PROBLEMS OF BODY COMPOSITION DIAGNOSTICS: BIOIMPEDANCE, CALIPEROMETRY OR ANTHROPOMETRY?



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Introduction: Dual-energy X-ray absorptiometry, bioimpedance (BIA), caliperometry, and anthropometry are used to determine the percentage of body fat mass (PBF). Caliperometry and anthropometry are the most accessible, but less accurate methods of assessing body composition. There was no comparison of the measurement results of various equations for calculating the PBF based on caliperometry and anthropometry with each other, as well as with the BIA data in the Russian population.

Objective: to compare the results of BIA measurements and 15 different methods for estimating PBF, based on measurements of skinfolds thickness (SF), body mass index (BMI), circumference of neck, waist, hips and thigh.

Materials and methods: A cross-sectional study of a consent sample aged 17 to 30 years. The main parameters of the study are: gender, age, weight, height, SF of the triceps, biceps, chest, anterior axillary line, scapular region, iliac crest, abdomen, anterior surface of the thigh, circumference of neck, waist, hips and thigh, BIA on the Accuniq BC720 device, 15 equations for estimating PBF.

Results: PBF (Me [IQR]), depending on the equations used, in women ranged from 17.6% [14.7% - 20.4%] to 41,8% [39,5% - 43,1%], in men – from 7.2% [5.2 – 10.2%] to 29,1% [27,5% - 31,5%]. The closest equation with results comparable to the BIA results, were obtained using the Navy Seal formula for women and the Davidson equation for men. The use of BIA helped to identify people with excess body fat mass even if they had normal BMI, PBF, waist circumference, and waist-hip ratio.

Conclusion: The Navy Seal formula for women and the Davidson equation for men have the highest accuracy in determining PBF, comparable to BIA. It is necessary to conduct further research and develop a formula for calculating PBF, which is typical for the Russian population

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Anna Turusheva

The North-Western State Medical University named after I.I. Mechnikov, St. Petersburg, Russia.

编辑信件的主要联系方式.
Email: anna.turusheva@gmail.com
ORCID iD: 0000-0003-3347-0984
SPIN 代码: 9658-8074
Researcher ID: U-3654-2017

PhD, MD, DSc, Professor of Department of Family Medicine

俄罗斯联邦

Vladimir Evpolov

Kirov Military Medical Academy, St. Petersburg, Russia

Email: evpol2008@mail.ru
ORCID iD: 0009-0006-7834-1421

applicant of Department of Physical and Rehabilitation Medicine

Denis Kovlen

Kirov Military Medical Academy, St. Petersburg, Russia

Email: denis.kovlen@mail.ru
ORCID iD: 0000-0001-6773-9713
SPIN 代码: 6002-2766

MD, DSc, associated professor, Сhief of Department of Physical and Rehabilitation Medicine

Elena Sharanina

The North-Western State Medical University named after I.I. Mechnikov, St. Petersburg, Russia

Email: elenasharan@ya.ru
ORCID iD: 0009-0006-3176-5286

6th year student of the Faculty of Medicine

Ekaterina Vedernikova

The North-Western State Medical University named after I.I. Mechnikov, St. Petersburg, Russia

Email: vedernikova1ekaterina@yandex.ru
ORCID iD: 0009-0009-3778-8683

first year resident Department of Family Medicine

Alexander Polysaev

The North-Western State Medical University named after I.I. Mechnikov, St. Petersburg, Russia.

Email: alexander.polysaev@yandex.ru
ORCID iD: 0009-0008-7136-2232

6th year student of the Faculty of Medicine

Anastasia Dmitrieva

The North-Western State Medical University named after I.I. Mechnikov, St. Petersburg, Russia

