The Association Between Triglyceride-Glucose Index and Its Combination with Obesity Indicators and Lower Extremity Peripheral Artery Disease in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study

Overview

Journal Diabetes Metab Syndr Obes

Publisher Dove Medical Press

Specialty Endocrinology

Date 2024 Jul 2

PMID 38953012

Authors

Ying Miao

Yu Wang

Yi Wang

Pijun Yan

Zhuang Chen

Qin Wan

Affiliations

Soon will be listed here.

Abstract

Background: Lower extremity peripheral artery disease (LEAD) is a significant chronic complication of type 2 diabetes mellitus (T2DM) that significantly contributes to disability and mortality. The subtle presentation of LEAD symptoms often leads to underrecognition and misdiagnosis. Therefore, identifying simple and effective evaluation indicators is essential for the early detection and management of LEAD. Insulin resistance is closely associated with diabetes and its complications. However, the specific relationship between insulin resistance-measured by the triglyceride-glucose (TyG) index-and obesity indicators in relation to LEAD remains unclear.

Objective: This study aims to investigate the association between the TyG index and its combination with obesity indicators in participants with T2DM and LEAD.

Methods: We performed a univariate analysis on 3176 T2DM patients to identify risk factors for LEAD. Patients were then divided into quartiles based on the TyG index combined with various obesity indicators. The chi-square test was used to compare the prevalence of LEAD across these groups. Logistic regression analysis was conducted to examine the association between the TyG index, in combination with different obesity indicators, and the occurrence of LEAD. Finally, we assessed the predictive ability of the TyG index combined with obesity indicators for LEAD by comparing the area under the ROC curve (AUC).

Results: The study included 3176 T2DM patients (1691 males and 1485 females) with a mean age of 56.16±10.60 years. Among them, 106 individuals had LEAD. The prevalence of LEAD varied significantly across quartiles of the TyG index, TyG-WC, and TyG-WHR (Q4 > Q3 > Q2 > Q1; P < 0.05). Multiple logistic regression analysis showed that the TyG index, TyG-WC, and TyG-WHR were positively associated with the risk of LEAD in T2DM patients. ROC curve analysis identified the best cutoff values for predicting LEAD: 9.8059 for the TyG index (sensitivity: 49.1%, specificity: 67.9%, AUC: 0.583), 808.8397 for TyG-WC (sensitivity: 70.8%, specificity: 47.8%, AUC: 0.603), and 8.8543 for TyG-WHR (sensitivity: 75.5%, specificity: 44.6%, AUC: 0.607).

Conclusion: In T2DM patients, the TyG index, TyG-WHR, and TyG-WC are positively associated with the occurrence of LEAD. TyG-WHR and TyG-WC exhibit a stronger correlation with LEAD compared to the TyG index alone, indicating their superior diagnostic value.

Citing Articles

The fibrosis-4 index and its association with carotid atherosclerosis in type 2 diabetes: a cross-sectional study in China.

Miao Y, Wang Y, Wan Q, Tong N BMC Cardiovasc Disord. 2025; 25(1):35.

PMID: 39833683 PMC: 11748503. DOI: 10.1186/s12872-025-04491-4.

References

Aday A, Matsushita K . Epidemiology of Peripheral Artery Disease and Polyvascular Disease. Circ Res. 2021; 128(12):1818-1832. PMC: 8202714. DOI: 10.1161/CIRCRESAHA.121.318535. View

Gao J, Hao Q, Gao M, Zhang K, Li X, Wang J . Triglyceride-glucose index in the development of peripheral artery disease: findings from the Atherosclerosis Risk in Communities (ARIC) Study. Cardiovasc Diabetol. 2021; 20(1):126. PMC: 8223290. DOI: 10.1186/s12933-021-01319-1. View

Lim J, Kim J, Koo S, Kwon G . Comparison of triglyceride glucose index, and related parameters to predict insulin resistance in Korean adults: An analysis of the 2007-2010 Korean National Health and Nutrition Examination Survey. PLoS One. 2019; 14(3):e0212963. PMC: 6405083. DOI: 10.1371/journal.pone.0212963. View

Love K, Liu Z . DPP4 Activity, Hyperinsulinemia, and Atherosclerosis. J Clin Endocrinol Metab. 2021; 106(6):1553-1565. PMC: 8118363. DOI: 10.1210/clinem/dgab078. View

