{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T23:01:49Z","timestamp":1792710109109,"version":"4.5.0"},"reference-count":63,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:00:00Z","timestamp":1760140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Medicine and Pharmacy of Craiova"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Diabetes mellitus (DM) is a complex chronic disease, with a prevalence that has reached alarming proportions in recent decades. In this study, we aimed to analyze the association of type 2 diabetes mellitus (T2DM) with certain insulin resistance (IR) indicators, according to the gender of the participants enrolled in the PREDATORR study. Biomarkers such as the triglyceride\u2013glucose (TyG) index and its derivates, triglyceride-to-high-density lipoprotein cholesterol (TG\/HDL-c), and metabolic score for insulin resistance (METS-IR), as well as recent indicators, like cholesterol, HDL, the glucose (CHG) index and its derivates, CHG\u2013body mass index (CHG-BMI), and CHG\u2013waist circumference (CHG-WC), as well as its newly proposed derivates, such as CHG\u2013waist-to-height ratio (CHG-WHtR), CHG\u2013neck circumference (CHG-NC), and CHG\u2013neck-to-height ratio (NHtRs were analyzed in 2080 subjects, divided into two groups, according to gender). Univariate and multivariate logistic regression was used to identify the relationships between IR indicators and T2DM. Regardless of gender, all the analyzed indicators presented statistically significantly higher values in T2DM (+) compared to T2DM (\u2212). For both studied groups, CHG\u2013WHtR had the largest AUROC curve: in males, the AUROC curve was 0.809, the cut-off value being 3.22, with a 70.7% sensitivity and 75.3% specificity; in females, the AUROC curve was 0.840, the cut-off value was 3.20, with a 79.3% sensitivity and 75.5% specificity, respectively. Regardless of gender, the age-adjusted model for multivariate logistic regression analysis demonstrated that TyG and CHG were predictive factors for T2DM.<\/jats:p>","DOI":"10.3390\/ijms26209888","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T16:13:03Z","timestamp":1760717583000},"page":"9888","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Relationship Between Insulin Resistance Indicators and Type 2 Diabetes Mellitus in Romania"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1159-3617","authenticated-orcid":false,"given":"Adela-Gabriela","family":"\u015etefan","sequence":"first","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Calafat Municipal Hospital, 205200 Calafat, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diana","family":"Clenciu","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6133-4341","authenticated-orcid":false,"given":"Ionela-Mihaela","family":"Vladu","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5310-3033","authenticated-orcid":false,"given":"Adina","family":"Mitrea","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diana-Cristina","family":"Protasiewicz-Timofticiuc","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Midwives and Nursing, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria-Magdalena","family":"Ro\u015fu","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Midwives and Nursing, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theodora-Claudia","family":"Gheonea","sequence":"additional","affiliation":[{"name":"Department of Diabetes, Nutrition and Metabolic Diseases, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beatrice-Elena","family":"Vladu","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8563-347X","authenticated-orcid":false,"given":"Ion-Cristian","family":"Efrem","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine\u2014Medical Semiology, Faculty of Dentistry, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3116-8151","authenticated-orcid":false,"given":"Delia-Viola Reurean","family":"Pintilei","sequence":"additional","affiliation":[{"name":"Department of Medical-Surgical and Complementary Sciences, Faculty of Medicine and Biological Sciences, \u201cStefan cel Mare\u201d University, 720229 Suceava, Romania"},{"name":"Consultmed Medical Centre, Department of Diabetes, Nutrition and Metabolic Diseases, 700544 Iasi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eugen","family":"Mo\u0163a","sequence":"additional","affiliation":[{"name":"Doctoral School, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Mo\u0163a","sequence":"additional","affiliation":[{"name":"Doctoral School, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,11]]},"reference":[{"key":"ref_1","unstructured":"American Diabetes Association Professional Practice Committee (2025). Introduction and Methodology: Standards of Care in Diabetes-2025. Diabetes Care, 48, S1\u2013S5."