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Association between the triglyceride–glucose index and chronic kidney disease in adults

  • Nephrology - Original Paper
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Abstract

Background

Chronic kidney disease (CKD) is characterized as a progressive dysfunction of the kidney, and it might have a close relationship with insulin resistance. We utilized the triglyceride–glucose (TyG) index, a reliable marker of insulin resistance, to evaluate the association between the TyG index and CKD in adults from the general population.

Methods

This was a cross-sectional study obtaining data from the 2015–2018 National Health and Nutrition Examination Survey. The estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) served as kidney function indicators. We defined CKD as the existence of either low eGFR (eGFR < 60 mL/min/1.73 m2 BSA) or albuminuria (UACR > 30 mg/g). Multivariate regressions, correlated subgroup analyses, and interaction terms were performed in this study.

Results

For 4361 recruited participants, the mean TyG index was 8.60 ± 0.68, and the prevalence of CKD was 13.35%. Participants with a higher TyG index showed a higher UACR level (β = 25.10, 95% CI: 6.76, 43.44, P = 0.0074) and higher levels of CKD (OR = 1.34, 95% CI: 1.13, 1.59, P = 0.0006). The positive relationship between the TyG index and CKD became stronger and remained significant in the overweight (OR = 1.61, 95% CI: 1.18, 2.20, P = 0.0027) and obese (OR = 2.48, 95% CI: 1.95, 3.15, P < 0.0001) groups and in people with diabetes (OR = 1.94, 95% CI: 1.46, 2.56, P < 0.0001).

Conclusions

Higher TyG index was strongly associated with a higher UACR level and higher values of albuminuria and CKD, which might be useful in kidney function screening especially among people in disadvantageous socioeconomic conditions with no availability for direct measurement of kidney function. However, more well-designed studies are still needed to validate this relationship.

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Availability of data and materials

Data described in the manuscript, codebook, and analytic code will be made publicly and freely available without restriction at www.cdc.gov/nchs/nhanes/.

References

  1. Dikaiakou E, Vlachopapadopoulou EA, Paschou SA, Athanasouli F, Panagiotopoulos Ι, Kafetzi M, Fotinou A, Michalacos S (2020) Τriglycerides-glucose (TyG) index is a sensitive marker of insulin resistance in Greek children and adolescents. Endocrine 70:58–64. https://doi.org/10.1007/s12020-020-02374-6

    Article  CAS  PubMed  Google Scholar 

  2. Bikbov B, Purcell CA, Levey AS, Smith M et al (2020) Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 395:709–733. https://doi.org/10.1016/s0140-6736(20)30045-3

    Article  Google Scholar 

  3. Levey AS, Andreoli SP, DuBose T, Provenzano R, Collins AJ (2007) Chronic kidney disease: common, harmful and treatable–World Kidney Day 2007. Am J Nephrol 27:108–112. https://doi.org/10.1159/000099801

    Article  PubMed  Google Scholar 

  4. Levey AS, Andreoli SP, DuBose T, Provenzano R, Collins AJ (2007) Chronic kidney disease: common, harmful, and treatable–World Kidney Day 2007. J Am Soc Nephrol 18:374–378. https://doi.org/10.1681/asn.2006121305

    Article  CAS  PubMed  Google Scholar 

  5. Smyth LJ, Duffy S, Maxwell AP, McKnight AJ (2014) Genetic and epigenetic factors influencing chronic kidney disease. Am J Physiol Renal Physiol 307:F757-776. https://doi.org/10.1152/ajprenal.00306.2014

    Article  CAS  PubMed  Google Scholar 

  6. Neugut YD, Mohan S, Gharavi AG, Kiryluk K (2019) Cases in precision medicine: APOL1 and genetic testing in the evaluation of chronic kidney disease and potential transplant. Ann Intern Med 171:659–664. https://doi.org/10.7326/m19-1389

