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Resting energy expenditure and body composition in children with cancer: indirect calorimetry and bioimpedance analysis

https://doi.org/10.17650/1818-8346-2014-9-1-25-34

Abstract

Resting energy expenditure (REE) by indirect calorimetry and body composition by bioimpedance analysis are studied in three groups of children aged 5–18 years. Group 1 (n = 181) – patients in remission of cancer, group 2 (n = 55) – children with oncology diseases receiving chemotherapy or who are in the early period after hematopoietic stem cell transplantation, group 3 (n = 63) – children with non-malignant diseases of the gastrointestinal tract. To eliminate the influence of age and gender on the intergroup comparisons, body composition parameters were expressed as standardized values (z-scores) relative to a reference group of healthy Russian children (n = 138,191). Group 1 was characterized by excess fat content with intact lean body mass, and groups 2 and 3 by protein depletion, more pronounced in Group 2 with a higher percentage of body fat. All used conventional formulas (WHO, Harris–Benedict and others) in groups 1 and 3 underestimated REE as compared with indirect calorimetry. A new formula for REE, giving an unbiased estimate in the group 1 was proposed: REE (kcal/day) = 28.7 × BCM (kg) +10.5 × Height (cm) – 38.6 × Age (years) – 134, where BCM – body cell mass according to bioimpedance analysis (R2 = 0.67, the standard deviation of 196 kcal/day).

About the Authors

M. V. Konovalova
Federal Research Center of Pediatric Hematology, Oncology and Immunology named after Dmitriy Rogachev, Ministry of Health of Russia
Russian Federation


S. G. Rudnev
Institute of Numerical Mathematics, Russian Academy of Sciences
Russian Federation


G. Ya. Tseytlin
Federal Research Center of Pediatric Hematology, Oncology and Immunology named after Dmitriy Rogachev, Ministry of Health of Russia
Russian Federation


A. Yu. Vashura
Federal Research Center of Pediatric Hematology, Oncology and Immunology named after Dmitriy Rogachev, Ministry of Health of Russia
Russian Federation


O. A. Starunova
Scientific Technical Centre “Medas”
Russian Federation


D. V. Nikolaev
Scientific Technical Centre “Medas”
Russian Federation


References

1. Хубутия М.Ш., Попова Т.С., Салтанов А.И. Парентеральное и энтеральное питание: национальное руководство. М.: ГЭОТАР-Медиа, 2014. 800 с.

2. Bauer J., Jürgens H., Frühwald M.C. Important aspects of nutrition in children with cancer. Adv Nutr 2011;2(2):67–77.

3. Цейтлин Г.Я., Вашура А.Ю., Коновалова М.В. и др. Значение биоимпедансного анализа и антропометрии для прогнозирования осложнений у детей с онкологическими и неонкологическими заболеваниями после трансплантации гемопоэтических стволовых клеток. Онкогематология 2013;3:50–6.

4. Bechard L.J., Feldman H.A., Venick R. et al. Attenuation of resting energy expenditure following hematopoietic SCT in children. Bone Marrow Transplant 2012;47(10):1301–6.

5. Haugen H.A., Chan L-N., Li F. Indirect calorimetry: a practical guide for clinicians. Nutr Clin Pract 2007;22(4):377–88.

6. Daly J.M., Heymsfield S.B., Head C.A. et al. Human energy requirements: overestimation by widely used prediction equation. Am J Clin Nutr 1985;42(6):1170–4.

7. Johnson G., Salle A., Lorimier G. et al. Cancer cachexia: measured and predicted resting energy expenditures for nutritional needs evaluation. Nutrition 2008;24(5):443–50.

8. Cao D-X., Wu G-H., Zhang B. et al. Resting energy expenditure and body composition in patients with newly detected cancer. Clin Nutr 2010;29(1):72–7.

9. Руднев С.Г., Соболева Н.П., Стерликов С.А. и др. Биоимпедансное исследование состава тела населения России. М.: РИО ЦНИИОИЗ, 2014. 493 с.

10. Cole T.J., Lobstein T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes 2012;7(4):284–94.

11. FAO/WHO/UNU. Energy and protein requirements: Report of a joint FAO/WHO/ UNU expert consultation. WHO Technical Report Series № 724. Geneva, 1985.

