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  • Original Article
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Body composition, energy expenditure and physical activity

Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin

European Journal of Clinical Nutrition volume 67, pages 956–960 (2013)Cite this article

Subjects

Abstract

Background/objectives:

Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.

Subjects/methods:

Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25–45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height2/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.

Results:

A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6 kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.

Conclusions:

Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

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References

  1. NHLBI Obesity Education Initiative. Practical Guide to the Identification, Evaluation and Treatment of Overweight and Obesity in Adults. National Heart, Lung and Blood Institute. U.S. Department of Health and Human Services., NIH Publication Number: Washington, DC, USA, 2000, NIH Publication no. 02–4084.

  2. Roche AF, Heymsfield SB, Lohman TG . Human Body Composition. Human Kinetics: Champaign, IL, USA, 1996, pp 25–78.

    Google Scholar 

  3. Lukaski HC, Bolonchuk WW, Hall CB, Siders WA . Validation of tetrapolar bioelectrical impedance method to assess human body composition. J Appl Physiol 1986; 60: 1327–1332.

    Article  CAS  Google Scholar 

  4. Snijder MB, Kuyf BE, Deurenberg P . Effect of body build on the validity of predicted body fat from body mass index and bioelectrical impedance. Ann Nutr Metab 1999; 43: 277–285.

    Article  CAS  Google Scholar 

  5. Leman CR, Adeyemo AA, Schoeller DA, Cooper RS, Luke A . Body composition of children in south-western Nigeria: validation of bio-electrical impedance analysis. Ann Trop Paediatr 2003; 23: 61–67.

    Article  Google Scholar 

  6. Schoeller DA, Luke A . Bioelectrical impedance analysis prediction equations differ between African Americans and Caucasians, but it is not clear why. Ann N Y Acad Sci 2000; 904: 225–226.

    Article  CAS  Google Scholar 

  7. Wells JC, Hawton K, Darch T, Lunn PG . Body composition by 2H dilution in Gambian infants: comparison with UK infants and evaluation of simple prediction methods. Br J Nutr 2009; 102: 1776–1782.

    Article  CAS  Google Scholar 

  8. Buffa R, Floris G, Marini E . Assessment of nutritional status in free-living elderly individuals by bioelectrical impedance vector analysis. Nutrition 2009; 25: 3–5.

    Article  Google Scholar 

  9. Hawkesworth S, Prentice AM, Fulford AJ, Moore SE . Dietary supplementation of rural Gambian women during pregnancy does not affect body composition in offspring at 11-17 years of age. J Nutr 2008; 138: 2468–2473.

    Article  CAS  Google Scholar 

  10. Prins M, Hawkesworth S, Wright A, Fulford AJ, Jarjou LM, Prentice AM et al. Use of bioelectrical impedance analysis to assess body composition in rural Gambian children. Eur J Clin Nutr 2008; 62: 1065–1074.

    Article  CAS  Google Scholar 

  11. VanderJagt DJ, Morales M, Thacher TD, Diaz M, Glew RH . Bioelectrical impedance analysis of the body composition of Nigerian children with calcium-deficiency rickets. J Trop Pediatr 2001; 47: 92–97.

    Article  CAS  Google Scholar 

  12. Medoua GN, Nana ES, Essa'a VJ, Ntsama PM, Matchawe C, Rikong HA et al. Body composition of Cameroonian lactating women determined by anthropometry, bioelectrical impedance, and deuterium dilution. Nutrition 2011; 27: 414–419.

    Article  Google Scholar 

  13. VanderJagt DJ, Trujillo MR, Jalo I, Bode-Thomas F, Glew RH, Agaba P . Pulmonary function correlates with body composition in Nigerian children and young adults with sickle cell disease. J Trop Pediatr 2008; 54: 87–93.

    Article  Google Scholar 

  14. VanderJagt DJ, Okolo SN, Rabasa AI, Glew RH . Bioelectrical impedance analysis of the body composition of Nigerian children with sickle cell disease. J Trop Pediatr 2000; 46: 67–72.

    Article  CAS  Google Scholar 

  15. Mutimura E, Anastos K, Zheng L, Cohen M, Binagwaho A, Kotler DP . Effect of HIV infection on body composition and fat distribution in Rwandan women. J Int Assoc Physicians AIDS Care (Chic) 2011; 9: 173–178.

    Article  Google Scholar 

  16. Villamor E, Saathoff E, Mugusi F, Bosch RJ, Urassa W, Fawzi WW . Wasting and body composition of adults with pulmonary tuberculosis in relation to HIV-1 coinfection, socioeconomic status, and severity of tuberculosis. Eur J Clin Nutr 2006; 60: 163–171.

    Article  CAS  Google Scholar 

  17. Papathakis PC, Rollins NC, Brown KH, Bennish ML, Van Loan MD . Comparison of isotope dilution with bioimpedance spectroscopy and anthropometry for assessment of body composition in asymptomatic HIV-infected and HIV-uninfected breastfeeding mothers. Am J Clin Nutr 2005; 82: 538–546.

