Skeletal muscle mass and device-estimated resting cardiac output in special medical group students: A cross-sectional study in Russia
DOI:
https://doi.org/10.58524/jcss.v5i3.1445Keywords:
Bioimpedance analysis, Cardiac output, Heart rate variability, Skeletal muscle mass, Special medical groupAbstract
Background: Special medical group (SMG) students at Russian universities are a heterogeneous population whose health conditions limit their participation in standard physical education. Integrated physiological characterisation remains limited, as earlier work has rarely combined body composition, hemodynamic, and autonomic data within a single protocol.
Aims: The study aimed to identify the body-composition variable most strongly and independently associated with device-estimated resting cardiac output and stroke volume in SMG students, while accounting for fat mass, visceral adipose tissue, phase angle, and body mass index.
Methods: In this cross-sectional study, 277 students aged 18-21 were assessed using the MS FIT diagnostic complex, which combines segmental bioimpedance, pulse-wave analysis, and short-term heart rate variability. Cardiac output and stroke volume were device-derived estimates. Spearman correlations, multiple linear regression, and tertile comparisons were computed in SPSS 26.0.
Result: The full five-predictor models explained 69.2% of the variance in cardiac output and 53.3% in stroke volume. Skeletal muscle mass had the largest standardized coefficient in both models (std. β=0.84 and 0.64; p<.001), and fat mass contributed independently to cardiac output (std. β=0.41; p<.001). Visceral adipose tissue and phase angle were not significant; body mass index was significant only for stroke volume.
Conclusion: Among the variables examined, skeletal muscle mass showed the strongest independent association with device-estimated resting cardiac output and stroke volume, with fat mass also contributing to cardiac output. These cross-sectional associations suggest that body mass index alone may be insufficient for describing the resting hemodynamic profile. Potential effects of skeletal muscle mass on resting hemodynamics require confirmation in longitudinal and interventional studies.
References
Adetunji, A., Uche-Orji, C., Ezebialu, C., Ahaiwe, V., Akinleye, O., Atanda, A. T., & Ojo, A. (2025). The prevalence and risk factors of pre-hypertension and hypertension among clinical students at the University of Ibadan, Nigeria. BMC Cardiovascular Disorders, 25(1), 393. https://doi.org/10.1186/s12872-025-04852-z
Akamatsu, Y., Kusakabe, T., Arai, H., Yamamoto, Y., Nakao, K., Ikeue, K., Ishihara, Y., Tagami, T., Yasoda, A., Ishii, K., & Satoh-Asahara, N. (2022). Phase angle from bioelectrical impedance analysis is a useful indicator of muscle quality. Journal of Cachexia, Sarcopenia and Muscle, 13(1), 180–189. https://doi.org/10.1002/jcsm.12860
Alibrahim, M. S., Said, M. A., Bursais, A. K., Atta, I. I., Abdelrahman, M. A., Mohamed, H. H., Hassan, A. K., Alaqil, A. I., Almudaires, N. S., & Alamer, N. M. A. (2025). Risk factors for cardiovascular disease among Saudi students: Association with BMI, current smoking, level of physical activity, and dietary habits. PLOS ONE, 20(5), e0321206. https://doi.org/10.1371/journal.pone.0321206
Almurdi, M. M. (2024). Postural balance and functional mobility in relation to BMI and body composition among female students at a College of Applied Medical Sciences: A cross-sectional study. Clinics, 79, 100401. https://doi.org/10.1016/j.clinsp.2024.100401
Banks NF, Rogers EM, Stanhewicz AE, Whitaker KM, Jenkins NDM. (2023). Resistance exercise lowers blood pressure and improves vascular endothelial function in individuals with elevated blood pressure or stage-1 hypertension. American Journal of Physiology-Heart and Circulatory Physiology, 326(1), H256-H269. https://doi.org/10.1152/ajpheart.00386.2023
Berezina, T., & Litvinova, A. (2026). Using Virtual Reality Sports Simulators in Adaptive Physical Education of Female College Students with Functional Disabilities. Education Sciences, 16(4), 580. https://doi.org/10.3390/educsci16040580
