Maria Cristina Gonzalez1, Thiago G Barbosa-Silva2, Renata M Bielemann2, Dympna Gallagher3, Steven B Heymsfield4. 1. Post-graduation Program on Health and Behavior, Catholic University of Pelotas, Pelotas, Brazil; cristinagbs@hotmail.com. 2. Post-graduation Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil; 3. The New York Obesity Nutrition Research Center, St. Luke's-Roosevelt Hospital Center, College of Physicians and Surgeons, Columbia University, New York, NY; and. 4. Pennington Biomedical Research Center, Baton Rouge, LA.
Abstract
BACKGROUND: The phase angle (PA) has been used as a prognostic marker in several clinical situations. Nevertheless, its biological meaning is not completely understood. OBJECTIVE: We verified how body-composition components could explain the PA. DESIGN: The trial was a cross-sectional study involving 1442 participants (women: 58.5%; Caucasian: 40.2%) from body-composition studies. Labeled tritium dilution and total-body potassium were used to estimate total-body water (TBW) and intracellular water (ICW), respectively. Extracellular water (ECW) and the ECW:ICW ratio were estimated from the difference and the ratio of these values. Fat-free mass (FFM) and fat mass (FM) were estimated with the use of dual-energy X-ray absorptiometry, underwater weighing (UWW), and TBW. The PA was estimated with the use of a single-frequency bioelectrical impedance analysis system. Correlations between the PA and all body-composition variables were evaluated. A multivariate linear regression analysis was performed to adjust for the effects of body-composition variables on the PA variability. All analyses were performed separately by sex. RESULTS: Compared with men, women exhibited significantly larger ECW:ICW ratios and FM. The highest positive correlation was shown between the PA and FFM obtained with the use of UWW (both sexes). The highest negative correlation was shown between the PA and ECW:ICW ratios for both sexes. Age, race, height, ECW:ICW, and FFM from UWW were significant PA determinants in a multivariate linear regression model. Even after adjustment for all significant covariates, the explained PA variance was low (adjusted R(2) = 0.539 and 0.421 in men and women, respectively). The greatest impact on the total PA prediction in both men and women were age, FFM, and height. CONCLUSIONS: Age is the most significant PA predictor in men and women followed by FFM and height. The ECW:ICW contribution may explain the association of the PA observed in the clinical setting and in people who are obese.
BACKGROUND: The phase angle (PA) has been used as a prognostic marker in several clinical situations. Nevertheless, its biological meaning is not completely understood. OBJECTIVE: We verified how body-composition components could explain the PA. DESIGN: The trial was a cross-sectional study involving 1442 participants (women: 58.5%; Caucasian: 40.2%) from body-composition studies. Labeled tritium dilution and total-body potassium were used to estimate total-body water (TBW) and intracellular water (ICW), respectively. Extracellular water (ECW) and the ECW:ICW ratio were estimated from the difference and the ratio of these values. Fat-free mass (FFM) and fat mass (FM) were estimated with the use of dual-energy X-ray absorptiometry, underwater weighing (UWW), and TBW. The PA was estimated with the use of a single-frequency bioelectrical impedance analysis system. Correlations between the PA and all body-composition variables were evaluated. A multivariate linear regression analysis was performed to adjust for the effects of body-composition variables on the PA variability. All analyses were performed separately by sex. RESULTS: Compared with men, women exhibited significantly larger ECW:ICW ratios and FM. The highest positive correlation was shown between the PA and FFM obtained with the use of UWW (both sexes). The highest negative correlation was shown between the PA and ECW:ICW ratios for both sexes. Age, race, height, ECW:ICW, and FFM from UWW were significant PA determinants in a multivariate linear regression model. Even after adjustment for all significant covariates, the explained PA variance was low (adjusted R(2) = 0.539 and 0.421 in men and women, respectively). The greatest impact on the total PA prediction in both men and women were age, FFM, and height. CONCLUSIONS: Age is the most significant PA predictor in men and women followed by FFM and height. The ECW:ICW contribution may explain the association of the PA observed in the clinical setting and in people who are obese.
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