RECALIBRATING INSULIN RESISTANCE DETECTION: INTEGRATIVE ANALYSIS OF TYG INDEX VS. GLYCATED ALBUMIN IN A HIGH-RISK POPULATION

Nitin Wathore, Saride Naveen Kumar, Urmila Umasekar, Panneerselvam Periasamy, Arbind Kumar Choudhary

Abstract


Background: Insulin resistance (IR) is an early driver of type 2 diabetes, fatty liver disease, and cardiovascular risk, yet reliable and affordable screening tools are limited in many low-resource settings. The triglyceride–glucose (TyG) index has emerged as a practical surrogate, while glycated albumin (GA) remains less well studied in this context. This study evaluated the diagnostic accuracy of TyG and GA against HOMA-IR in South Asian adults, while exploring phenotype-specific thresholds to improve early detection.

Materials & Methods: We conducted a cross-sectional study of 349 South Asian adults without known diabetes. Participants underwent anthropometric assessment and fasting laboratory testing, including glucose, triglycerides, insulin, GA, HbA1c, hs-CRP, adiponectin, and liver enzymes. HOMA-IR > 2.5 was used as the reference standard. Diagnostic accuracy was assessed using correlation analyses, multivariable regression, and ROC curves, with subgroup evaluation by BMI, sex, and inflammatory status.

Results: TyG showed stronger correlation with HOMA-IR than GA and achieved good diagnostic accuracy (AUC 0.72 overall, 0.80 in obesity). GA failed to reach statistical significance. TyG retained independent predictive value alongside hs-CRP, adiponectin, and liver enzymes. Stratified thresholds (≥ 8.95 in obesity, ≥ 9.00 in males, ≥ 9.10 with high hs-CRP) improved performance.

Conclusion: TyG is an accessible and cost-effective tool for detecting insulin resistance in South Asians, while GA lacks discriminatory utility. Tailored cut-offs may enhance precision screening.


Keywords


Adiponectin; Diagnostic Thresholds; Glycated Albumin; HOMA-IR; Inflammatory Biomarkers; Insulin Resistance; South Asia; TyG Index.

Full Text:

PDF

References


Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med. 2011;9:48. https://doi.org/10.1186/1741-7015-9-48

Rochlani Y, Pothineni NV, Kovelamudi S, Mehta JL. Metabolic syndrome: pathophysiology, management, and modulation by natural compounds. Ther Adv Cardiovasc Dis. 2017;11(8):215–25. https://doi.org/10.1177/1753944717711379

Ramdas Nayak VK, Satheesh P, Shenoy MT, Kalra S. Triglyceride glucose (TyG) index: a surrogate biomarker of insulin resistance. J Pak Med Assoc. 2022;72(5):986–8. https://doi.org/10.47391/JPMA.22-63

Son DH, Lee HS, Lee YJ, Lee JH, Han JH. Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome. Nutr Metab Cardiovasc Dis. 2022;32(3):596–604. https://doi.org/10.1016/j.numecd.2021.11.017 PMID: 35090800

Sharma K, Poudyal S, Subba HK, Khatiwada S. Metabolic syndrome and lifestyle factors among diabetes patients attending in a teaching hospital, Chitwan. PLoS One. 2023;18(5):e0286139. https://doi.org/10.1371/journal.pone.0286139

Lee SH, Kwon HS, Park YM, Ha HS, Jeong SH, Yang HK, et al. Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study. PLoS One. 2014;9(2):e90430. https://doi.org/10.1371/journal.pone.0090430

Kurniawan LB. Triglyceride-glucose index as a biomarker of insulin resistance, diabetes mellitus, metabolic syndrome, and cardiovascular disease: a review. EJIFCC. 2024;35:44–51. Available from: https://www.ifcc.org/ejifcc/volumes/vol-35-no-1/ (ifcc.org in Bing)

Li M, Chi X, Wang Y, Setrerrahmane S, Xie W, Xu H. Trends in insulin resistance: insights into mechanisms and therapeutic strategy. Signal Transduct Target Ther. 2022;7:216. https://doi.org/10.1038/s41392-022-01073-0

Roberts CK, Hevener AL, Barnard RJ. Metabolic syndrome and insulin resistance: underlying causes and modification by exercise training. Compr Physiol. 2013;3(1):1–58. https://doi.org/10.1002/cphy.c110062 PMID: 23720280

