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Development and cross-validation of prediction equations for estimating resting energy expenditure in severely obese Caucasian children and adolescents

Published online by Cambridge University Press:  08 March 2007

Stefano Lazzer ,
Fiorenza Agosti ,
Alessandra De Col  and
Alessandro Sartorio
Stefano Lazzer
Affiliation:
Experimental Laboratory for Endocrinological Research, Italian Institute for Auxology, IRCCS, Milan and Piancavallo (VB), Italy Department of Biomedical Sciences and Technologies, University of Udine, Udine, Italy
Fiorenza Agosti
Affiliation:
Experimental Laboratory for Endocrinological Research, Italian Institute for Auxology, IRCCS, Milan and Piancavallo (VB), Italy
Alessandra De Col
Affiliation:
Experimental Laboratory for Endocrinological Research, Italian Institute for Auxology, IRCCS, Milan and Piancavallo (VB), Italy
Alessandro Sartorio*
Affiliation:
Experimental Laboratory for Endocrinological Research, Italian Institute for Auxology, IRCCS, Milan and Piancavallo (VB), Italy Division of Auxology, Italian Institute for Auxology, IRCCS, Milan and Piancavallo (VB), Italy
*
*Corresponding author: Dr Alessandro Sartorio, fax +39 02 619112435, email [email protected]
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Abstract

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The objectives of the present study were to develop and cross-validate new equations for predicting resting energy expenditure (REE) in severely obese children and adolescents, and to determine the accuracy of new equations using the Bland–Altman method. The subjects of the study were 574 obese Caucasian children and adolescents (mean BMI z-score 3·3). REE was determined by indirect calorimetry and body composition by bioelectrical impedance analysis. Equations were derived by stepwise multiple regression analysis using a calibration cohort of 287 subjects and the equations were cross-validated in the remaining 287 subjects. Two new specific equations based on anthropometric parameters were generated as follows: (1) REE=(Sex×892·68)−(Age×115·93)+(Weight×54·96)+(Stature×1816·23)+1484·50 (R2 0·66; se 1028·97 kJ); (2) REE=(Sex×909·12)−(Age×107·48)+(fat-free mass×68·39)+(fat mass×55·19)+3631·23 (R2 0·66; se 1034·28 kJ). In the cross-validation group, mean predicted REE values were not significantly different from the mean measured REE for all children and adolescents, as well as for boys and for girls (difference <2 %) and the limits of agreement (±2 sd) were +2·06 and −1·77 MJ/d (NS). The new prediction equations allow an accurate estimation of REE in groups of severely obese children and adolescents. These equations might be useful for health care professionals and researchers when estimating REE in severely obese children and adolescents.

Keywords

Prediction equationEnergy expenditureChildrenAdolescentsBody compositionObesity
Type
Research Article
Information
British Journal of Nutrition , Volume 96 , Issue 5 , November 2006 , pp. 973 - 979
Copyright
Copyright © The Nutrition Society 2006

References

American Diabetes Association (2000) Type 2 diabetes in children and adolescents. Diabetes Care 23, 381–389.CrossRefGoogle Scholar
Bland, JM & Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476), 307–310CrossRefGoogle ScholarPubMed
Bouchard, C & Blair, SN (1999) Introductory comments for the consensus on physical activity and obesity. Med Sci Sports Exerc 31, Suppl. 11, S498–S501.Google Scholar
de Weir, JB (1949) New methods for calculating metabolic rate with special references to protein metabolism. J Physiol (Lond) 109, 1–9.CrossRefGoogle Scholar
DeLany, JP, Bray, GA, Harsha, DW & Volaufova, J (2002) Energy expenditure in preadolescent African American and white boys and girls: the Baton Rouge Children's Study. Am J Clin Nutr 75, 705–713.CrossRefGoogle ScholarPubMed
Derumeaux-Burel, H, Meyer, M, Morin, L & Boirie, Y (2004) Prediction of resting energy expenditure in a large population of obese children. Am J Clin Nutr 80, 1544–1550.Google Scholar
Dietz, WH, Bandini, LG, Morelli, JA, Peers, KF & Ching, PL (1994) Effect of sedentary activities on resting metabolic rate. Am J Clin Nutr 59, 556–559.Google Scholar
Dietz, WH, Bandini, LG & Schoeller, DA (1991) Estimates of metabolic rate in obese and nonobese adolescents. J Pediatr 118, 146–149.CrossRefGoogle ScholarPubMed
Ekelund, U, Aman, J, Yngve, A, Renman, C, Westerterp, K & Sjostrom, M (2002) Physical activity but not energy expenditure is reduced in obese adolescents: a case-control study. Am J Clin Nutr 76, 935–941.Google Scholar
Elia, M (1992) Organ and tissue contribution to metabolic rate. In Energy Metabolism: Tissue Determinants and Cellular Corollaries, pp. 61–79 [Kinney, MJ and Tucker, HN, editors]. New York: Raven Press.Google Scholar
Ferraro, R, Lillioja, S, Fontvieille, AM, Rising, R, Bogardus, C & Ravussin, E (1992) Lower sedentary metabolic rate in women compared with men. J Clin Invest 90, 780–784.CrossRefGoogle ScholarPubMed
Flatt, JP (2001) Macronutrient composition and food selection. Obes Res 9, Suppl. 4, 256S–262S.Google Scholar
Goran, MI, Kaskoun, M & Johnson, R (1994) Determinants of resting energy expenditure in young children. J Pediatr 125, 362–367.Google Scholar
Harris, JA & Benedict, FG (1919) A Biometric Study of Basal Metabolism in Man. Washington, DC: Carnegie Institute of Washington.Google Scholar
Houtkooper, LB, Lohman, TG, Going, SB & Howell, WH (1996) Why bioelectrical impedance analysis should be used for estimating adiposity. Am J Clin Nutr 64, Suppl. 3, 436S–448S.CrossRefGoogle ScholarPubMed
Lazzer, S, Boirie, Y, Bitar, A, Montaurier, C, Vernet, J, Meyer, M & Vermorel, M (2003) Assessment of energy expenditure associated with physical activities in free-living obese and nonobese adolescents. Am J Clin Nutr 78, 471–479.Google Scholar
Lazzer, S, Boirie, Y, Meyer, M & Vermorel, M (2005) Which alternative method to dual-energy X-ray absorptiometry for assessing body composition in overweight and obese adolescents? Arch Pediatr 12, 1094–1101.Google Scholar
Lazzer, S, Boirie, Y, Montaurier, C, Vernet, J, Meyer, M & Vermorel, M (2004) A weight reduction program preserves fat-free mass but not metabolic rate in obese adolescents. Obes Res 12, 233–240.CrossRefGoogle Scholar
Lobstein, T & Frelut, ML (2003) Prevalence of overweight among children in Europe. Obes Rev 4, 195–200.CrossRefGoogle ScholarPubMed
Luciano, A, Bressan, F & Zoppi, G (1997) Body mass index reference curves for children aged 3–19 years from Verona, Italy. Eur J Clin Nutr 51, 6–10.Google Scholar
Lukaski, HC (1987) Methods for the assessment of human body composition: traditional and new. Am J Clin Nutr 46, 537–556.CrossRefGoogle ScholarPubMed
McDuffie, JR, Adler-Wailes, DC, Elberg, J, Steinberg, EN, Fallon, EM, Tershokovec, AM, Arslanian, SA, Delany, JP, Bray, GA & Yanovski, JA (2004) Prediction equations for resting energy expenditure in overweight and normal-weight black and white children. Am J Clin Nutr 80, 365–373.CrossRefGoogle ScholarPubMed
Maffeis, C, Schutz, Y, Zoccante, L, Micciolo, R & Pinelli, L (1993) Meal-induced thermogenesis in lean and obese prepubertal children. Am J Clin Nutr 57, 481–485.Google Scholar
Molnar, D & Schutz, Y (1997) The effect of obesity, age, puberty and gender on resting metabolic rate in children and adolescents. Eur J Pediatr 156, 376–381.Google ScholarPubMed
NHBP (2004) The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 114, Suppl. 2, 555–576.Google Scholar
Ravussin, E, Lillioja, S, Anderson, TE, Christin, L & Bogardus, C (1986) Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest 78, 1568–1578.Google Scholar
Rolland-Cachera, MF, Cole, TJ, Sempe, M, Tichet, J, Rossignol, C & Charraud, A (1991) Body Mass Index variations: centiles from birth to 87 years. Eur J Clin Nutr 45, 13–21.Google Scholar
Salas-Salvado, J, Barenys-Manent, M, Recasens Gracia, MA & Marti-Henneberg, C (1993) Influence of adiposity on the thermic effect of food and exercise in lean and obese adolescents. Int J Obes Relat Metab Disord 17, 717–722.Google Scholar
Schaefer, F, Georgi, M, Zieger, A & Scharer, K (1994) Usefulness of bioelectric impedance and skinfold measurements in predicting fat-free mass derived from total body potassium in children. Pediatr Res 35, 617–624.Google Scholar
Schofield, WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39, Suppl. 1, 5–41.Google Scholar
Simat, BM, Mayrand, RR, From, AH, Morley, JE, Billington, C, Fullerton, DS & Ahmed, K (1983) Is the erythrocyte sodium pump altered in human obesity? J Clin Endocrinol Metab 56, 925–929.Google Scholar
Simoneau, JA & Bouchard, C (1989) Human variation in skeletal muscle fiber-type proportion and enzyme activities. Am J Physiol 257, E567–E572.Google Scholar
Tanner, JM (1961) Growth at Adolescence. Oxford: Blackwell Scientific Publications.Google Scholar
Tverskaya, R, Rising, R, Brown, D & Lifshitz, F (1998) Comparison of several equations and derivation of a new equation for calculating basal metabolic rate in obese children. J Am Coll Nutr 17, 333–336.CrossRefGoogle ScholarPubMed
Wabitsch, M, Braun, U, Heinze, E, Muche, R, Mayer, H, Teller, W & Fusch, C (1996) Body composition in 5–18-y-old obese children and adolescents before and after weight reduction as assessed by deuterium dilution and bioelectrical impedance analysis. Am J Clin Nutr 64, 1–6.Google Scholar
Weinsier, RL, Schutz, Y & Bracco, D (1992) Reexamination of the relationship of resting metabolic rate to fat-free mass and to the metabolically active components of fat-free mass in humans. Am J Clin Nutr 55, 790–794.CrossRefGoogle Scholar
World Health Organization (1985) Energy and Protein Requirements: Report of Joint FAO/WHO/UNU Expert Consultation. WHO Technical Report Series no. 724. Geneva: WHO.Google Scholar