},{"key":"ref_2","unstructured":"International Diabetes Federation (2025, June 15). IDF Diabetes Atlas 11th Edition. Available online: https:\/\/diabetesatlas.org\/media\/uploads\/sites\/3\/2025\/04\/IDF_Atlas_11th_Edition_2025.pdf."},{"key":"ref_3","unstructured":"NCD Risk Factor Collaboration (NCD-RisC) (2024). Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: A pooled analysis of 1108 population-representative studies with 141 million participants. Lancet, 404, 2077\u20132093."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1111\/1753-0407.12297","article-title":"Prevalence of diabetes mellitus and prediabetes in the adult Romanian population: PREDATORR study","volume":"8","author":"Mota","year":"2016","journal-title":"J. Diabetes"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"American Diabetes Association Professional Practice Committee (2025). 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2025. Diabetes Care, 48, S27\u2013S49.","DOI":"10.2337\/dc25-S002"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"15019","DOI":"10.1038\/nrdp.2015.19","article-title":"Type 2 diabetes mellitus","volume":"1","author":"DeFronzo","year":"2015","journal-title":"Nat. Rev. Dis. Primers"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s11892-022-01453-4","article-title":"Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus","volume":"22","author":"Hlavinka","year":"2022","journal-title":"Curr. Diab. Rep."},{"key":"ref_8","first-page":"e62742","article-title":"Triglyceride-Fasting Glucose Index and Homeostatic Model Assessment for Insulin Resistance as Predictors of Type 2 Diabetes Mellitus in South Indians with Normal Body Mass Index","volume":"16","author":"Ca","year":"2024","journal-title":"Cureus"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"217","DOI":"10.6065\/apem.2040090.045","article-title":"Insulin resistance and type 2 diabetes in children","volume":"25","author":"Castorani","year":"2020","journal-title":"Ann. Pediatr. Endocrinol. Metab."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Tagi, V.M., Giannini, C., and Chiarelli, F. (2019). Insulin Resistance in Children. Front. Endocrinol., 10.","DOI":"10.3389\/fendo.2019.00342"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1038\/nm.4350","article-title":"Insulin action and resistance in obesity and type 2 diabetes","volume":"23","author":"Czech","year":"2017","journal-title":"Nat. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1111\/jdi.14343","article-title":"A novel index for diagnosis of type 2 diabetes mellitus: Cholesterol, High density lipoprotein, and Glucose (CHG) index","volume":"16","author":"Mansoori","year":"2025","journal-title":"J. Diabetes Investig."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1177\/1479164119827611","article-title":"Insulin resistance and insulin hypersecretion in the metabolic syndrome and type 2 diabetes: Time for a conceptual framework shift","volume":"16","author":"Nolan","year":"2019","journal-title":"Diab. Vasc. Dis. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1727","DOI":"10.1210\/js.2019-00065","article-title":"Hyperinsulinemia: An Early Indicator of Metabolic Dysfunction","volume":"3","author":"Thomas","year":"2019","journal-title":"J. Endocr. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s12902-025-01848-w","article-title":"Triglyceride-glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: A national prospective cohort study","volume":"25","author":"Shan","year":"2025","journal-title":"BMC Endocr. Disord."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"108050","DOI":"10.1016\/j.diabres.2020.108050","article-title":"Progression of insulin resistance: A link between risk factors and the incidence of diabetes","volume":"161","author":"Wu","year":"2020","journal-title":"Diabetes Res. Clin. Pract."