CARDIOMETABOLIC RISK IN OBESITY AND METABOLIC SYNDROME: CONTEMPORARY ALGORITHMS FOR STRATIFICATION

Highlights

Modern stratification algorithms, which are based on obesity phenotyping (considering visceral fat and body composition) and novel biomarkers, allow for a more accurate prediction of cardiometabolic risk compared to classical scales that rely solely on body mass index and waist circumference. NAFLD and insulin resistance indices (including TyG and combined indices) serve as important independent risk components and should be integrated into clinical algorithms for early risk stratification.

Abstract

Obesity and metabolic syndrome are key drivers of cardiovascular disease and type 2 diabetes mellitus. Contemporary research identifies distinct obesity phenotypes, including metabolically healthy obesity and normal-weight obesity, necessitating refinement of approaches to cardiometabolic risk stratification. The aim of the article was to systematize current evidence on cardiometabolic risk in obesity and metabolic syndrome and to analyze contemporary risk stratification algorithms. A systematic literature review was conducted in accordance with PRISMA guidelines. The search was performed in PubMed, Google Scholar, and eLibrary databases covering the period from 2020 to 2024. Following screening of 1,099 publications, 10 studies meeting the eligibility criteria were included in the final analysis. Contemporary cardiometabolic risk stratification methods based on obesity phenotyping, visceral fat assessment, and novel biomarkers substantially outperform traditional approaches. Insulin resistance indices demonstrate high predictive value for cardiovascular mortality. The important role of non-alcoholic fatty liver disease as a component of cardiometabolic risk has been established. Contemporary cardiometabolic risk stratification methods that account for distinct obesity phenotypes and novel biomarkers provide more accurate prediction of cardiovascular complications compared to conventional approaches. Promising directions include the implementation of personalized prevention strategies and broader adoption of novel risk stratification tools in clinical practice.

1. Arabidze GG, Mamedov MN. Cardiovascular-kidney-metabolic syndrome – a new concept of the association of risk factors and metabolic disorders within the cardiovascular and renal continuum. View on the issue. Russian Journal of Cardiology. 2024;29(5):5772. (In Russ.) doi:10.15829/1560-4071-2024-5772 EDN: YQSFCR

2. German AI, Sedykh DYu, Hryachkova ON, Kashtalap VV. Abdominal obesity and ten-year prognosis of patients with myocardial infarction. Complex Issues of Cardiovascular Diseases. 2021;10(1):26-39. (In Russ.) doi: 10.17802/2306-1278-2021-10-1-26-39

3. Fahed G, Aoun L, Bou Zerdan M, et al. Metabolic Syndrome: Updates on Pathophysiology and Management in 2021. Int J Mol Sci. 2022;23(2):786. Published 2022 Jan 12. doi:10.3390/ijms23020786

4. Zafar U, Khaliq S, Ahmad HU, et al. Metabolic syndrome: an update on diagnostic criteria, pathogenesis, and genetic links. Hormones (Athens). 2018;17(3):299-313. doi:10.1007/s42000-018-0051-3

5. Bitew ZW, Alemu A, Ayele EG, et al. Metabolic syndrome among children and adolescents in low and middle income countries: a systematic review and meta-analysis. Diabetol Metab Syndr. 2020;12:93. Published 2020 Oct 27. doi:10.1186/s13098-020-00601-8

6. Hayden MR. Overview and New Insights into the Metabolic Syndrome: Risk Factors and Emerging Variables in the Development of Type 2 Diabetes and Cerebrocardiovascular Disease. Medicina (Kaunas). 2023;59(3):561. Published 2023 Mar 13. doi:10.3390/medicina59030561

7. Romantsova TI, Ostrovskaya EV. Metabolically healthy obesity: definitions, protective factors, clinical relevance. Almanac of Clinical Medicine. 2015;1(1):75-86. (In Russ.) doi: 10.18786/2072-0505-2015-1-75-86

8. Ostrominski JW, Powell-Wiley TM. Risk Stratification and Treatment of Obesity for Primary and Secondary Prevention of Cardiovascular Disease. Curr Atheroscler Rep. 2024;26(1):11-23. doi:10.1007/s11883-023-01182-3

