Skip to main content

Advertisement

SpringerLink
Log in

The association between triglyceride-glucose index and the incidence of type 2 diabetes mellitus—a systematic review and dose–response meta-analysis of cohort studies

  • Meta- Analysis
  • Published:
Endocrine Aims and scope Submit manuscript

Abstarct

Aims

We aimed to assess the dose–response relationship between triglyceride–glucose (TyG) index and the incidence of type 2 diabetes mellitus (T2DM).

Methods

We performed a comprehensive systematic literature search using PubMed, Scopus, and Embase for records published from inception until 9 February 2021. The effect estimates were reported as relative risks (RRs).

Results

270,229 subjects from 14 studies were included in this systematic review and meta-analysis. The pooled incidence of T2DM was 9%. Meta-regression analysis indicates that baseline age (coefficient: 0.67, p = 0.026), drinking (coefficient: 0.03, p = 0.035), and HDL (coefficient: −0.89, p = 0.035) affected the incidence of T2DM in future. High TyG index was associated with increased incidence of T2DM in pooled unadjusted (RR 4.68 [3.01, 7.29], p < 0.001; I2: 96.6%) and adjusted model (adjusted RR 3.54 [2.75, 4.54], p < 0.001; I2: 83.7%). Dose–response meta-analysis for the adjusted RR showed that the linear association analysis was not significant per 0.1 increase in TyG index (RR 1.01 [0.99, 1.03], p = 0.223). There is a non-linear trend (p < 0.001) for the association between TyG index and incidence of T2DM. The dose–response curve became increasingly steeper at TyG index above 8.6.

Conclusions

TyG index was associated with the incidence of T2DM in a non-linear fashion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

Associated data are available upon reasonable request.

References

  1. Internation Diabetes Federation (2019) International Diabetes Federation; Diabetes Atlas 9th edition (Internation Diabetes Federation, Brussels 2019)

  2. P. Chamroonkiadtikun, T. Ananchaisarp, W. Wanichanon, The triglyceride-glucose index, a predictor of type 2 diabetes development: a retrospective cohort study. Prim. Care Diabetes 14, 161–167 (2020). https://doi.org/10.1016/j.pcd.2019.08.004

    Article  PubMed  Google Scholar 

  3. B. Park, H.S. Lee, Y.J. Lee, Triglyceride glucose (TyG) index as a predictor of incident type 2 diabetes among nonobese adults: a 12-year longitudinal study of the Korean Genome and Epidemiology Study cohort. Transl. Res. 228, 42–51 (2021). https://doi.org/10.1016/j.trsl.2020.08.003

    Article  CAS  PubMed  Google Scholar 

  4. E. Bonora, G. Formentini, F. Calcaterra et al. HOMA-estimated insulin resistance is an independent predictor of cardiovascular disease in type 2 diabetic subjects: prospective data from the Verona Diabetes Complications Study. Diabetes Care 25, 1135–1141 (2002). https://doi.org/10.2337/diacare.25.7.1135

    Article  PubMed  Google Scholar 

  5. C.S. Tam, W. Xie, W.D. Johnson et al. Defining insulin resistance from hyperinsulinemic-euglycemic clamps. Diabetes Care 35, 1605 LP–1601610 (2012). https://doi.org/10.2337/dc11-2339

    Article  CAS  Google Scholar 

  6. A. Sánchez-García, R. Rodríguez-Gutiérrez, L. Mancillas-Adame et al. Diagnostic accuracy of the triglyceride and glucose index for insulin resistance: a systematic review. Int. J. Endocrinol. 2020, 1–7 (2020). https://doi.org/10.1155/2020/4678526

    Article  CAS  Google Scholar 

  7. K. Park, C.W. Ahn, S.B. Lee et al. Elevated TyG index predicts progression of coronary artery calcification. Diabetes Care 42, 1569–1573 (2019). https://doi.org/10.2337/dc18-1920

    Article  CAS  PubMed  Google Scholar 

  8. A. da Silva, A.P.S. Caldas, D.M.U.P. Rocha, J. Bressan, Triglyceride-glucose index predicts independently type 2 diabetes mellitus risk: a systematic review and meta-analysis of cohort studies. Prim. Care Diabetes 14, 584–593 (2020). https://doi.org/10.1016/j.pcd.2020.09.001

    Article  PubMed  Google Scholar 

  9. C. Chen, L. Liu, K. Lo et al. Association between triglyceride glucose index and risk of new-onset diabetes among chinese adults: findings from the China Health and Retirement Longitudinal Study. Front. Cardiovasc. Med. 7, 1–8 (2020). https://doi.org/10.3389/fcvm.2020.610322

    Article  CAS  Google Scholar 

  10. M. Janghorbani, S.Z. Almasi, M. Amini, The product of triglycerides and glucose in comparison with fasting plasma glucose did not improve diabetes prediction. Acta Diabetol. 52, 781–788 (2015). https://doi.org/10.1007/s00592-014-0709-5