},{"key":"ref_17","first-page":"E214","article-title":"Glucose clamp technique: A method for quantifying insulin secretion and resistance","volume":"237","author":"DeFronzo","year":"1979","journal-title":"Am. J. Physiol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1007\/BF00280883","article-title":"Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man","volume":"28","author":"Matthews","year":"1985","journal-title":"Diabetologia"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.2337\/diacare.27.6.1487","article-title":"Use and abuse of HOMA modeling","volume":"27","author":"Wallace","year":"2004","journal-title":"Diabetes Care"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.pcd.2020.09.001","article-title":"Triglyceride-glucose index predicts independently type 2 diabetes mellitus risk: A systematic review and meta-analysis of cohort studies","volume":"14","author":"Caldas","year":"2020","journal-title":"Prim. Care Diabetes"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3325","DOI":"10.2147\/DMSO.S478287","article-title":"Role of Triglyceride-Glucose Index in Type 2 Diabetes Mellitus and Its Complications","volume":"17","author":"Pan","year":"2024","journal-title":"Diabetes Metab. Syndr. Obes."},{"key":"ref_22","first-page":"44","article-title":"Triglyceride-Glucose Index As A Biomarker Of Insulin Resistance, Diabetes Mellitus, Metabolic Syndrome, And Cardiovascular Disease: A Review","volume":"35","author":"Kurniawan","year":"2024","journal-title":"EJIFCC"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Han, Y., Hu, H., Li, Q., Dengm, Z., and Liu, D. (2023). Triglyceride glucose-body mass index and the risk of progression to diabetes from prediabetes: A 5-year cohort study in Chinese adults. Front. Public Health, 11.","DOI":"10.3389\/fpubh.2023.1028461"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Xuan, W., Liu, D., Zhong, J., Luo, H., and Zhang, X. (2022). Impacts of Triglyceride Glucose-Waist to Height Ratio on Diabetes Incidence: A Secondary Analysis of A Population-Based Longitudinal Data. Front. Endocrinol., 13.","DOI":"10.3389\/fendo.2022.949831"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.jdiacomp.2018.10.018","article-title":"The triglyceride to high-density lipoprotein cholesterol (TG\/HDL-C) ratio as a predictor of insulin resistance, \u03b2-cell function, and diabetes in Hispanics and African Americans","volume":"33","author":"Young","year":"2019","journal-title":"J. Diabetes Complicat."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1186\/s12902-024-01769-0","article-title":"Assessing the validity of METS-IR for predicting the future onset of diabetes: An analysis using time-dependent receiver operating characteristics","volume":"24","author":"Qiu","year":"2024","journal-title":"BMC Endocr. Disord."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1007\/s12020-024-03830-3","article-title":"Relationship between indices of insulin resistance and incident type 2 diabetes mellitus in Chinese adults","volume":"85","author":"Qin","year":"2024","journal-title":"Endocrine"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hou, Y., Li, R., Xu, Z., Chen, W., Li, Z., Jiang, W., Meng, Y., and Han, J. (2024). Association of METS-IR index with Type 2 Diabetes: A cross-sectional analysis of national health and nutrition examination survey data from 2009 to 2018. PLoS ONE, 19.","DOI":"10.1101\/2024.07.30.24311210"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"\u015etefan, A.G., Clenciu, D., Mitrea, A., Vladu, I.M., Protasiewicz-Timofticiuc, D.C., Ro\u015fu, M.M., Maria, D.T., Dinu, I.R., Gheonea, T.C., and Vladu, B.E. (2025). Metabolic Syndrome and Insulin Resistance in Romania. Int. J. Mol. Sci., 26.","DOI":"10.3390\/ijms26062389"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1007\/s40618-021-01608-2","article-title":"Newly proposed insulin resistance indexes called TyG-NC and TyG-NHtR show efficacy in diagnosing the metabolic syndrome","volume":"44","author":"Mirr","year":"2021","journal-title":"J. Endocrinol. Investig."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zou, S., Yang, C., Shen, R., Wei, X., Gong, J., Pan, Y., Lv, Y., and Xu, Y. (2021). Association Between the Triglyceride-Glucose Index and the Incidence of Diabetes in People with Different Phenotypes of Obesity: A Retrospective Study. Front. Endocrinol., 12.","DOI":"10.3389\/fendo.2021.784616"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"109042","DOI":"10.1016\/j.diabres.2021.109042","article-title":"The triglyceride-glucose index is a more powerful surrogate marker for predicting the prevalence and incidence of type 2 diabetes mellitus than the homeostatic model assessment of insulin resistance","volume":"180","author":"Park","year":"2021","journal-title":"Diabetes Res. Clin. Pract."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1007\/s40519-021-01238-w","article-title":"Comparison of obesity indices and triglyceride glucose-related parameters to predict type 2 diabetes mellitus among normal-weight elderly in China","volume":"27","author":"Ke","year":"2022","journal-title":"Eat Weight Disord."