Bioelectrical impedance analysis for body composition assessment: reflections on accuracy, clinical utility, and standardisation

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Bioelectrical impedance analysis is an extremely popular method for assessment of body composition. Despite its wide-spread use over the past thirty years, its accuracy and clinical value is still questioned. Most frequently, criticisms focus on its purported poor absolute accuracy and that different impedance analysers or prediction equations fail to measure body composition identically. This perspective review highlights that the magnitude of errors associated with impedance methods are not dissimilar to those observed for so-called gold standard methods. It is argued that the focus on statistically significant but small differences between methods can obscure operational equivalence and that such differences may be of minor clinical significance. Finally, the need for better standardization of protocols and the need for consensus on what is a minimal clinically important difference between methods is highlighted.

Related collections

Most cited references 27

Record: found
Abstract: not found
Article: not found

Users' Guides to the Medical Literature

Roman Jaeschke (1994)

0 comments Cited 120 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: phase angle and impedance ratio.

Henry Lukaski, Ursula Kyle, Jens Kondrup (2017)

Malnutrition affects prognosis in many groups of patients. Although screening tools are available to identify adults at risk for poor nutritional status, a need exists to improve the assessment of malnutrition by identifying the loss of functional tissues that can lead to frailty, compromised physical function, and increased risk of morbidity and mortality, particularly among hospitalized and ill patients and older adults. Bioimpedance analysis (BIA) offers a practical approach to identify malnutrition and prognosis by assessing whole-body cell membrane quality and depicting fluid distribution for an individual.

0 comments Cited 117 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement

YANG BAI, PAUL HIBBING, YOUNGWON KIM … (2018)

Purpose Statistical equivalence testing is more appropriate than conventional tests of difference to assess the validity of physical activity (PA) measures. This paper presents the underlying principles of equivalence testing and gives three examples from PA and fitness assessment research. Methods The three examples illustrate different uses of equivalence tests. Example 1 uses PA data to evaluate an activity monitor’s equivalence to a known criterion. Example 2 illustrates the equivalence of two field-based measures of physical fitness with no known reference method. Example 3 uses regression to evaluate an activity monitor’s equivalence across a suite of 23 activities. Results The examples illustrate the appropriate reporting and interpretation of results from equivalence tests. In the first example, the mean criterion measure is significantly within +/−15% of the mean PA monitor. The mean difference is 0.18 METs and the 90% confidence interval of [−0.15, 0.52] is inside the equivalence region of [−0.65, 0.65]. In the second example, we chose to define equivalence for these two measures as a ratio of mean values between 0.98 and 1.02. The estimated ratio of mean VO2 values is 0.99, which is significantly (p=0.007) inside the equivalence region. In the third example, the PA monitor is not equivalent to the criterion across the suite of activities. The estimated regression intercept and slope are −1.23 and 1.06. Neither confidence interval is within the suggested regression equivalence regions. Conclusions When the study goal is to show similarity between methods, equivalence testing is more appropriate than traditional statistical tests of differences (e.g., ANOVA and t-tests).