    Article  PubMed  PubMed Central  Google Scholar 

  7. Genovese G, Friedman DJ, Ross MD, Lecordier L, Uzureau P, Freedman BI, Bowden DW, Langefeld CD, Oleksyk TK, Uscinski Knob AL et al (2010) Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329:841–845. https://doi.org/10.1126/science.1193032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Orr SE, Bridges CC (2017) Chronic kidney disease and exposure to nephrotoxic metals. Int J Mol Sci. https://doi.org/10.3390/ijms18051039

    Article  PubMed  PubMed Central  Google Scholar 

  9. Lebovitz HE (2001) Insulin resistance: definition and consequences. Exp Clin Endocrinol Diabetes 109(Suppl 2):S135-148. https://doi.org/10.1055/s-2001-18576

    Article  CAS  PubMed  Google Scholar 

  10. Navaneethan SD, Kirwan JP, Remer EM, Schneider E, Addeman B, Arrigain S, Horwitz E, Fink JC, Lash JP, McKenzie CA et al (2021) Adiposity, physical function, and their associations with insulin resistance, inflammation, and adipokines in CKD. Am J Kidney Dis 77:44–55. https://doi.org/10.1053/j.ajkd.2020.05.028

    Article  CAS  PubMed  Google Scholar 

  11. DeFronzo RA, Alvestrand A, Smith D, Hendler R, Hendler E, Wahren J (1981) Insulin resistance in uremia. J Clin Invest 67:563–568. https://doi.org/10.1172/jci110067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Pham H, Utzschneider KM, de Boer IH (2011) Measurement of insulin resistance in chronic kidney disease. Curr Opin Nephrol Hypertens 20:640–646. https://doi.org/10.1097/MNH.0b013e32834b23c1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Siew ED, Ikizler TA (2008) Determinants of insulin resistance and its effects on protein metabolism in patients with advanced chronic kidney disease. Contrib Nephrol 161:138–144. https://doi.org/10.1159/000130659

    Article  PubMed  Google Scholar 

  14. Shinohara K, Shoji T, Emoto M, Tahara H, Koyama H, Ishimura E, Miki T, Tabata T, Nishizawa Y (2002) Insulin resistance as an independent predictor of cardiovascular mortality in patients with end-stage renal disease. J Am Soc Nephrol 13:1894–1900. https://doi.org/10.1097/01.asn.0000019900.87535.43

    Article  PubMed  Google Scholar 

  15. Singh B, Saxena A (2010) Surrogate markers of insulin resistance: A review. World J Diabetes 1:36–47. https://doi.org/10.4239/wjd.v1.i2.36

    Article  PubMed  PubMed Central  Google Scholar 

  16. Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F (2008) The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord 6:299–304. https://doi.org/10.1089/met.2008.0034

    Article  CAS  PubMed  Google Scholar 

  17. Vasques AC, Novaes FS, de Oliveira Mda S, Souza JR, Yamanaka A, Pareja JC, Tambascia MA, Saad MJ, Geloneze B (2011) TyG index performs better than HOMA in a Brazilian population: a hyperglycemic clamp validated study. Diabetes Res Clin Pract 93:e98–e100. https://doi.org/10.1016/j.diabres.2011.05.030

    Article  CAS  PubMed  Google Scholar 

  18. Lee SH, Kwon HS, Park YM, Ha HS, Jeong SH, Yang HK, Lee JH, Yim HW, Kang MI, Lee WC et al (2014) Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study. PLoS ONE 9:e90430. https://doi.org/10.1371/journal.pone.0090430

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Du T, Yuan G, Zhang M, Zhou X, Sun X, Yu X (2014) Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance. Cardiovasc Diabetol 13:146. https://doi.org/10.1186/s12933-014-0146-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Mirr M, Skrypnik D, Bogdański P, Owecki M (2021) Newly proposed insulin resistance indexes called TyG-NC and TyG-NHtR show efficacy in diagnosing the metabolic syndrome. J Endocrinol Invest 44:2831–2843. https://doi.org/10.1007/s40618-021-01608-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. da Silva A, Caldas APS, Rocha D, Bressan J (2020) 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. https://doi.org/10.1016/j.pcd.2020.09.001

