Hand-Held Indirect Calorimeter Offers Advantages Compared with Prediction Equations, in a Group of Overweight Women, to Determine Resting Energy Expenditures and Estimated Total Energy Expenditures during Research Screening

Journal of the American Dietetic Association

Volumn 109, Issue 5, 2009, Pages 836-845

  Spears, Karen E ^a   Kim, Hyunsook ^a   Behall, Kay M ^a   Conway, Joan M ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ANALYSIS OF VARIANCE; ARTICLE; BASAL METABOLIC RATE; BODY MASS; CALORIMETRY; COMPARATIVE STUDY; ENERGY METABOLISM; EXERCISE; FEMALE; HEALTH CARE POLICY; HUMAN; LIFESTYLE; MATHEMATICS; METABOLISM; METHODOLOGY; MIDDLE AGED; NUTRITIONAL REQUIREMENT; OBESITY; PHYSIOLOGY; PREDICTION AND FORECASTING; REFERENCE VALUE; REGRESSION ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STANDARD; WORLD HEALTH ORGANIZATION;

ADULT; AGED; ANALYSIS OF VARIANCE; BASAL METABOLISM; BODY MASS INDEX; CALORIMETRY, INDIRECT; ENERGY METABOLISM; EXERCISE; FEMALE; HUMANS; LIFE STYLE; MATHEMATICS; MIDDLE AGED; NUTRITION POLICY; NUTRITIONAL REQUIREMENTS; OVERWEIGHT; PREDICTIVE VALUE OF TESTS; REFERENCE VALUES; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; WORLD HEALTH ORGANIZATION;

EID: 65249088023     PISSN: 00028223     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jada.2009.02.016     Document Type: Article

References (42)

