Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models.
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.


METHODS
All RMR and body composition measurements were conducted on the same day for each subject following compliance with premeasurement protocols.


METHODS
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%).


METHODS
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)).


CONCLUSIONS
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.


BACKGROUND
Australian Research Council (small grants scheme).
LaForgia
J
J
School of Pharmaceutical, Molecular and Biomedical Sciences, University of South Australia, Adelaide, Australia. joe.laforgia@unisa.edu.au
van der Ploeg
G E
GE
Withers
R T
RT
Gunn
S M
SM
Brooks
A G
AG
Chatterton
B E
BE
D015502:Absorptiometry, Photon / Q000379:methods; D000273:Adipose Tissue / Q000378:metabolism; D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D001481:Basal Metabolism / Q000502:physiology*; D001823:Body Composition / Q000502:physiology*; D001834:Body Water / Q000378:metabolism; D004734:Energy Metabolism / Q000502:physiology; D006801:Humans; D007101:Immersion; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000378:metabolism; D011237:Predictive Value of Tests; D011865:Radioisotope Dilution Technique