Nabipoorashrafi SA, Seyedi SA, Rabizadeh S, Ebrahimi M, Ranjbar SA, Reyhan SK, et al. The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: a systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2022;32(12):2677–88. https://doi.org/10.1016/j.numecd.2022.07.024

Yu X, Wang L, Zhang W, Ming J, Jia A, Xu S, et al. Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: a nationwide study. J Diabetes Investig. 2019;10(4):1050–8. https://doi.org/10.1111/jdi.12975

Nevárez-Sida A, Guerrero-Romero F. The triglycerides and glucose index: a cost-effectiveness analysis compared with the homeostatic model assessment for insulin resistance. Value Health Reg Issues. 2023;37:49–52. https://doi.org/10.1016/j.vhri.2023.01.002

Wan H, Cao H, Ning P. Superiority of the triglyceride glucose index over the homeostasis model in predicting metabolic syndrome based on NHANES data analysis. Sci Rep. 2024;14:15499. https://doi.org/10.1038/s41598-024-52765-9

Ambroselli D, Mancini A, Turco I. New advances in metabolic syndrome, from prevention to treatment: the role of diet and food. Nutrients. 2023;15(3):640. https://doi.org/10.3390/nu15030640

Kang SW, Kim SK, Kim YS, Park MS. Risk prediction of the metabolic syndrome using TyG Index and SNPs: a 10-year longitudinal prospective cohort study. Mol Cell Biochem. 2023;478:39–45. https://doi.org/10.1007/s11010-022-04494-1

Couto AN, Pohl HH, Bauer ME, Schwanke CHA. Accuracy of the triglyceride-glucose index as a surrogate marker for identifying metabolic syndrome in non-diabetic individuals. Nutrition. 2023;109:111978. https://doi.org/10.1016/j.nut.2023.111978

Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6(4):299–304. https://doi.org/10.1089/met.2008.0034 PMID: 19067533

Giannini C, Caprio S. Progression of β-cell dysfunction in obese youth. Curr Diab Rep. 2013;13(1):89–95. https://doi.org/10.1007/s11892-012-0347-7

Lee S, Yoon J, Chun J. Weight control patterns, substance use, and mental health in Korean adolescents: A latent class analysis. Int J Ment Health Addict. 2024. https://doi.org/10.1007/s11469-024-01385-y

Son DH, Lee HS, Lee YJ, Lee JH, Han JH. Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome. Nutr Metab Cardiovasc Dis. 2022;32(3):596–604. https://doi.org/10.1016/j.numecd.2021.11.017 PMID: 35090800

Reckziegel MB, Nepomuceno P, Machado T, Renner JD, Pohl HH, Nogueira-de-Almeida CA, Mello ED. The triglyceride-glucose index as an indicator of insulin resistance and cardiometabolic risk in Brazilian adolescents. Arch Endocrinol Metab. 2023;67(2):153–61. https://doi.org/10.20945/2359-3997000000617

Aslan Çin NN, Yardımcı H, Koç N, Uçaktürk SA, Akçil Ok M. 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. J Pediatr Endocrinol Metab. 2020;33(6):777–84. https://doi.org/10.1515/jpem-2019-0463

Nabipoorashrafi SA, Seyedi SA, Rabizadeh S, et al. The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: a systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2022;32(12):2677–88. https://doi.org/10.1016/j.numecd.2022.07.024

Ramdas Nayak VK, Satheesh P, Shenoy MT, Kalra S. Triglyceride glucose (TyG) index: a surrogate biomarker of insulin resistance. J Pak Med Assoc. 2022;72(5):986–8. https://doi.org/10.47391/JPMA.22-63




DOI: https://doi.org/10.46903/gjms/23.4.Suppl.2061

Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 Nitin Wathore, Saride Naveen Kumar, Urmila Umasekar, Panneerselvam Periasamy, Arbind Kumar Choudhary

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Gomal Medical College, Daraban Road, Dera Ismail Khan, Pakistan

ISSN: 1819-7973, e-ISSN: 1997-2067

Website: https://www.gmcdikhan.edu.pk

Phone: +92-966-747373

Scimago Journal & Country Rank