Bioelectric impedance phase angle and body composition.

Department of Pediatrics, Wright State University School of Medicine, Dayton, OH.
American Journal of Clinical Nutrition (Impact Factor: 6.92). 08/1988; 48(1):16-23.
Source: PubMed

ABSTRACT The use of bioelectric impedance phase angle for predicting body composition was determined in 53 males and 69 females 9-62 y of age. The phase angle describes the amount of reactance (Xc) in a conductor relative to the amount of resistance (R). Bioelectric resistance (R) and reactance (Xc) were determined for the whole body and separately for arm, leg, and trunk. Weight, stature, and skinfold thicknesses were measured. Body composition was determined from densitometry. Phase angles for the trunk (phi t), leg (phi 1), and whole body (phi w) had significant (p less than 0.05) negative correlations with percent body fat (%BF) in each sex, and positive correlations with fat-free mass (FFM) in males. In multiple regression analyses, phi t was associated significantly with %BF after controlling for age, mean skinfold thickness, and weight/stature2 in each sex. Bioelectric phase angle for the trunk may be useful for predicting %BF in clinical and survey research.

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    ABSTRACT: We hypothesize that longitudinal changes in phase angle (PA) have independent associations with changes in inflammatory parameters over time and consequently with long-term survival in patients on maintenance hemodialysis (MHD). The aim of the present study was to determine the effect of change in nutritional and inflammatory parameters over time on change in PA and on subsequent mortality in patients on MHD. A 2-y prospective longitudinal study was performed on 91 prevalent HD patients (57 men and 34 women), followed by an additional 3 y of clinical observations. Dietary intake, biochemical markers of nutrition, body composition, and interleukin (IL)-6 levels were measured at baseline and at 6, 12, 18, and 24 mo following enrollment. In a linear mixed-effect model adjusted for baseline demographic and clinical parameters, each pg/mL increase in IL-6 over time was associated with a decrease in PA levels of 0.001°/2-y (P = 0.003 for IL-6 × time interaction). PA remained associated with the rate of change in IL-6 even after controlling for extracellular water and fat mass. Changes in PA over time were associated with inverse linear changes in IL-6 (adjusted r = -0.32; P = 0.005) and consequently with mortality risk. For each 1° increase in PA, the crude and adjusted mortality hazard ratios using Cox models with effect of time-varying risk were 0.62 (95% confidence interval [CI], 0.54-0.71) and 0.61 (95% CI, 0.53-0.71), respectively. Additionally, longitudinal changes in PA exhibited significant associations with slopes of changes over time in main nutritional markers. Longitudinal changes in PA appear to be reliable in detecting changes in nutritional and inflammatory parameters over time, a combination that may contribute to the understanding of its prognostic utility.
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    ABSTRACT: The main purpose of the present study was to assess the prognostic value of the bioelectrical phase angle (PA) in patients with heart failure independently of other parameters of a poor prognosis. This retrospective study included 389 patients with heart failure. Anthropometric, body composition, clinical, biochemical, and echocardiographic data were collected from all patients. The quartiles were obtained for the PA, and patients were classified according to the quartiles into four groups. The endpoint was all-cause mortality. A Cox proportional hazards regression analysis was performed to estimate the adjusted relative risks, and 95% confidence intervals were obtained for the potential predictors of death. Patients below the lowest quartile of PA (<4.2°) had decreased mean body mass index, handgrip strength, and hemoglobin values and a larger proportion of patients in New York Heart Association functional class III and renal failure. The Kaplan-Meier survival analysis among PA groups showed a better survival for patients above the highest quartile of PA (≥5.7°), and survival decreased as the PA decreased. The Cox regression analysis found that a PA <4.2 was an independent predictor of mortality (relative risk 3.08, 95% confidence interval 1.06-8.99), adjusting for age, hemoglobin levels, and diabetes, compared with a PA ≥5.7. In this study population, a smaller PA was associated with malnutrition markers such as decreased body mass index, handgrip strength, and hemoglobin values and with a poor New York Heart Association functional class and renal failure. Adjusting for age, hemoglobin levels, and diabetes, a PA <4.2 was found to be an independent predictor of all-cause mortality in chronic heart failure.
    Nutrition 03/2012; 28(9):901-5. DOI:10.1016/j.nut.2011.11.033
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    ABSTRACT: Malnutrition is regularly associated with weight loss and changes in body composition, which lead to an increase in disability, complications and mortality. Bioelectric impedance analysis (BIA) is a simple and non-invasive bedside body composition analysis technique. In particular, bioelectric impedance phase angle (PA) has been shown to predict prognosis and mortality in several clinical conditions. The purpose of this study was to determine the relationship of BIA measurements and hospital mortality in multimorbid geriatric patients. The data obtained from the routine clinical admissions of 1071 consecutive patients (783 women and 288 men, age 81.4±8.5 years) to a geriatric hospital unit was analyzed retrospectively. A significant difference of PA (50 kHz) between survivors (4.2±1.1°) and non-survivors (3.6±1.2°; p<0.001) of the hospital stay could be detected. Subjects with a PA below 3.5° showed a significant fourfold increased hospital mortality of 20% (95% CI=15-24%) compared to all other subjects (5%; 95% CI=4-7%). No calculated parameters of BIA reflecting body composition were associated with hospital mortality. Although the extent to which the PA may be regarded as a marker of nutritional state is still controversial, it was associated with hospital mortality in geriatric patients.
    Archives of gerontology and geriatrics 11/2010; 51(3):290-4. DOI:10.1016/j.archger.2009.12.002


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