|Kehayias, Joseph - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Skahan, Amanda - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Itzkowitz, Laura - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Khodier, Maha - Department Of Veterans Affairs|
Submitted to: Journal of Nutrition Health and Aging
Publication Type: Abstract Only
Publication Acceptance Date: 3/24/2009
Publication Date: 7/5/2009
Citation: Kehayias, J., Skahan, A., Itzkowitz, L., Khodier, M. 2009. Bioelectrical Impedance Vector Analysis Identifies Sarcopenia in Nursing Home Residents. Journal of Nutrition Health and Aging. 13:S432-3.
Technical Abstract: Loss of muscle mass and water shifts between body compartments are contributing factors to frailty in the elderly. The body composition changes are especially pronounced in institutionalized elderly. We investigated the ability of single-frequency bioelectrical impedance analysis (BIA) to identify body composition deficiency in nursing home residents compared to free-living elderly Americans. Methods: Thirty-three nursing home residents (aged 72-93y) participated. Resistance (R) and reactance (Xc) values were measured at 50-kHz using the Xitron 4200 Hydra BIA instrument. Reference data for 2571 free-living adults aged 70-90 y was obtained from the NHANES III database (measured at 50-kHz using the Valhalla Scientific Body Composition Analyzer 1990B). The groups were compared using the method and bioelectrical impedance vector analysis (BIVA) software developed by Piccoli et al (Piccoli A, Pastori G: BIVA software, University of Padova, Italy, 2002). R and Xc values were standardized by the participant’s height (H) in meters. The mean R/H and Xc/H values were calculated for each group by sex. The ratio of resistance to height (Ohm/m) was plotted on the major axis against the ratio of reactance to height (Ohm/m) on the minor axis. Bioelectrical impedance vector analysis software was used to plot the mean R/H and Xc/H values for each sex on a RXc graph with 95% confidence ellipses. Results: Comparison of the distribution of mean vectors in each population illustrates a significant difference in the body composition of nursing home residents compared to the non-institutionalized American population. Nursing home vectors were outside the 75% tolerance ellipses of the reference population. Conclusion: Single frequency BIA successfully identifies the body composition deficiencies present in nursing home residents associated with sarcopenia and fluid redistribution. However, more detailed methods (such as stable isotopes) should be used for monitoring the status of individuals rather than groups.