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Body composition, energy expenditure and physical activity

Development and validation of bioelectrical impedance analysis equations for predicting total body water and fat-free mass in North-African adults

European Journal of Clinical Nutrition volume 67, pages 1081–1086 (2013)Cite this article

Subjects

Abstract

Background/objectives:

Accuracy of the bioelectrical impedance analysis (BIA) depends on population-specific prediction equations. The aim of our study was to develop prediction equations for assessing total body water (TBW) and fat-free mass (FFM) in healthy North-African adults.

Subjects/methods:

In all, 250 participants (194 women, 56 men) aged 18–64 years were included in the analysis. BIA variables were measured by a tetra-polar device. TBW and FFM were assessed by the dilution of deuterium (D2O). The participants were sorted by gender and randomly split into development and validation subgroups. The validity of other published equations was also tested using Bland and Altman procedure, proportional bias and pure error.

Results:

The prediction equations derived were: TBW (l)=5.68+0.267 height2/resistance+4.42 sex (male=1, female=0)+0.225 weight—0.052 age (R2=0.92, root mean square error (RMSE)=1.75 l, RMSE%=5.65); and FFM (kg)=7.47+0.366 height2/resistance+6.04 sex+0.306 weight—0.063 age (R2=0.92, RMSE=2.38 kg, RMSE%=5.61). The new equations provided nonsignificant proportional bias values, and better agreement than other tested equations. Bias and pure error values were 0.36 and 1.88 l for men and 0.00 and 1.82 l for women, for TBW equation. For FFM equation, bias values were 0.43 and −0.04 kg, and pure errors were 2.57 and 2.46 kg for men and women, respectively.

Conclusions:

The new prediction equations provide reliable estimates of TBW and FFM in North-African adults and are recommended for use in these populations.

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References

  1. Popkin BM, Adair LS, Ng SW . Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012; 70: 3–21.

    Article  Google Scholar 

  2. Holdsworth M, El Ati J, Bour A, Kameli Y, Derouiche A . Millstone E et al. Developing national obesity policy in middle-income countries: a case study from North Africa. Health Policy Plan 2012 doi:10.1093/heapol/czs125.

  3. Crowther NJ . Early determinants of chronic disease in developing countries. Best Pract Res Clin Endocrinol Metab 2012; 26: 655–665.

    Article  Google Scholar 

  4. Mattei J, Malik V, Wedick NM, Campos H, Spiegelman D, Willett W et al. A symposium and workshop report from the Global Nutrition and Epidemiologic Transition Initiative: nutrition transition and the global burden of type 2 diabetes. Br J Nutr 2012; 108: 1325–1335.

    Article  CAS  Google Scholar 

  5. Gallagher D, Chung S, Akram M Body Composition. In: Encyclopedia of Human Nutrition, Caballero B, Allen L, Prentice A (3 edn) Academic Press: Amsterdam 2013, pp 191–199.

  6. Jackson AA, Johnson M, Durkin K, Wootton S . Body composition assessment in nutrition research: value of BIA technology. Eur J Clin Nutr 2013; 67 (Suppl 1)), S71–S78.

    Article  Google Scholar 

  7. Jaffrin MY, Morel H . Body fluid volumes measurements by impedance: A review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods. Med Eng Phys 2008; 10: 1257–1269.

    Article  Google Scholar 

  8. Rush EC, Freitas I, Plank LD . Body size, body composition and fat distribution: comparative analysis of European, Maori, Pacific Island and Asian Indian adults. Br J Nutr 2009; 102: 632–641.

    Article  CAS  Google Scholar 

  9. Deurenberg P, Deurenberg-Yap M, Schouten FJ . Validity of total and segmental impedance measurements for prediction of body composition across ethnic population groups. Eur J Clin Nutr 2002; 56: 214–220.

    Article  CAS  Google Scholar 

  10. Siervo M, Davies AA, Jebb SA, Jalil F, Moore SE, Prentice AM . Ethnic differences in the association between body mass index and impedance index (Ht2/Z) in adult women and men using a leg-to-leg bioimpedance method. Eur J Clin Nutr 2007; 61: 1337–1340.

    Article  CAS  Google Scholar 

  11. 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 

  12. Badro DA, Douaihy B, Haber M, Youhanna SC, Salloum A, Ghassibe-Sabbagh M et al. Y-chromosome and mtDNA genetics reveal significant contrasts in affinities of modern Middle Eastern populations with European and African populations. PLoS One 2013; 8: e54616.

    Article  CAS  Google Scholar 

  13. Levinson D, Ethnic Groups Worldwide: A Ready Reference Handbook. Oryx Press: Phoenix, AZ.

  14. Lohman TG . Skinfolds and body density and their relation to body fatness: a review. Hum Biol 1981; 53: 181–225.

    CAS  PubMed  Google Scholar 

  15. Plowman SA, Smith DL . Body composition: determination and importance. In: Exercise Physiology for Health, Fitness, and Performance 4th edn Lippincott Williams & Wilkins: Baltimore, USA, 2013, p 207.

    Google Scholar 

  16. Chumlea WC, Guo SS, Zeller CM, Reo NV, Siervogel RM . Total body water data for white adults 18 to 64 years of age: the Fels Longitudinal Study. Kidney Int 1999; 56: 244–252.

    Article  CAS  Google Scholar 

  17. Schoeller DA . Changes in total body water with age. Am J Clin Nutr 1989; 50 (suppl), 1176–1181.

    Article  CAS  Google Scholar 

  18. Lohman TG, Roche AF, Martorell R . Anthropometric standardization reference manual. Human Kinetics: Champaign, IL, 1988.

