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Title: The use of bioimpedance in pediatric health, nutrition, and disease

item SHYPAILO, ROMAN - Children'S Nutrition Research Center (CNRC)
item MOTIL, KATHLEEN - Children'S Nutrition Research Center (CNRC)

Submitted to: Journal of Pediatric Gastroenterology and Nutrition
Publication Type: Other
Publication Acceptance Date: 10/1/2018
Publication Date: 10/1/2018
Citation: Shypailo, R.J., Motil, K.J. 2018. The use of bioimpedance in pediatric health, nutrition, and disease. Journal of Pediatric Gastroenterology and Nutrition. 67(4):435-436.

Interpretive Summary:

Technical Abstract: Researchers continue to test and promote bioimpedance technology (BIA) for clinical use. BIA is used to estimate body composition. We summarized what is known about the technology so that readers can better understand its limitations. BIA often correlates well with other techniques, but the limits of agreement are usually very wide. This limits its accuracy. The equations used in BIA to estimate body composition are normally limited to specific populations. BIA measures water and body composition indirectly. Its calibration depend on validation techniques such as dual-energy X-ray absorptiometry (DXA) that can be susceptible to fluid imbalance. So those uncertainties are passed on to the BIA measurement. In pediatrics, BIA measurements are even more challenging since children differ from adults in hydration and in relative ratios of protein and mineral. Thus, BIA equations based on adults cannot be used for children. In addition, certain health issues such as renal disease, or deviations from normal physiology will affect BIA results. BIA does a better job of measuring water, rather than fat or lean mass. Researchers have also looked at the raw data values measured by BIA, like resistance and phase angle. Some of these show promise as indexes of certain diseases. They may be predictive of health status associated with disease. While it is tempting to continue to use BIA clinically for body composition, it may be preferable to focus on studying the raw values as disease indicators.