Prediction of resting energy expenditure in severely obese Italian women
- PMID: 17318018
- DOI: 10.1007/BF03347391
Prediction of resting energy expenditure in severely obese Italian women
Abstract
The aims of the present study were to develop and cross-validate new equations for predicting resting energy expenditure (PREE) in severely obese Italian women, and to compare their accuracy with those of the Harris-Benedict, Bernstein, WHO/FAO/UNU, Owen, Mifflin, Nelson, Siervo, Huang and Livingston equations to predict REE, using the Bland-Altman method. One hundred and eighty two women [mean body mass index (BMI) 45.6 kg/m2; 56.7% fat mass (FM)], aged 19 to 60 yr participated in this study. REE was measured by indirect calorimetry and body composition by bioelectrical analysis. Equations were derived by stepwise multiple regression analysis, using a calibration group and tested against the validation group. Two new specific equations based on anthropometric REE=Weightx0.042+Heightx3.619-2.678 (R2=0.66, SE=0.56 MJ) or body composition parameters REE=FFMx0.067+FMx0.046+1.568 (R2=0.63, SE=0.58 MJ) were generated. Mean PREE were no different from the mean measured resting energy expenditure (MREE) (<1%, p>0.800) and REE was predicted accurately (95-105% of MREE) in 60% of subjects. The WHO/FAO/UNU, Harris-Benedict and Siervo equations showed mean differences <2% and PREE was accurate in <44% of subjects. The Huang, Mifflin and Livingston equations showed a mean PREE underestimation (>5.0%, p<0.001) and PREE was accurate in <38% of subjects. The Owen, Bernstein and Nelson equations showed a greater PREE underestimation (>14%, p<0.001) in >90% of subjects. The new prediction equations allow an accurate estimation of REE in groups of severely obese women and result in lower mean differences and lower limits of agreement between PREE and MREE than commonly used equations.
Similar articles
-
Prediction of resting energy expenditure in severely obese Italian males.J Endocrinol Invest. 2007 Oct;30(9):754-61. doi: 10.1007/BF03350813. J Endocrinol Invest. 2007. PMID: 17993767
-
Determining the accuracy of predictive energy expenditure (PREE) equations in severely obese adolescents.Clin Nutr. 2017 Aug;36(4):1158-1164. doi: 10.1016/j.clnu.2016.08.006. Epub 2016 Aug 13. Clin Nutr. 2017. PMID: 27612920
-
Comparison of predictive equations for resting energy expenditure in severely obese Caucasian children and adolescents.J Endocrinol Invest. 2007 Apr;30(4):313-7. doi: 10.1007/BF03346298. J Endocrinol Invest. 2007. PMID: 17556868
-
Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?Nutrients. 2019 Feb 4;11(2):334. doi: 10.3390/nu11020334. Nutrients. 2019. PMID: 30720726 Free PMC article. Review.
-
Energy Expenditure and Liver Transplantation: What We Know and Where We Are.JPEN J Parenter Enteral Nutr. 2021 Mar;45(3):456-464. doi: 10.1002/jpen.1985. Epub 2020 Aug 25. JPEN J Parenter Enteral Nutr. 2021. PMID: 32744332 Review.
Cited by
-
Validity of the dietary reference intakes for determining energy requirements in older adults.Nutr Res Pract. 2019 Jun;13(3):256-262. doi: 10.4162/nrp.2019.13.3.256. Epub 2019 May 31. Nutr Res Pract. 2019. PMID: 31214294 Free PMC article.
-
Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population.Nutrients. 2021 Jan 29;13(2):458. doi: 10.3390/nu13020458. Nutrients. 2021. PMID: 33573101 Free PMC article.
-
Resting Energy Expenditure during Breastfeeding: Body Composition Analysis vs. Predictive Equations Based on Anthropometric Parameters.Nutrients. 2020 Apr 30;12(5):1274. doi: 10.3390/nu12051274. Nutrients. 2020. PMID: 32365825 Free PMC article.
-
Validity of predictive equations for resting energy expenditure in Korean non-obese adults.Nutr Res Pract. 2018 Aug;12(4):283-290. doi: 10.4162/nrp.2018.12.4.283. Epub 2018 Jun 1. Nutr Res Pract. 2018. PMID: 30090165 Free PMC article.
-
Issues in Measuring and Interpreting Energy Balance and Its Contribution to Obesity.Curr Obes Rep. 2019 Jun;8(2):88-97. doi: 10.1007/s13679-019-00339-z. Curr Obes Rep. 2019. PMID: 30903595 Review.
References
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources