Specific metabolic rates of major organs and tissues across adulthood: evaluation by mechanistic model of resting energy expenditure

Abstract

Background: The specific resting metabolic rates (K(i); in kcal · kg(-1 )· d(-1)) of major organs and tissues in adults were suggested by Elia (in Energy metabolism: tissue determinants and cellular corollaries. New York, NY: Raven Press, 1992) to be as follows: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue, and 12 for residual organs and tissues. However, Elia's K(i) values have never been fully evaluated.

Objectives: The objectives of the present study were to evaluate the applicability of Elia's K(i) values across adulthood and to explore the potential influence of age on the K(i) values.

Design: A new approach was developed to evaluate the K(i) values of major organs and tissues on the basis of a mechanistic model: REE = Σ(K(i) × T(i)), where REE is whole-body resting energy expenditure measured by indirect calorimetry, and T(i) is the mass of individual organs and tissues measured by magnetic resonance imaging. With measured REE and T(i), marginal 95% CIs for K(i) values were calculated by stepwise univariate regression analysis. An existing database of nonobese, healthy adults [n = 131; body mass index (in kg/m²) <30] was divided into 3 age groups: 21-30 y (young, n = 43), 31-50 y (middle-age, n = 51), and > 50 y (n = 37).

Results: Elia's K(i) values were within the range of 95% CIs in the young and middle-age groups. However, Elia's K(i) values were outside the right boundaries of 95% CIs in the >50-y group, which indicated that Elia's study overestimated K(i) values by 3% in this group. Age-adjusted K(i) values for adults aged >50 y were 194 for liver, 233 for brain, 426 for heart and kidneys, 12.6 for skeletal muscle, 4.4 for adipose tissue, and 11.6 for residuals.

Conclusion: The general applicability of Elia's K(i) values was validated across adulthood, although age adjustment is appropriate for specific applications.

FIGURE 1.

The difference between measured and predicted resting energy expenditure (ie, REEm – REEp) compared with the mean of REEm and REEp for all subjects. (REEm – REEp) = 0.0306 × mean – 61.2; r = 0.09, P > 0.20; n = 131. REEp was calculated by using the K_i values suggested by Elia (1), according to Equation 3. The regression line, zero difference line, and the lines representing 2 SDs for the differences (146, −172 kcal/d; indicated by the upper and lower lines) are shown.

FIGURE 2.

The 95% marginal CIs for K_i values of major organs and tissues, fitted by stepwise univariate analysis and shown on a logarithmic scale, for all adult subjects. The Xs represent the K_i values suggested by Elia (1). AT, adipose tissue; Res, residual mass; SM, skeletal muscle.

FIGURE 3.

The difference between measured and predicted resting energy expenditure (ie, REEm – REEp) compared with age for all subjects. (REEm – REEp) = 47.7 − 1.45 × age; r = −0.27, P < 0.01; n = 131. REEp was calculated by using the K_i values suggested by Elia (1), according to Equation 3. The zero difference line is shown.

FIGURE 4.

The 95% marginal CIs for K_i values of major organs and tissues, fitted by stepwise univariate analysis and shown on a logarithmic scale, for the young (upper line), middle-age (middle line), and >50-y (lower line) groups. The Xs represent the K_i values suggested by Elia (1). AT, adipose tissue; Res, residual mass; SM, skeletal muscle.