A new equation to estimate basal energy expenditure of patients with diabetes

Clinical Nutrition

Volumn 32, Issue 5, 2013, Pages 777-782

  Ikeda, Kaori ^a   Fujimoto, Shimpei ^a,b   Goto, Masashi ^a   Yamada, Chizumi ^a   Hamasaki, Akihiro ^a   Ida, Megumi ^c   Nagashima, Kazuaki ^a   Shide, Kenichiro ^c   Kawamura, Takashi ^a   Inagaki, Nobuya ^a  

^a KYOTO UNIVERSITY   (Japan)

^b KOCHI MEDICAL SCHOOL   (Japan)

^c KYOTO UNIVERSITY HOSPITAL   (Japan)

Author keywords

Basal metabolic rate; Diabetes; Indirect calorimetry; Medical nutrition therapy; Prediction equation; Resting metabolic rate

Indexed keywords

GLUCOSE; HEMOGLOBIN A1C;

ADULT; AGED; ANTHROPOMETRIC PARAMETERS; ARM MUSCLE AREA; ARTICLE; BASAL ENERGY EXPENDITURE; BASAL METABOLIC RATE; BODY HEIGHT; BODY WEIGHT; CALORIMETRY; CONTROLLED STUDY; ENERGY EXPENDITURE; FAT FREE MASS; FEMALE; GANPULE EQUATION; GLUCOSE BLOOD LEVEL; HARRIS BENEDICT EQUATION; HEMOGLOBIN DETERMINATION; HIP CIRCUMFERENCE; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; INTERMETHOD COMPARISON; JAPANESE; LIU EQUATION; MAJOR CLINICAL STUDY; MALE; MEASUREMENT ACCURACY; NON INSULIN DEPENDENT DIABETES MELLITUS; OXFORD EQUATION; PREDICTIVE VALUE; STATISTICAL ANALYSIS; TRICEPS SKINFOLD THICKNESS; VALIDATION PROCESS; WAIST CIRCUMFERENCE;

BASAL METABOLIC RATE; DIABETES; INDIRECT CALORIMETRY; MEDICAL NUTRITION THERAPY; PREDICTION EQUATION; RESTING METABOLIC RATE;

ADULT; AGE FACTORS; AGED; ALGORITHMS; BASAL METABOLISM; BODY COMPOSITION; BODY WEIGHT; CALORIMETRY, INDIRECT; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; ENERGY METABOLISM; FEMALE; HUMANS; JAPAN; MALE; MIDDLE AGED; MODELS, BIOLOGICAL; REGRESSION ANALYSIS; SEX CHARACTERISTICS; YOUNG ADULT;

EID: 84883551458     PISSN: 02615614     EISSN: 15321983     Source Type: Journal    
DOI: 10.1016/j.clnu.2012.11.017     Document Type: Article

References (30)

