4.4 Article

Disease-related malnutrition but not underweight by BMI is reflected by disturbed electric tissue properties in the bioelectrical impedance vector analysis

Journal

BRITISH JOURNAL OF NUTRITION
Volume 100, Issue 3, Pages 590-595

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0007114508911545

Keywords

disease-related malnutrition; bioelectrical impedance vector analysis; subjective global assessment; BMI; phase angle; gastrointestinal disease

Funding

  1. Charite Umversit itsmedizin Berlin [05/25 369]

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The calculation of body composition Using bioelectrical impedance analysis in sick and hospitalized patients is hampered due to altered hydration state. We wanted to investigate how disease-related malnutrition assessed by the Subjective Global Assessment (SGA) is reflected in the bioelectrical impedance vector analysis. Patients with benign gastrointestinal disease (n 242) were entered in the study. Nutritional status was assessed by SGA. Arm muscle and fat area were estimated by anthropometry, muscle function was determined by hand grip strength. Whole body impedance measurements were made at 50kHz. Ninety-eight patients were considered well nourished (SGA A), ninety-four were classified moderately malnourished (SGA B) and fifty patients were classified severely malnourished (SGA C) according to the SGA. The mean vector was significantly displaced between SGA C and SGA A and B, showing comparable resistance with a significantly reduced reactance, indicating comparable hydration but loss of dielectrical mass of soft tissues. This distinctive vector migration was not seen when studying the patients grouped according to BMI. In conclusion, disease-related malnutrition as assessed by the SGA is associated with a distinctive bioelectrical vector migration, implying that abnormal tissue structure and not reduced body mass only occurs in disease-related malnutrition. These disturbances are not seen in underweight according to BMI. Bioelectrical impedance vector analysis appears to be an attractive tool to identify disease-related malnutrition and to monitor nutritional intervention.

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