JOMPAC
Journal of Medicine and Palliative Care

Journal of Medicine and Palliative Care (JOMPAC) is an open access scientific journal with independent, unbiased, and double-blind review under international guidelines. The purpose of JOMPAC is to contribute to the literature by publishing articles on health sciences and medicine.

eISSN: 2717-7505
Creative Commons CC BY-NC-ND 4.0 International License.
EndNote Style

Submit Manuscript

Index
Original Article
Novel and traditional anthropometric indices to identify metabolic syndrome and metabolically healthy obesity in obese women
Abstract
Aims: Traditional anthropometric indices may be inadequate for distinguishing obese individuals with low metabolic risk or those who are metabolically healthy. Therefore, newer, innovative indices may offer improved diagnostic accuracy. Current study aims to evaluate effectiveness of both traditional and novel anthropometric indices in identifying metabolic syndrome (MetS) and assessing metabolic risk factors such serum uric acid (SUA) and atherogenic index of plasma (AIP).
Methods: This was a retrospective study involving data of 292 obese women. The patients were separated into groups according to presence of MetS and their SUA and AIP levels. Predictive power was estimated using receiver operating characteristic curves, by comparing the area under the curve (AUC).
Results: Our results showed that all novel indices except the weight-adjusted waist index (WWI) had potential utility in diagnosing MetS. The lipid accumulation product (LAP) index had the highest AUC for MetS diagnosis, with a value of 0.832 (95% CI: 0.783–0.880). The abdominal volume index (AVI) and waist-to-height ratio (WHtR) showed the highest sensitivity (82.3%), while the waist-triglyceride index (WTI) had the highest specificity (89%).
Conclusion: Notably, both the visceral adiposity index (VAI) and LAP index achieved specificity and sensitivity values exceeding 70% and can be used in MetS screening of obese women. In contrast, the WWI was found to be statistically insufficient for defining MetS and distinguishing between SUA and AIP groups.