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1007\/s13410-024-01369-7","article-title":"Gender differences in triglyceride glucose index predictive power for type 2 diabetes mellitus: A Chinese cohort study","volume":"45","author":"Guo","year":"2025","journal-title":"Int. J. Diabetes Dev. Ctries."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Pan, L., Gao, Y., Han, J., Li, L., Wang, M., Peng, H., Liao, J., Wan, H., Xiang, G., and Han, Y. (2022). Comparison of longitudinal changes in four surrogate insulin resistance indexes for incident T2DM in middle-aged and elderly Chinese. Front. Public Health, 10.","DOI":"10.3389\/fpubh.2022.1046223"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1007\/s12020-020-02374-6","article-title":"Triglycerides-glucose (TyG) index is a sensitive marker of insulin resistance in Greek children and adolescents","volume":"70","author":"Dikaiakou","year":"2020","journal-title":"Endocrine"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Lee, D.Y., Lee, E.S., Kim, J.H., Park, S.E., Park, C.Y., Oh, K.W., Park, S.W., Rhee, E.J., and Lee, W.Y. (2016). Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0163465"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3795","DOI":"10.2147\/DMSO.S433493","article-title":"Stronger Associations of TyG Index with Diabetes Than TyG-Obesity-Related Parameters: More Pronounced in Young, Middle-Aged, and Women","volume":"16","author":"Xing","year":"2023","journal-title":"Diabetes Metab. Syndr. Obes."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1186\/s12933-017-0514-x","article-title":"Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study","volume":"16","author":"Zhang","year":"2017","journal-title":"Cardiovasc. Diabetol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Mitrea, A., Vladu, I.M., Ro\u015fu, M.M., Clenciu, D., Mota, E., and Mota, M. (2023). Paradigm of Insulin Resistance, Type 2 Diabetes, Obesity, Fatty Liver and Atherosclerosis in Metabolic Syndrome. Type 2 Diabetes in 2024\u2014From Early Suspicion to Effective Management, IntechOpen.","DOI":"10.5772\/intechopen.1002510"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4001","DOI":"10.1172\/JCI129188","article-title":"\u03b2 Cell dysfunction during progression of metabolic syndrome to type 2 diabetes","volume":"129","author":"Hudish","year":"2019","journal-title":"J. Clin. Investig."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1007\/s11684-019-0729-1","article-title":"Oxidative stress and diabetes: Antioxidative strategies","volume":"14","author":"Zhang","year":"2020","journal-title":"Front. Med."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Vilas-Boas, E.A., Almeida, D.C., Roma, L.P., Ortis, F., and Carpinelli, A.R. (2021). Lipotoxicity and \u03b2-Cell Failure in Type 2 Diabetes: Oxidative Stress Linked to NADPH Oxidase and ER Stress. Cells, 10.","DOI":"10.3390\/cells10123328"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1514","DOI":"10.1016\/j.jmb.2019.09.016","article-title":"Recent Insights Into Mechanisms of \u03b2-Cell Lipo- and Glucolipotoxicity in Type 2 Diabetes","volume":"432","author":"Lytrivi","year":"2020","journal-title":"J. Mol. Biol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1186\/s12933-024-02392-y","article-title":"Diagnostic and prognostic value of triglyceride glucose index: A comprehensive evaluation of meta-analysis","volume":"23","author":"Nayak","year":"2024","journal-title":"Cardiovasc. Diabetol."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Mitroi Sakizlian, D.D., Boldeanu, L., Mitrea, A., Clenciu, D., Vladu, I.M., Ciobanu Plasiciuc, A.E., \u0218arla, A.V., Silo\u0219i, I., Boldeanu, M.V., and Assani, M.-Z. (2025). The Interplay of Cardiometabolic Syndrome Phenotypes and Cardiovascular Risk Indices in Patients Diagnosed with Diabetes Mellitus. Int. J. Mol. Sci., 26.","DOI":"10.3390\/ijms26136227"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Efrem, I.C., Mo\u021ba, M., Vladu, I.M., Mitrea, A., Clenciu, D., Timofticiuc, D.C.P., Diaconu, I.-D., Turcu, A., Cri\u0219an, A.E., and Georm\u0103neanu, C. (2022). A Study of Biomarkers Associated with Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Type 2 Diabetes. Diagnostics, 12.","DOI":"10.3390\/diagnostics12102426"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1507\/endocrj.EJ21-0560","article-title":"Triglyceride glucose index is superior biomarker for predicting type 2 diabetes mellitus in children and adolescents","volume":"69","author":"Yoon","year":"2022","journal-title":"Endocr. J."