Abstract. Metabolic syndrome is a global health issue associated with an increased risk of cardiovascular disease and mortality. While the role of obesity in metabolic syndrome development is well-established, data on the influence of fat-free mass on the metabolic profile remain contradictory. Some studies suggest a protective role of muscle tissue, while others demonstrate a direct association between fat free mass and insulin resistance. This highlights the need to explore new integrative body composition indices for assessing the severity of metabolic disorders. Methods. This cross-sectional study involved 216 men aged 25–50 years. Body composition was assessed using an InBody 720 analyzer to determine absolute fat-free mass and visceral fat area. The ratio 〖Log〗_10(FFM/VFA) was calculated. Metabolic syndrome severity (MetS z-score) was evaluated using a standardized score incorporating waist circumference, blood pressure, and fasting levels of triglycerides, glucose, and high-density lipoprotein cholesterol. Statistical analysis included Pearson's correlation, one-way ANOVA with Tukey's post-hoc test, and linear regression models. Results. A significant negative correlation was found between 〖Log〗_10(FFM/VFA) and the MetS z-score (r = -0.69; p < 0.05). Regression analysis showed that a 0.01 increase in 〖Log〗_10(FFM/VFA) was associated with a 0.04-point decrease in the MetS z-score. In contrast, absolute FPM demonstrated a moderate positive correlation with MetS severity (r = 0.62; p < 0.05). Comparison of the extreme quartiles (Q1 and Q4) revealed that a decrease in 〖Log〗_10(FFM/VFA) was accompanied by a statistically significant (p < 0.01) worsening of all individual MetS components. Conclusions. The ratio of fat-free mass to visceral fat area is a more sensitive predictor of metabolic syndrome severity than the isolated assessment of fat-free mass. These findings underscore the importance of considering muscle quality and fat distribution in the context of cardiometabolic risk, warranting further investigation in prospective studies.
Autors:
Sverchkov V. V., Bykov E. V.
Keywords:
#Metabolic syndrome
List of literature:
- GBD 2021 Diabetes Collaborators. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2023;402(10397):203-234. doi: 10.1016/S0140-6736(23)01301-6.
- Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, et al. Geographic distribution of metabolic syndrome and its components in the general adult population: A meta-analysis of global data from 28 million individuals. Diabetes Res Clin Pract. 2022;188:109924. doi: 10.1016/j.diabres.2022.109924.
- Tomic D, Shaw JE, Magliano DJ. The burden and risks of emerging complications of diabetes mellitus. Nat Rev Endocrinol. 2022;18(9):525-539. doi: 10.1038/s41574-022-00690-7.
- Chen F, Shi Y, Yu M, et al. Joint effect of BMI and metabolic status on mortality among adults: a population-based longitudinal study in United States. Sci Rep. 2024;14(1):2775. doi: 10.1038/s41598-024-53229-3.
- Jiang J, Cai X, Pan Y, et al. Relationship of obesity to adipose tissue insulin resistance. BMJ Open Diabetes Res Care. 2020;8(1):e000741. doi: 10.1136/bmjdrc-2019-000741.
- Després JP, Carpentier AC, Tchernof A, Neeland IJ, Poirier P. Management of Obesity in Cardiovascular Practice: JACC Focus Seminar. J Am Coll Cardiol. 2021;78(5):513-531. doi: 10.1016/j.jacc.2021.05.035.
- Wu SE, Chen WL. Not the enemy: potential protective benefits of superficial subcutaneous adipose tissue. Pol Arch Intern Med. 2022;132(7-8):16237. doi: 10.20452/pamw.16237.
- Takamura T, Kita Y, Nakagen M, et al. Weight-adjusted lean body mass and calf circumference are protective against obesity-associated insulin resistance and metabolic abnormalities. Heliyon. 2017;3(7):e00347. doi: 10.1016/j.heliyon.2017.e00347.
- Shao Y, Li L, Zhong H, Wang X, Hua Y, Zhou X. Anticipated correlation between lean body mass to visceral fat mass ratio and insulin resistance: NHANES 2011-2018. Front Endocrinol (Lausanne). 2023;14:1232896. doi: 10.3389/fendo.2023.1232896.
