Accuracy of the triglyceride-glucose index as a surrogate marker for identifying metabolic syndrome in non-diabetic individuals

Analie Nunes Couto; Hildegard Hedwig Pohl; Moisés Evandro Bauer; Carla Helena Augustin Schwanke

doi:10.1016/j.nut.2023.111978

Accuracy of the triglyceride-glucose index as a surrogate marker for identifying metabolic syndrome in non-diabetic individuals

Nutrition. 2023 May:109:111978. doi: 10.1016/j.nut.2023.111978. Epub 2023 Jan 21.

Authors

Analie Nunes Couto¹, Hildegard Hedwig Pohl², Moisés Evandro Bauer³, Carla Helena Augustin Schwanke⁴

Affiliations

¹ Graduate Program in Biomedical Gerontology, School of Medicine, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil. Electronic address: analiecouto@hotmail.com.
² Graduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, Brazil.
³ Graduate Program in Biomedical Gerontology, School of Medicine, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil; Laboratory of Immunobiology, School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil; National Institute of Science and Technology - Neuroimmunomodulation (INCT-NIM), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brasília, Brazil.
⁴ Graduate Program in Biomedical Gerontology, School of Medicine, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil; Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil.

PMID: 36842288
DOI: 10.1016/j.nut.2023.111978

Abstract

Objectives: This study aimed to verify the performance of the triglyceride-glucose (TyG) index in predicting metabolic syndrome (MetS) using three different criteria in healthy individuals living in rural areas. In addition, it aimed to estimate the TyG index cutoff point in the prediction of MetS.

Methods: The study was a cross-sectional study of healthy individuals (aged ≥18 y) living in rural areas of southern Brazil. Individuals with diabetes mellitus were excluded. The variables investigated were waist circumference, blood pressure, triglycerides, high-density lipoprotein cholesterol, fasting glucose, and TyG index. MetS was defined using three criteria: harmonized, International Diabetes Foundation, and National Cholesterol Education Program Adult Treatment Panel III. The Poisson regression model was used for the multivariate analysis. The performance of the TyG index in identifying MetS was determined by receiver operating characteristic curves.

Results: A total of 133 individuals were included in this study, with a mean age of 49.0 ± 13.5 y; 54.1% were female. The TyG index performed better in predicting MetS through the harmonized criteria, with area under the curve (AUC) = 0.889 (95% confidence interval [CI], 0.829-0.949), followed by the International Diabetes Foundation criteria, with AUC = 0.877 (95% CI, 0.814-0.940), and the National Cholesterol Education Program criteria, with AUC = 0.867 (95% CI, 0.797-0.937). The TyG index cutoff points defined for the harmonized and International Diabetes Foundation criteria were ≥ 8.61, and ≥ 8.79 for the National Cholesterol Education Program Adult Treatment Panel III.

Conclusions: The TyG index proved to be valid for diagnosing MetS. The largest AUC of the TyG index was identified for the harmonized criteria. Thus, the TyG index can be used to diagnose MetS in individuals living in rural areas.

Keywords: Farmers; Health; Insulin resistance; Metabolic syndrome; Rural; Rural population; Triglyceride-glucose index.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Biomarkers
Blood Glucose / metabolism
Cross-Sectional Studies
Female
Glucose / metabolism
Humans
Male
Metabolic Syndrome* / diagnosis
Middle Aged
Triglycerides

Substances

Glucose
Blood Glucose
Triglycerides
Biomarkers