1991
DOI: 10.1093/ajcn/54.6.963
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Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation

Abstract: Differences in body composition have often been examined in conjunction with measurements of energy expenditure in men and women. Numerous studies during the past decade examined the relationship between resting energy expenditure (REE) and the components of a two-compartment model of composition, namely the fat-free mass (FFM) and the fat mass (FM). A synthetic review of these studies confirms a primary correlation between REE and FFM in adults over a broad range of body weights. A generalized prediction equa… Show more

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Cited by 510 publications
(415 citation statements)
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“…The relationship of age and gender with metabolic rates disappeared after adjustment for fat mass and fat-free mass, except for SMR-8h. Similar results have been reported showing that the effect of age and gender on metabolic rates is mainly due to fat-free mass (Ravussin et al, 1986;Astrup et al, 1990;Cunningham, 1991;Nelson et al, 1992) and fat mass (Dionne et al, 1999).…”
Section: Discussionsupporting
confidence: 88%
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“…The relationship of age and gender with metabolic rates disappeared after adjustment for fat mass and fat-free mass, except for SMR-8h. Similar results have been reported showing that the effect of age and gender on metabolic rates is mainly due to fat-free mass (Ravussin et al, 1986;Astrup et al, 1990;Cunningham, 1991;Nelson et al, 1992) and fat mass (Dionne et al, 1999).…”
Section: Discussionsupporting
confidence: 88%
“…In our equations, fatfree mass (measured using skinfold thickness) accounted for 84À89% of the variation in SMR, which is better than previously reported (Ravussin et al, 1990;Toubro et al, 1996;Weyer et al, 1999). In addition, results for the BMR equations are in good agreement with those of others (Cunningham, 1991;Ravussin and Bogardus, 1989;Tataranni and Ravussin, 1995). After fat-free mass, fat mass predicted metabolic rate, but accounted for less than 1% of variation in SMR.…”
Section: Discussionsupporting
confidence: 77%
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“…For the calculation of RMR, only data of subjects in apparently steady-state conditions (ie VO 2 and VCO 2 did not vary more than 5% from the mean value of the 30 min measurement period) were used. In addition to measured values, RMR was predicted using the equations formulated by Harris and Benedict (1919), Robertson and Reid (1952), Scho®eld (1985), Pavlou et al (1986), Owen et al (1986Owen et al ( ,1987, Mif¯in et al (1990) and Cunningham (1991). The equations are given in Table 2.…”
Section: Methodsmentioning
confidence: 99%
“…Typically, the predictive relationships for BMR have r 2 values in the range from 60 to 70% (reviewed by Shetty et al, 1996) leading to residual errors averaging 600-900 kJ (coefficient of variation 8-12%) (e.g., Jequier and Schutz, 1981;Dallosso and James 1984;Soares and Shetty, 1986;Weyer et al, 2000). Studies employing more direct analyses of body composition, by for example dual energy X-ray absorptiometry, at the same time as BMR measurements, have revealed that the major predictor of BMR is fat-free mass (FFM) (Fukagawa et al, 1990;Cunningham 1991;Weinsier et al, 1992), and this explains approximately 70% of the total variation, with some studies finding a secondary, independent contribution of fat mass (FM) (Nelson et al, 1992;Svendsen et al, 1993). Because the 'Schofield equation' only includes body weight and height as predictors, with sex and age being accommodated by a series of different equations for various subgroups, the important roles played by FFM and FM in the determination of BMR raise the possibility that additional anthropogenic measures (such as circumferences or skinfolds) might enhance predictability, with a relatively trivial increase in the workload involved in the predictor measurements (Shetty et al, 1994).…”
Section: Introductionmentioning
confidence: 99%