Cited by 371Body Composition Measurement TechniquesClinical Nutrition and GastroenterologyRegulation of Appetite and Obesity

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Prediction of resting energy expenditure from fat-free mass and fat mass

Nelson, KM, Weinsier, RL, Long, CL, Schutz, Y·1992·The American Journal of Clinical Nutrition

DOI 10.1093/ajcn/56.5.848

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Abstract

On the basis of literature values, the relationship between fat-free mass (FFM), fat mass (FM), and resting energy expenditure [REE (kJ/24 h)] was determined for 213 adults (86 males, 127 females). The objectives were to develop a mathematical model to predict REE based on body composition and to evaluate the contribution of FFM and FM to REE. The following regression equations were derived: 1) REE = 1265 + (93.3 x FFM) (r2 = 0.727, P < 0.001); 2) REE = 1114 + (90.4 x FFM) + (13.2 x FM) (R2 = 0.743, P < 0.001); and 3) REE = (108 x FFM) + (16.9 x FM) (R2 = 0.986, P < 0.001). FM explained only a small part of the variation remaining after FFM was accounted for. The models that include both FFM and FM are useful in examination of the changes in REE that occur with a change in both the FFM and FM. To account for more of the variability in REE, FFM will have to be divided into organ mass and skeletal muscle mass in future analyses.

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“However, also fat mass (FM), depending on its extent and location, may play a role in RMR variability, although FM shows a 6 to 7 times lower specific metabolic rate than FFM (7).”
Background
Centile reference chart for resting metabolic rate through the life course
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“[34] and whole body energy expenditure [35] is dependent predominately on fat free mass (FFM) rather than total body mass, and fat mass accumulated at a greater rate than lean body mass.”
Background
A Resting Metabolic Rate Equation Including Bioelectrical Impedance– Derived Lean Body Mass Provides a Better Prediction in Premenopausal African American Women Across a Spectrum of Body Mass Indices
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Dobratz, J. R., Sibley, S. D., Beckman, T. R., Valentine, B. J., Kellogg, T. A., Ikramuddin, S., & Earthman, C. P. (2007) · Topics in Clinical Nutrition · doi:10.1097/01.tin.0000270131.48518.76 · Cited by 3
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“Some researchers attribute an important role to it in influencing energy expenditure [9], while other studies do not show such a relationship [10].”
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“Although the brain (240 kcal/kg/d), liver (200 kcal/kg/d), and kidneys (400 kcal/kg/d) represent only about 5% of the body weight 21 – 23 , theyaccount for51%of the totalRMR.”
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“…that RMR is primarily influenced by FFM, which may not be adequately modu - lated by exercise alone in the context of rapid postoperative metabolic changes [ 74 ]. are particularly relevant given the pronounced decline in fat-free mass that typically occurs in the early postoperative period.”
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“…cornerstone in the study of physiological aspects of body weight regulation and human energy requirements (Weinsier et al. 1992; Wang et al. 2000), the additional role played by FM as an independent factor influencing BMR has been a matter of contention (Nelson et al. 1992; Svendsen et al. 1993).”
Background
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“The amount of lean skeletal muscle controls how quickly the body burns calories (Mifflin et al. 1990; Nelson et al. 1992; Taguchi et al. 2011).”
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Authors: Nelson, K., Weinsier, R., Long, C., & Schutz, Y.
Affiliations: University of Alabama at Birmingham (US)
Corresponding author: Nelson, KM
Venue: The American Journal of Clinical Nutrition
Publisher: Elsevier BV
Published: 1992-11
Volume: 56
Issue: 5
Pages: 848-856
ISSN: 0002-9165 (ISSN-L)
DOI: 10.1093/ajcn/56.5.848
OpenAlex: W1954962848
Cited by: 371
References: 44
Citations by year: 2026: 11 · 2025: 3 · 2024: 10 · 2023: 13 · 2022: 16 · 2021: 23 · 2020: 19 · 2019: 9 · 2018: 17 · 2017: 15 · 2016: 15 · 2015: 19 · 2014: 16 · 2013: 16 · 2012: 13
FWCI: 1.95
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: American Journal of Clinical Nutrition (publishedVersion)
PubMed (publishedVersion)
IRIS (submittedVersion)
SERVAL (Université de Lausanne) (submittedVersion)
Topics: Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
Health Sciences › Nursing › Nutrition and Dietetics › Clinical Nutrition and Gastroenterology
Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
Keywords: resting energy expenditure, fat-free mass, fat mass, body composition, energy expenditure estimation, regression models, skeletal muscle mass, organ mass, adults
MeSH terms: Adipose Tissue, Adult, Basal Metabolism, Body Composition, Energy Metabolism, Female, Humans, Male, Mathematics, Models, Biological, Obesity, Regression Analysis

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Prediction of resting energy expenditure from fat-free mass and fat mass

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