Comorbid obesity diseases and polypathies in young and middle-aged individuals
https://doi.org/10.15829/1728-8800-2025-4103
EDN: ZKQUXH
Abstract
Aim. To assess the characteristics of comorbid obesity diseases and polypathies in young and middle-aged individuals taking into account the obesity phenotype.
Material and methods. This cohort cross-sectional study was used to examine 201 patients with a body mass index (BMI) ≥25 kg/m2 and/or abdominal obesity (AO) (median age 39 [33-47] years). Anthropometry was performed. Visceral fat (VF) level was measured using the bioelectrical impedance analysis. We analyzed participants for the following diseases/conditions comorbid with obesity: hypertension (HTN), dyslipidemia, prediabetes, osteoarthritis, gastroesophageal reflux disease, non-alcoholic fatty liver disease (NAFLD), pancreatic steatosis, obstructive sleep apnea (OSA).
Results. Dyslipidemia (77,6%), HTN (32,3%), prediabetes (25,4%), less often — osteoarthritis (21,9%), pancreatic steatosis (19,9%), NAFLD (16,9%), OSA (10,4%), gastroesophageal reflux disease (9,0%) were established in more than a quarter of cases. Obesity multimorbidity prevailed (83,1%), represented by combinations of HTN with prediabetes, NAFLD, pancreatic steatosis; HTN with prediabetes, OSA. Based on the decision tree, multimorbidity was most common among individuals aged ≥32 years with a VF ≥7 units. Therefore, an algorithm was developed to prioritise screening for polypathy of obesity related comorbidity.
Conclusion. With a phenotype of BMI ≥25 kg/m2, AO and an increased VF level, there is a high probability of HTN, NAFLD, and pancreatic steatosis. Obesity multimorbidity was diagnosed in every eighth patient. The highest probability of ≥3 comorbid obesity diseases was observed in individuals with a BMI ≥25 kg/m2 and/or AO at the age of ≥32 years and VF ≥7 units.
About the Authors
A. V. SineglazovaRussian Federation
Kazan
A. R. Nurieva
Russian Federation
Kazan
References
1. Drapkina OM, Kontsevaya AV, Kalinina AM, et al. Comorbidity of patients with noncommunicable diseases in general practice. Eurasian guidelines. Cardiovascular Therapy and Prevention. 2024; 23(3):3996. (In Russ.) doi:10.15829/1728-8800-2024-3996.
2. Boutari C, Mantzoros CS. A 2022 update on the epidemiology of obesity and a call to action: as its twin COVID-19 pandemic appears to be receding, the obesity and dysmetabolism pandemic continues to rage on. Metabolism. 2022;133:155217. doi:10.1016/j.metabol.2022.155217.
3. Dedov II, Shestakova MV, Melnichenko GA, et al. Interdisciplinary clinical practice guidelines "management of obesity and its comorbidities". Obesity and metabolism. 2021;18(1):5-99. (In Russ.) doi:10.14341/omet12714.
4. Neeland IJ, Yokoo T, Leinhard OD, et al. 21st century advances in multimodality imaging of obesity for care of the cardiovascular patient. JACC Cardiovasc Imaging. 2021;14(2):482-94. doi:10.1016/j.jcmg.2020.02.031.
5. Iankovskaia SV, Novikova EG, Epanchintseva EA, et al. Association of comorbid somatic pathology with fat distribution type and body mass index in men. Siberian Scientific Medical Journal. 2020;40(4):70-7. (In Russ.) doi:10.15372/SSMJ20200410.
6. Blaho M, Macháčková J, Dítě P, et al. Use of magnetic resonance imaging to quantify fat and steatosis in the pancreas in patients after bariatric surgery: a retrospective study. Obes Surg. 2022; 32(11):3666-74. doi:10.1007/s11695-022-06278-4.
7. Strelnikova MV, Sineglazova AV, Sumerkina VA, et al. Humoral mediators in men with acute coronary syndrome and hypertension. Arterial Hypertension. 2019;25(3):278-84. (In Russ.) doi:10.18705/1607-419X-2019-25-3-278-284.
8. Sineglazova AV, Faxrutdinova ASh, Parve SD, et al. Dyslipidaemic profile as an important dominator of cardiometabolic risk in young age. Modern Problems of Science and Education. 2023;2. (In Russ.) doi:10.17513/spno.32546. https://science-education.ru/ru/article/view?id=32546 (19 июня 2024).
9. Boytsov SA, Drapkina OM, Shlyakhto EV, et al. Epidemiology of cardiovascular diseases and their risk factors in regions of Russian Federation (ESSE-RF) study. Ten years later. Cardiovascular Therapy and Prevention. 2021;20(5):3007. (In Russ.) doi:10.15829/1728-8800-2021-3007.
10. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6-10. doi:10.1016/j.metabol.2018.09.005.
11. Kivimäki M, Strandberg T, Pentti J, et al. Bodymass index and risk of obesity-related complex multimorbidity: an observational multicohort study. Lancet Diabetes Endocrinol. 2022;10(4):253-63. doi:10.1016/S2213-8587(22)00033-X.
12. Canizares M, Hogg-Johnson S, Gignac MAM, et al. Increasing trajectories of multimorbidity over time: birth cohort differences and the role of changes in obesity and income. J Gerontol B Psychol Sci Soc Sci. 2018;73(7):1303-14. doi:10.1093/geronb/gbx004.
13. Chowdhury SR, Chandra Das D, Sunna TC, et al. Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis. EClinicalMedicine. 2023;57:101860. doi:10.1016/j.eclinm.2023.101860.
14. Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3(3):223-8. doi:10.1370/afm.272.
