Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Maternal and pediatric nutrition

Bioimpedance spectroscopy in the infant: effect of milk intake and extracellular fluid reservoirs on resistance measurements in term breastfed infants

European Journal of Clinical Nutrition volume 70, pages 843–851 (2016)Cite this article

Subjects

A Corrigendum to this article was published on 06 July 2016

This article has been updated

Abstract

Background/Objectives:

Bioimpedance spectroscopy is an accurate non-invasive method for measuring body composition in adults, but in infants it requires further testing and validation. Of the few studies of bioimpedance conducted in infants, none have comprehensively investigated the effect of milk intake volume. This study assessed the effect of the milk intake, feed duration and the volume of the infant’s stomach and bladder on the resistance values pre-/post-feed to establish the feasibility of using these values interchangeably during data collection.

Subjects/Methods:

Forty-eight breastfeeding infants were measured at 2, 5, 9 and/or 12 months (n=62 sessions) within 1–2 min before the start and after the end of breastfeed. Median (IQR) time between measurements was 24 (20.0–30.0) min. Resistance measurements at 0 and 50 kHz, and infinite frequency (R0, R50 and Rinf) and resistance of intracellular water (Ricw) were analysed with customised infant settings. Milk intake was measured by test weights. Free-water volumes and free-water change were determined from stomach and bladder volumes calculated from ultrasound images.

Results:

Small pre-to-post-feed changes (median (IQR): R0 −3.7 (−14.8, 14.3); R50 0.3 (−10.4, 15.0); Rinf 2.8 (−13.3, 35.5); Ricw 20.8 (−98.1, 290.9)) were not significantly different from zero (R0: P=0.92; R50: P=0.48; Rinf: P=0.32; Ricw: P=0.097). No significant effect of milk intake or free-water change was detected.

Conclusions:

The lack of consistent change in resistance across a breastfeed provides flexibility in the timing of measurements of infants in the research setting, such that typically pre- and post-feed measures of resistance can be used interchangeably.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

Change history

  • 05 July 2016

    This article has been corrected since Advance Online Publication and a corrigendum is also printed in this issue

References

  1. Tuorkey M . Bioelectrical impedance as a diagnostic factor in the clinical practice and prognostic factor for survival in cancer patients: prediction, accuracy and reliability. J Biosens Bioelectron 2012; 3: 1000121.

    Article  Google Scholar 

  2. Ferreira DM, Souza MN . Bioelectrical impedance spectroscopy for the assessment of body fluid volumes of term neonates. Braz J Med Biol Res 2004; 37: 1595–1606.

    Article  CAS  PubMed  Google Scholar 

  3. Mayfield S, Uauy R, Waidelich D . Body composition of low-birth-weight infants determined by using bioelectrical resistance and reactance. Am J Clin Nutr 1991; 54: 296–303.

    Article  CAS  PubMed  Google Scholar 

  4. Lingwood B, Coghlan J, Ward L, Charles B, Colditz P . Measurement of extracellular fluid volume in the neonate using multiple frequency bio-impedance analysis. Physiol Meas 2000; 21: 251–262.

    Article  CAS  PubMed  Google Scholar 

  5. Lingwood B . Bioelectrical impedance analysis for assessment of fluid status and body composition in neonates—the good, the bad and the unknown. Eur J Clin Nutr 2013; 67: S28–S33.

    Article  PubMed  Google Scholar 

  6. Kraemer M, Rode C, Wizemann V . Detection limits of methods to assess fluid status changes in dialysis patients. Kidney Int 2006; 69: 1609–1620.

    Article  CAS  PubMed  Google Scholar 

  7. Wieskotten S, Knobloch V, Wiemann K, Wabel P, Schafer F . Use of BCM - body composition monitor in children - establishing new reference ranges. Pediatr Nephrol 2008; 23: 1571–1719.

    Article  Google Scholar 

  8. Zaloszyc A, Schmitt C, Schaefer B, Salomon R, Krid S, Fischbach M . Assessment of water-, salt and nutritional status by multifrequency body impedance analysis in children on hemodialysis. Pediatr Nephrol 2012; 27: 1605–1829.

    Article  Google Scholar 

  9. Zaloszyc A, Schaefer B, Schaefer F, Krid S, Salomon R, Niaudet P et al. Hydration measurement by bioimpedance spectroscopy and blood pressure management in children on hemodialysis. Pediatr Nephrol 2013; 28: 2169–2177.

    Article  PubMed  Google Scholar 

  10. Oh G, Wong C, Begin B, Salsbery K, Sutherland S, Chaudhuri A . Whole-body single-frequency bioimpedance analysis in pediatric hemodialysis patients. Pediatr Nephrol 2014; 29: 1417–1423.

    Article  PubMed  Google Scholar 

  11. Sesmero M, Mazariegos M, Pedron C, Jones J, Solomons N . Bioimpedance electrical spectroscopy in the first six months of life: some methodologic considerations. Nutrition 2005; 21: 567–573.

    Article  PubMed  Google Scholar 

  12. Lingwood B, van Leeuwen A, Carberry A, Fitzgerald E, Callaway L, Colditz P et al. Prediction of fat-free mass and percentage of body fat in neonates using biolelectrical impedance analysis and anthropometric measures: validation against PEA POD. Br J Nutr 2012; 107: 1545–1552.

    Article  CAS  PubMed  Google Scholar 

  13. Lorenz J . Assessing fluid and electrolyte status in the newborn. Clin Chem 1997; 43: 205–210.

    CAS  PubMed  Google Scholar 

  14. Benelam B, Wyness L . Hydration and health: a review. Nutr Bull 2010; 35: 3–25.

    Article  Google Scholar 

  15. Kushner R, Gudivaka R, Schoeller D . Clinical characteristics influencing bioelectrical impedance analysis measurements. Am J Clin Nutr 1996; 64: S423–S427.