    Article  CAS  Google Scholar 

  18. Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Schoeller DA et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health 2012; 11: 927.

    Article  Google Scholar 

  19. Barro RJ, Lee JW . A New Data Set of Educational Attainment in the World, 1950–2010. The National Bureau of Economic Research, 2011.

    Google Scholar 

  20. Lukaski HC, Bolonchuk WW . Estimation of body fluid volumes using tetrapolar bioelectrical impedance measurements. Aviat Space Environ Med 1988; 59: 1163–1169.

    CAS  PubMed  Google Scholar 

  21. Schoeller DA, van Santen E, Peterson DW, Dietz W, Jaspan J, Klein PD . Total body water measurement in humans with 18O and 2H labeled water. Am J Clin Nutr 1980; 33: 2686–2693.

    Article  CAS  Google Scholar 

  22. Wang Z, Deurenberg P, Wang W, Pietrobelli A, Baumgartner RN, Heymsfield SB . Hydration of fat-free body mass: new physiological modeling approach. Am J Physiol 1999; 276 (6 Pt 1), E995–E1003.

    CAS  PubMed  Google Scholar 

  23. Lin LI . A concordance correlation coefficient to evaluate reproducibility. Biometrics 1989; 45: 255–268.

    Article  CAS  Google Scholar 

  24. Kushner RF, Schoeller DA, Fjeld CR, Danford L . Is the impedance index (ht2/R) significant in predicting total body water? Am J Clin Nutr 1992; 56: 835–839.

    Article  CAS  Google Scholar 

  25. Kushner RF, Schoeller DA . Estimation of total body water by bioelectrical impedance analysis. Am J Clin Nutr 1986; 44: 417–424.

    Article  CAS  Google Scholar 

  26. Luke A, Durazo-Arvizu R, Rotimi C, Prewitt TE, Forrester T, Wilks R et al. Relation between body mass index and body fat in black population samples from Nigeria, Jamaica, and the United States. Am J Epidemiol 1997; 145: 620–628.

    Article  CAS  Google Scholar 

  27. Wang J, Thornton JC, Burastero S, Heymsfield SB, Pierson RN Jr . Bio-Impendance analysis for estimation of total body potassium, total body water, and fat-free mass in white, black and asian adults. Am J Hum Biol 1995; 7: 33–40.

    Article  Google Scholar 

  28. Zillikens MC, Conway JM . Estimation of total body water by biolectrical impedance analysis in blacks. Am J Hum Biol 1991; 3: 25–32.

    Article  Google Scholar 

  29. Lukaski HC, Johnson PE, Bolonchuk WW, Lykken GI . Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Am J Clin Nutr 1985; 41: 810–817.

    Article  CAS  Google Scholar 

  30. Segal KR, Burastero S, Chun A, Coronel P, Pierson RN Jr ., Wang J . Estimation of extracellular and total body water by multiple-frequency bioelectrical-impedance measurement. Am J Clin Nutr 1991; 54: 26–29.

    Article  CAS  Google Scholar 

  31. Sun SS, Chumlea WC, Heymsfield SB, Lukaski HC, Schoeller D, Friedl K et al. Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys. Am J Clin Nutr 2003; 77: 331–340.

    Article  CAS  Google Scholar 

  32. Van Loan MD, Mayclin P . Bioelectrical impedance analysis: is it a reliable estimator of lean body mass and total body water? Hum Biol 1987; 1987: 299–309.

    Google Scholar 

  33. Dioum A, Gartner A, Cisse AS, Delpeuch F, Maire B, Wade S et al. Validity of impedance-based equations for the prediction of total body water as measured by deuterium dilution in African women. Am J Clin Nutr 2005; 81: 597–604.

    Article  CAS  Google Scholar 

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Acknowledgements

The authors acknowledge the site-specific clinical staff members as well as the 2500 participants. METS is funded in part by the National Institutes of Health (1R01DK80763).

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Author notes

  1. A Luke, L R Dugas, R A Durazo-Arvizu and D A Schoeller: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL, USA

    A Luke, L R Dugas, R A Durazo-Arvizu & W N Richie

  2. Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland

    P Bovet

  3. Ministry of Health, Mahe, Republic of Seychelles

    P Bovet

  4. Tropical Medicine Research Institute, University of the West Indies, Kingston, Jamaica

    T E Forrester

  5. Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa

    E V Lambert & J Kroff

  6. Department of Physiology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    J Plange-Rhule

  7. Department of Nutritional Sciences, University of Wisconsin, Madison, WI, USA

    D A Schoeller

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  1. A Luke
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Correspondence to A Luke.

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Luke, A., Bovet, P., Forrester, T. et al. Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin. Eur J Clin Nutr 67, 956–960 (2013). https://doi.org/10.1038/ejcn.2013.123

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