Preview

Problems of Endocrinology

Advanced search

Interchangeability of different indirect methods for determining body composition

https://doi.org/10.14341/probl13538

Abstract

BACKGROUND: Determination of body composition components — muscle and fat mass — is an important step in clinical and epidemiological studies. The most common methods for quantitative determination of body composition are indirect methods. However, the variety of methods and models of devices used makes direct comparison of data at both group and individual levels difficult.

AIM: The aim of the study is to analyze the consistency of estimates of absolute values of fat and lean body mass, as well as the proportion of body fat mass, obtained using bioimpedance analyzers ABC-02 «Medas» (STC Medas, Russia), 770InBody (InBody, Korea) and ultrasound scanner BodyMetrix BX2000 (IntelaMetrix, USA) in a group of men and women.

MATERIALS AND METHODS: An observational, single-center, cross-sectional, uncontrolled study was conducted. The main anthropometric characteristics (height and weight, waist circumference) were measured. Body composition was determined by bioimpedancemetry (BIA) using the octopolar scheme on the 770InBody device and the tetrapolar scheme on the ABC-02 Medass device and ultrasound scanning using the BodyMetrix BX2000 (BM) ultrasound scanner. The absolute (FM) and relative amount of body fat (PBF) and lean body mass were calculated.

RESULTS: A total of 48 people (38 women and 10 men) aged 24 to 74 years were examined. The anthropometric characteristics of the examined subjects were presented in a wide range. A strong correlation was found for all pairs of body composition components: the minimum value for the pair PBF ABC-BM was 0.853 [0.730, 0.913], the maximum was 0.988 [0.977, 0.993] for the pair FM ABC-InBody. Also, significant statistical differences (p<0.001) were found for all pairs of measurements, except for PBF determined by the BIA method. High agreement (CCC>0.95) of BIA estimates of the absolute amount of fat mass was shown, moderate agreement (CCC 0.9–0.95) is characteristic of the PBF determined by different BIA analyzers, and for all other pairs the agreement of measurements can be assessed as weak (CCC<0.90).

CONCLUSION: The best agreement at the group and individual levels was found for FM estimates by two different BIA analyzers (InBody and ABC).

About the Authors

E. A. Bondareva
Lopukhin Federal research and clinical center of physical-chemical medicine, Federal medical biological agency
Russian Federation

Elvira A. Bondareva, PhD

1a Malaya Pirogovskaya street, 119435 Moscow



B. A. Garasko
Lopukhin Federal research and clinical center of physical-chemical medicine, Federal medical biological agency
Russian Federation

Boris A. Garasko, PhD

Moscow



N. N. Khromov-Borisov
Commission on Pseudoscience of Russian Academy of Sciences
Russian Federation

Nikita N. Khromov-Borisov, PhD

Moscow



N. V. Mazurina
I.I. Dedov Endocrinology Research Centre
Russian Federation

Natalya V. Mazurina, MD. PhD

Moscow



E. V. Ershova
I.I. Dedov Endocrinology Research Centre
Russian Federation

Ekaterina V. Ershova, MD. PhD

Moscow



K. A. Komshilova
I.I. Dedov Endocrinology Research Centre
Russian Federation

Kseniya A. Komshilova, PhD

Moscow



E. A. Troshina
I.I. Dedov Endocrinology Research Centre
Russian Federation

Ekaterina A. Troshina, MD. PhD, Professor

Moscow



References

1. Price KL, Earthman CP. Update on body composition tools in clinical settings: computed tomography, ultrasound, and bioimpedance applications for assessment and monitoring. European journal of clinical nutrition. 2019;73(2):187-193. doi: https://doi.org/10.1038/s41430-018-0360-2

2. Tinsley GM. Five-component model validation of reference, laboratory and field methods of body composition assessment. The British journal of nutrition. 2021;125(11):1246-1259. doi: https://doi.org/10.1017/S0007114520003578

3. Johnson KE, Miller B, Gibson AL, McLain TA, Juvancic-Heltzel JA, Kappler RM, Otterstetter R. A comparison of dual-energy X-ray absorptiometry, air displacement plethysmography and A-mode ultrasound to assess body composition in college-age adults. Clinical physiology and functional imaging. 2017;37(6):646-654. doi: https://doi.org/10.1111/cpf.12351

4. Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J. 2008;7:26. doi: https://doi.org/10.1186/1475-2891-7-26

5. Vaquero-Cristóbal R, Catarina-Moreira A, Esparza-Ros F, Barrigas C, Albaladejo-Saura M, Vieira F. Skinfolds compressibility and digital caliper’s time response in skinfold measurement in male and female young adults. J Int Soc Sports Nutr. 2023;20(1):2265888. doi: https://doi.org/10.1080/15502783.2023.2265888

6. Araújo D, Teixeira VH, Carvalho P, Amaral TF. Exercise induced dehydration status and skinfold compressibility in athletes: an intervention study. Asia Pac J Clin Nutr. 2018;27(1):189-194. doi: https://doi.org/10.6133/apjcn.022017.20