Bernárdez-Vázquez, R., Raya-González, J., Castillo, D., & Beato, M. (2022). Resistance training variables for optimization of muscle hypertrophy: An umbrella review. Frontiers in Sports and Active Living, 4, 949021. https://doi.org/10.3389/fspor.2022.949021
Bocharin, I., Guryanov, M., Mukhina, I., Limarenko, O., Kolokoltsev, M., Vrachinskaya, T., Romanova, E., Aganov, S., & Martusevich, A. (2022). Comparative analysis of methods for determining some hemodynamic parameters for students. Journal of Physical Education and Sport, 22(11), 2663–2668. https://doi.org/10.7752/jpes.2022.11338
Bocharin, I., Guryanov, M., Romanova, E., Pozdeeva, A., Kolokoltsev, M., Vorozheikin, A., Malkin, A., Poboronchuk, T., Lobastova, R., & Kovalev, A. (2023). Instrumental control of functional indicators in students with health deviation. Journal of Physical Education and Sport, 23(5), 1096–1102. https://doi.org/10.7752/jpes.2023.05137
Chantler, P. D., Lakatta, E. G., & Najjar, S. S. (2008). Arterial-ventricular coupling: mechanistic insights into cardiovascular performance at rest and during exercise. Journal of Applied Physiology, 105(4), 1342–1351. https://doi.org/10.1152/japplphysiol.90600.2008
Cornelissen, V. A., & Smart, N. A. (2013). Exercise training for blood pressure: A systematic review and meta-analysis. Journal of the American Heart Association, 2(1), e004473. https://doi.org/10.1161/JAHA.112.004473
Cvijetic, S., Macan, J., Boschiero, D., & Ilich, J. Z. (2023). Body fat and muscle in relation to heart rate variability in young-to-middle age men: A cross sectional study. Annals of Human Biology, 50(1), 108–116. https://doi.org/10.1080/03014460.2023.2180089
de Borba, E. L., Ceolin, J., Ziegelmann, P. K., Bodanese, L. C., Gonçalves, M. R., Cañon-Montañez, W., & Mattiello, R. (2022). Phase angle of bioimpedance at 50 kHz is associated with cardiovascular diseases: Systematic review and meta-analysis. European Journal of Clinical Nutrition, 76(10), 1366–1373. https://doi.org/10.1038/s41430-022-01131-4
de Borba, E. L., Wichbold, C., Ceolin, J., Gonçalves, M. R., Cañon-Montañez, W., Padoin, A. V., & Mattiello, R. (2024). Exploring the association between phase angle of bioimpedance at 50 kHz and cardiovascular risk. BMC Cardiovascular Disorders, 24(1), 606. https://doi.org/10.1186/s12872-024-04211-4
Dlamini, S. N., Norris, S. A., & Micklesfield, L. K. (2025). Associations between skeletal muscle mass and elevated blood pressure are independent of body fat: A cross-sectional study in young adult women of African ancestry. British Journal of Nutrition, 133(3), 316-330. https://doi.org/10.1017/S0007114525000029
Dorofieieva, O., Yarymbash, K., & Skrypchenko, I. (2025). Features of physical rehabilitation of students with various diseases studying at universities. Sports Science & Health Advances, 3(1), 341–348. https://doi.org/10.60081/SSHA.3.1.2025.341-348
Ferreira, G.O.C., Ferrari, G., Langer, R.D., Cossio-Bolaños M., Gomez-Campos R., Lázari E., & Moraes A.M. (2024). Phase angle and its determinants among adolescents: influence of body composition and physical fitness level. Scientific Reports, 14, 13697. https://doi.org/10.1038/s41598-024-62546-6
Han, T. S., & Lean, M. E. J. (2016). A clinical perspective of obesity, metabolic syndrome and cardiovascular disease. JRSM Cardiovascular Disease, 5. https://doi.org/10.1177/2048004016633371
Heinonen, I. (2025). Cardiac output limits maximal oxygen consumption, but what limits maximal cardiac output? Experimental Physiology, 110(5), 666–674. https://doi.org/10.1113/EP091594
Hostrup, M., & Onslev, J. (2022). The beta2-adrenergic receptor – a re-emerging target to combat obesity and induce leanness? The Journal of Physiology, 600(5), 1209–1227. https://doi.org/10.1113/JP281819
Hunt, B. E., Davy, K. P., & Seals, D. R. (1998). Role of central circulatory factors in the fat-free mass–maximal aerobic capacity relation across age. American Journal of Physiology-Heart and Circulatory Physiology, 275(4), H1178–H1182. https://doi.org/10.1152/ajpheart.1998.275.4.H1178