1. Harris J.A., and Benedict F.G. A Biometric Study of the Basal Metabolism in Man, Publication No. 279 (1919), Carnegie Institution of Washington, Washington, DC
2. Mifflin M.D., St Jeor S.T., Hill L.A., Scott B.J., Daugherty S.A., and Koh Y.O. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr 51 (1990) 241-247
3. Energy and protein requirements. Report of a joint FAO/WHO/UNU expert consultation. World Health Organ Tech Rep Ser 724 (1985) 1-206
4. Shils M.E., Olson J.A., and Shike M. Modern nutrition in health and disease. 8th ed. (1994), Lea & Febiger, Philadelphia, PA 101-111
5. Case K.O., Brahler J., and Heiss C. Resting energy expenditures in Asian women measured by indirect calorimetry are lower than expenditures calculated from prediction equations. J Am Diet Assoc 97 (1997) 1288-1292
6. de Luis D.A., Aller R., Izaola O., and Romero E. Prediction equation of resting energy expenditure in an adult Spanish population of obese adult population. Ann Nutr Metab 50 (2006) 193-196
7. Frankenfield D., Roth-Yousey L., and Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: A systematic review. J Am Diet Assoc 105 (2005) 775-789
8. Frankenfield D.C., Rowe W.A., Smith J.S., and Cooney R.N. Validation of several established equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc 103 (2003) 1152-1159
9. Frankenfield D.C., Muth E.R., and Rowe W.A. The Harris-Benedict studies of human basal metabolism: History and limitations. J Am Diet Assoc 98 (1998) 439-445
10. Lazzer S., Agosti F., De Col A., Mornati D., and Sartorio A. Comparison of predictive equations for resting energy expenditure in severely obese Caucasian children and adolescents. J Endocrinol Invest 30 (2007) 313-317
11. Siervo M., Boschi V., and Falconi C. Which REE prediction equations should we use in normal-weight, overweight and obese women?. Clin Nutr 22 (2003) 193-204
12. Rocha E.E.M., Alves V., Silva M.H.N., Chiesa C.A., and Fonseca R.B.V. Can measured resting energy expenditure be estimated by formulae in daily clinical nutrition practice?. Curr Opin Clin Nutr Metab Care 8 (2005) 319-328
13. St-Onge M.P., Rubiano F., Jones Jr. A., and Heymsfield S.B. A new hand-held indirect calorimeter to measure postprandial energy expenditure. Obes Res 12 (2004) 704-709
14. Melanson E., Coelho L., Tran Z., Haugen H., Kearney J., and Hill J. Validation of the BodyGem hand-held calorimeter. Int J Obes Relat Metab Disord 28 (2004) 1479-1484
15. Nieman D.C., Trone G.A., and Austin M.D. A new handheld device for measuring resting metabolic rate and oxygen consumption. J Am Diet Assoc 103 (2003) 588-592
16. Nieman D.C., Austin M.D., Chilcote S.M., and Benezra L. Validation of a new handheld device for measuring resting metabolic rate and oxygen consumption in children. Int J Sport Nutr Exerc Metab 15 (2005) 186-194
17. Kato M., Tajika M., Miwa Y., and Moriwaki H. Validation of a portable indirect calorimeter (Metavine) for measuring energy expenditure in an elderly population. Clin Exp Pharmacol Physiol Suppl (2002) S9-S12
18. Reeves M.M., Capra S., Bauer J., Davies P.S., and Battistutta D. Clinical accuracy of the MedGem indirect calorimeter for measuring resting energy expenditure in cancer patients. Eur J Clin Nutr 59 (2005) 603-610
19. Compher C., Hise M., Sternberg A., and Kinosian B.P. Comparison between Medgem and Deltatrac resting metabolic rate measurements. Eur J Clin Nutr 59 (2005) 1136-1141
20. Institute of Medicine Panel on Macronutrients, Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids (2005), National Academies Press, Washington, DC 107-264
21. da Rocha E.E., Alves V.G., Silva M.H., Chiesa C.A., and da Fonseca R.B. Can measured resting energy expenditure be estimated by formulae in daily clinical nutrition practice?. Curr Opin Clin Nutr Metab Care 8 (2005) 319-328
22. Godin G., and Shephard R.J. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 10 (1985) 141-146
23. Bland J.M., and Altman D.G. Applying the right statistics: Analyses of measurement studies. Ultrasound Obstet Gynecol 22 (2003) 85-93
24. Bland J.M., and Altman D.G. Measuring agreement in method comparison studies. Stat Methods Med Res 8 (1999) 135-160
25. Ludbrook J. Statistical techniques for comparing measurers and methods of measurement: A critical review. Clin Exp Pharmacol Physiol 29 (2002) 527-536
26. Heshka S., Feld K., Yang M.U., Allison D.B., and Heymsfield S.B. Resting energy expenditure in the obese: A cross-validation and comparison of prediction equations. J Am Diet Assoc 93 (1993) 1031-1036
27. Müller M.J., Bosy-Westphal A., Klaus S., Kreymann G., Lührmann P.M., Neuhäuser-Berthold M.M., Noack R., Pirke K.M., Platte P., Selberg O., and Steiniger J. 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 80 (2004) 1379-1390
28. Garrel R.D., Jobin N., and DeJonge L.H.M. Should we still use the Harris-Benedict equations?. Nutr Clin Pract 11 (1996) 99-103
29. Horgan G., and Stubbs J. Predicting basal metabolic rate in the obese is difficult. Eur J Clin Nutr 57 (2003) 335-340
30. Carpenter W.H., Poehlman E.T., O'Connell M., and Goran M.I. Influence of body composition and resting metabolic rate on variation in total energy expenditure: A meta-analysis. Am J Clin Nutr 61 (1995) 4-10
31. Alfonzo-Gonzalez G., Doucet E., Almeras N., Bouchard C., and Tremblay A. Estimation of daily energy needs with the FAO/WHO/UNU 1985 procedures in adults: Comparison to whole-body indirect calorimetry measurements. Eur J Clin Nutr 58 (2004) 1125-1131
32. Benedict F. Basal metabolism data on normal men and women (series II) with some considerations on the use of prediction standards. Am J Physiol 85 (1928) 607-620
33. Geissler C.A., Dzumbira T.M., and Noor M.I. Validation of a field technique for the measurement of energy expenditure: Factorial method versus continuous respirometry. Am J Clin Nutr 44 (1986) 596
34. Vander Weg M.W., Watson J.M., Klesges R.C., Eck Clemens L.H., Slawson D.L., and McClanahan B.S. Development and cross-validation of a prediction equation for estimating resting energy expenditure in healthy African-American and European-American women. Eur J Clin Nutr 58 (2004) 474-480
35. Leung R., Woo J., Chan D., and Tang N. Validation of prediction equations for basal metabolic rate in Chinese subjects. Eur J Clin Nutr 54 (2000) 551-554
36. Almendingen K., Trygg K., and Pedersen J.I. An assessment of the use of simple methods to predict individual energy intakes for intervention studies. Eur J Clin Nutr 52 (1998) 54-59
37. Kien C.L., and Ugrasbul F. Prediction of daily energy expenditure during a feeding trial using measurements of resting energy expenditure, fat-free mass, or Harris-Benedict equations. Am J Clin Nutr 80 (2004) 876-880
38. Lin P., Proschan M., Bray G., Fernandez C., Hoben K., Most-Windhauser M., Karanja N., and Obarzanek E. Estimation of energy requirements in a controlled feeding trial. Am J Clin Nutr 77 (2003) 639-645
39. Dobratz J.R., Sibley S.D., Beckman T.R., Valentine B.J., Kellogg T.A., Ikramuddin S., and Earthman C.P. Predicting energy expenditure in extremely obese women. JPEN J Parenter Enteral Nutr 31 (2007) 217-227
40. Rubenbauer J.R., Johannsen D.L., Baier S.M., Litchfield R., and Flakoll P.J. The use of a handheld calorimetry unit to estimate energy expenditure during different physiological conditions. JPEN J Parenter Enteral Nutr 30 (2006) 246-250
41. Stewart C.L., Goody C.M., and Branson R. Comparison of two systems of measuring energy expenditure. JPEN J Parenter Enteral Nutr 29 (2005) 212-217
42. Alam D.S., Hulshof P.J., Roordink D., Meltzer M., Yunus M., Salam M.A., and van Raaij J.M. Validity and reproducibility of resting metabolic rate measurements in rural Bangladeshi women: Comparison of measurements obtained by Medgem and by Deltatrac device. Eur J Clin Nutr 59 (2005) 651-657