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Japanese Journal of Physical Fitness and Sports Medicine ; : 125-136, 2006.
Article in Japanese | WPRIM | ID: wpr-362358

ABSTRACT

The purpose of this study was to investigate the accuracy of estimating human body composition changes using bioelectrical impedance (BI) methods during a weight-loss intervention. Subjects were forty-three obese men (age : 49.2±10.5 yr, BMI : 27.8±1.7 kg/m<sup>2</sup>) who completed a 14-week weight-loss intervention. In all subjects, fat mass (FM) and fat-free mass (FFM) were assessed by dual energy x-ray absorptiometry (DXA) as well as single- and multi-frequency BI methods (SBIM, MBIM) before and after the intervention. Resistance parameters were measured by SBIM and MBIM (SBIM : R<sub>50</sub> ; MBIM : R∞, R0, and Rfc). In nine subjects these variables were also measured at weeks 1 and 4. Weight decreased (P<0.05) by -8.0±3.2 kg during the intervention while FFM changes averaged -0.4±1.6 kg (DXA), -2.0±1.5 kg (SBIM), and -1.6±1.7 kg (MBIM). BI methods overestimated FFM before the intervention (before ; DXA : 54.4±4.8 kg, SBIM : 56.5±4.3 kg, MBIM : 55.9±4.5 kg). In nine subjects, FFM measured by SBIM (FFM<sub>SBIM</sub>) and MBIM (FFM<sub>MBIM</sub>) was similar to FFM measured by DXA(FFM<sub>DXA</sub>)(after ; DXA : 54.6±5.4 kg, SBIM : 54.6±3.8 kg, MBIM : 54.6±4.1 kg), although BI methods overestimated the FFM before the intervention (before ; DXA : 54.9±5.1 kg, SBIM : 56.9±3.8 kg, MBIM : 56.3±4.4 kg). The ΔFM<sub>SBIM</sub> and ΔFM<sub>MBIM</sub> were highly correlated with the ΔFM<sub>DXA</sub>(SBIM : r=0.87, MBIM : r=0.88). The ΔFFM<sub>SBIM</sub> andΔFFM<sub>MBIM</sub> were significantly correlated with the ΔFFM<sub>DXA</sub>(SBIM : r=0.54, MBIM : r=0.49). The ΔR<sub>50</sub> and ΔRfc were also significantly correlated with the ΔFFM<sub>DXA</sub>(R<sub>50</sub> : r=-0.63, Rfc : r=-0.48). These results suggest that during a weight-loss intervention, 1) BI methods and DXA provide similar estimates of human body composition change, although they overestimate FFM in obese men, and 2) changes of resistance parameters observed with BI methods may estimate human body composition change more accurately.

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