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Triglycerides/high-density lipoprotein cholesterol is a predictor similar to the triglyceride–glucose index for the diagnosis of metabolic syndrome using International Diabetes Federation criteria of insulin resistance in obese adolescents: a cross-sectional study

  • Nazlı Nur Aslan Çin ORCID logo EMAIL logo , Hülya Yardımcı ORCID logo , Nevra Koç , Seyit Ahmet Uçaktürk ORCID logo and Mehtap Akçil Ok
Published/Copyright: May 24, 2020

Abstract

Objectives

Metabolic syndrome (MS) is a fatal endocrinopathy that begins with insulin resistance (IR) and causes abdominal obesity, glucose intolerance, or systemic disorders. This study was aimed to determine the cut-off values for the triglyceride (TG)/high-density lipoprotein cholesterol (TG/HDL-C) ratio, the TG glucose (TyG) index and homeostasis model assessment (HOMA-IR) for the diagnosis of MS in obese adolescents, and to compare which of the three indexes would offer a more accurate approach to diagnosis.

Methods

The study population comprised 1,171 obese adolescents (639 females and 532 males aged 10–16 years, Body Mass Index (BMI)>=95th percentile). Indirect measures of IR screening for MS were the TG/HDL ratio, TyG index, and HOMA-IR. The cut-off values of the TG/HDL ratio, TyG index, and HOMA-IR were obtained from receiver operation characteristic (ROC) curves.

Results

HOMA-IR had a significant positive correlation with the TyG index (r=0.352, p<0.001) and TG/HDL-C (r=0.291, p<.001). The TyG index and TG/HDL-C showed a strong positive correlation (r=0.901, p<0.001). The TG/HDL-C ratio showed a larger ROC Area under Curve (AUC=0.849) than HOMA-IR index (AUC=0.689), but as a predictor similar to TyG index (AUC=0.833) when screening for MS. The cut-off values for MS were as follows: TG/HDL-C ratio>2.16 (sensitivity: 88.8%; specificity: 49.7%), TyG index>8.50 (sensitivity: 85.6%; specificity: 57.0%) and HOMA-IR>2.52 (sensitivity: 83.2%; specificity: 40.4%).

Conclusions

Both the TyG index and TG/HDL-C ratio are better markers than HOMA-IR to determine the risk of metabolic syndrome according to IDF criteria. Besides, the TyG index and TG/HDL-C ratio have similar differentiating powers to determine this risk in obese Turkish adolescents.


Corresponding author: Nazlı Nur Aslan Çin, Research Assistant, Ankara University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Fatih Cad. Tepebaşı Mah, No:197/A, 06300, Ankara, Kecioren, Turkey, E-mail:

  1. Author contributions: NNAÇ and HY designed the study. NNAÇ and MAO performed the analysis. NNAÇ, HY and MAO drafted the initial manuscript and NK and SAU revised the manuscript; NNAÇ, MAO and HY provided important advice for the calculations, reviewed and revised the manuscript making important intellectual contributions; All authors read and approved the final manuscript.

  2. Competing interests: The authors declare no conflict of interest.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

References

1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the global burden of disease study 2013. Lancet 2014;384:766–81. https://doi.org/10.1016/S0140-6736(14)60460-80.Search in Google Scholar

2. World Health Organization. Commission on ending childhood obesity interim report of the commission on ending childhood obesity. Geneva: World Health Organization; 2015. Available from: https://www.who.int/end-childhood-obesity/interim-report-for-comment/en/.Search in Google Scholar

3. Simsek E, Akpinar S, Bahcebasi T, Senses DA, Kocabay K. The prevalence of overweight and obese children aged 6-17 years in the West Black Sea region of Turkey. Int J Clin Pract 2008;62:1033–8. https://doi.org/10.1111/j.1742-1241.2007.01421.x.Search in Google Scholar

4. Lissner L, Sohlstrom A, Sundblom E, Sjoberg A. Trends in overweight and obesity in Swedish schoolchildren 1999-2005: has the epidemic reached a plateau?. Obes Rev 2010;11:553–9. https://doi.org/10.1111/j.1467-789X.2009.00696.x.10.1111/j.1467-789X.2009.00696.xSearch in Google Scholar PubMed

5. Senol V, Unalan D, Bayat M, Mazicioglu MM, Ozturk A, Kurtoglu S. Change in reference body mass index percentiles and deviation in overweight and obesity over 3 years in Turkish children and adolescents. J Pediatr Endocrinol Metab 2014;27:1121–9. https://doi.org/10.1515/jpem-2013-0467.Search in Google Scholar

6. Romualdo MC, Nobrega FJ, Escrivao MA. Insulin resistance in obese children and adolescents. J Pediatr 2014;90:600–7. https://doi.org/10.1016/j.jped.2014.03.005.Search in Google Scholar

7. Kang B, Yang Y, Lee EY, Yang HK, Kim HS, Lim SY, et al. Triglycerides/glucose index is a useful surrogate marker of insulin resistance among adolescents. Int J Obes 2017;41:789. https://doi.org/10.1038/ijo.2017.14.Search in Google Scholar

8. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112:3066–72. https://doi.org/10.1161/CIRCULATIONAHA.105.539528.Search in Google Scholar

9. Meigs JB, Wilson PW, Fox CS, Vasan RS, Nathan DM, Sullivan LM, et al. Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab 2006;91:2906–12. https://doi.org/10.1210/jc.2006-0594.Search in Google Scholar

10. Kim JW, Park SH, Kim Y, Im M, Han HS. The cutoff values of indirect indices for measuring insulin resistance for metabolic syndrome in Korean children and adolescents. Ann Pediatr Endocrinol Metab 2016;21:143. https://doi.org/10.6065/apem.2016.21.3.143.10.6065/apem.2016.21.3.143Search in Google Scholar PubMed PubMed Central

11. Sangun O, Dundar B, Kosker M, Pirgon O, Dundar N. Prevalence of metabolic syndrome in obese children and adolescents using three different criteria and evaluation of risk factors. J Clin Res Pediatr Endocrinol 2011;3:70–6. https://doi.org/10.4274/jcrpe.v3i2.15.Search in Google Scholar

12. Martin BC, Warram JH, Krolewski AS, Bergman RN, Soeldner JS, Kahn CR. Role of glucose and insulin resistance in development of type 2 diabetes mellitus: results of a 25-year follow-up study. Lancet 1992;340:925–9. https://doi.org/10.1016/0140-6736(92)92527-m.Search in Google Scholar

13. Tam CS, Xie W, Johnson WD, Cefalu WT, Redman LM, Ravussin E. Defining insulin resistance from hyperinsulinemic-euglycemic clamps. Diabetes Care 2012;35:1605–10. https://doi.org/10.2337/dc11-2339.Search in Google Scholar

14. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27:1487–95. https://doi.org/10.2337/diacare.27.6.1487.Search in Google Scholar

15. Hirschler V, Maccallini G, Sanchez M, Gonzalez Z, Molinari C. Association between triglyceride to HDL-C ratio and insulin resistance in indigenous argentinean children. Pediatr Diabetes 2015;16:606–12. https://doi.org/10.1111/pedi.12228.Search in Google Scholar

16. Quijada Z, Paoli M, Zerpa Y, Camacho N, Cichetti R, Villarroel V, et al. The triglyceride/HDL-cholesterol ratio as a marker of cardiovascular risk in obese children; association with traditional and emergent risk factors. Pediatr Diabetes 2008;9:464–71. https://doi.org/10.1111/j.1399-5448.2008.00406.x.Search in Google Scholar

17. Soutelo J, Graffigna M, Honfi M, Migliano M, Aranguren M, Proietti A, et al. Triglycerides/HDL-cholesterol ratio: in adolescents without cardiovascular risk factors. Arch Latinoam Nutr 2012;62:167–71. PMID: 23610904.Search in Google Scholar

18. Shimizu Y, Nakazato M, Sekita T, Kadota K, Yamasaki H, Takamura N, et al. Association of arterial stiffness and diabetes with triglycerides-to-HDL cholesterol ratio for Japanese men: the nagasaki islands study. Atherosclerosis 2013;228:491–5. https://doi.org/10.1016/j.atherosclerosis.2013.03.021.Search in Google Scholar

19. Wakabayashi I. Influence of age and gender on triglycerides-to-HDLcholesterol ratio (TG/HDL ratio) and its association with adiposity index. Arch Gerontol Geriatr 2012;55:729–34. https://doi.org/10.1016/j.archger.2012.07.001.Search in Google Scholar

20. Du T, Yuan G, Zhang M, Zhou X, Sun X, Yu X. Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance. Cardiovasc Diabetol 2014;13:146. https://doi.org/10.1186/s12933-014-0146-3.10.1186/s12933-014-0146-3Search in Google Scholar PubMed PubMed Central

21. Unger G, Benozzi SF, Perruzza F, Pennacchiotti GL. Triglycerides and glucose index: a useful indicator of insulin resistance. Endocrinol Nutr 2014;61:533–40. https://doi.org/10.1016/j.endonu.2014.06.009.Search in Google Scholar

22. Giannini C, Santoro N, Caprio S, Kim G, Lartaud D, Shaw M, et al. The triglyceride-to-hdl cholesterol ratio: association with insulin resistance in obese youths of different ethnic backgrounds. Diabetes Care 2011;34:1869–74. https://doi.org/10.2337/dc10-2234.10.2337/dc10-2234Search in Google Scholar PubMed PubMed Central

23. Iwani NA, Jalaludin MY, Zin RM, Fuziah MZ, Hong JY, Abqariyah Y, et al. Triglyceride to HDL-C ratio is associated with insulin resistance in overweight and obese children. Sci Rep 2017;7:40055. https://doi.org/10.1038/srep40055.Search in Google Scholar

24. Olson K, Hendricks B, Murdock D. The triglyceride to HDL ratio and its relationship to insulin resistance in pre- and postpubertal children: observation from the wausau SCHOOL project. Cholesterol 2012;2012:794252. https://doi.org/10.1155/2012/794252.Search in Google Scholar

25. Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books; 1988.Search in Google Scholar

26. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS, Wei R, et al. CDC growth charts: united states. Hyattsville, MD: National Center for Health Statistics; 2000.Search in Google Scholar

27. Zimmet P, Alberti G, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents. Lancet 2007;369:2059–61. https://doi.org/10.1016/S0140-6736(07)60958-1.Search in Google Scholar

28. Abbasi F, Reaven GM. Comparison of two methods using plasma triglyceride concentration as a surrogate estimate of insulin action in nondiabetic subjects: triglycerides× glucose versus triglyceride/high-density lipoprotein cholesterol. Metabolism 2011;60:1673–6. https://doi.org/10.1016/j.metabol.2011.04.006.Search in Google Scholar

29. Zhou M, Zhu L, Cui X, Feng L, Zhao X, He S, et al. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of insulin resistance but not of β cell function in a chinese population with different glucose tolerance status. Lipids Health Dis 2016;15:104. https://doi.org/10.1186/s12944-016-0270-z.Search in Google Scholar

30. Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res 1999;8:135–60. https://doi.org/10.1177/096228029900800204.Search in Google Scholar

31. Khan SH, Sobia F, Niazi NK, Manzoor SM, Fazal N, Ahmad F. Metabolic clustering of risk factors: evaluation of triglyceride-glucose index (TyG index) for evaluation of insulin resistance. Diabetes Metab Syndr 2018;10:74. https://doi.org/10.1186/s13098-018-0376-8.Search in Google Scholar

32. Laws A, Reaven GM. Evidence for an independent relationship between insulin resistance and fasting plasma HDL-cholesterol, triglyceride and insulin concentrations. J Intern Med 1992;231:25–30. https://doi.org/10.1111/j.1365-2796.1992.tb00494.x.Search in Google Scholar

33. Vega GL, Barlow CE, Grundy SM, Leonard D, DeFina LF. Triglyceride–to–high-density-lipoprotein-cholesterol ratio is an index of heart disease mortality and of incidence of type 2 diabetes mellitus in men. JIM 2014;62:345–9. https://doi.org/10.22088/cjim.11.1.53.10.2310/JIM.0000000000000044Search in Google Scholar PubMed

34. Shimodaira M, Niwa T, Nakajima K, Kobayashi M, Hanyu N, Nakayama T. Impact of serum triglyceride and high density lipoprotein cholesterol levels on early-phase insulin secretion in normoglycemic and prediabetic subjects. Diabetes Metab J 2014;38:294–301. https://doi.org/10.4093/dmj.2014.38.4.294.Search in Google Scholar

35. Matsuzawa Y, Shimomura I, Nakamura T, Keno Y, Kotani K, Tokunaga K. Pathophysiology and pathogenesis of visceral fat obesity. Obes Res 1995;3:187–94. 10.1002/j.1550-8528.1995.tb00462.x.10.1002/j.1550-8528.1995.tb00462.xSearch in Google Scholar PubMed

36. Bickerton AS, Roberts R, Fielding BA, Hodson L, Blaak EE, Wagenmakers AJ et al. Preferential uptake of dietary Fatty acids in adipose tissue and muscle in the postprandial period. Diabetes 2007;56:168–76. https://doi.org/10.2337/db06-0822.Search in Google Scholar

37. Shimabukuro M, Zhou YT, Levi M, Unger RH. Fatty acid-induced beta cell apoptosis: a link between obesity and diabetes. Proc Natl Acad Sci USA 1998;95:2498–502. 10.1073/pnas.95.5.2498.10.1073/pnas.95.5.2498Search in Google Scholar PubMed PubMed Central

38. Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez JA. 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 2016;86:99–105. https://doi.org/10.1016/j.ypmed.2016.01.022.Search in Google Scholar

39. Tohidi M, Baghbani-Oskouei A, Ahanchi NS, Azizi F, Hadaegh F. Fasting plasma glucose is a stronger predictor of diabetes than triglyceride–glucose index, triglycerides/high-density lipoprotein cholesterol, and homeostasis model assessment of insulin resistance: tehran lipid and glucose study. Acta Diabetol 2018;55:1067–74. 10.1007/s00592-018-1195-y.10.1007/s00592-018-1195-ySearch in Google Scholar PubMed

40. Mazidi M, Kengne AP, Katsiki N, Mikhailidis DP, Banach, M. Lipid accumulation product and triglycerides/glucose index are useful predictors of insulin resistance. J Diabetes Complicat 2018;32:266–70. https://doi.org/10.1016/j.jdiacomp.2017.10.007.Search in Google Scholar

41. Liang J, Fu J, Jiang Y, Dong G, Wang X, Wu W. TriGlycerides and high-density lipoprotein cholesterol ratio compared with homeostasis model assessment insulin resistance indexes in screening for metabolic syndrome in the Chinese obese children: a cross section study. BMC Pediatr 2015;15:138. https://doi.org/10.1186/s12887-015-0456-y.Search in Google Scholar

Received: 2019-07-08
Accepted: 2020-03-16
Published Online: 2020-05-24

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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