Hu, Z., Jiang, S., Hu, C., Shen, B., & Gu, J. (2025). The effects of circuit-based resistance training on blood pressure, arterial stiffness, and body composition in community-dwelling older adults: A systematic review and meta-analysis. Frontiers in Physiology, 16, 1609013. https://doi.org/10.3389/fphys.2025.1609013
Jirků, J., & Křížová, J. (2025). Phase angle in bioelectrical impedance: New perspectives in health and body composition assessment. Physiological Research, 74, 1007–1019. https://doi.org/10.33549/physiolres.935629
Kirsten I de Oude, Roy G Elbers, Heike Gerger, Dederieke A M Maes-Festen, & Alyt Oppewal (2025), The effect of different resistance exercise training intensities on cardiovascular risk factors: a systematic review and meta-analysis, European Heart Journal Open, 5(5), oeaf093. https://doi.org/10.1093/ehjopen/oeaf093
Mabe-Castro, D., Castillo-Aguilar, M., Mabe-Castro, M., Méndez Muñoz, R., Basualto-Alarcón, C., & Nuñez-Espinosa, C. A. (2024). Associations between physical fitness, body composition, and heart rate variability during exercise in older people: Exploring mediating factors. PeerJ, 12, e18061. https://doi.org/10.7717/peerj.18061
Middlemiss, J. E., Miles, K. L., McDonnell, B. J., Yasmin, Maki-Petaja, K. M., Cockcroft, J. R., Wilkinson, I. B., & McEniery, C. M. (2016). Mechanisms underlying elevated SBP differ with adiposity in young adults: the Enigma study. Journal of Hypertension, 34(2), 290–297. https://doi.org/10.1097/HJH.0000000000000798
Musijowska M, & Kwilosz E. (2024). Association between Physical Activity Level, Body Composition, and Phase Angle in University Students from Bioelectrical Impedance Analysis (BIA). J Clin Med, 13(10), 2743. https://doi.org/10.3390/jcm13102743
Miazgowski, T., Miazgowski, B., Kaczmarkiewicz, A., & Kopeć, J. (2021). Associations of circulating irisin with 24-h blood pressure, total and visceral fat, and metabolic parameters in young adult hypertensives. Archives of Endocrinology and Metabolism, 65(2), 137–143. https://doi.org/10.20945/2359-3997000000333
Moonen, H. P. F. X., & Van Zanten, A. R. H. (2021). Bioelectric impedance analysis for body composition measurement and other potential clinical applications in critical illness. Current Opinion in Critical Care, 27(4), 344–353. https://doi.org/10.1097/MCC.0000000000000840
Morris, B. A., Sinaei, R., & Smart, N. A. (2024). Resistance is not futile: A systematic review of the benefits, mechanisms and safety of resistance training in people with heart failure. Heart Failure Reviews, 29(4), 827–839. https://doi.org/10.1007/s10741-024-10402-0
Munoz, M. L., van Roon, A., Riese, H., Thio, C., Oostenbroek, E., Westrik, I., de Geus, E. J. C., Gansevoort, R., Lefrandt, J., Nolte, I. M., & Snieder, H. (2015). Validity of (ultra-)short recordings for heart rate variability measurements. PLOS ONE, 10(9), e0138921. https://doi.org/10.1371/journal.pone.0138921
Nussinovitch, U., Elishkevitz, K. P., Katz, K., Nussinovitch, M., Segev, S., Volovitz, B., & Nussinovitch, N. (2011). Reliability of ultra-short ECG indices for heart rate variability. Annals of Noninvasive Electrocardiology, 16(2), 117–122. https://doi.org/10.1111/j.1542-474X.2011.00417.x
Paluch, A. E., Boyer, W. R., Franklin, B. A., Laddu, D., Lobelo, F., Lee, D.-C., McDermott, M. M., Swift, D. L., Webel, A. R., & Lane, A. (2024). Resistance exercise training in individuals with and without cardiovascular disease: 2023 update: A scientific statement from the American Heart Association. Circulation, 149(3), e217–e231. https://doi.org/10.1161/CIR.0000000000001189
Páramo-Lira, A., Camarillo-Romero, S., de Jesús Garduño-García, J., Cruz-López, P., Abarca-Castro, E. A., Talavera-Peña, A. K., & Reyes-Lagos, J. J. (2026). Associations between body composition and autonomic cardiorespiratory modulation in young adults. Physiological Reports, 14, e70760. https://doi.org/10.14814/phy2.70760
Podberezko, N. A. (2023). Osobennost' praktiki provedeniya fizkul'turno-sportivnykh meropriyatiy dlya studentov s otkloneniyami v sostoyanii zdorov'ya [The specifics of physical culture and sports events for students with health deviations]. Adaptivnaya Fizicheskaya Kul'tura [Adaptive Physical Culture], (4(96)), 33–34.
