Accessible Requires Authentication Published by De Gruyter March 15, 2017

Infrared analyzers for breast milk analysis: fat levels can influence the accuracy of protein measurements

Celia Kwan, Gerhard Fusch ORCID logo, Aldin Bahonjic, Niels Rochow and Christoph Fusch ORCID logo

Abstract:

Background:

Currently, there is a growing interest in lacto-engineering in the neonatal intensive care unit, using infrared milk analyzers to rapidly measure the macronutrient content in breast milk before processing and feeding it to preterm infants. However, there is an overlap in the spectral information of different macronutrients, so they can potentially impact the robustness of the measurement. In this study, we investigate whether the measurement of protein is dependent on the levels of fat present while using an infrared milk analyzer.

Methods:

Breast milk samples (n=25) were measured for fat and protein content before and after being completely defatted by centrifugation, using chemical reference methods and near-infrared milk analyzer (Unity SpectraStar) with two different calibration algorithms provided by the manufacturer (released 2009 and 2015).

Results:

While the protein content remained unchanged, as measured by elemental analysis, measurements by infrared milk analyzer show a difference in protein measurements dependent on fat content; high fat content can lead to falsely high protein content. This difference is less pronounced when measured using the more recent calibration algorithm.

Conclusions:

Milk analyzer users must be cautious of their devices’ measurements, especially if they are changing the matrix of breast milk using more advanced lacto-engineering.


Corresponding author: Christoph Fusch, MD, PhD, FRCPC, Professor and Holder of the Jack Sinclair Chair in Division of Neonatology, Department of Pediatrics, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada; and Department of Pediatrics, Paracelsus Medical School, General Hospital of Nuremberg, Breslauer Straße 201, 90471 Nuremberg, Germany, Phone: +49 (911) 398-2307, Fax: +49 (911) 398-5107, E-mail:

Acknowledgments

Christoph Fusch holds the Hamilton Health Sciences Foundation – Jack Sinclair Chair in Neonatology at McMaster University, Faculty of Health Sciences.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: The study is funded by Canadian Institute of Health Research (CIHR) #MOP – 125883.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Rochow N, Fusch G, Choi A, Chessell L, Elliott L, McDonald K, et al. Target fortification of breast milk with fat, protein, and carbohydrates for preterm infants. J Pediatr 2013;163:1001–7.10.1016/j.jpeds.2013.04.05223769498 Search in Google Scholar

2. Rochow N, Fusch G, Zapanta B, Ali A, Barui S, Fusch C. Target fortification of breast milk: how often should milk analysis be done? Nutrients 2015;7:2297–310.2583507310.3390/nu7042297 Search in Google Scholar

3. Fusch G, Mitra S, Rochow N, Fusch C. Target fortification of breast milk: levels of fat, protein or lactose are not related. Acta Paediatr 2015;104:38–42.2521319310.1111/apa.12804 Search in Google Scholar

4. Maggio L, Costa S, Gallini F. Human milk fortifiers in very low birth weight infants. Early Hum Dev 2009;85(Suppl 10): S59–61.10.1016/j.earlhumdev.2009.08.01819762172 Search in Google Scholar

5. Radmacher PG, Lewis SL, Adamkin DH. Individualizing fortification of human milk using real time human milk analysis. J Neonatal Perinatal Med 2013;6:319–23.24441088 Search in Google Scholar

6. Lessen R. Use of skim breast milk for an infant with chylothorax. ICAN: Infant Child Adoles Nutr 2009;1:303–10. Search in Google Scholar

7. Cooper AR, Barnett D, Gentles E, Cairns L, Simpson JH. Macronutrient content of donor human breast milk. Arch Dis Child Fetal Neonatal Ed 2013;98:F539–41.2386770710.1136/archdischild-2013-304422 Search in Google Scholar

8. Fusch G, Rochow N, Choi A, Fusch S, Poeschl S, Ubah AO, et al. Rapid measurement of macronutrients in breast milk: how reliable are infrared milk analyzers? Clin Nutr 2015;34:465–76.10.1016/j.clnu.2014.05.00524912866 Search in Google Scholar

9. Kotrri G, Fusch G, Kwan C, Choi D, Choi A, Al Kafi N, et al. Validation of correction algorithms for near-IR analysis of human milk in an independent sample set-effect of pasteurization. Nutrients 2016;8:119. doi:10.3390/nu8030119.10.3390/nu8030119 Search in Google Scholar

10. Fusch G, Kwan C, Huang RC, Rochow N, Fusch C. Need of quality control programme when using near-infrared human milk analyzers. Acta Paediatr 2016;105:324–5.10.1111/apa.1330526663457 Search in Google Scholar

11. Choi A, Fusch G, Rochow N, Sheikh N, Fusch C. Establishment of micromethods for macronutrient contents analysis in breast milk. Matern Child Nutr 2015;11:761–72.10.1111/mcn.1205323782538 Search in Google Scholar

12. Ezzelle J, Rodriguez-Chavez IR, Darden JM, Stirewalt M, Kunwar N, Hitchcock R, et al. Guidelines on good clinical laboratory practice: bridging operations between research and clinical research laboratories. J Pharm Biomed Anal 2008;46:18–29.1803759910.1016/j.jpba.2007.10.010 Search in Google Scholar

Received: 2016-11-11
Accepted: 2017-2-7
Published Online: 2017-3-15
Published in Print: 2017-10-26

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