    Google Scholar 

  19. International Atomic Energy Agency. Introduction to body composition assessment using the deuterium dilution technique with analysis of saliva samples by Fourier transform infrared spectrometry. IAEA Human Health Series. No. 12. Vol. 1, International Atomic Energy Agency: Vienna, Austria, 2010, pp 4–47.

  20. Schoeller DA, van Santen E, Paterson 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: 2688–2693.

    Google Scholar 

  21. Wang ZM, Deurenberg P, Wang W, Pietrobelli A, Baumgartner RN, Heymsfield SB . Fat-free body mass hydration: review and critique of a classic body composition constant. Am J Clin Nutr 1999; 69: 833–841.

    Article  CAS  Google Scholar 

  22. Lohman TG . Advances in body composition assessment. Human Kinetics Publishers: Champaign, IL, 1992, pp 65–77.

    Google Scholar 

  23. 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 

  24. 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 epidemiological surveys. Am J Clin Nutr 2003; 77: 331–340.

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  26. Deurenberg P, van der Kooy K, Leenen R, Westrate JA, Seidell JC . Sex and age specific prediction formulas for estimating body composition from bioelectrical impedance: a cross-validation study. Int J Obesity 1991; 15: 17–25.

    CAS  Google Scholar 

  27. Kyle UG, Genton L, Karsegard L, Slosman DO, Pichard C . Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition 2001; 17: 248–253.

    Article  CAS  Google Scholar 

  28. Lindsey C, Sheather S . Variable selection in linear regression. Stata J 2010; 10: 650–669.

    Article  Google Scholar 

  29. Lin LIK . A note on the concordance correlation coefficient. Biometrics 2000; 56: 324–325.

    Article  Google Scholar 

  30. Bland JM, Altman DG . Applying the right statistics: analyses of measurement studies. Ultrasound Obstet Gynecol 2003; 22: 85–93.

    Article  CAS  Google Scholar 

  31. Ludbrook J . Statistical techniques for comparing measurers and methods of measurement: a critical review. Clin Exp Pharmacol Physiol 2002; 29: 527–536.

    Article  CAS  Google Scholar 

  32. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM et al. Bioelectrical impedance analysis-part I: review of principles and methods. Clin Nutr 2004; 5: 1226–1243.

    Article  Google Scholar 

  33. Houtkooper LB, Lohman TG, Going SB, Howell WH . Why bioelectrical impedance analysis should be used for estimating adiposity. Am J Clin Nutr 1996; 64: 436S–448S.

    Article  CAS  Google Scholar 

  34. Martinoli R, Mohamed EI, Maiolo C, Cianci R, Denoth F, Salvadori S et al. Total body water estimation using bioelectrical impedance: a meta-analysis of the data available in the literature. Acta Diabetol 2003; 40 (Suppl 1), S203–S206.

    Article  Google Scholar 

  35. Rush EC, Chandu V, Plank LD . Prediction of fat-free mass by bioimpedance analysis in migrant Asian Indian men and women: a cross validation study. Int J Obes 2003; 57: 1394–1401.

    CAS  Google Scholar 

  36. Kanellakis S, Kourlaba G, Moschonis G, Vandorou A, Manios Y . Development and validation of two equations estimating body composition for overweight and obese postmenopausal women. Maturitas 2010; 65: 64–68.

    Article  Google Scholar 

  37. Pietrobelli A, Heymsfield SB, Wang ZM, Gallagher D . Multi-component body composition models: recent advances and future directions. Eur J Clin Nutr 2001; 55: 69–75.

    Article  CAS  Google Scholar 

  38. Guo SS, Chumlea WC, Cockram DB . Use of statistical methods to estimate body composition. Am J Clin Nutr 1996; 64: 428S–435S.

    Article  CAS  Google Scholar 

  39. Dehghan M, Merchant AT . Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J 2008; 7: 26.

    Article  Google Scholar 

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Acknowledgements

We thank all the participants in the present study and Ghizlane Choua, Hanane Labraimi, Naima Atalhi, Lucien Etame, Bahia Biba, Abdsalam Hamrani and Pata-Eting Kougnassoukou Tchara for their support on the field and for their assistance. IAEA provided technical support and deuterium oxide doses. The project was fully funded by the Joint Unit of Research in Nutrition and Food Sciences University Ibn Tofail-CNESTEN’s laboratory.

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Authors and Affiliations

  1. Joint Unit of Research in Nutrition and Food Sciences, Ibn Tofail University-CNESTEN, Rabat, Morocco

    K E Aglago, I El Menchawy, K El Kari, A El Hamdouchi, A Barkat, R Bengueddour, N El Haloui, N Mokhtar & H Aguenaou

  2. Hospital Center Ibn Sina, Children’s Hospital, Rabat, Morocco

    A Barkat

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  1. K E Aglago
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Correspondence to H Aguenaou.

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Contributors: EKA drafted the project design, analysed the samples, performed the statistical analysis and wrote the paper, IEM trained the field operators and directed the data collecting process, AEH and KEK supervised the analysis and the calibration of the devices, AB and RB assisted during recruitment and data analysis. NM, NEH and HA designed the study, supervised at all levels of the project, and assured final corrections of the paper. All the authors have read and approved the final manuscript.

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Aglago, K., Menchawy, I., Kari, K. et al. Development and validation of bioelectrical impedance analysis equations for predicting total body water and fat-free mass in North-African adults. Eur J Clin Nutr 67, 1081–1086 (2013). https://doi.org/10.1038/ejcn.2013.125

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