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Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models.
Eur J Clin Nutr. 2004 Aug; 58(8):1132-41.EJ

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).

Authors+Show Affiliations

School of Pharmaceutical, Molecular and Biomedical Sciences, University of South Australia, Adelaide, Australia. joe.laforgia@unisa.edu.auNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

15054426

Citation

LaForgia, J, et al. "Impact of Indexing Resting Metabolic Rate Against Fat-free Mass Determined By Different Body Composition Models." European Journal of Clinical Nutrition, vol. 58, no. 8, 2004, pp. 1132-41.
LaForgia J, van der Ploeg GE, Withers RT, et al. Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models. Eur J Clin Nutr. 2004;58(8):1132-41.
LaForgia, J., van der Ploeg, G. E., Withers, R. T., Gunn, S. M., Brooks, A. G., & Chatterton, B. E. (2004). Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models. European Journal of Clinical Nutrition, 58(8), 1132-41.
LaForgia J, et al. Impact of Indexing Resting Metabolic Rate Against Fat-free Mass Determined By Different Body Composition Models. Eur J Clin Nutr. 2004;58(8):1132-41. PubMed PMID: 15054426.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Impact of indexing resting metabolic rate against fat-free mass determined by different body composition models. AU - LaForgia,J, AU - van der Ploeg,G E, AU - Withers,R T, AU - Gunn,S M, AU - Brooks,A G, AU - Chatterton,B E, PY - 2004/4/1/pubmed PY - 2004/11/2/medline PY - 2004/4/1/entrez SP - 1132 EP - 41 JF - European journal of clinical nutrition JO - Eur J Clin Nutr VL - 58 IS - 8 N2 - 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). SN - 0954-3007 UR - https://www.unboundmedicine.com/medline/citation/15054426/Impact_of_indexing_resting_metabolic_rate_against_fat_free_mass_determined_by_different_body_composition_models_ L2 - http://dx.doi.org/10.1038/sj.ejcn.1601941 DB - PRIME DP - Unbound Medicine ER -