    Article  PubMed  Google Scholar 

  22. Tutunchi H, Naeini F, Mobasseri M, Ostadrahimi A (2021) Triglyceride glucose (TyG) index and the progression of liver fibrosis: A cross-sectional study. Clin Nutr ESPEN 44:483–487. https://doi.org/10.1016/j.clnesp.2021.04.025

    Article  PubMed  Google Scholar 

  23. Park K, Ahn CW, Lee SB, Kang S, Nam JS, Lee BK, Kim JH, Park JS (2019) Elevated TyG index predicts progression of coronary artery calcification. Diabetes Care 42:1569–1573. https://doi.org/10.2337/dc18-1920

    Article  CAS  PubMed  Google Scholar 

  24. Chen Y, Chang Z, Zhao Y, Liu Y, Fu J, Zhang Y, Liu Y, Fan Z (2021) Association between the triglyceride–glucose index and abdominal aortic calcification in adults: A cross-sectional study. Nutr Metab Cardiovasc Dis 31:2068–2076. https://doi.org/10.1016/j.numecd.2021.04.010

    Article  CAS  PubMed  Google Scholar 

  25. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612. https://doi.org/10.7326/0003-4819-150-9-200905050-00006

    Article  PubMed  PubMed Central  Google Scholar 

  26. Sanders AP, Mazzella MJ, Malin AJ, Hair GM, Busgang SA, Saland JM, Curtin P (2019) Combined exposure to lead, cadmium, mercury, and arsenic and kidney health in adolescents age 12–19 in NHANES 2009–2014. Environ Int 131:104993. https://doi.org/10.1016/j.envint.2019.104993

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Guo J, Wu C, Zhang J, Chang X, Zhang Y, Cao Y, Zhou Z (2020) Associations of melamine and cyanuric acid exposure with markers of kidney function in adults: Results from NHANES 2003–2004. Environ Int 141:105815. https://doi.org/10.1016/j.envint.2020.105815

    Article  CAS  PubMed  Google Scholar 

  28. Webster AC, Nagler EV, Morton RL, Masson P (2017) Chronic kidney disease. Lancet 389:1238–1252. https://doi.org/10.1016/s0140-6736(16)32064-5

    Article  PubMed  Google Scholar 

  29. Chapter 1: Definition and classification of CKD. Kidney Int Suppl (2011) 2013 3:19–62. doi:https://doi.org/10.1038/kisup.2012.64.

  30. Qin Z, Zhao J, Li J, Yang Q, Geng J, Liao R, Su B (2021) Low lean mass is associated with lower urinary tract symptoms in US men from the 2005–2006 national health and nutrition examination survey dataset. Aging (Albany NY) 13:21421–21434. https://doi.org/10.18632/aging.203480

    Article  PubMed  Google Scholar 

  31. Liu N, Ma F, Feng Y, Ma X (2021) The Association between the Dietary Inflammatory Index and Thyroid Function in U.S. Adult Males. Nutrients. https://doi.org/10.3390/nu13103330

    Article  PubMed  PubMed Central  Google Scholar 

  32. Wiener RC (2015) Serum cotinine and chronic pain NHANES 2003–2004. J Drug Abuse. https://doi.org/10.21767/2471-853X.10003

    Article  PubMed  PubMed Central  Google Scholar 

  33. Egan BM, Li J, Shatat IF, Fuller JM, Sinopoli A (2014) Closing the gap in hypertension control between younger and older adults: National Health and Nutrition Examination Survey (NHANES) 1988 to 2010. Circulation 129:2052–2061. https://doi.org/10.1161/circulationaha.113.007699