Email: anastasia.dmitrieva.0000@gmail.com
ORCID iD: 0009-0003-2945-9288

6th year student of the Faculty of Medicine

参考

  1. Boutari C, Mantzoros CS. A 2022 update on the epidemiology of obesity and a call to action: as its twin COVID-19 pandemic appears to be receding, the obesity and dysmetabolism pandemic continues to rage on. Metabolism. - 2022. V – 133. - P. 155217. doi: 10.1016/j.metabol.2022.155217.
  2. Савина А.А., Фейгинова С.И. Распространенность ожирения среди населения Российской Федерации: период до пандемии COVID-19. // Социальные аспекты здоровья населения [сетевое издание]. - 2022. Т - 68. №5: doi: 10.21045/2071-5021-2022-68-5-4
  3. Savina A.A., Feiginova S.I. The prevalence of obesity among the population of the Russian Federation: the period before the COVID-19 pandemic. // Social Aspects of Population Health [online publication], 2022; 68(5): doi: 10.21045/2071-5021-2022-68-5-4.
  4. Драпкина О.М., Елиашевич С.О., Шепель Р.Н. Ожирение как фактор риска хронических неинфекционных заболеваний. // Российский кардиологический журнал. - 2016; №6. - Р.73-79. https://doi.org/10.15829/1560-4071-2016-6-73-79 [Drapkina O.M., Eliashevich S.O., Shepel R.N. Obesity as a risk factor for chronic non-communicable diseases. // Russian Journal of Cardiology. 2016;(6):73-79. (In Russ.) https://doi.org/10.15829/1560-4071-2016-6-73-79]
  5. Chen GC, Arthur R, Iyengar NM, Kamensky V, Xue X, Wassertheil-Smoller S, Allison MA, Shadyab AH, Wild RA, Sun Y, Banack HR, Chai JC, Wactawski-Wende J, Manson JE, Stefanick ML, Dannenberg AJ, Rohan TE, Qi Q. Association between regional body fat and cardiovascular disease risk among postmenopausal women with normal body mass index. // Eur Heart J. - 2019 Sep 7;40(34):2849-2855. doi: 10.1093/eurheartj/ehz391
  6. Zeng Q, Dong SY, Sun XN, Xie J, Cui Y. Percent body fat is a better predictor of cardiovascular risk factors than body mass index. // Braz J Med Biol Res. 2012 Jul;45(7):591-600. doi: 10.1590/s0100-879x2012007500059.
  7. Ofstad AP, Sommer C, Birkeland KI, Bjørgaas MR, Gran JM, Gulseth HL, Johansen OE. Comparison of the associations between non-traditional and traditional indices of adiposity and cardiovascular mortality: an observational study of one million person-years of follow-up. // Int J Obes (Lond). 2019 May;43(5):1082-1092. doi: 10.1038/s41366-019-0353-9.
  8. Zadarko-Domaradzka M, Sobolewski M, Zadarko E. Comparison of Several Anthropometric Indices Related to Body Fat in Predicting Cardiorespiratory Fitness in School-Aged Children—A Single-Center Cross-Sectional Study. // Journal of Clinical Medicine. 2023; 12(19):6226. https://doi.org/10.3390/jcm12196226
  9. Ackland TR, Lohman TG, Sundgot-Borgen J, Maughan RJ, Meyer NL, Stewart AD, Müller W. Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the I.O.C. Medical Commission. // Sports Med. 2012 Mar 1;42(3):227-49. doi: 10.2165/11597140-000000000-00000.
  10. Yang SW, Kim TH, Choi HM. The reproducibility and validity verification for body composition measuring devices using bioelectrical impedance analysis in Korean adults. // J Exerc Rehabil. 2018 Aug 24;14(4):621-627. doi: 10.12965/jer.1836284.142.
  11. https://www.accuniq.com/data/bbsData/16812751743s.pdf
  12. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. // Br J Nutr. 1974 Jul;32(1):77-97. doi: 10.1079/bjn19740060.
  13. Pollock ML, Hickman T, Kendrick Z, Jackson A, Linnerud AC, Dawson G. Prediction of body density in young and middle-aged men. // J Appl Physiol. 1976 Mar;40(3):300-4. doi: 10.1152/jappl.1976.40.3.300.
  14. Технологии и методы определения состава тела человека/ Э.Г. Мартиросов, Д.В. Николаев, С.Г. Руднев. — М.: Наука, 2006. — 248 c. — ISBN 5-02-035624-7 (в пер.). Technologies and methods of human body composition assessment / E.G. Martirosov, D.V. Nikolaev, S.G. Rudnev. — M.: Nauka, 2006. — 248 p. — ISBN 5-02-035624-7.
  15. Jackson AS, Pollock ML. Practical Assessment of Body Composition. // Phys Sportsmed. 1985 May;13(5):76-90. doi: 10.1080/00913847.1985.11708790. PMID: 27463295.
  16. Espana Romero V, Ruiz JR, Ortega FB, Artero EG, Vicente-Rodriguez G, Moreno LA, Castillo MJ, Gutierrez A. Body fat measurement in elite sport climbers: comparison of skinfold thickness equations with dual energy X-ray absorptiometry. // J Sports Sci. 2009 Mar;27(5):469-77. doi: 10.1080/02640410802603863.
