Nutrition Research and Practice

The Korean Nutrition Society (한국영양학회)
권호 표지
DOI QR코드

DOI QR Code

Accuracy of predictive equations for resting energy expenditure (REE) in non-obese and obese Korean children and adolescents

  • Kim, Myung-Hee (Department of Food and Nutrition, Gangneung-Wonju National University) ;
  • Kim, Jae-Hee (Department of Food and Nutrition, Gangneung-Wonju National University) ;
  • Kim, Eun-Kyung (Department of Food and Nutrition, Gangneung-Wonju National University)
  • Received : 2011.11.14
  • Accepted : 2012.01.09
  • Published : 2012.02.29
Download PDF
⟨ Previous Next ⟩

Abstract

Weight-controlling can be supported by a proper prescription of energy intake. The individual energy requirement is usually determined through resting energy expenditure (REE) and physical activity. Because REE contributes to 60-70% of daily energy expenditure, the assessment of REE is very important. REE is often predicted using various equations, which are usually based on the body weight, height, age, gender, and so on. The aim of this study is to validate the published predictive equations for resting energy expenditure in 76 normal weight and 52 obese Korean children and adolescents in the 7-18 years old age group. The open-circuit indirect calorimetry using a ventilated hood system was used to measure REE. Sixteen REE predictive equations were included, which were based on weight and/or height of children and adolescents, or which were commonly used in clinical settings despite its use based on adults. The accuracy of the equations was evaluated on bias, RMSPE, and percentage of accurate prediction. The means of age and height were not significantly different among the groups. Weight and BMI were significantly higher in obese group (64.0 kg, $25.9kg/m^2$) than in the non-obese group (44.8 kg, $19.0kg/m^2$). For the obese group, the Molnar, Mifflin, Liu, and Harris-Benedict equations provided the accurate predictions of > 70% (87%, 79% 77%, and 73%, respectively). On the other hand, for non-obese group, only the Molnar equation had a high level of accuracy (bias of 0.6%, RMSPE of 90.4 kcal/d, and accurate prediction of 72%). The accurate prediction of the Schofield (W/WH), WHO (W/WH), and Henry (W/WH) equations was less than 60% for all groups. Our results showed that the Molnar equation appears to be the most accurate and precise for both the non-obese and the obese groups. This equation might be useful for clinical professionals when calculating energy needs in Korean children and adolescents.