Keywords : Uric acid, atherogenic index of plasma, obesity, metabolic syndrome

Download Article


1. Bray GA, Kim KK, Wilding JPH. Obesity: a chronic relapsing progressive disease process. A position statement of the World Obesity Federation. Obesity Reviews. 2017;18(7):715-723. doi:10.1111/OBR.12551
2. Phillips CM. Metabolically healthy obesity: definitions, determinants and clinical implications. Rev Endocr Metab Disord. 2013;14(3):219-227. doi:10.1007/S11154-013-9252-X/TABLES/1
3. Tsatsoulis A, Paschou SA. Metabolically healthy obesity: criteria, epidemiology, controversies, and consequences. Curr Obes Rep. 2020; 9(2):109-120. doi:10.1007/S13679-020-00375-0/FIGURES/1
4. Blüher M. Metabolically healthy obesity. Endocr Rev. 2020;3(21):1-16. doi:10.1210/endrev/bnaa004
5. Elagizi A, Kachur S, Lavie CJ, et al. An overview and update on obesity and the obesity paradox in cardiovascular diseases. Prog Cardiovasc Dis. 2018;61(2):142-150. doi:10.1016/J.PCAD.2018.07.003
6. Suliga E, Ciesla E, Gluszek-Osuch M, Rogula T, Gluszek S, Koziel D. The usefulness of anthropometric indices to identify the risk of metabolic syndrome. Nutrients. 2019;11(11):2598-2612. doi:10.3390/nu11112598
7. Wu L, Zhu W, Qiao Q, Huang L, Li Y, Chen L. Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults. Nutr Metab (Lond). 2021;18(1):3. doi:10.1186/s12986-020-00536-x
8. Wang H, Liu A, Zhao T, et al. Comparison of anthropometric indices for predicting the risk of metabolic syndrome and its components in Chinese adults: a prospective, longitudinal study. BMJ Open. 2017;7(9): e016062. doi:10.1136/bmjopen-2017-016062
9. Adejumo EN, Adejumo AO, Azenabor A, et al. Anthropometric parameter that best predict metabolic syndrome in South west Nigeria. Diabetes Metab Syndr. 2019;13(1):48-54. doi:10.1016/J.DSX.2018.08.009
10. Ozturk EE, Yildiz H. Evaluation of different anthropometric indices for predicting metabolic syndrome. Eur Rev Med Pharmacol Sci. 2022; 26(22):8317-8325. doi:10.26355/eurrev_202211_30364
11. Li G, Wu HK, Wu XW, et al. The feasibility of two anthropometric indices to identify metabolic syndrome, insulin resistance and inflammatory factors in obese and overweight adults. Nutrition. 2019;57:194-201. doi: 10.1016/J.NUT.2018.05.004
12. Rasaei N, Mirzababaei A, Arghavani H, et al. A comparison of the sensitivity and specificity of anthropometric measurements to predict unhealthy metabolic phenotype in overweight and obese women. Diabetes Metab Syndr. 2018;12(6):1147-1153. doi:10.1016/J.DSX.2018.06. 023
13. Zaki M, El-Bassyouni H, El-Gammal M, Kamal S. Indicators of the metabolic syndrome in obese adolescents. Arch Med Sci. 2015;11(1):92-98. doi:10.5114/aoms.2015.49214
14. Shi J, Chen Z, Zhang Y. Associations between body fat anthropometric indices and mortality among individuals with metabolic syndrome. Lipids Health Dis. 2024;23(1):318. doi:10.1186/S12944-024-02272-0/TABLES/4
15. Saito Y, Tanaka A, Node K, Kobayashi Y. Uric acid and cardiovascular disease: a clinical review. J Cardiol. 2021;78(1):51-57. doi:10.1016/J.JJCC. 2020.12.013
16. Dobiášová M. Atherogenic index of plasma [Log(triglycerides/HDL-cholesterol)]: theoretical and practical implications. Clin Chem. 2004; 50(7):1113-1115. doi:10.1373/CLINCHEM.2004.033175
17. Surrati AMQ, Mohammedsaeed W, Alfadhli EM. Anthropometrics and plasma atherogenic index in Saudi women Madinah KSA. Pak J Med Sci. 2024;40(3, Part-II):364-370. doi:10.12669/PJMS.40.3.8318
18. Akbarirad M, Darroudi S, Farsi Farima, et al. Investigation of the relationship between atherogenic index, anthropometric characteristics, and 10-year risk of metabolic syndrome: a population-based study. Ir J Med Sci. 2024;193(6):2705-2711. doi:10.1007/s11845-024-03791-6
19. Hamzeh B, Pasdar Y, Mirzaei N, et al. Visceral Adiposity Index and atherogenic index of plasma as useful predictors of risk of cardiovascular diseases: evidence from a cohort study in Iran. Lipids Health Dis. 2021; 20(1):82. doi:10.1186/s12944-021-01505-w
20. Lin SD, Tsai DH, Hsu SR. Association between serum uric acid level and components of the metabolic syndrome. J Chin Med Assoc. 2006;69(11): 512-516. doi:10.1016/S1726-4901(09)70320-X
21. Kanbay M, Jensen T, Solak Y, et al. Uric acid in metabolic syndrome: from an innocent bystander to a central player. Eur J Intern Med. 2016; 29:3-8. doi:10.1016/J.EJIM.2015.11.026
22. Sagun G, Oguz A, Karagoz E, Filizer AT, Tamer G, Mesci B. Application of alternative anthropometric measurements to predict metabolic syndrome. Clinics. 2014;69(5):347-353. doi:10.6061/CLINICS/2014(05)09
23. Akbas EM, Timuroglu A, Ozcicek A, et al. Association of uric acid, atherogenic index of plasma and albuminuria in diabetes mellitus. Int J Clin Exp Med. 2014;7(12):5737-5743.
24. Hongwei L, Zhenhai S, Wei J, et al. The effects and predictive values of novel anthropometric parameters on uric acid levels and hyperuricemia in adults. Sci Rep. 2025;15(1):956-966. doi:10.1038/s41598-024-84617-4
25. Chen D, Lu C, Chen K, et al. Association between anthropometric indices and hyperuricemia: a nationwide study in China. Clin Rheumatol. 2024; 43(3):907-920. doi:10.1007/S10067-024-06884-W/TABLES/5
26. Tu CM, Wei TE, Tseng GS, Chen CC, Liu CW. Serum uric acid is associated with incident metabolic syndrome independent of body shape index and body roundness index in healthy individuals. Nutr Metab Cardiovasc Dis. 2021;31(11):3142-3151. doi:10.1016/J.NUMECD.2021.07. 008
27. Luo Y, Hao J, He X, et al. Association between triglyceride-glucose index and serum uric acid levels: a biochemical study on anthropometry in non-obese type 2 diabetes mellitus patients. Diabetes Metab Syndr Obes. 2022;15:3447-3458. doi:10.2147/DMSO.S387961
Article available in :
Volume 6, Issue 2, 2025
Page : 91-97
https://doi.org/10.47582/jompac.1640684
Article Information
Received : 15 Şub 2025
Accepted : 05 Mar 2025
Published : 23 Mar 2025
Corresponding Author :

Nergis Akbaş: Department of Medical Biochemistry, Faculty of Medicine, Erzincan Binali Yıldırım University, Erzincan, Turkey

[email protected]
Citation : Akbaş N, Uzun A. Novel and traditional anthropometric indices to identify metabolic syndrome and metabolically healthy obesity in obese women. J Med Palliat Care. 2025;6(2):91-97.

Read: 12
Cited: 0
Download : 25
_Footer