    Article  Google Scholar 

  16. Ellis K . Body Composition Assessment in Early Infancy: A Review. A White Paper. Prepared for the Food Advisory Committee on Infant Formula, Food and Drug Administration: Huston, Texas 2002; pp 1–11.

  17. Kent J, Mitoulas L, Cregan M, Ramsay D, Doherty D, Hartmann P . Volume and frequency of breastfeedings and fat content of breast milk throughout the day. Pediatrics 2006; 117: e387–e395.

    Article  PubMed  Google Scholar 

  18. Lukaski H . Evolution of bioimpedance: a circuitous journey from estimation of physiological function to assessment of body composition and a return to clinical research. Eur J Clin Nutr 2013; 67: S2–S9.

    Article  PubMed  Google Scholar 

  19. Matthie J . Bioimpedance measurements of human body composition: critical analysis and outlook. Expert Rev Med Devices 2008; 5: 239–261.

    Article  PubMed  Google Scholar 

  20. Perrella S, Hepworth A, Simmer K, Geddes D . Validation of ultrasound methods to monitor gastric volume changes in preterm infants. J Paediatr Gastroenterol Nutr 2013; 57: 741–749.

    Article  Google Scholar 

  21. Erasmie U, Lidefelt K . Accuracy of ultrasonic assessment of residual urine in children. Pediatr Radiol 1989; 19: 388–390.

    Article  CAS  PubMed  Google Scholar 

  22. Arthur P, Hartmann P, Smith M . Measurement of the milk intake of breast-fed infants. J Paediatr Gastroenterol Nutr 1987; 6: 758–763.

    Article  CAS  Google Scholar 

  23. Core Team R, Pinheiro J, Bates D, DebRoy S, Sarkar D, Team RC (eds). R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria, 2009.

    Google Scholar 

  24. Pinheiro J, Bates D, DebRoy S, Sarkar D, Team TRC. nlme: linear and nonlinear mixed effects models. R Package 2009; (Version 3.1-96).

  25. Gamer M, Lemon J, Fellows I, Irr: various coefficients of interrater reliability and agreement. R Package 2007; (Version 0.70): See http://www.r-project.org.

  26. Hothorn T, Bretz F, Westfall P . Simultaneous inference in general parametric models. Biom J 2008; 50: 346–363.

    Article  PubMed  Google Scholar 

  27. Landis J, Koch G . The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159–174.

    Article  CAS  PubMed  Google Scholar 

  28. Bland J, Altman D . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 8: 307–310.

    Article  Google Scholar 

  29. Khaled M, McCutcheon M, Reddy S, Pearman P, Hunter G, Weinsier R . Electrical impedance in assessing human body composition: the BIA method. Am J Clin Nutr 1988; 47: 789–792.

    Article  PubMed  Google Scholar 

  30. Czerniec S, Ward L, Refshauge K, Beith J, Lee M, York S et al. Assessment of breast cancer-related arm lymphedema - comparison of physical measurement methods and self-report. Cancer Invest 2010; 28: 54–62.

    Article  CAS  PubMed  Google Scholar 

  31. Cornish B, Jacobs A, Thomas B, Ward L . Optimizing electrode sites for segmental bioimpedance measurements. Physiol Meas 1999; 20: 241–250.

    Article  CAS  PubMed  Google Scholar 

  32. Cornish B, Ward L, Thomas B, Jebb S, Elia M . Evaluation of multiple frequency bioelectrical impedance and Cole-Cole analysis for the assessment of body water volumes in healthy humans. Eur J Clin Nutr 1996; 50: 159–164.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

All authors read and approved the final manuscript. Authors thank all participants for their time and effort. This study was supported by an Australian Postgraduate Award from The University of Western Australia (Australia) and an unrestricted research grant from Medela AG (Switzerland). This study was supported by an Australian Postgraduate Award from The University of Western Australia (Australia; ZG) and an unrestricted research grant from Medela AG (Switzerland; DTG, PEH, ARH, CTL). Medela AG had no involvement in the inception, conduct of this research or in writing of the manuscript.

Author information

Authors and Affiliations

  1. School of Chemistry and Biochemistry, The University of Western Australia, Crawley, Western Australia, Australia

    Z Gridneva, A R Hepworth, C T Lai, P E Hartmann & D T Geddes

  2. School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia

    L C Ward

Authors
  1. Z Gridneva
    View author publications

    Search author on:PubMed Google Scholar

  2. A R Hepworth
    View author publications

    Search author on:PubMed Google Scholar

  3. L C Ward
    View author publications

    Search author on:PubMed Google Scholar

  4. C T Lai
    View author publications

    Search author on:PubMed Google Scholar

  5. P E Hartmann
    View author publications

    Search author on:PubMed Google Scholar

  6. D T Geddes
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Z Gridneva.

Ethics declarations

Competing interests

LCW provides consultancy services to ImpediMed Ltd, which had no involvement in the inception, conduct of this research or in writing of the manuscript. The remaining authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gridneva, Z., Hepworth, A., Ward, L. et al. Bioimpedance spectroscopy in the infant: effect of milk intake and extracellular fluid reservoirs on resistance measurements in term breastfed infants. Eur J Clin Nutr 70, 843–851 (2016). https://doi.org/10.1038/ejcn.2016.26

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/ejcn.2016.26

This article is cited by

Search

Advanced search

Quick links