Rosengren A . Obesity and cardiovascular health: the size of the problem. Eur Heart J. 2021; 42(34):3404-3406. PMC: 8423455. DOI: 10.1093/eurheartj/ehab518. View

Hill M, Yang Y, Zhang L, Sun Z, Jia G, Parrish A . Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism. 2021; 119:154766. DOI: 10.1016/j.metabol.2021.154766. View

Barnes J, Eid M, Creager M, Goodney P . Epidemiology and Risk of Amputation in Patients With Diabetes Mellitus and Peripheral Artery Disease. Arterioscler Thromb Vasc Biol. 2020; 40(8):1808-1817. PMC: 7377955. DOI: 10.1161/ATVBAHA.120.314595. View

Liu Y, Chang L, Wu M, Xu B, Kang L . Triglyceride Glucose Index Was Associated With the Risk of Peripheral Artery Disease. Angiology. 2022; 73(7):655-659. DOI: 10.1177/00033197211070644. View

Iacobellis G . Epicardial fat links obesity to cardiovascular diseases. Prog Cardiovasc Dis. 2023; 78:27-33. DOI: 10.1016/j.pcad.2023.04.006. View

10.

Alnima T, Meijer R, Spronk H, Warle M, ten Cate H . Diabetes- versus smoking-related thrombo-inflammation in peripheral artery disease. Cardiovasc Diabetol. 2023; 22(1):257. PMC: 10514957. DOI: 10.1186/s12933-023-01990-6. View

11.

Nogueira M, Braga R, Manios Y, Androutsos O, Molnar D, Polito A . New indices in predicting cardiometabolic risk and its relation to endothelial dysfunction in adolescents: The HELENA study. Nutr Metab Cardiovasc Dis. 2023; 33(5):1037-1048. DOI: 10.1016/j.numecd.2023.01.015. View

12.

Yang W, Jiang W, Guo S . Regulation of Macronutrients in Insulin Resistance and Glucose Homeostasis during Type 2 Diabetes Mellitus. Nutrients. 2023; 15(21). PMC: 10647592. DOI: 10.3390/nu15214671. View

13.

. 2. Classification and Diagnosis of Diabetes: . Diabetes Care. 2019; 43(Suppl 1):S14-S31. DOI: 10.2337/dc20-S002. View

14.

Cardoso C, Melo J, Santos T, Leite N, Salles G . Traditional and non-traditional risk factors for peripheral artery disease development/progression in patients with type 2 diabetes: the Rio de Janeiro type 2 diabetes cohort study. Cardiovasc Diabetol. 2021; 20(1):54. PMC: 7912919. DOI: 10.1186/s12933-021-01249-y. View

15.

Dang K, Wang X, Hu J, Zhang Y, Cheng L, Qi X . The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003-2018. Cardiovasc Diabetol. 2024; 23(1):8. PMC: 10771672. DOI: 10.1186/s12933-023-02115-9. View

16.

Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N . Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9 edition. Diabetes Res Clin Pract. 2019; 157:107843. DOI: 10.1016/j.diabres.2019.107843. View

17.

Pizzimenti M, Meyer A, Charles A, Giannini M, Chakfe N, Lejay A . Sarcopenia and peripheral arterial disease: a systematic review. J Cachexia Sarcopenia Muscle. 2020; 11(4):866-886. PMC: 7432591. DOI: 10.1002/jcsm.12587. View

18.

Wang X, Shen Y, Shang M, Liu X, Munn L . Endothelial mechanobiology in atherosclerosis. Cardiovasc Res. 2023; 119(8):1656-1675. PMC: 10325702. DOI: 10.1093/cvr/cvad076. View

19.

Hussain M, Al-Omran M, Salata K, Sivaswamy A, Forbes T, Sattar N . Population-based secular trends in lower-extremity amputation for diabetes and peripheral artery disease. CMAJ. 2019; 191(35):E955-E961. PMC: 6721859. DOI: 10.1503/cmaj.190134. View

20.

Sonaglioni A, Barlocci E, Adda G, Esposito V, Ferrulli A, Nicolosi G . The impact of short-term hyperglycemia and obesity on biventricular and biatrial myocardial function assessed by speckle tracking echocardiography in a population of women with gestational diabetes mellitus. Nutr Metab Cardiovasc Dis. 2021; 32(2):456-468. DOI: 10.1016/j.numecd.2021.10.011. View