    Article  CAS  PubMed  Google Scholar 

  11. D.Y. Lee, E.S. Lee, J.H. Kim et al. Predictive value of triglyceride glucose index for the risk of incident diabetes: A 4-year retrospective longitudinal study. PLoS ONE 11, 1–14 (2016). https://doi.org/10.1371/journal.pone.0163465

    Article  CAS  Google Scholar 

  12. J.W. Lee, N.K. Lim, H.Y. Park, The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans. BMC Endocr. Disord. 18, 1–10 (2018). https://doi.org/10.1186/s12902-018-0259-x

    Article  CAS  Google Scholar 

  13. S.H. Lee, H.S. Kwon, Y.M. Park et al. Predicting the development of diabetes using the product of triglycerides and glucose: The chungju metabolic disease cohort (CMC) study. PLoS ONE 9 (2014). https://doi.org/10.1371/journal.pone.0090430

  14. X. Li, G. Li, T. Cheng et al. Association between triglyceride-glucose index and risk of incident diabetes: a secondary analysis based on a Chinese cohort study: TyG index and incident diabetes. Lipids Health Dis. 19, 1–11 (2020). https://doi.org/10.1186/s12944-020-01403-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. E.Q. Liu, Y.P. Weng, A.M. Zhou, C.L. Zeng, Association between triglyceride-glucose index and type 2 diabetes mellitus in the Japanese population: a secondary analysis of a retrospective cohort study. Biomed. Res. Int. (2020). https://doi.org/10.1155/2020/2947067

  16. S. Low, K.C.J. Khoo, B. Irwan et al. The role of triglyceride glucose index in development of Type 2 diabetes mellitus. Diabetes Res. Clin. Pract. 143, 43–49 (2018). https://doi.org/10.1016/j.diabres.2018.06.006

    Article  CAS  PubMed  Google Scholar 

  17. D. Navarro-González, L. Sánchez-Íñigo, J. Pastrana-Delgado et al. Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort. Prev. Med. 86, 99–105 (2016). https://doi.org/10.1016/j.ypmed.2016.01.022

    Article  PubMed  Google Scholar 

  18. B. Wang, M. Zhang, Y. Liu et al. Utility of three novel insulin resistance-related lipid indices for predicting type 2 diabetes mellitus among people with normal fasting glucose in rural China. J. Diabetes 10, 641–652 (2018). https://doi.org/10.1111/1753-0407.12642

    Article  CAS  PubMed  Google Scholar 

  19. Z. Wang, L. Zhao, S. He. Triglyceride–glucose index as predictor for future type 2 diabetes mellitus in a Chinese population in southwest China: a 15-year prospective study. Endocrine (2021). https://doi.org/10.1007/s12020-020-02589-7

  20. M. Zhang, B. Wang, Y. Liu et al. Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study. Cardiovasc. Diabetol. 16, 1–11 (2017). https://doi.org/10.1186/s12933-017-0514-x

    Article  CAS  Google Scholar 

  21. S.-H. Lee, H.-S. Kim, Y.-M. Park et al. HDL-cholesterol, its variability, and the risk of diabetes: a nationwide population-based study. J. Clin. Endocrinol. Metab. 104, 5633–5641 (2019). https://doi.org/10.1210/jc.2019-01080

    Article  PubMed  Google Scholar 

  22. P.W.F. Wilson, J.B. Meigs, L. Sullivan et al. Prediction of incident diabetes mellitus in middle-aged adults: The framingham offspring study. Arch. Intern. Med. 167, 1068–1074 (2007). https://doi.org/10.1001/archinte.167.10.1068

    Article  PubMed  Google Scholar 

  23. A.L. Siebel, S.E. Heywood, B.A. Kingwell, HDL and glucose metabolism: Current evidence and therapeutic potential. Front. Pharmacol. 6 (2015). https://doi.org/10.3389/fphar.2015.00258

  24. B.G. Drew, K.A. Rye, S.J. Duffy et al. The emerging role of HDL in glucose metabolism. Nat. Rev. Endocrinol. 8, 237–245 (2012). https://doi.org/10.1038/nrendo.2011.235

    Article  CAS  PubMed  Google Scholar 

  25. X. He, C.M. Rebholz, N. Daya et al. Alcohol consumption and incident diabetes: the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia 62, 770–778 (2019). https://doi.org/10.1007/s00125-019-4833-1

    Article  PubMed  PubMed Central  Google Scholar 

  26. S. Carlsson, N. Hammar, V. Grill, J. Kaprio, Alcohol consumption and the incidence of type 2 diabetes: a 20-year follow-up of the Finnish Twin Cohort Study. Diabetes Care 26, 2785–2790 (2003). https://doi.org/10.2337/diacare.26.10.2785

    Article  PubMed  Google Scholar 

  27. M. Snel, J.T. Jonker, J. Schoones et al. Ectopic fat and insulin resistance: pathophysiology and effect of diet and lifestyle interventions. Int J. Endocrinol. 2012, 983814 (2012). https://doi.org/10.1155/2012/983814