9. Mohammadian Khonsari N, Khashayar P, Shahrestanaki E, et al. Normal Weight Obesity and Cardiometabolic Risk Factors: A Systematic Review and Meta-Analysis. Front Endocrinol (Lausanne). 2022;13:857930. Published 2022 Mar 24. doi:10.3389/fendo.2022.857930

10. Rakhmat II, Putra ICS, Wibowo A, et al. Cardiometabolic risk factors in adults with normal weight obesity: A systematic review and meta-analysis. Clin Obes. 2022;12(4):e12523. doi:10.1111/cob.12523

11. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. Published 2021 Mar 29. doi:10.1136/bmj.n71

12. Ishchenko AY, Galushko MY, Bakulin IG. The interrelation of cardiometabolic risk factors and metabolic dysfunction-associated steatotic liver disease subtypes. Meditsinskiy sovet = Medical Council. 2024;(15):146–157. (In Russ.) doi: 10.21518/ms2024-447

13. Korneeva EV, Voevoda MI, Semaev SE, Maksimov VN. Genetic determinants of hypertriglyceridemia and cardiometabolic risks. International heart and vascular disease journal. 2022;9(32):05-10. (In Russ.) doi: 10.24412/2311-1623-2021-32-05-10

14. Mustafina SV, Denisova DV, Alferova VI, Shramko VS, Shcherbakova LV. Leptin and cardiometabolic risk factors in overweight persons in young age. Ateroscleroz. 2021;17(2):51-60. (In Russ.) doi: 10.52727/2078-256X-2021-17-2-51-60

15. Sergienko IV, Malyshev PP, Zubareva MY, et al. Assessment of Cardiometabolic Risk Associated With Overweight, Based on the Use of the Aterostop Calculator. The Journal of Atherosclerosis and Dyslipidemias. 2021;42(1):42-51. (In Russ.) doi:10.34687/2219-8202.JAD.2021.01.0004

16. Sineglazova AV, Parve SD, Fakhrutdinova AS, et al. Cardiometabolic profile in relation to CMDS staging in young adults. The Bulletin of Contemporary Clinical Medicine. 2024; 17 (4): 82-92. (In Russ.) doi: 10.20969/VSKM.2024.17(4).82-92

17. Chulkov VS, Gavrilova ES, Chulkov VS, et al. Cardiometabolic risk factors and renin-angiotensin system polymorphisms in young individuals with various metabolic phenotypes. Arterial Hypertension. 2022;28(1):58-66. (In Russ.) doi:10.18705/1607-419X-2022-28-1-58-66

18. Yakovleva S. V., Pirogova I. Yu. Relationship between cardiometabolic risk factors and 25(OH)D levels in young men with non-alcoholic fatty liver disease. Experimental and Clinical Gastroenterology. 2022;206(10): 50–57. (In Russ.) doi: 10.31146/1682-8658-ecg-206-10-50-57

19. Agrawal S, Klarqvist MDR, Diamant N, et al. BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases. Nat Commun. 2023;14(1):266. Published 2023 Jan 17. doi:10.1038/s41467-022-35704-5

20. Gómez-Ambrosi J, Catalán V, Ramírez B, et al. Cardiometabolic risk stratification using a novel obesity phenotyping system based on body adiposity and waist circumference. Eur J Intern Med. 2024;124:54-60. doi:10.1016/j.ejim.2024.02.027

21. Liu J, Fu Y, Liang P, et al. The association between novel metabolic parameters and all-cause/cardiovascular mortality in patients with metabolic syndrome is modified by age. Cardiovasc Diabetol. 2025;24(1):96. Published 2025 Feb 28. doi:10.1186/s12933-025-02587-x

22. Rosero-Revelo R, Tamayo M, Correa R, et al. Exploring obesity phenotypes: a longitudinal perspective. Rev Endocr Metab Disord. 2025 Dec;26(6):889-899. doi: 10.1007/s11154-025-09976-3

23. Tanasescu MD, Rosu AM, Minca A, et al. Beyond BMI: Rethinking Obesity Metrics and Cardiovascular Risk in the Era of Precision Medicine. Diagnostics (Basel). 2025 Nov 27;15(23):3025. doi: 10.3390/diagnostics15233025

