Bioimpedance Vector Analysis of Elite, Subelite, and Low-Level Male Volleyball Players

in International Journal of Sports Physiology and Performance
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Purpose: To establish a specific player profile on body-composition parameters and to provide a data set of bioelectric impedances values for male volleyball players. Methods: The study included 201 athletes (age 26.1 [5.4] y, height 191.9 [9.7] cm, weight 86.8 [10.8] kg) registered in the Italian volleyball divisions. The athletes were divided into 3 groups: The elite group comprised 75 players participating in the 1st (Super Lega) division, the subelite group included 65 athletes performing in the 2nd (Serie A2) division, and the low-level group included 61 players participating in the 3rd (Serie B) division. Bioelectric impedance, body weight, and height of the athletes were measured in the second half of the competitive season. In addition, bioelectrical impedance vector analysis was performed. Results: The elite group showed a greater amount of fat-free mass (FFM) and total body water (TBW) and a lower fat mass (FM) than the subelite group (P < .05). In addition, the elite players were taller and heavier and had a higher FFM, FM, TBW, and body cellular mass than the low-level athletes (P < .05). Finally, the mean impedance vectors of the elite group significantly differed from those measured in the normal population and in the other 2 groups (P < .05). Conclusions: This study provides an original data set of body-composition and bioelectric impedance reference values of elite male volleyball players. The results might be useful for interpretation of individual bioimpedance vectors and for defining target regions for volleyball players.

The authors are with the Dept of Biomedical and Neuromotor Science, University of Bologna, Bologna, Italy.

Campa (francesco.campa3@unibo.it) is corresponding author.
  • 1.

    Saunders MJ, Blevins JE, Broeder CE. Effects of hydration changes on bioelectrical impedance in endurance trained individuals. Med Sci Sports Exerc. 1998;30:885–892. PubMed ID: 9624647 doi:10.1097/00005768-199806000-00017

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Piccoli A, Rossi B, Pillon L, Bucciante G. A new method for monitoring body fluid variation by bioimpedance analysis: the RXc graph. Kidney Int. 1994;46:534–539. PubMed ID: 7967368 doi:10.1038/ki.1994.305

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Brocherie F, Girard O, Forchino F, Al Haddad H, Dos Santos GA, Millet GP. Relationships between anthropometric measures and athletic performance, with special reference to repeated-sprint ability, in the Qatar national soccer team. J Sports Sci. 2014;32(13):1243–1254. PubMed ID: 24742185 doi:10.1080/02640414.2013.862840

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Andreoli A, Monteleone M, Van Loan M, Promenzio L, Tarantino U, De Lorenzo A. Effects of different sports on bone density and muscle mass in highly trained athletes. Med Sci Sports Exerc. 2001;33(4):507–511. PubMed ID: 11283423. doi:10.1097/00005768-200104000-00001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Carrasco-Marginet M, Castizo-Olier J, Rodríguez-Zamora L, et al. Bioelectrical impedance vector analysis (BIVA) for measuring the hydration status in young elite synchronized swimmers. PLoS ONE. 2017;12(6):0178819. PubMed ID: 28591135 doi:10.1371/journal.pone.0178819

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Micheli ML, Pagani L, Marella M, et al. Bioimpedance and impedance vector patterns as predictors of league level in male soccer players. Int J Sports Physiol Perform. 2014;9(3):532–539. PubMed ID: 23881291 doi:10.1123/ijspp.2013-0119

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Kyle UG, Bosaeus I, De Lorenzo AD, et al. Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. 2004;23:1226–1243. PubMed ID: 15380917 doi:10.1016/j.clnu.2004.06.004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Kotler DP, Burastero S, Wang J, Pierson RN Jr. Prediction of body cell mass, fat-free mass, and total body water with bioelectrical impedance analysis: effects of race, sex, and disease. Am J Clin Nutr. 1996;64:489S–497S. PubMed ID: 8780369 doi:10.1093/ajcn/64.3.489S

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Piccoli A, Pastori G. BIVA Software. Padova, Italy: Department of Medical and Surgical Sciences, University of Padua; 2002. (Available at E-mail: apiccoli@unipd.it)

    • Search Google Scholar
    • Export Citation
  • 10.

    Piccoli A, Nigrelli S, Caberlotto A, et al. Bivariate normal values of the bioelectrical impedance vector in adult and elderly populations. Am J Clin Nutr. 1995;61(2):269–270. PubMed ID: 7840061 doi:10.1093/ajcn/61.2.269

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Mascherini G, Gatterer H, Lukaski H, Burtscher M, Galanti G. Changes in hydration, body-cell mass and endurance performance of professional soccer players through a competitive season. J Sports Med Phys Fitness. 2015;55(7–8):749–755. PubMed ID: 26470638

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Buffa R, Mereu E, Comandini O, Ibanez ME, Marini E. Bioelectrical impedance vector analysis (BIVA) for the assessment of two-compartment body composition. Eur J Clin Nutr. 2014;68(11):1234–1240. PubMed ID: 25139557 doi:10.1038/ejcn.2014.170

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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