Keywords

References

  1. World Health Organization [Internet]. Obesity. [cited 2011 December 2]. Available from: http://www.who.int/mediacentre/ factsheets/fs311/en/.
  2. Ministry of Health and Welfare. Korea Centers for Disease Control and Prevention. Korea Health Statistics 2005: Korea National Health and Nutrition Examination Survey (KNHANES III). 2006.
  3. Zalesin KC, Franklin BA, Miller WM, Peterson ED, McCullough PA. Impact of obesity on cardiovascular disease. Med Clin North Am 2011;95:919-37. https://doi.org/10.1016/j.mcna.2011.06.005
  4. Food and Agriculture Organization, World Health Organization, United Nations University. Energy and Protein Requirements. Report of a Joint FAO/WHO/UNU Expert Consultation. WHO Technical Report Series No. 724. Geneva: WHO; 1985.
  5. Owen OE, Holup JL, D'Alessio DA, Craig ES, Polansky M, Smalley KJ, Kavle EC, Bushman MC, Owen LR, Mozzoli MA, Kendrick ZV, Boden GH. A reappraisal of the caloric requirements of men. Am J Clin Nutr 1987;46:875-85. https://doi.org/10.1093/ajcn/46.6.875
  6. Matarese LE. Indirect calorimetry: technical aspects. J Am Diet Assoc 1997;97:S154-60. https://doi.org/10.1016/S0002-8223(97)00754-2
  7. Stewart CL, Goody CM, Branson R. Comparison of two systems of measuring energy expenditure. JPEN J Parenter Enteral Nutr 2005;29:212-7. https://doi.org/10.1177/0148607105029003212
  8. Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc 2005; 105:775-89. https://doi.org/10.1016/j.jada.2005.02.005
  9. Derumeaux-Burel H, Meyer M, Morin L, Boirie Y. Prediction of resting energy expenditure in a large population of obese children. Am J Clin Nutr 2004;80:1544-50. https://doi.org/10.1093/ajcn/80.6.1544
  10. Hofsteenge GH, Chinapaw MJ, Delemarre-van de Waal HA, Weijs PJ. Validation of predictive equations for resting energy expenditure in obese adolescents. Am J Clin Nutr 2010;91: 1244-54. https://doi.org/10.3945/ajcn.2009.28330
  11. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 1985;39 Suppl 1:5-41.
  12. James WP. Basal metabolic rate: comments on the new equations. Hum Nutr Clin Nutr 1985;39 Suppl 1:92-6.
  13. Liu HY, Lu YF, Chen WJ. Predictive equations for basal metabolic rate in Chinese adults: a cross-validation study. J Am Diet Assoc 1995;95:1403-8. https://doi.org/10.1016/S0002-8223(95)00369-X
  14. Compher C, Frankenfield D, Keim N, Roth-Yousey L; Evidence Analysis Working Group. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc 2006;106:881-903. https://doi.org/10.1016/j.jada.2006.02.009
  15. Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol 1949;109:1-9.
  16. Institute of Medicine of the National Academies. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington D.C.: The National Academies Press; 2002. p.107-264.
  17. Henry CJ. Basal metabolic rate studies in humans: measurement and development of new equations. Public Health Nutr 2005; 8:1133-52.
  18. Harris JA, Benedict FG. A Biometric Study of Basal Metabolism in Man. Washington DC: Carnegie Institute of Washington; 1919.
  19. Lawrence JC, Lee HM, Kim JH, Kim EK. Variability in results from predicted resting energy needs as compared to measured resting energy expenditure in Korean children. Nutr Res 2009;29: 777-83. https://doi.org/10.1016/j.nutres.2009.10.017
  20. Taaffe DR, Thompson J, Butterfield G, Marcus R. Accuracy of equations to predict basal metabolic rate in older women. J Am Diet Assoc 1995;95:1387-92. https://doi.org/10.1016/S0002-8223(95)00366-5
  21. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1: 307-10.
  22. Korea Centers for Disease Control and Prevention; The Korean Pediatric Society; The Committee for the Development of Growth Standard for Korean Children and Adolescents. 2007 Korean Children and Adolescents Growth Standard (commentary for the development of 2007 growth chart). Government report online. Seoul: Division of Chronic Disease Surveillance; 2007 November. Available from: http://www.cdc.go.kr/.
  23. 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: 333-6. https://doi.org/10.1080/07315724.1998.10718771
  24. Rodriguez G, Moreno LA, Sarria A, Fleta J, Bueno M. Resting energy expenditure in children and adolescents: agreement between calorimetry and prediction equations. Clin Nutr 2002;21:255-60. https://doi.org/10.1054/clnu.2001.0531
  25. Maffeis C, Schutz Y, Micciolo R, Zoccante L, Pinelli L. Resting metabolic rate in six- to ten-year-old obese and nonobese children. J Pediatr 1993;122:556-62. https://doi.org/10.1016/S0022-3476(05)83535-8
  26. Molnár D, Jeges S, Erhardt E, Schutz Y. Measured and predicted resting metabolic rate in obese and nonobese adolescents. J Pediatr 1995;127:571-7. https://doi.org/10.1016/S0022-3476(95)70114-1
  27. 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;96:973-9.
  28. Owen OE, Kavle E, Owen RS, Polansky M, Caprio S, Mozzoli MA, Kendrick ZV, Bushman MC, Boden G. A reappraisal of caloric requirements in healthy women. Am J Clin Nutr 1986; 44:1-19. https://doi.org/10.1093/ajcn/44.1.1
  29. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr 1990;51:241-7. https://doi.org/10.1093/ajcn/51.2.241

Cited by

  1. Consensus Statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition vol.30, pp.1, 2015, https://doi.org/10.1177/0884533614557642
  2. Estimation of Resting Energy Expenditure: Validation of Previous and New Predictive Equations in Obese Children and Adolescents vol.36, pp.6, 2017, https://doi.org/10.1080/07315724.2017.1320952
  3. Energy expenditure of physical activity in Korean adults and assessment of accelerometer accuracy by gender vol.50, pp.6, 2017, https://doi.org/10.4163/jnh.2017.50.6.552
  4. Validation of Dietary Reference Intakes for predicting energy requirements in elementary school-age children vol.12, pp.4, 2018, https://doi.org/10.4162/nrp.2018.12.4.336
  5. Resting Energy Expenditure (REE) in Six- to Seventeen-Year-Old Japanese Children and Adolescents vol.59, pp.4, 2012, https://doi.org/10.3177/jnsv.59.299
  6. Association between daily step counts and physical activity level among Korean elementary schoolchildren vol.20, pp.3, 2016, https://doi.org/10.20463/jenb.2016.09.20.3.8
  7. Indirect Calorimetry: From Bench to Bedside vol.21, pp.4, 2012, https://doi.org/10.4103/ijem.ijem_484_16
  8. Comparison of daily physical activity parameters using objective methods between overweight and normal-weight children vol.7, pp.2, 2012, https://doi.org/10.1016/j.jshs.2017.01.008
  9. Clinical Nutrition Approaches to Medical Management of Children with Obesity and Critical Illnesses vol.11, pp.1, 2012, https://doi.org/10.5812/compreped.92108