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Type: Journal article
Title: Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models
Author: La Forgia, J.
van der Ploeg, G.
Withers, R.
Gunn, S.
Brooks, A.
Chatterton, B.
Citation: European Journal of Clinical Nutrition, 2004; 58(8):1132-1141
Publisher: Nature Publishing Group
Issue Date: 2004
ISSN: 0954-3007
Statement of
LaForgia, J; van der Ploeg, GE; Withers, RT; Gunn, SM; Brooks, AG and Chatterton BE.
Abstract: OBJECTIVE: To examine the differences arising from indexing resting metabolic rate (RMR) against fat-free mass (FFM) determined using two-, three- and four-compartment body composition models. DESIGN: All RMR and body composition measurements were conducted on the same day for each subject following compliance with premeasurement protocols. SUBJECTS: Data were generated from measurements on 104 males (age 32.1+/-12.1 y (mean+/-s.d.); body mass 81.15+/-12.85 kg; height 179.5+/-6.5 cm; body fat 20.6+/-7.6%). INTERVENTIONS: Body density (BD), total body water (TBW) and bone mineral mass (BMM) were measured by hydrodensitometry, deuterium dilution and dual energy X-ray absorptiometry (DXA), respectively. These measures were used to determine two (hydrodensitometry: BD; hydrometry: TBW)-, three (BD and TBW)- and four- compartment (BD, TBW and BMM) FFM values. DXA also provided three compartment derived FFM values. RMR was measured using open circuit indirect calorimetry. RESULTS: Three (body fat group: lean, moderate, high) x five (body composition determination: hydrodensitometry, hydrometry, three-compartment, DXA, four-compartment) ANOVAs were conducted on FFM and RMR FFM(-1).d(-1). Within-group comparisons revealed that hydrodensitometry and DXA were associated with significant (P<0.001) overestimations and underestimations of FFM and RMR FFM(-1).d(-1), respectively, compared with four-compartment-derived criterion values. A significant interaction (P<0.001) resulted from DXA's greater deviations from criterion values in lean subjects. While hydrometric means were not significantly (P> or =0.68) different from criterion values intraindividual differences were large (FFM: -1.5 to 2.9 kg; RMR: -6.0 to 3.2 FFM(-1).d(-1)). CONCLUSION: The relationship between RMR FFM(-1).d(-1) and exercise status would best be investigated using three (BD, TBW)- or four (BD, TBW, BMM)-compartment body composition models to determine FFM. Other models either significantly underestimate indexed RMR (hydrodensitometry, DXA) or display large intraindividual differences (hydrometry) compared with four-compartment derived criterion values. SPONSORSHIP: Australian Research Council (small grants scheme).
Keywords: Muscle, Skeletal
Adipose Tissue
Body Water
Absorptiometry, Photon
Basal Metabolism
Radioisotope Dilution Technique
Analysis of Variance
Predictive Value of Tests
Body Composition
Energy Metabolism
Models, Biological
Middle Aged
DOI: 10.1038/sj.ejcn.1601941
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