24. Salmón-Gómez L, Catalán V, Frühbeck G, Gómez-Ambrosi J. Relevance of body composition in phenotyping the obesities. Rev Endocr Metab Disord. 2023 Oct;24(5):809-823. doi: 10.1007/s11154-023-09796-3

25. Bennett JP, Prado CM, Heymsfield SB, Shepherd JA. Evaluation of visceral adipose tissue thresholds for elevated metabolic syndrome risk across diverse populations: A systematic review. Obes Rev. 2024 Sep;25(9):e13767. doi: 10.1111/obr.13767

26. Abiri B, Koohi F, Ebadinejad A, et al. Transition from metabolically healthy to unhealthy overweight/obesity and risk of cardiovascular disease incidence: A systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2022 Sep;32(9):2041-2051. doi: 10.1016/j.numecd.2022.06.010

27. Lara-Guzmán ÓJ, Arango-González ÁM, Álvarez-Quintero R, et al. Circulating hs-CRP, IL-18, Chemerin, Leptin, and Adiponectin Levels Reflect Cardiometabolic Dysfunction in Adults with Excess Weight. Int J Mol Sci. 2025 Jan 29;26(3):1176. doi: 10.3390/ijms26031176

28. Hamedi-Shahraki S, Klisic A, Amirkhizi F, Mercantepe F. Association of the triglyceride-glucose index with inflammatory markers and dysregulation of adipokines in patients with metabolic syndrome. BMC Endocr Disord. 2026 Jan 16;26(1):44. doi: 10.1186/s12902-025-02142-5

29. Montagnana M, Fava C, Targher G, et al. Plasma Leptin in Patients at Intermediate to High Cardiovascular Risk With and Without Type 2 Diabetes Mellitus. J Clin Lab Anal. 2017 Mar;31(2):e22031. doi: 10.1002/jcla.22031

30. Ismaiel A, Oliveira-Grilo G, Leucuta DC, et al. Leptin Unveiled: A Potential Biomarker for Acute Coronary Syndrome with Implications for Tailored Therapy in Patients with Type 2 Diabetes-Systematic Review and Meta-Analysis. Int J Mol Sci. 2025 Apr 22;26(9):3925. doi: 10.3390/ijms26093925

31. Parker J, Hashmi O, Dutton D, et al. Levels of vitamin D and cardiometabolic disorders: systematic review and meta-analysis. Maturitas. 2010 Mar;65(3):225-36. doi: 10.1016/j.maturitas.2009.12.013

32. Hauger H, Laursen RP, Ritz C, Mølgaard C, et al. Effects of vitamin D supplementation on cardiometabolic outcomes in children and adolescents: a systematic review and meta-analysis of randomized controlled trials. Eur J Nutr. 2020 Apr;59(3):873-884. doi: 10.1007/s00394-019-02150-x

33. Xia X, Chen S, Tian X, et al. Association of triglyceride-glucose index and its related parameters with atherosclerotic cardiovascular disease: evidence from a 15-year follow-up of Kailuan cohort. Cardiovasc Diabetol. 2024 Jun 19;23(1):208. doi: 10.1186/s12933-024-02290-3

34. Raimi TH, Dele-Ojo BF, Dada SA, et al. Triglyceride-Glucose Index and Related Parameters Predicted Metabolic Syndrome in Nigerians. Metab Syndr Relat Disord. 2021 Mar;19(2):76-82. doi: 10.1089/met.2020.0092

35. Lv L, Zhang P, Chen X, Gao Y. The association between triglyceride glucose-waist height ratio index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national prospective cohort study. Cardiovasc Diabetol. 2025 Sep 2;24(1):358. doi: 10.1186/s12933-025-02919-x

36. Park S, Kim S, Kim B, et al. Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome. Nat Genet. 2024 Nov;56(11):2380-2391. doi: 10.1038/s41588-024-01933-1

