Lokman Hekim Health Sciences
Article Open Access Volume 6 · Issue 1 · 2026 pp. 134–143

Comparative Diagnostic Performance of Anthropometric and Composite Indices for Metabolic Syndrome in Adults with Obesity

Taha Gökmen Ülger1 ORCID, Songül Çağlar2 ORCID, Okan Güler3 ORCID
1 Department of Nutrition and Dietetics, Bolu Abant İzzet Baysal University Faculty of Health Sciences, Bolu, Türkiye
2 Department of Nursing, Bolu Abant İzzet Baysal University Faculty of Health Sciences, Bolu, Türkiye
3 Department of Nutrition and Dietetics, Bolu Abant İzzet Baysal University Training and Research Hospital, Bolu, Türkiye
Published: 2026 DOI: 10.14744/lhhs.2025.76721 Article ID: LHHS-76721
Graphical abstract
Click to view in full size
Abstract
Introduction: This study aimed to compare the diagnostic performance of conventional anthropometric and novel composite indices in identifying metabolic syndrome (MetS) in adults with obesity and to examine their associations with cardiometabolic risk markers and lipid profiles.
Methods: This study was designed as a descriptive diagnostic accuracy study and conducted in the Nutrition and Dietetics outpatient clinic of a university hospital. A total of 496 adults with a body mass index greater than 30 kg/m² were included. MetS was diagnosed according to the criteria of the Turkish Society of Endocrinology and Metabolism. In addition to anthropometric indices, composite indices such as the visceral adiposity index, lipid accumulation product, cardiometabolic index, and the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio were also calculated. Statistical analyses included receiver operating characteristic curve analysis, logistic regression, and correlation analysis.
Results: Composite indices, including TG/HDL-C ratio, visceral adiposity index, lipid accumulation product, and cardiometabolic index, were significantly associated with MetS. Conventional anthropometric indices showed limited diagnostic value. TG/HDL-C ratio demonstrated the highest accuracy with an area under the curve of 0.721 and an optimal cutoff value of 2.68. Logistic regression identified TG/HDL-C ratio, age, and cardiometabolic index as significant predictors. The overall model had an area under the curve of 0.726 and a classification accuracy of 69.6 percent. Discussion and Conclusion: Lipid-based indices outperform conventional anthropometric measures in diagnosing metabolic syndrome among individuals with obesity. Their use may improve cardiometabolic risk assessment in clinical settings.

Keywords: Anthropometric indices; Cardiometabolic risk; Metabolic syndrome; Obesity

Article information

933 Views
932 Downloads
View / Download PDF

Current Issue Vol 6 · Iss 1

Submit manuscript
Most read & early access
Click an article to open abstract.
View all articles