Rosa, G.B., Lukaski, H.C. & Sardinha, L.B. (2025). The science of bioelectrical impedance-derived phase angle: Insights from body composition in youth. Rev Endocr Metab Disord, 26, 603–624. https://doi.org/10.1007/s11154-025-09964-7
Rossi RC, Vanderlei LC, Gonçalves AC, Vanderlei FM, Bernardo AF, Yamada KM, da Silva NT, & de Abreu LC. (2015). Impact of obesity on autonomic modulation, heart rate and blood pressure in obese young people. Autonomic Neuroscience: Basic and Clinical, 193, 138–141. https://doi.org/10.1016/j.autneu.2015.07.424
Schierbauer J, Ficher S, Zimmermann P, Wachsmuth NB, & Schmidt WFJ (2022) Cardiac stroke volume in females and its correlation to blood volume and cardiac dimensions. Front. Physiol, 13, 895805. https://doi.org/10.3389/fphys.2022.895805
Siedler, M. R., Rodriguez, C., Stratton, M. T., Harty, P. S., Keith, D. S., Green, J. J., Boykin, J. R., White, S. J., Williams, A. D., DeHaven, B., Florez, C. M., & Tinsley, G. M. (2023). Assessing the reliability and cross-sectional and longitudinal validity of fifteen bioelectrical impedance analysis devices. British Journal of Nutrition, 130(5), 827–840. https://doi.org/10.1017/S0007114522003749
Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5, 258. https://doi.org/10.3389/fpubh.2017.00258
Son JW, Han B-D, Bennett JP, Heymsfield S, & Lim S. (2025). Development and clinical application of bioelectrical impedance analysis method for body composition assessment. Obesity Reviews, 26(1), e13844. https://doi.org/10.1111/obr.13844
Spataeva, M. Kh., Bebinova, O. N., Patrina, S. G., & Salugin, F. V. (2024). Issledovanie dinamiki zdorov'ya studentov raznykh meditsinskikh grupp v tekhnicheskom vuze [Investigation of health dynamics of students from different medical groups at a technical university]. Obzor Pedagogicheskikh Issledovaniy [Review of Pedagogical Research], 4(6), 278–284. https://doi.org/10.58224/2687-0428-2024-6-4-278-284
Srikanthan, P., & Karlamangla, A. S. (2014). Muscle mass index as a predictor of longevity in older adults. The American Journal of Medicine, 127(6), 547–553. https://doi.org/10.1016/j.amjmed.2014.02.007
Terekhina, E. N., Bakhareva, A. S., Burnashov, Ya. V., & Nenashev, A. I. (2023). Otsenka metabolicheskogo statusa i komponentnogo sostava tela studentov spetsial'noy meditsinskoy gruppy v nachale uchebnogo goda [Assessment of metabolic status and body composition in special medical group students at the beginning of the academic year]. Human. Sport. Medicine, 23(2), 7–15. https://doi.org/10.14529/hsm230201
Vincent, J.-L. (2008). Understanding cardiac output. Critical Care, 12(4), 174. https://doi.org/10.1186/cc6975
Yuri, G., Santillana, N., Soto, L., Pereira, A., Corvalán, C., & Cifuentes, M. (2026). Association between metabolic and endocrine parameters with visceral adiposity index–defined adipose tissue dysfunction in young adult males. Journal of Obesity, Article 5233463, 8 pages. https://doi.org/10.1155/jobe/5233463
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ivan Bocharin, Maxim Guryanov, Elena Romanova, Natalya Balashkevich, Sergey Mironov, Asylbek Eshiev, Yaroslav Kiseliv, Elena Rychagova, Alyona Zaripova

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