- Lagacé JC, Marcotte-Chenard A, Paquin J, Tremblay D, Brochu M, Dionne IJ. Increased odds of having the metabolic syndrome with greater fat-free mass: counterintuitive results from the National Health and Nutrition Examination Survey database. J Cachexia Sarcopenia Muscle. 2022;13(1):377-385. doi: 10.1002/jcsm.12856.
- Ghachem A, Lagacé JC, Brochu M, Dionne IJ. Fat-free mass and glucose homeostasis: is greater fat-free mass an independent predictor of insulin resistance? Aging Clin Exp Res. 2019;31(4):447-454. doi: 10.1007/s40520-018-0993-y.
- von Elm E, Altman D, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344-349. doi: 10.1016/j.jclinepi.2007.11.008.
- DeBoer M, Gurka M. Clinical utility of metabolic syndrome severity scores: considerations for practitioners. Diabetes Metab Syndr Obes. 2017;10:65-72. doi: 10.2147/DMSO.S101624.
- Sverchkov VV, Bykov EV. [Influence of appendicular muscle mass on the risk of chronic diseases and mortality: a review of studies with Mendelian randomization]. Adaptivnaya Fizicheskaya Kultura. 2024;98(2):17-20. Russian. (In Russ).
- Rehunen SK, Kautiainen H, Korhonen PE, Eriksson JG. Lean body mass is not beneficial, but may be detrimental for glucose tolerance - Splitting body mass index according to body composition. Prim Care Diabetes. 2020;14(6):747-752. doi: 10.1016/j.pcd.2020.05.003.
- Fisher G, Windham ST, Griffin P, Warren JL, Gower BA, Hunter GR. Associations of human skeletal muscle fiber type and insulin sensitivity, blood lipids, and vascular hemodynamics in a cohort of premenopausal women. Eur J Appl Physiol. 2017;117(7):1413-1422. doi: 10.1007/s00421-017-3634-9.
- Gueugneau M, Coudy-Gandilhon C, Théron L, et al. Skeletal muscle lipid content and oxidative activity in relation to muscle fiber type in aging and metabolic syndrome.
J Gerontol A Biol Sci Med Sci. 2015;70(5):566-576. doi: 10.1093/gerona/glu086. - Poggiogalle E, Lubrano C, Gnessi L, et al. The decline in muscle strength and muscle quality in relation to metabolic derangements in adult women with obesity. Clin Nutr. 2019;38(5):2430-2435. doi: 10.1016/j.clnu.2019.01.028.
- Huang B, DePaolo J, Judy RL, et al. Relationships between body fat distribution and metabolic syndrome traits and outcomes: A mendelian randomization study. PLoS One. 2023;18(10):e0293017. doi: 10.1371/journal.pone.0293017.
- Alser M, Naja K, Elrayess MA. Mechanisms of body fat distribution and gluteal-femoral fat protection against metabolic disorders. Front Nutr. 2024;11:1368966. doi: 10.3389/fnut.2024.1368966.
- Borges MC, Oliveira IO, Freitas DF, et al. Obesity-induced hypoadiponectinaemia: the opposite influences of central and peripheral fat compartments. Int J Epidemiol. 2017;46(6):2044-2055. doi: 10.1093/ije/dyx022.
- Koster A, Stenholm S, Alley DE, et al. Body fat distribution and inflammation among obese older adults with and without metabolic syndrome. Obesity (Silver Spring). 2010;18(12):2354-2361. doi: 10.1038/oby.2010.86.
- Arner P. Differences in lipolysis between human subcutaneous and omental adipose tissues. Ann Med. 1995;27(4):435-438. doi: 10.3109/07853899709002451.
- Karpe F, Pinnick KE. Biology of upper-body and lower-body adipose tissue--link to whole-body phenotypes. Nat Rev Endocrinol. 2015;11(2):90-100. doi: 10.1038/nrendo.2014.185.
More about the authors:
Evgenii V. Bykov ‒ Doctor of Medical Sciences, Professor, Professor of the Department of Sports Medicine and Physical Rehabilitation. Director of the Olympic Sports Research Institute.Ural State University of Physical Culture. Chelyabinsk, Russia. E-mail: bev58@yandex.ru
Vadim V. Sverchkov – Junior Researcher, Research Institute of Olympic Sports, Ural State University of Physical Culture, Chelyabinsk, e-mail: vadim.sverchkov@yandex.ru