New equations for estimating body cell mass from bioimpedance parallel models in healthy older Germans
Abstract
The objectives of this study were to assess for elderly Germans the validity of existing equations for predicting body cell mass (BCM) and to develop from single- and multifrequency bioimpedance (SFBIA, MFBIA) models new prediction equations. In a data-splitting approach, validation and cross-validation were performed in 160 healthy elderly (60- to 90-yr) subjects. BCM was determined using a tetrapolar bioimpedance analyzer (800 μA; 4 fixed frequencies: 1, 5, 50, and 100 kHz; electrodes placed to hand, wrist, ankle, and foot) and whole body 40 K counting as a reference method. New prediction equations were derived by multiple stepwise regression analysis. The Bland-Altman procedure was used for methods comparison. Relative to whole body counting, the manufacturer's equation overestimated BCM by 9% in men ( P < 0.0001, paired t-test) and 4% in women ( P = 0.002). Compared with the manufacturer's equation, the newly derived equations ( r = 0.92, RMSE = 6–9%) improved accuracy (pure error = 13 vs. 7–8%) and reduced bias and limits of agreement. SFBIA and MFBIA equations did not differ in precision or accuracy. We conclude that the newly derived equations improved BCM estimates in the elderly compared with existing equations. There was no advantage of MFBIA over SFBIA equations.
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Concerns with applicability were unclear in 12 studies.
“Concerns with applicability were high in 19 studies [37, 42–59] and unclear [41, 50, 60–69] in 12 studies due to the restricted sample size.”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [63]
There is one equation for estimating BCM in elderly.
“There is one equation for estimating BCM [63], four equations for assessing appendicular LSM [46, 67, 92, 93], and one equation for assessing SMM [95] suitable for males and females.”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [63]
Concerning foot-to-hand technology for elderly, thirteen equations are suitable for both sexes.
“Concerning foot-to-hand technology, three predictive equations were suitable for males [36, 49, 53] and four for females only [36, 49, 53, 97], while thirteen equations suitable for both sexes [38, 46, 63, 67, 89–93, 95].”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [63]
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References 42 · Cited by 45
- Authors
- Dittmar, M., & Reber, H.
- Affiliations
- Johannes Gutenberg University Mainz (DE)
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- ORCID
- Dittmar, Manuela
- Venue
- American Journal of Physiology-Endocrinology and Metabolism
- Publisher
- American Physiological Society
- Published
- 2001-11-01
- Volume
- 281
- Issue
- 5
- Pages
- E1005-E1014
- ISSN
- 0193-1849 (ISSN-L)
- 1522-1555
- OpenAlex
- W2288030777
- Cited by
- 45
- References
- 42
- Citations by year
- 2025: 1 · 2024: 4 · 2023: 2 · 2022: 4 · 2021: 3 · 2020: 1 · 2018: 2 · 2017: 1 · 2016: 1 · 2015: 1 · 2014: 4 · 2013: 1 · 2012: 4
- FWCI
- 0.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Physiology-Endocrinology and Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical and Bioimpedance Tomography
- Keywords
- body cell mass, bioimpedance, prediction equations, older adults, multifrequency bioimpedance, equation validation
- MeSH terms
- Aged, Aged, 80 and over, Body Composition, Extracellular Space, Female, Germany, Humans, Male, Mathematics, Middle Aged, Models, Biological, Potassium Radioisotopes, Regression Analysis, Sensitivity and Specificity, Sex Characteristics, Whole-Body Counting, Bone Density, Linear Models, Electric Impedance
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