15. Nurieva AR, Parve SD, Sineglazova AV. Heterogeneous comorbidity in individuals with different phenotypes of obesity. Cureus. 2023;15(5):e38995. doi:10.7759/cureus.38995.
16. Drapkina OM, Samorodskaya IV, Starinskaya MA, et al. Obesity: assessment and tactics of patient management. Collective monograph. M.: izdatel`stvo OOO "Siliceya-Poligraf", 2021. p. 174. (In Russ.) ISBN: 978-5-9907556-0-4.
17. Salmón-Gómez L, Catalán V, Frühbeck G, et al. Relevance of body composition in phenotyping the obesities. Rev Endocr Metab Disord. 2023;24(5):809-23. doi:10.1007/s11154-023-09796-3.
18. de Oliveira Correia ET, Mechanick JI, Dos Santos Barbetta LM, et al. Cardiometabolicbased chronic disease: adiposity and dysglycemia drivers of heart failure. Heart Fail Rev. 2023; 28(1):47-61. doi:10.1007/s10741-022-10233-x.
19. Cosentino F, Verma S, Ambery P, et al. Cardiometabolic risk management: insights frm a European Society of Cardiology Cardiovascular Round Table. Eur Heart J. 2023;44(39):4141-56. doi:10.1093/eurheartj/ehad445.
20. Jones R, Junghard O, Dent J, et al. Development of the GerdQ, a tool for the diagnosis and management of gastrooesophageal reflux disease in primary care. Aliment Pharmacol Ther. 2009; 30(10):1030-8. doi:10.1111/j.1365-2036.2009.04142.x.
21. Chiu HY, Chen PY, Chuang LP, et al. Diagnostic accuracy of the Berlin questionnaire, STOP-BANG, STOP, and Epworth sleepiness scale in detecting obstructive sleep apnea: a bivariate meta-analysis. Sleep Med Rev. 2017;36:57-70. doi:10.1016/j.smrv.2016.10.004.
22. Ezhov MV, Kukharchuk VV, Sergienko IV, et al. Disorders of lipid metabolism. Clinical Guidelines 2023. Russian Journal of Cardiology. 2023;28(5):5471. (In Russ.) doi:10.15829/1560-4071-2023-5471.
23. Lazebnik LB, Golovanova EV, Turkina SV, et al. Non-alcoholic fatty liver disease in adults: clinic, diagnostics, treatment. Guidelines for therapists, third version. Experimental and Clinical Gastroenterology. 2021;1(1):4-52. (In Russ.) doi:10.31146/1682-8658-ecg-185-1-4-52.
24. Paul J, Shihaz AVH. Pancreatic steatosis: a new diagnosis and therapeutic challenge in gastroenterology. Arq Gastroenterol. 2020;57(2):216-20. doi:10.1590/s0004-2803.202000000-27.
25. Drapkina OM, Shutov AM, Efremova EV. Comorbidity, multimorbidity, dual diagnosis — synonyms or different terms? Cardiovascular Therapy and Prevention. 2019;18(2):65-9. (In Russ.) doi:10.15829/1728-8800-2019-2-65-69.
26. Shamurova YuYu, Kalev OF. Polypathy: monograph. M.: Publishing House "Pero", 2019. p. 191. (In Russ.) ISBN: 978-5-00150-195-4.
27. Zharkova OS, Sharopin KA, Seidova AS, et al. Construction of decision support systems in medicine based decision tree. Sovremenny`e naukoemkie texnologii. 2016;6:33-7. (In Russ.)
28. Mustafina SV, Vinter DA, Rymar OD, et al. Cardiometabolic risk factors in obese individuals and the risk of incident diabetes mellitus in 12-year prospective study. Ateroscleroz. 2021;17(1): 52-61. (In Russ.) doi:10.52727/2078-256X-2021-17-52-61.
29. Liu CA, Liu T, Ruan GT, et al. The relationship between fat distribution in central region and comorbidities in obese people: Based on NHANES 2011-2018. Front Endocrinol (Lausanne). 2023;14:1114963. doi:10.3389/fendo.2023.1114963.
30. Stumpf FMM, de Oliveira ASD, Faerstein E, et al. Cross-sectional associations between body mass index, waist circumference, and multimorbidity: Pró-Saúde study. Peer J. 2023;11:e14744. doi:10.7717/peerj.14744.
31. Peasey A, Bobak M, Kubinova R, et al. Determinants of crdiovascular disease and other non-communicable diseases in Central and Eastern Europe: rationale and design of the HAPIEE study. BMC Public Health. 2006;6:255. doi:10.1186/1471-2458-6-255.
32. Yang M, Zhang Y, Zhao W, et al. Individual and combined associations of body mass index and waist circumference with components of metabolic syndrome among multiethnic middleaged and older adults: A cross-sectional study. Front Endocrinol (Lausanne). 2023;14:1078331. doi:10.3389/fendo.2023.1078331.
33. Drapkina OM, Imaeva AE, Kutsenko VA, et al. Dyslipidemia in the Russian Federation: population data, associations with risk factors. Cardiovascular Therapy and Prevention. 2023;22(8S): 3791. (In Russ.) doi:10.15829/1728-8800-2023-3791.
34. Takale G, Handore A, Jeyakumar A, et al. Prevalence and determinants of multiple chronic conditions (MCC) among young adults in Indian households: an analysis of NFHS-5. J Health Popul Nutr. 2024;43(1):77. doi:10.1186/s41043-024-00560-0.
Supplementary files
Review
For citations:
Sineglazova A.V., Nurieva A.R. Comorbid obesity diseases and polypathies in young and middle-aged individuals. Cardiovascular Therapy and Prevention. 2025;24(6):4103. (In Russ.) https://doi.org/10.15829/1728-8800-2025-4103. EDN: ZKQUXH