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.pcd.2019.08.007","article-title":"Neck circumference as a predictor of metabolic syndrome: A cross-sectional study","volume":"14","author":"Laohabut","year":"2020","journal-title":"Prim. Care Diabetes"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"34","DOI":"10.31372\/20190401.1031","article-title":"Association Between Neck Circumference and Coronary Heart Disease: A Meta-analysis","volume":"4","author":"Yang","year":"2019","journal-title":"Asian Pac. Isl. Nurs. J."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1007\/s00592-018-1195-y","article-title":"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","volume":"55","author":"Tohidi","year":"2018","journal-title":"Acta Diabetol."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Lee, S.H., Kwon, H.S., Park, Y.M., Ha, H.S., Jeong, S.H., Yang, H.K., Lee, J.H., Yim, H.W., Kang, M.I., and Lee, W.C. (2014). Predicting the development of diabetes using the product of triglycerides and glucose: The Chungju Metabolic Disease Cohort (CMC) study. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0090430"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1530\/EJE-17-0883","article-title":"METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes","volume":"178","author":"Campos","year":"2018","journal-title":"Eur. J. Endocrinol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1111\/1753-0407.13161","article-title":"Association of metabolic score for insulin resistance and its 6-year change with incident type 2 diabetes mellitus","volume":"13","author":"Zhang","year":"2021","journal-title":"J. Diabetes"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Cheng, H., Yu, X., Li, Y.T., Jia, Z., Wang, J.J., Xie, Y.J., Hernandez, J., Wang, H.H.X., and Wu, H.F. (2023). Association between METS-IR and Prediabetes or Type 2 Diabetes Mellitus among Elderly Subjects in China: A Large-Scale Population-Based Study. Int. J. Environ. Res. Public Health, 20.","DOI":"10.3390\/ijerph20021053"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"WHO Expert Consultation (2004). Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet, 363, 157\u2013163.","DOI":"10.1016\/S0140-6736(03)15268-3"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1640","DOI":"10.1161\/CIRCULATIONAHA.109.192644","article-title":"Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity","volume":"120","author":"Alberti","year":"2009","journal-title":"Circulation"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"e010159","DOI":"10.1136\/bmjopen-2015-010159","article-title":"Waist-to-height ratio as an indicator of \u2018early health risk\u2019: Simpler and more predictive than using a \u2018matrix\u2019 based on BMI and waist circumference","volume":"6","author":"Ashwell","year":"2016","journal-title":"BMJ Open"},{"key":"ref_59","unstructured":"World Health Organization (2025, July 27). Waist Circumference and Waist\u2013Hip Ratio: Report of a WHO Expert Consultation, Geneva, 8\u201311 December 2008. Available online: https:\/\/iris.who.int\/bitstream\/handle\/10665\/44583\/9789241501491_eng.pdf."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1089\/met.2008.0034","article-title":"The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects","volume":"6","year":"2008","journal-title":"Metab. Syndr. Relat. Disord."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Er, L.K., Wu, S., Chou, H.H., Hsu, L.A., Teng, M.S., Sun, Y.C., and Ko, Y.L. (2016). Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0149731"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Lim, J., Kim, J., Koo, S.H., and Kwon, G.C. (2019). 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, 14.","DOI":"10.1371\/journal.pone.0212963"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"802","DOI":"10.7326\/0003-4819-139-10-200311180-00007","article-title":"Use of metabolic markers to identify overweight individuals who are insulin resistant","volume":"139","author":"McLaughlin","year":"2003","journal-title":"Ann. Intern. Med."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/20\/9888\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T16:18:38Z","timestamp":1760717918000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/20\/9888"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,11]]},"references-count":63,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["ijms26209888"],"URL":"https:\/\/doi.org\/10.3390\/ijms26209888","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,11]]}}}