12. Schofield W.N. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 1985;39(Suppl 1):5–41.

13. Harris J.A., Benedict F.G. A biometric study of human basal metabolism. Proc Natl Acad Sci USA 1918;4(12):370–3.

14. Tverskaya R., Rising R., Brown D., Lifshitz F. Comparison of several equations and derivation of a new equation for calculating basal metabolic rate in obese children. J Am Coll Nutr 1998;17(4):333–6.

15. Cunningham J.J. Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation. Am J Clin Nutr 1991;54(6):963–9.

16. Lazzer S., Agosti F., De Col A., Sartorio A. Development and cross-validation of prediction equations for estimating resting energy expenditure in severely obese Caucasian children and adolescents. Br J Nutr 2006;96(5):973–9.

17. Maffeis C., Schutz Y., Micciolo R. et al. Resting metabolic rate in six- to ten-year-old obese and non-obese children. J Pediatr 1993;122(4):556–62.

18. Mifflin M.D., Jeor S.T., Hill L.A. et al. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr 1990;51(2):241–7.

19. Molnar D., Jeges S., Erhardt E., Schutz Y. Measured and predicted resting metabolic rate in obese and nonobese adolescents. J Pediatr 1995;127(4):571–7.

20. Müller M.J., Bosy-Westphal A., Klaus S. et al. World Health Organization equations have shortcomings for predicting resting energy expenditure in persons from a modern, affluent population: generation of a new reference standard from a retrospective analysis of a German database of resting energy expenditure. Am J Clin Nutr 2004;80(5):1379–90.

21. Николаев Д.В., Смирнов А.В., Бобринская И.Г., Руднев С.Г. Биоимпедансный анализ состава тела человека. М.: Наука, 2009. 392 с.

22. Kim M.H., Kim J.H., Kim E.K. Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents. Nutr Res Pract 2012;6(1):51–60.

23. Kross E.K., Sena M., Schmidt K., Stapleton R.D. A comparison of predictive equations of energy expenditure and measured energy expenditure in critically ill patients. J Crit Care 2012;27:321.e5–12.

24. Cole T.J., Green P.J. Smoothing reference centile curves: the LMS method and penalized likelihood. Stat Med 1992;11(10):1305–19.

25. Rigby R.A., Stasinopoulos D.M. Using the Box-Cox t distribution in GAMLSS to model skewness and curtosis. Stat Modelling 2006;6(3):209–29.

26. Stasinopoulos D.M., Rigby R.A. Generalized additive models for location scale and shape (GAMLSS) in R. J Stat Software 2007;23(7):1–46.

27. Старунова О.А. Создание программной среды для статистической обработки данных биоимпедансных измерений. Сб. статей молодых ученых факультета ВМК МГУ им. М.В. Ломоносова. М., 2011. Вып. 8. С. 129–134.

28. Bland J.M., Altman D.G. Statistical methods for assessing agreement between two methods of clinical measurements. Lancet 1986;1(8476):307–10.

29. Duggan C., Bechard L., Donovan K. et al. Changes in resting energy expenditure among children undergoing allogeneic stem cell transplantation. Am J Clin Nutr 2003;78(1):104–9.

30. Nelson K.M., Weinsier R.L., Long C.L., Schutz Y. Prediction of resting energy expenditure from fat-free mass and fat mass. Am J Clin Nutr 1992;56(5):848–56.

31. Вашура А.Ю., Коновалова М.В., Скоробогатова Е.В. и др. Нутритивный статус и тканевый состав тела у детей после трансплантации гемопоэтических стволовых клеток. Онкогематология 2011;4:33–8.


Review

For citations:


Konovalova M.V., Rudnev S.G., Tseytlin G.Ya., Vashura A.Yu., Starunova O.A., Nikolaev D.V. Resting energy expenditure and body composition in children with cancer: indirect calorimetry and bioimpedance analysis. Oncohematology. 2014;9(1):25-34. (In Russ.) https://doi.org/10.17650/1818-8346-2014-9-1-25-34

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ISSN 1818-8346 (Print)
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