OBJECTIVE: Our objective was to perform a systematic review and meta-analysis of cohort studies evaluating the triglyceride-glucose (TyG) index as a tool for type 2 diabetes (T2D) prediction in adults and older adults. METHODS: Studies were identified in PubMed, Cochrane, Scopus, and Lilacs. Studies with cohort design, which evaluated the T2D incidence through the hazard ratio (HR) or relative risk (RR) or odds ratio values were included. Were included both studies that evaluated the incidence of T2D from tertiles, quartiles, quintiles, or single TyG index values. First, a meta-analysis only for studies that reported data in HR values was performed. Additionally, given the different association measurements used, the number of T2D cases, non-T2D cases, and the total number of participants were extracted from exposed and non-exposed groups when available. Then the risk ratio was calculated. A meta-analysis using the inverse variance method and the random-effects model was performed. Heterogeneity was assessed by I2 statistics and by inspecting funnel plots. RESULTS: Thirteen cohort studies with a total of 70,380 subjects, both sexes, adults, and older adults were included in the meta-analysis. Ten studies showed a significant association of the TyG index with T2D risk through HR estimative (overall HR: 2.44, 95% CI: 2.17-2.76). After estimating RR for nine studies, we also observed a significant association of the TyG index with T2D risk (RR: 3.12, 95 CI: 2.31-4.21). For all analyses, high heterogeneity was verified by I2 and visual inspection of funnel plots. CONCLUSIONS: TyG index has a positive and significant association with T2D risk, suggesting that the TyG index may become an applicable tool to identify subjects with T2D risk. However, due to the high heterogeneity observed in overall HR and RR analysis, more studies could be necessary to confirm these results.
OBJECTIVE: Our objective was to perform a systematic review and meta-analysis of cohort studies evaluating the triglyceride-glucose (TyG) index as a tool for type 2 diabetes (T2D) prediction in adults and older adults. METHODS: Studies were identified in PubMed, Cochrane, Scopus, and Lilacs. Studies with cohort design, which evaluated the T2D incidence through the hazard ratio (HR) or relative risk (RR) or odds ratio values were included. Were included both studies that evaluated the incidence of T2D from tertiles, quartiles, quintiles, or single TyG index values. First, a meta-analysis only for studies that reported data in HR values was performed. Additionally, given the different association measurements used, the number of T2D cases, non-T2D cases, and the total number of participants were extracted from exposed and non-exposed groups when available. Then the risk ratio was calculated. A meta-analysis using the inverse variance method and the random-effects model was performed. Heterogeneity was assessed by I2 statistics and by inspecting funnel plots. RESULTS: Thirteen cohort studies with a total of 70,380 subjects, both sexes, adults, and older adults were included in the meta-analysis. Ten studies showed a significant association of the TyG index with T2D risk through HR estimative (overall HR: 2.44, 95% CI: 2.17-2.76). After estimating RR for nine studies, we also observed a significant association of the TyG index with T2D risk (RR: 3.12, 95 CI: 2.31-4.21). For all analyses, high heterogeneity was verified by I2 and visual inspection of funnel plots. CONCLUSIONS:TyG index has a positive and significant association with T2D risk, suggesting that the TyG index may become an applicable tool to identify subjects with T2D risk. However, due to the high heterogeneity observed in overall HR and RR analysis, more studies could be necessary to confirm these results.
Authors: Fernando Vidal-Ostos; Omar Ramos-Lopez; Susan A Jebb; Angeliki Papadaki; Andreas F H Pfeiffer; Teodora Handjieva-Darlenska; Marie Kunešová; Ellen E Blaak; Arne Astrup; J Alfredo Martinez Journal: Nutr Metab (Lond) Date: 2022-10-19 Impact factor: 4.654
Authors: Júlia L Dos Santos; Vera L Portal; Melissa M Markoski; Alexandre S de Quadros; Ângela Bersch-Ferreira; Aline Marcadenti Journal: Eur J Clin Nutr Date: 2021-11-22 Impact factor: 4.884
Authors: Benedetta Salvatori; Tina Linder; Daniel Eppel; Micaela Morettini; Laura Burattini; Christian Göbl; Andrea Tura Journal: Cardiovasc Diabetol Date: 2022-10-18 Impact factor: 8.949