37. Romeo S, Vidal-Puig A, Husain M, et al. Clinical staging to guide management of metabolic disorders and their sequelae: a European Atherosclerosis Society consensus statement. Eur Heart J. 2025 Oct 7;46(38):3685-3713. doi: 10.1093/eurheartj/ehaf314. Erratum in: Eur Heart J. 2025 Nov 21;46(44):4791. doi: 10.1093/eurheartj/ehaf431

38. Ting R, Dutton H, Sorisky A. In vitro studies of the renin-angiotensin system in human adipose tissue/adipocytes and possible relationship to SARS-CoV-2: a scoping review. Adipocyte. 2023 Dec;12(1):2194034. doi: 10.1080/21623945.2023.2194034

39. Vargas Vargas RA, Varela Millán JM, Fajardo Bonilla E. Renin-angiotensin system: Basic and clinical aspects-A general perspective. Endocrinol Diabetes Nutr (Engl Ed). 2022 Jan;69(1):52-62. doi: 10.1016/j.endien.2022.01.005

40. Chulkov VS, Lenets EA, Gavrilova ES, et al. Gender differences in cardiometabolic risks among young adults. Complex Issues of Cardiovascular Diseases. 2021;10(2):94-98. (In Russ.) doi: 10.17802/2306-1278-2021-10-2S-94-98

41. Takakura Y, Yoshida T, Yoshioka K, et al. Angiotensinogen gene polymorphism (Met235Thr) influences visceral obesity and insulin resistance in obese Japanese women. Metabolism. 2006 Jun;55(6):819-24. doi: 10.1016/j.metabol.2006.02.008

42. Freitas AI, Mendonça I, Brión M, et al. RAS gene polymorphisms, classical risk factors and the advent of coronary artery disease in the Portuguese population. BMC Cardiovasc Disord. 2008 Jul 17;8:15. doi: 10.1186/1471-2261-8-15

43. Kalideen K, Rayner B, Ramesar R. Genetic Factors Contributing to the Pathogenesis of Essential Hypertension in Two African Populations. Journal of Personalized Medicine. 2024;14(3):323. doi: 10.3390/jpm14030323

44. Shahid M, Rehman K, Akash MSH, et al. Genetic Polymorphism in Angiotensinogen and Its Association with Cardiometabolic Diseases. Metabolites. 2022 Dec 19;12(12):1291. doi: 10.3390/metabo12121291

45. Melake A, Jegnie M. Angiotensinogen M235T Gene Polymorphism and Risk of Ischemic Heart Disease Complication among Patients with Hypertension in the Ethiopian Population. Ethiop J Health Sci. 2025 May;35(3):165-170. doi: 10.4314/ejhs.v35i3.3

46. De Luca C, Ciciola P, D’Errico G, et al. Genetic Assessment and Clinical Correlates in Severe Hypertriglyceridemia: A Systematic Review. Genes. 2025; 16(11):1377. doi: 10.3390/genes16111377

47. Montes-de-Oca-García A, Perez-Bey A, Velázquez-Díaz D, et al. Influence of ACE Gene I/D Polymorphism on Cardiometabolic Risk, Maximal Fat Oxidation, Cardiorespiratory Fitness, Diet and Physical Activity in Young Adults. Int J Environ Res Public Health. 2021 Mar 26;18(7):3443. doi: 10.3390/ijerph18073443

48. Procopciuc LM, Sitar-Tăut A, Pop D, et al. Renin angiotensin system polymorphisms in patients with metabolic syndrome (MetS). Eur J Intern Med. 2010 Oct;21(5):414-8. doi: 10.1016/j.ejim.2010.06.001

49. Polyakova OA, Ostroumova OD, Kovaleva GP, Pavleeva EE. Comorbidity of non-alcoholic fatty liver disease and cardiovascular disease: focus on ademetionine and ursodeoxycholic acid. Medical alphabet. 2021;1(29):13-20. (In Russ.) doi: 10.33667/2078-5631-2021-29-13-20

50. Feng Y, Zheng S, Liu L, Yang Y. Association of serum uric acid with hepatic steatosis detected by controlled attenuation parameter in the United States population. Lipids Health Dis. 2023;22(1):76. Published 2023 Jun 20. doi:10.1186/s12944-023-01846-8

51.