1. American Diabetes Association Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care 2008, 31(Suppl. 1):S61-S78.
2. 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, 54:963-969.
3. Bitz C., Toubro S., Larsen T.M., Harder H., Rennie K.L., Jebb S.A., et al. Increased 24-h energy expenditure in type 2 diabetes. Diabetes Care 2004, 27:2416-2421.
4. Martin K., Wallace P., Rust P.F., Garvey W.T. Estimation of resting energy expenditure considering effects of race and diabetes status. Diabetes Care 2004, 27:1405-1411.
5. Ikeda K., Fujimoto S., Goto M., Yamada C., Hamasaki A., Shide K., et al. Impact of endogenous and exogenous insulin on basal energy expenditure in patients with type 2 diabetes under standard treatment. Am J Clin Nutr 2011, 94:1513-1518.
6. Ryan M., Sallé A., Guilloteau G., Genaitay M., Livingstone M.B., Ritz P. Resting energy expenditure is not increased in mildly hyperglycaemic obese diabetic patients. Br J Nutr 2006, 96:945-948.
7. Harris J.A., Benedict F.G. Abiometric study of basal metabolism in man 1919, Carnegie Institute of Washington, Washington, DC, [Publication number 297].
8. Leung R., Woo J., Chan D., Tang N. Validation of prediction equations for basal metabolic rate in Chinese subjects. Eur J Clin Nutr 2000, 54:551-554.
9. Case K.O., Brahler C.J., Heiss C. Resting energy expenditures in Asian women measured by indirect calorimetry are lower than expenditures calculated from prediction equations. JAm Diet Assoc 1997, 97:1288-1292.
10. Liu H.-Y., Lu Y.-F., Chen W.-J. Predictive equations for basal metabolic rate in Chinese adults: a cross-validation study. JAm Diet Assoc 1995, 95:1403-1408.
11. Henry C.J.K., Rees D.G. New predictive equations for the estimation of basal metabolic rate in tropical peoples. Eur J Clin Nutr 1991, 45:177-185.
12. Cole T.J., Henry C.J.K. The Oxford Brookes basal metabolic rate database- a reanalysis. Public Health Nutr 2005, 8:1202-1212.
13. Wouters-Adeiaens M.P.E., Westerterp K.R. Low resting energy expenditure in Asians can be attributed to body composition. Obesity 2008, 16:2212-2216.
14. Soares M.J., Piers L.S., O'Dea K., Shetty P.S. No evidence for an ethnic influence on basal metabolism: an examination of data from India and Australia. Br J Nutr 1998, 79:333-341.
15. Miyake R., Tanaka S., Ohkawara K., Ishikawa-Takata K., Hikihara Y., Taguri E., et al. Validity of predictive equations for basal metabolic rate in Japanese adults. JNutr Sci Vitaminol 2011, 57:224-232.
16. Bursztein S., Elwyn D.H., Askanazi J., Kinney J.M. Energy metabolism, indirect calorimetry, and nutrition 1989, Lippincott Williams & Wilkins, Baltimore.
17. 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. JAm Diet Assoc 2006, 106:881-903.
18. Frary C.D., Johnson R.K. Energy. Krause's food & nutrition therapy 2007, 22-38. 12th ed. L.K. Mahan, S. Escott-Stump (Eds.).
19. Japan Diabetes Society Treatment guide for diabetes 2007, Bunkodo, Tokyo Japan.
20. Weir J.B. New methods for calculating metabolic rate with special reference to protein metabolism. JPhysiol 1949, 109:1-9.
21. Japanese anthropometric reference data. Jpn J Nutr Assesment 2002, 19:12-19.
22. The Committee of the Japan Diabetes Society on the diagnostic criteria of diabetes mellitus Report of the committee on the classification and diagnostic criteria of diabetes mellitus. JDiabetes Invest 2010, 1:212-228.
23. Weijs P.J.M., Vansant G.A.A.M. Validity of predictive equations for resting energy expenditure in Belgian normal weight to morbid obese women. Clin Nutr 2010, 29:347-351.
24. 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, 56:848-856.
25. Lean M.E.J., Han T.S., Deurenberg P. Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr 1996, 63:4-14.
26. Johnstone A.M., Rance K.A., Murison S.D., Duncan J.S., Speakman J.R. Additional anthropometric measures may improve the predictability of basal metabolic rate in adult subjects. Eur J Clin Nutr 2006, 60:1437-1444.
27. Korth O., Bosy-Westphal A., Zschoche P., Glüer C.C., Heller M., Müller M.J. Influence of methods used in body composition analysis on the prediction of resting energy expenditure. Eur J Clin Nutr 2007, 61:582-589.
28. Hebert S.L., Nair K.S. Protein and energy metabolism in type 1 diabetes. Clin Nutr 2010, 29:13-17.
29. Ministry of Health, Labour and Welfare of Japan Dietary reference intakes for Japanese, 2010 2009, Daiichi Shuppan, Tokyo, Japan.
30. Usui C., Takahashi E., Gando Y., Sanada K., Oka J., Miyachi M., et al. Resting energy expenditure can be assessed by dual-energy X-ray absorptiometry in women regardless of age and fitness. Eur J Clin Nutr 2009, 63:529-535.