Relationships Between Blood Volume And Bioelectrical Impedance

Por: A. Stahn, Elmarie Terblanche e G. Strobel.

Athens 2004: Pre-olympic Congress

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Introduction
According to the follow-up to the National Institutes of Health Technology Assessment Conference on bioelectrical impedance analysis (BIA) the relationship between BIA and blood parameters is still poorly understood [1]. In vitro studies suggest that these relationships offer the potential for several future clinical applications. This has recently been confirmed by Varlet-Marie et al. who proposed BIA as a non-invasive evaluation of blood rheology [2]. Consequently, it was speculated that blood volume (BV) also explains a large source of variance in relation to BIA. Therefore, the aim of the present study was to investigate the relationship between BIA and BV and to determine if BIA provides a means to estimate the latter.

Methods
67 participants (35 men; 32 women) between 18-33 years volunteered for the study. Bioelectric impedance was measured using a Bodystat Quadscan 4000® multifrequency bioelectrical impedance analyzer (Bodystat LTD, Isle of Man, UK). The system applies a constant sinusoidal current of 200 μA at 5, 100 and 200 kHz. Reactance and resistance were calculated using the Bodystat® Phase Angle Software Program (Bodystat LTD, Isle of Man, UK). Results were used to transform serial in parallel values. Subsequently, impedance indices (Height2/impedance) were calculated at all frequencies. Blood, plasma as well as erythrocyte volume were determined using a standardized carbon monoxide closed-circuit rebreathing procedure. Carboxyhemoglobin, hemoglobin concentration ([Hb]), and hematocrit (Hct) were obtained from capillary blood [3]. Hct was corrected for trapped plasma (Hct x 0.96) but not for body Hct phenomenon [4]. Pearson correlations were calculated to examine the relationships between BIA and BV, PV and EV, respectively.

Results
Highly significant positive linear relationships could be demonstrated between BIA and BV, PV and EV at all fre-quencies (Table 1). The highest correlation coefficient was found between BIA and BV (r = 0.89), the lowest between BIA and PV (r = 0.83). Yet, differences between correlation coefficients did not reach statistical significance (P > 0.05).

Conclusion
Our results suggest there is a high degree of correlation between BIA and BV, EV and PV, respectively. This does not only provide some essential insight into applied research of BIA but may also extend the applications of the technique if further research can confirm the excellent relationships found in the present study. In particular, in situations where a direct measurement is not always practical, such as in epidemiological settings, BIA might be used to estimate the volume of blood.

References
[1]. Ellis K.J. et al. (1999). Nutrition, 15, 874-880.
[2]. Varlet-Marie E. et al. (2003). Clin. Hemorheol. Microcirc., 28 (3), 129-137.
[3]. Hütler, M. et al. (2000). Med. Sci. Sports Exerc., 32 (5), 1024-1027.
[4]. Burge C.M. et al. (1995). J. Appl. Physiol., 79, 623-631.

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