Elsevier

Clinical Nutrition

Volume 39, Issue 2, February 2020, Pages 447-454
Clinical Nutrition

Original article
Phase angle and bioelectrical impedance vector analysis in the evaluation of body composition in athletes

https://doi.org/10.1016/j.clnu.2019.02.016Get rights and content

Highlights

  • Classic and specific BIVA, and PA were tested against DXA and dilution techniques.

  • Classic BIVA correctly detected changes of TBW, but not those of %FM.

  • Specific BIVA detected changes of %FM, but not those of TBW.

  • PA (equal in classic and specific BIVA) was sensitive to ECW/ICW ratio and ICW.

Summary

Aims

To analyze the association of classic and specific bioelectrical impedance vector analysis (BIVA) and phase angle with reference techniques for the assessment of body composition in athletes.

Methods

202 athletes of both sexes (men: 21.5 ± 5.0; women: 20.7 ± 5.1) engaged in different sports were evaluated during the in-season period. Bioelectrical resistance (R, ohm) and reactance (Xc, ohm) were obtained with a phase-sensitive 50 kHz bioelectrical impedance analysis device. The classic and specific BIVA procedures, which respectively correct bioelectrical values for body height (R/H and Xc/H, ohm/m) and body geometry (Rsp and Xcsp, ohm cm), were applied. Dual energy X-ray absorptiometry was used as the reference method to assess fat-mass (FM), fat-free mass (FFM) and %FM. Deuterium dilution and bromide dilution where used as the criterion method for total body water (TBW) and extracellular water (ECW), respectively. Intracellular water (ICW) was calculated as TBW minus ECW.

Results

Specific bioelectrical values (Rsp, Xcsp, Zsp) were positively correlated with FM and %FM (%FM; Zsp men: r = 0.569, p < 0.001; Zsp women: r = 0.773, p < 0.001). Classic values (R/H, Xc/H, Z/H) were negatively correlated with FM and FFM, but were correlated with %FM only in men (Z/H men: r = −0.214, p = 0.013; Z/H women: r = 0.218, p = 0.097). As to body fluid, classic BIVA showed strong associations (Z/H men: r = −0.880, p < 0.001; Z/H women: r = −0.829, p < 0.001) with TBW, whereas Zsp was not correlated. Phase angle was negatively correlated with ECW/ICW ratio in both sexes (men: r = −0.493, p < 0.001; women: r = −0.408, p < 0.001) and positively with ICW (men: r = 0.327, p < 0.001; women: r = 0.243, p = 0.080).

Conclusions

Specific BIVA turns out to be more accurate for the analysis of %FM in athletes, while it does not correctly evaluate TBW, for which classic BIVA appears to be a suitable approach. Phase angles, and hence both BIVA approaches, can detect ECW/ICW changes.

Introduction

The analysis and monitoring of body composition is fundamental in sport, because of its relevance to athletes' health and performance, and to team success. Such analysis can be performed in different contexts and with different approaches, i.e. in cross-sectional studies aimed to characterise sporting group samples, in longitudinal researches finalised to define short-term or long-term changes, or in applications aimed to detect and monitor muscle injuries [1]. Variations of body composition can interest diversely athletes practicing different sport, because of their different exercise type and requirements for body physique and composition. In general, lean mass is considered a predictor of muscular fitness [2], [3]. Furthermore, while overhydration is quite uncommon in athletes, physiological dehydration processes can be induced by physical activity, leading to hypotonic, isotonic, or hypertonic dehydration [4].

Several techniques can be used to assess body composition in athletes. At the molecular level, though the four-compartment model is considered the reference method for body composition assessment [5], dual energy X-ray absorptiometry (DXA), a three-compartment model, has been recognized as a precise and accurate technique for determining fat-mass (FM) and fat-free mass (FFM) [6]. Still, DXA is an expensive method to be used in the field setting as a minimum space to accommodate the DXA machine, a potential radiation shielding, and specialized technicians to perform and analyze the exams are required [7]. Considering the main FFM component, total-body water (TBW), its amount and the content of the extracellular water compartment (ECW) can be accurately assessed through dilution techniques, specifically using deuterium and bromide dilution, respectively [8]. However, these analytic procedures are time-consuming, costly and laborious, thus compromising their routine use in a clinical or field setting [9]. Therefore, simple methods to determine water compartments, easily applied during training and competition, are required.

