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https://hdl.handle.net/2440/54760
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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 1476-5640 |
Statement of Responsibility: | 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 kJ.kg 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 kJ.kg 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 kJ.kg FFM(-1).d(-1)). CONCLUSION: The relationship between RMR kJ.kg 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 Humans Absorptiometry, Photon Basal Metabolism Radioisotope Dilution Technique Analysis of Variance Predictive Value of Tests Immersion Body Composition Energy Metabolism Models, Biological Adolescent Adult Middle Aged Male |
DOI: | 10.1038/sj.ejcn.1601941 |
Description (link): | http://www.ncbi.nlm.nih.gov/pubmed/15054426 |
Published version: | http://dx.doi.org/10.1038/sj.ejcn.1601941 |
Appears in Collections: | Aurora harvest 5 Medicine publications |
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