  17. Davidson LE, Wang J, Thornдоn JC, Kaleem Z, Silva-Palacios F, Pierson RN, Heymsfield SB, Gallagher D. Predicting fat percent by skinfolds in racial groups: Durnin and Womersley revisited. // Med Sci Sports Exerc. 2011 Mar;43(3):542-9. doi: 10.1249/MSS.0b013e3181ef3f07.
  18. Peterson MJ, Czerwinski SA, Siervogel RM. Development and validation of skinfold-thickness prediction equations with a 4-compartment model. // Am J Clin Nutr. 2003 May;77(5):1186-91. doi: 10.1093/ajcn/77.5.1186.
  19. Gause-Nilsson I, Dey DK. Percent body fat estimation from skin fold thickness in the elderly. Development of a population-based prediction equation and comparison with published equations in 75-year-olds. // J Nutr Health Aging. 2005;9:19–24
  20. Kwok T, Woo J, Lau E. Prediction of body fat by anthropometry in older Chinese people. // Obes Res. 2001;9:97–101. doi: 10.1038/oby.2001.12.
  21. Visser M, van den Heuvel E, Deurenberg P. Prediction equations for the estimation of body composition in the elderly using anthropometric data. // Br J Nutr. 1994;71: 823–833 10.1079/BJN19940189
  22. Cicone ZS, Nickerson BS, Choi YJ, Holmes CJ, Hornikel B, Fedewa MV, Esco MR. Generalized Equations for Predicting Percent Body Fat from Anthropometric Measures Using a Criterion Five-Compartment Model. // Med Sci Sports Exerc. 2021 Dec 1;53(12):2675-2682. doi: 10.1249/MSS.0000000000002754.
  23. Cicone ZS, Nickerson BS, Choi YJ, Holmes CJ, Hornikel B, Fedewa MV, Esco MR. Generalized Equations for Predicting Percent Body Fat from Anthropometric Measures Using a Criterion Five-Compartment Model. // Med Sci Sports Exerc. 2021 Dec 1;53(12):2675-2682. doi: 10.1249/MSS.0000000000002754.
  24. Subramanian, S. K., Rajendran, R., Venkata Vijaya Sai, A., & Ramachandra, S. (2023). Correlation of Neck Circumference with Body Fat Percentage by Bioelectrical Impedance Analysis. // International Journal of Kinanthropometry, 3(1), 102–108. https://doi.org/10.34256/ijk23111
  25. Yuhasz, M.S.: Physical Fitness Manual, London Ontario,University of Western Ontario, (1974)
  26. Siri, W. E. (1993). Body composition from fluid spaces and density: Analysis of methods. Nutrition, 9, 480–491; discussion 492.
  27. Brozek, J., Grande, F., Anderson, J. T., & Keys, A. (1963). Densiдоmetric analysis of body composition: Revision of some quantitative assumptions. // Annals of the New York Academy of Sciences, 110, 113–140.
  28. Peterson DD. History of the U.S. Navy Body Composition program. // Mil Med. 2015 Jan;180(1):91-6. doi: 10.7205/MILMED-D-14-00266.
  29. Preis SR, Massaro JM, Hoffmann U, D'Agostino RB Sr, Levy D, Robins SJ, Meigs JB, Vasan RS, O'Donnell CJ, Fox CS. Neck circumference as a novel measure of cardiometabolic risk: the Framingham Heart study. // J Clin Endocrinol Metab. 2010 Aug;95(8):3701-10. doi: 10.1210/jc.2009-1779.
  30. Joshipura K, Muñoz-Torres F, Vergara J, Palacios C, Pérez CM. Neck Circumference May Be a Better Alternative to Standard Anthropometric Measures. // J Diabetes Res. 2016;2016:6058916. doi: 10.1155/2016/6058916.
  31. Hao X, He H, Tao L, Zhao W, Wang P. Waistline to thigh circumference ratio as a predictor of MAFLD: a health care worker study with 2-year follow-up. // BMC Gastroenterol. 2024 Apr 24;24(1):144. doi: 10.1186/s12876-024-03229-4.
  32. Chuang YC, Hsu KH, Hwang CJ, Hu PM, Lin TM, Chiou WK. Waist-to-thigh ratio can also be a better indicator associated with type 2 diabetes than traditional anthropometrical measurements in Taiwan population. // Ann Epidemiol. 2006 May;16(5):321-31. doi: 10.1016/j.annepidem.2005.04.014.
  33. Sinning WE, Dolny DG, Little KD, Cunningham LN, Racaniello A, Siconolfi SF, Sholes JL. Validity of "generalized" equations for body composition analysis in male athletes. // Med Sci Sports Exerc. 1985 Feb;17(1):124-30.
  34. Chambers AJ, Parise E, McCrory JL, Cham R. A comparison of prediction equations for the estimation of body fat percentage in non-obese and obese older Caucasian adults in the United States. // J Nutr Health Aging. 2014;18(6):586-90. doi: 10.1007/s12603-014-0017-3

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