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. D. Ferrara, F. Montecucco, F. Dallegri, F. Carbone, Impact of different ectopic fat depots on cardiovascular and metabolic diseases. J. Cell Physiol. 234, 21630–21641 (2019). https://doi.org/10.1002/jcp.28821

    Article  CAS  PubMed  Google Scholar 

  29. V.T. Samuel, G.I. Shulman, The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J. Clin. Investig. 126, 12–22 (2016). https://doi.org/10.1172/JCI77812

    Article  PubMed  PubMed Central  Google Scholar 

  30. K. Morino, K.F. Petersen, G.I. Shulman, Molecular mechanisms of insulin resistance in humans and their potential links with mitochondrial dysfunction. Diabetes 55(Suppl 2), S9–S15 (2006). https://doi.org/10.2337/db06-S002

    Article  CAS  PubMed  Google Scholar 

  31. E.-Q. Liu, Y.-P. Weng, A.-M. Zhou, C.-L. Zeng, Association between triglyceride-glucose index and type 2 diabetes mellitus in the Japanese population: a secondary analysis of a retrospective cohort study. Biomed. Res. Int. 2020, 2947067 (2020). https://doi.org/10.1155/2020/2947067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. B. Gustafson, S. Hedjazifar, S. Gogg et al. Insulin resistance and impaired adipogenesis. Trends Endocrinol. Metab. 26, 193–200 (2015). https://doi.org/10.1016/j.tem.2015.01.006

    Article  CAS  PubMed  Google Scholar 

  33. A. Katsuki, Y. Sumida, E.C. Gabazza et al. Homeostasis model assessment is a reliable indicator of insulin resistance during follow-up of patients with type 2 diabetes. Diabetes Care 24, 362 LP–362365 (2001). https://doi.org/10.2337/diacare.24.2.362

    Article  Google Scholar 

  34. Y. Wang, P. Fedorcsák, P.O. Dale et al. Simplification of continuous infusion of glucose with model assessment in the evaluation of insulin resistance in women with PCOS. Gynecol. Endocrinol. 15, 192–197 (2001). https://doi.org/10.1080/gye.15.3.192.197

    Article  CAS  PubMed  Google Scholar 

  35. L.U. Monzillo, O. Hamdy, Evaluation of insulin sensitivity in clinical practice and in research settings. Nutr. Rev. 61, 397–412 (2003). https://doi.org/10.1301/nr.2003.dec.397-412

    Article  PubMed  Google Scholar 

  36. J.C. Locateli, W.A. Lopes, C.F. Simões et al. Triglyceride/glucose index is a reliable alternative marker for insulin resistance in South American overweight and obese children and adolescents. J. Pediatr. Endocrinol. Metab. 32, 1163–1170 (2019). https://doi.org/10.1515/jpem-2019-0037

    Article  CAS  PubMed  Google Scholar 

  37. E. Dikaiakou, E.A. Vlachopapadopoulou, S.A. Paschou et al. Τriglycerides-glucose (TyG) index is a sensitive marker of insulin resistance in Greek children and adolescents. Endocrine 70, 58–64 (2020). https://doi.org/10.1007/s12020-020-02374-6

    Article  CAS  PubMed  Google Scholar 

  38. H. Van Minh, H.A. Tien, C.T. Sinh et al. Assessment of preferred methods to measure insulin resistance in Asian patients with hypertension. J. Clin. Hypertens. (2021). https://doi.org/10.1111/jch.14155

  39. V. Calcaterra, C. Montalbano, A. de Silvestri et al. Triglyceride Glucose Index as a Surrogate Measure of Insulin Sensitivity in a Caucasian Pediatric Population. J. Clin. Res. Pediatr. Endocrinol. (2019). https://doi.org/10.4274/jcrpe.galenos.2019.2019.0024

Download references

Author contributions

R.P.: conceptualization, methodology, data curation, formal analysis, investigation, validation, writing—original draft, writing—review & editing. I.H.: data curation, investigation, writing - original draft, writing—review & editing. Irvan: data curation, investigation, writing—original draft. M.A.L.: data curation, investigation, writing—original draft. R.V.: investigation, validation, writing—review and editing.

Author information

Authors and Affiliations

  1. Faculty of Medicine, Universitas Pelita Harapan, Tangerang, Indonesia

    Raymond Pranata, Ian Huang,  Irvan, Michael Anthonius Lim & Rachel Vania

  2. Department of Internal Medicine, Faculty of Medicine, Universitas Padjadjaran, Hasan Sadikin General Hospital, Bandung, Indonesia

    Ian Huang

Authors
  1. Raymond Pranata
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ian Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Irvan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael Anthonius Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rachel Vania
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Raymond Pranata.

Ethics declarations

Conflict of interest

The authors declare no competing interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pranata, R., Huang, I., Irvan et al. The association between triglyceride-glucose index and the incidence of type 2 diabetes mellitus—a systematic review and dose–response meta-analysis of cohort studies. Endocrine 74, 254–262 (2021). https://doi.org/10.1007/s12020-021-02780-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12020-021-02780-4

Keywords

Search

Navigation