    Article  PubMed  PubMed Central  Google Scholar 

  34. Johnson CL, Paulose-Ram R, Ogden CL, Carroll MD, Kruszon-Moran D, Dohrmann SM, Curtin LR (2013) National health and nutrition examination survey: analytic guidelines, 1999–2010. Vital Health Stat 2:1–24

    Google Scholar 

  35. Wang L, Cong HL, Zhang JX, Hu YC, Wei A, Zhang YY, Yang H, Ren LB, Qi W, Li WY et al (2020) Triglyceride–glucose index predicts adverse cardiovascular events in patients with diabetes and acute coronary syndrome. Cardiovasc Diabetol 19:80. https://doi.org/10.1186/s12933-020-01054-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhang K, Chen Y, Liu L, Lu M, Cheng J, Gao F, Wang N, Shen Z, Lu Y (2017) The Triglycerides and glucose index rather than HOMA-IR is more associated with Hypogonadism in Chinese men. Sci Rep 7:15874. https://doi.org/10.1038/s41598-017-16108-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Brito ADM, Hermsdorff HHM, Filgueiras MS, Suhett LG, Vieira-Ribeiro SA, Franceschini S, Novaes JF (2021) Predictive capacity of triglyceride–glucose (TyG) index for insulin resistance and cardiometabolic risk in children and adolescents: a systematic review. Crit Rev Food Sci Nutr 61:2783–2792. https://doi.org/10.1080/10408398.2020.1788501

    Article  CAS  PubMed  Google Scholar 

  38. Sánchez-García A, Rodríguez-Gutiérrez R, Mancillas-Adame L, González-Nava V, Díaz González-Colmenero A, Solis RC, Álvarez-Villalobos NA, González-González JG (2020) Diagnostic accuracy of the triglyceride and glucose index for insulin resistance: a systematic review. Int J Endocrinol 2020:4678526. https://doi.org/10.1155/2020/4678526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Liu Y, Wu M, Xu J, Sha D, Xu B, Kang L (2020) Association between Triglyceride and glycose (TyG) index and subclinical myocardial injury. Nutr Metab Cardiovasc Dis 30:2072–2076. https://doi.org/10.1016/j.numecd.2020.06.019

    Article  CAS  PubMed  Google Scholar 

  40. Fritz J, Brozek W, Concin H, Nagel G, Kerschbaum J, Lhotta K, Ulmer H, Zitt E (2021) The triglyceride–glucose index and obesity-related risk of end-stage kidney disease in Austrian Adults. JAMA Netw Open 4:e212612. https://doi.org/10.1001/jamanetworkopen.2021.2612

    Article  PubMed  PubMed Central  Google Scholar 

  41. Lv L, Zhou Y, Chen X, Gong L, Wu J, Luo W, Shen Y, Han S, Hu J, Wang Y et al (2021) Relationship between the TyG index and diabetic kidney disease in patients with Type-2 diabetes mellitus. Diabetes Metab Syndr Obes 14:3299–3306. https://doi.org/10.2147/dmso.s318255

    Article  PubMed  PubMed Central  Google Scholar 

  42. Spoto B, Pisano A, Zoccali C (2016) Insulin resistance in chronic kidney disease: a systematic review. Am J Physiol Renal Physiol 311:F1087-f1108. https://doi.org/10.1152/ajprenal.00340.2016

    Article  CAS  PubMed  Google Scholar 

  43. Bergman RN, Ider YZ, Bowden CR, Cobelli C (1979) Quantitative estimation of insulin sensitivity. Am J Physiol 236:E667-677. https://doi.org/10.1152/ajpendo.1979.236.6.E667

    Article  CAS  PubMed  Google Scholar 

  44. Kawagishi T, Nishizawa Y, Konishi T, Kawasaki K, Emoto M, Shoji T, Tabata T, Inoue T, Morii H (1995) High-resolution B-mode ultrasonography in evaluation of atherosclerosis in uremia. Kidney Int 48:820–826. https://doi.org/10.1038/ki.1995.356