7. García-Almeida JM, García-García C, Vegas-Aguilar IM, et al. Nutritional ultrasound: Conceptualization, technical considerations and standardization. Endocrinol Diabetes Nutr (Engl Ed). 2023;70 Suppl 1:74-84. doi: https://doi.org/10.1016/j.endien.2022.11.010

8. Bullen BA, Quaade F, Olessen E, Lund SA. Ultrasonic reflections used for measuring subcutaneous fat in humans. Hum Biol. 1965;37(4):375-384

9. Booth RA, Goddard BA, Paton A. Measurement of fat thickness in man: a comparison of ultrasound, Harpenden calipers and electrical conductivity. Br J Nutr. 1966;20(4):719-725. doi: https://doi.org/10.1079/bjn19660073

10. Marín Baselga R, Teigell-Muñoz FJ, Porcel JM, Ramos Lázaro J, García Rubio S. Ultrasound for body composition assessment: a narrative review. Intern Emerg Med. 2024. doi: https://doi.org/10.1007/s11739-024-03756-8

11. Wagner DR, Teramoto M. Interrater reliability of novice examiners using A-mode ultrasound and skinfolds to measure subcutaneous body fat. PloS one. 2020;15(12):e0244019. doi: https://doi.org/10.1371/journal.pone.0244019

12. Ranganathan P, Pramesh CS, Aggarwal R. Common pitfalls in statistical analysis: Measures of agreement. Perspect Clin Res. 2017;8:187-91. DOI: doi: https://doi.org/10.4103/picr.PICR_123_17

13. Vetter TR, Schober P. Agreement analysis: what he said, she said versus you said. Anesthesia & Analgesia. 2018;126(6):2123-2128. doi: https://doi.org/10.1213/ANE.0000000000002924.

14. Bonett DG. Interval Estimation of Standardized Mean Differences in Paired-Samples Designs. Journal of Educational and Behavioral Statistics. 2015;40(4):366-376. doi: https://doi.org/10.3102/1076998615583904

15. Хромов-Борисов Н.Н. Диалоги о статистике в научных публикациях. Научный редактор и издатель. 2024;9(1 Suppl. 1):1S5–1S32. doi: https://doi.org/10.24069/SEP-24-01

16. Hammer Ø, Harper DAT, Ryan PD. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica. 2001;4(1):9

17. Kelter R. Bayesian alternatives to null hypothesis significance testing in biomedical research: a non-technical introduction to Bayesian inference with JASP. BMC Med Res Methodol.2020;20:142. doi: https://doi.org/10.1186/s12874-020-00980-6

18. Bondareva EA, Parfenteva OI, Troshina EA, et al. Agreement between bioimpedance analysis and ultrasound scanning in body composition assessment. Am J Hum Biol. 2024;36(4):e24001. doi: https://doi.org/10.1002/ajhb.24001

19. Kogure GS, Silva RC, Ribeiro VB, Mendes MC, Menezes-Reis R, Ferriani RA, Furtado C, Reis R. Concordance in prediction body fat percentage of Brazilian women in reproductive age between different methods of evaluation of skinfolds thickness. Archives of endocrinology and metabolism. 2020;64(3):257-268. doi: https://doi.org/10.20945/2359-3997000000246

20. Bondareva EA, Parfent’eva OI, Vasil’eva AA. et al. Reproducibility of Body Fat and Fat-Free Mass Measurements by Bioimpedance and Ultrasound Scanning Analysis in a Group of Young Adults. Hum Physiol. 2023;49:411–420. doi: https://doi.org/10.1134/S0362119723600042

21. Nickerson BS, McLester CN, McLester JR, Kliszczewicz BM. Agreement Between 2 Segmental Bioimpedance Devices, BOD POD, and DXA in Obese Adults. Journal of clinical densitometry: the official journal of the International Society for Clinical Densitometry. 2020;23(1):138-148. doi: https://doi.org/10.1016/j.jocd.2019.04.005

22. Miclos-Balica M, Muntean P, Schick F, Haragus HG, Glisici B, Pupazan V, Neagu A, Neagu M. Reliability of body composition assessment using A-mode ultrasound in a heterogeneous sample. European journal of clinical nutrition. 2021;75(3):438-445. doi: https://doi.org/10.1038/s41430-020-00743-y

23. Tinsley GM, Rodriguez C, White SJ, et al. A Field-based Three-Compartment Model Derived from Ultrasonography and Bioimpedance for Estimating Body Composition Changes. Med Sci Sports Exerc. 2021;53(3):658-667. doi: https://doi.org/10.1249/MSS.0000000000002491


Supplementary files

Review

For citations:


Bondareva E.A., Garasko B.A., Khromov-Borisov N.N., Mazurina N.V., Ershova E.V., Komshilova K.A., Troshina E.A. Interchangeability of different indirect methods for determining body composition. Problems of Endocrinology. 2025;71(4):47-56. (In Russ.) https://doi.org/10.14341/probl13538

Views: 14


ISSN 0375-9660 (Print)
ISSN 2308-1430 (Online)