Bioelectrical impedance analysis (BIA) is a fast, safe and non-invasive method to obtain quantitative estimates of body composition. Multifrequency BIA and, specifically, bioimpedance spectroscopy is preferable for fluid volume measurements, though for general body composition assessment BIA at 50 kHz is more widely used [10], [11]. Bioelectrical impedance (Z, ohm) is composed by resistance (R, ohm) and reactance (Xc, ohm) [Z=(R2+Xc2)0.5]. R represents the opposition offered by the body to the flow of an alternating electrical current and is inversely related to the water and electrolyte content of tissues. Xc, which is detectable by phase sensitive devices only, is related to the capacitance properties of the cell membrane and to variations that can occur depending on its integrity, function and composition [12]. Phase angle (PA) [PA = arctn Xc/R 180/π] is determined by the time delay occurring when the electric current passes the cell membrane [13], [14].

Bioelectrical impedance can be applied using prediction equations [15]. However, the dependency on population-specific equations and hydration status is considered the major weakness of conventional bioelectrical-impedance analysis [16]. Alternatively, the analysis can be performed using raw data, namely phase angles, or bioelectrical impedance vectors, i.e. phase angle and vector length jointly, as in the bioelectrical impedance vector analysis approaches (BIVA; [17], [18], [19]).

Bioelectrical impedance vector analysis, both classic [14], [17] and specific BIVA [20], is based on the analysis of impedance vectors (at 50 kHz), projected on a RXc graph in relation to tolerance ellipses, or for intergroup comparisons (confidence ellipses). The two BIVA approaches differ each other in that classic BIVA analyses bioelectrical values standardized for subject's height (which represents the conductor's length), whereas in specific BIVA R and Xc values are corrected also for cross-sectional areas, in order to reduce the effect of body dimensions. According to classic BIVA [17], variations of bioelectrical vectors along the major axis of tolerance ellipses indicate changes in total body water (dehydration towards the upper pole, fluid overload towards the lower pole). The minor axis refers to variations of absolute amount of body cell mass, FM, and FFM (left side: more mass; right side: less mass) and to variations of extracellular/intracellular water ratio (ECW/ICW) (low values in the left side). Within classic tolerance ellipses, the left upper side would correspond to athletic individuals, whereas the left lower side to obese ones. In specific BIVA [18], [19], the major axis relates to %FM variation (higher values towards the upper pole), while the minor axis gives the same information as in classic BIVA (more mass and lower ECW/ICW ratio on the left side). In fact, the minor axis is mainly related to variations of phase angle, which is unaffected by the correction.

PA allows the interpretation of total body water and body cell mass [14], [21]. However, the analysis of PA only, without considering the information furnished by vector length, can lead to interpretation errors. In fact, groups of individuals characterized by quite identical PA, but different vector lengths, may show different body fluids or %FM [22]. The vectorial approach appears to be more efficient, as it considers both influential variables, phase angle and vector length.

PA, classic and specific BIVA have been applied in different groups, particularly obese, athletic subjects, and in the elderly, and in the clinical setting [13], [14], [16], [20], [23]. A growing body of literature on BIVA in sport and exercise research and practice is also noticeable (see the review by Castizo-Olier et al. [1] and more recently [24], [25]), and specific BIVA has been proposed as a promising approach in this field [1].

Although largely used, reliability studies of phase angle, classic or specific BIVA in the assessment of body composition [18], [19], [21], [26], or of hydration [21], [26], [27], [28], [29] through reference techniques are very scarce in the general population and totally lacking in athletes [1].

Therefore, the aim of this research was to evaluate the accuracy of phase angle, classic and specific BIVA in body composition assessment of athletes, focusing the analysis on absolute values of body mass (FM, FFM, TBW, ECW, ICW), and on values independent from body dimensions (%FM, ECW/ICW). At this purpose, DXA was used as a reference for FM, FFM and %FM, and dilution techniques for TBW and ECW.

Section snippets

Subjects

This was a cross-sectional, observational study on 202 athletes (139 men and 63 women) over 16 years of age (men: 21.5 ± 5.0; women: 20.7 ± 5.1). The sample included athletes involved in a total of 11 sports (Athletics, Basketball, Handball, Judo, Karate, Pentathlon, Rugby, Soccer, Swimming, Triathlon, Volleyball; suppl. table 1). The results of a medical screening indicated that all subjects were in good health. The following inclusion criteria were used: 1) 10 or more hours of training per

Results

Athletes of both sexes showed a condition of normal weight, with low mean values of BMI and low average values of %FM, as expected in a sample of young sportive subjects (Table 1).