    Article  CAS  PubMed  Google Scholar 

  45. Qin Y, Tang H, Yan G, Wang D, Qiao Y, Luo E, Hou J, Tang C (2020) A High Triglyceride–glucose index is associated with contrast-induced acute kidney injury in Chinese patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne) 11:522883. https://doi.org/10.3389/fendo.2020.522883

    Article  PubMed  Google Scholar 

  46. Thomas SS, Dong Y, Zhang L, Mitch WE (2013) Signal regulatory protein-α interacts with the insulin receptor contributing to muscle wasting in chronic kidney disease. Kidney Int 84:308–316. https://doi.org/10.1038/ki.2013.97

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bailey JL, Zheng B, Hu Z, Price SR, Mitch WE (2006) Chronic kidney disease causes defects in signaling through the insulin receptor substrate/phosphatidylinositol 3-kinase/Akt pathway: implications for muscle atrophy. J Am Soc Nephrol 17:1388–1394. https://doi.org/10.1681/asn.2004100842

    Article  CAS  PubMed  Google Scholar 

  48. Kawazoe Y, Naka T, Fujimoto M, Kohzaki H, Morita Y, Narazaki M, Okumura K, Saitoh H, Nakagawa R, Uchiyama Y et al (2001) Signal transducer and activator of transcription (STAT)-induced STAT inhibitor 1 (SSI-1)/suppressor of cytokine signaling 1 (SOCS1) inhibits insulin signal transduction pathway through modulating insulin receptor substrate 1 (IRS-1) phosphorylation. J Exp Med 193:263–269. https://doi.org/10.1084/jem.193.2.263

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Okumura F, Matsuzaki M, Nakatsukasa K, Kamura T (2012) The role of elongin BC-containing ubiquitin ligases. Front Oncol 2:10. https://doi.org/10.3389/fonc.2012.00010

    Article  PubMed  PubMed Central  Google Scholar 

  50. Pereira BJ, Sundaram S, Snodgrass B, Hogan P, King AJ (1996) Plasma lipopolysaccharide binding protein and bactericidal/permeability increasing factor in CRF and HD patients. J Am Soc Nephrol 7:479–487. https://doi.org/10.1681/asn.v73479

    Article  CAS  PubMed  Google Scholar 

  51. Ndisang JF, Vannacci A, Rastogi S (2017) Insulin resistance, Type 1 and Type 2 diabetes, and related complications 2017. J Diabetes Res 2017:1478294. https://doi.org/10.1155/2017/1478294

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Gu S, Wang A, Ning G, Zhang L, Mu Y (2020) Insulin resistance is associated with urinary albumin-creatinine ratio in normal weight individuals with hypertension and diabetes: The REACTION study. J Diabetes 12:406–416. https://doi.org/10.1111/1753-0407.13010

    Article  CAS  PubMed  Google Scholar 

  53. Hill MA, Yang Y, Zhang L, Sun Z, Jia G, Parrish AR, Sowers JR (2021) Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism 119:154766. https://doi.org/10.1016/j.metabol.2021.154766

    Article  CAS  PubMed  Google Scholar 

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Conceptualization: NL and JT. Methodology: NL and CL. Formal analysis and investigation: NL, CL, JT and ZQ. Writing—original draft preparation: NL, CL and ZQ. Writing—review and editing: JT. Funding acquisition: none. Resources: NL. Supervision: JT.

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Correspondence to Jiaxing Tan.

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All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (National Center for Health Statistics (NCHS) at the U.S. Centers for Disease Control and Prevention (CDC)) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all individual participants included in the study.

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Liu, N., Liu, C., Qu, Z. et al. Association between the triglyceride–glucose index and chronic kidney disease in adults. Int Urol Nephrol 55, 1279–1289 (2023). https://doi.org/10.1007/s11255-022-03433-9

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