reclassification ability. Compared to FPG, TyG index was a more robust T2DM predictor in the stratified sex and fasting glucose level. Therefore, TyG index should be considered as a screening tool for identification of people at high risk for T2DM in practice.

Association Between Triglyceride-Glucose Index and Risk of Incident Diabetes: A Secondary Analysis Based on A Chinese Cohort Study

“…This association was particularly obvious in females, and was consistent with the cohort study by Zhang et al [14]. This may be because serum lipids in female hepatocytes were higher than that in male hepatocytes under fasting and glucose lipid loading [30,31]. In clinical practice, obese and older individuals are generally considered the primary targets for diabetes screening.…”

U-Shaped Association Between the Triglycerides-Glucose index and the Risk of Incident Diabetes in Apparently Healthy Population: A Population-based Cohort Study

“…More importantly, previous cohort studies showed a positive relationship between high levels of the TyG index and the risk of incident diabetes [17][18][19][20], but the positive association disappeared at low levels of the TyG index [17,18,20]. This trend suggested a nonlinear association which had never been well characterized in previous studies.…”

“…The TyG index was suggested to be considered as a screening tool for identifying people at a high risk of T2DM in clinical practice [18]. Although studies on the TyG index as a risk of T2DM have been conducted in Singapore, Korean, Thailand, and the white European population [17][18][19][20], no data on the Japanese population are currently available.…”

Long-term sucrose solution consumption causes metabolic alterations and affects hepatic oxidative stress in wistar rats

“…Serum insulin quantification was performed using an enzymelinked immunosorbent assay kit (Mouse Insulin ELISA kit, Thermo Fisher Scientific, USA). The insulin sensitivity indices, such as homeostasis model assessment of insulin resistance (HOMA IR=fasting insulin×fasting glucose/ 22.5) (Antunes et al, 2016); quantitative insulin sensitivity check index [QUICKI=1/(log insulin concentration+log blood glucose concentration)] (Bowe et al, 2014); the product of fasting plasma glucose and triglyceride [TyG index=ln (fasting triacylglycerol×fasting glucose/2)] (Lee et al, 2018); hepatic insulin sensitivity (HIS=1000/fasting insulin×fasting glucose) (Matsuda and DeFronzo, 1999) were calculated. HIS assumes that higher values of the product of glucose and insulin are inversely related to the capacity of the liver to respond to insulin.…”