Anthropometric and body composition measurements showed significant differences between sexes. Consistently with the known pattern of sexual dimorphism in adults, men showed higher values of all anthropometric measurements, FFM, TBW, ECW, ICW, while women showed higher bioelectrical values (with the only exception of

Discussion

The present study, for the first time, analysed the association of PA, classic and specific BIVA with DXA and dilution techniques, for body composition assessment in athletes. Data showed that classic BIVA correctly detect differences of TBW, but was weak in the assessment of %FM. On the contrary, specific BIVA detected changes of %FM, but not those of TBW. The relation with FM and FFM was different in classic and specific BIVA: classic bioelectrical values were negatively related to body

Conclusions

The present study shows that specific BIVA is more accurate than classic BIVA in the %FM assessment in athletes, whereas the classic method is able to analyze body fluids with a higher accuracy. PA (and hence both classic and specific BIVA) was sensitive to ECW/ICW ratio. Physicians and sports coaches should consider using both BIVA approaches (classic and specific) to obtain reliable body composition evaluations in athletes. More research is needed to analyse the sensitivity of BIVA to each

Acknowledgments

The authors thank the athletes for participating in the study. This work was supported by the Portuguese Foundation for Science and Technology (Grants: PTDC/DES/69495/2006 and PTDC/DES/098963/2008). Silvia Stagi acknowledges Sardinia Regional Government for the financial support of her PhD scholarship (P.O.R. Sardegna F.S.E. Operational Programme, European Social Fund 2014-2020 - Axis III Education and training, Thematic goal 10, Priority of investment 10ii, Specific goal 10.5., Action

References (52)

  • B. Bronhara et al.

    Fuzzy linguistic model for bioelectrical impedance vector analysis

    Clin Nutr

    (2012)
  • A. Piccoli

    Estimation of fluid volumes in hemodialysis patients: comparing bioimpedance with isotopic and dilution methods

    Kidney Int

    (2014)
  • S.N. Cheuvront et al.

    Physiologic basis for understanding quantitative dehydration assessment

    Am J Clin Nutr

    (2013)
  • J. Castizo-Olier et al.

    Bioelectrical impedance vector analysis (BIVA) in sport and exercise: systematic review and future perspectives

    PLoS One

    (2018)
  • P. Henriksson et al.

    Associations of fat mass and fat-free mass with physical fitness in 4-year-old children: results from the MINISTOP trial

    Nutrients

    (2016)
  • A. Köhler et al.

    Cardiopulmonary fitness is strongly associated with body cell mass and fat-free mass: the Study of Health in Pomerania (SHIP)

    Scand J Med Sci Sports

    (2018)
  • R.A. Oppliger et al.

    Hydration testing of athletes

    Sports Med

    (2002)
  • S.B. Heymsfield et al.

    Multi-component molecular-level body composition reference methods: evolving concepts and future directions

    Obes Rev

    (2015)
  • R.J. Toombs et al.

    The impact of recent technological advances on the trueness and precision of DXA to assess body composition

    Obesity

    (2012)
  • M. Dehghan et al.

    Is bioelectrical impedance accurate for use in large epidemiological studies?

    Nutr J

    (2008)
  • K.J. Ellis et al.

    Human hydrometry: comparison of multifrequency bioelectrical impedance with2H2O and bromine dilution

    J Appl Physiol

    (1998)
  • M.Y. Jaffrin

    Body composition determination by bioimpedance: an update

    Curr Opin Clin Nutr Metab Care

    (2009)
  • J.R. Moon

    Body composition in athletes and sports nutrition: an examination of the bioimpedance analysis technique

    Eur J Clin Nutr

    (2013)
  • M.C.G. Barbosa-Silva et al.

    Bioelectrical impedance analysis in clinical practice: a new perspective on its use beyond body composition equations

    Curr Opin Clin Nutr Metab Care

    (2005)
  • National Institutes of Health (NIH)

    Bioelectrical impedance analysis in body composition measurement: assessment conference statement

    Am J Clin Nutr

    (1996)
  • R. Buffa et al.

    Accuracy of Specific BIVA for the Assessment of Body Composition in the United States Population

    PLoS One

    (2013)
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