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Phenotyping in clinical nutrition

Development and validation of bioelectrical impedance prediction equations estimating regional lean soft tissue mass in middle-aged adults

European Journal of Clinical Nutrition volume 77, pages 202–211 (2023)Cite this article

Subjects

Abstract

Background/Objectives

Bioelectrical impedance (BIA) whole-body and regional raw parameters have been used to develop prediction models to estimate whole-body lean soft tissue (LSTM), with less attention being given to the development of models for regional LSTM. Therefore, we aimed to develop and validate BIA-derived equations predicting regional LSTM against dual x-ray absorptiometry (DXA) in healthy adults.

Subjects/Methods

149 adults were included in this cross-sectional investigation. Whole-body and regional LSTM were assessed by DXA, and raw bioelectrical parameters of distinct body regions were measured using a 50 kHz phase sensitive BIA analyzer. BIA-derived equations were developed using a stepwise multiple linear regression approach in 2/3 of the sample and cross-validated in the remaining sample.

Results

Slopes and intercepts of predicted LSTM and DXA measured LSTM did not differ from 1 and 0, respectively, for each region (p ≥ 0.05), with the exception for the trunk (p < 0.05). The BIA-derived equations exhibited a strong relationship (p < 0.001) between the predicted and measured LSTM for each of the following body regions: right and left arms (R = 0.94; R = 0.96), right and left legs (R = 0.88; R = 0.88), upper body (R = 0.96), lower body (R = 0.89), right and left sides of the body (R = 0.94; R = 0.94), and trunk (R = 0.90). Agreement analyses revealed no associations between the differences and the means of the predicted and DXA-derived LSTM.

Conclusion

The developed BIA-derived equations provide a valid estimate of regional LSTM in middle-aged healthy adults, representing a cost-effective and time-efficient alternative to DXA for the assessment and identification of LSTM imbalances in both clinical and sport-specific contexts.

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Fig. 1: Relationship between the measured and predicted LSTM.
Fig. 2: Bland-Altman plots of the difference between observed and predicted LSTM.

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Data availability

Data are available from the corresponding author on reasonable request.

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Acknowledgements

We would like to express our gratitude to the participants for their contribution in the present investigation. This investigation was conducted at Interdisciplinary Center of the Study of Human. Performance (CIPER), Faculty of Human Kinetics of the University of Lisbon, and supported by. fellowships from the Portuguese Foundation for Science and Technology (grant to GBR: 2020.07856.BD; grant to IRC: SFRH/BD/149394/2019; grant within the unit I&D 472 -UIDB/00447/2020).

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Authors and Affiliations

  1. Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz-Quebrada, Portugal

    Luís B. Sardinha, Gil B. Rosa, Megan Hetherington-Rauth, Inês R. Correia, João P. Magalhães & Analiza M. Silva

  2. Department of Kinesiology and Public Health Education, Hyslop Sports Center, University of North Dakota, Grand Forks, ND, USA

    Henry Lukaski

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  1. Luís B. Sardinha
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Contributions

LBS conceived and planned the experiments. GBR, JPM and IRC carried out the experiments and data collection. GBR, MHR and AMS did the data analysis. LBS, GBR, AMS and HL contributed to the interpretation of the results. LBS took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis, and manuscript.

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Correspondence to Luís B. Sardinha.

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The authors declare no competing interests.

Ethical approval

The investigation protocol was approved by the Ethics Committee of the Faculty of Human Kinetics (12/2020), University of Lisbon, and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before participation.

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Sardinha, L.B., Rosa, G.B., Hetherington-Rauth, M. et al. Development and validation of bioelectrical impedance prediction equations estimating regional lean soft tissue mass in middle-aged adults. Eur J Clin Nutr 77, 202–211 (2023). https://doi.org/10.1038/s41430-022-01224-0

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