Physiological Application Two Examples Example

Expressing heat production relative to body mass is required when comparing energy expenditure rates between individuals that differ in size. Age and gender-specific resting energy expenditure (REE) norms based on body weight and stature-derived were developed in the early 1900s by Kleiber and showed that adult mammals differing widely in body size had similar metabolic rates relative to body weight raised to the 0.75 power. Two components are usually considered as representative of whole-body metabolically active tissue, body cell mass (BCM), and FFM. BCM is typically estimated as the exchangeable potassium space that can be measured by total body potassium. The FFM component can be measured using two-component body composition methods.

In studies assessing REE, FFM is considered the principal contributor to energy requirements, and is commonly used as a surrogate for metabolically active tissue. However, this practice is inherently flawed as it pools together numerous organs and tissues that differ significantly in metabolic rate. The brain, liver, heart, and kidneys alone account for approximately 60% of REE in adults while their combined weight is less than 6% of total body weight or 7% of FFM. The skeletal muscle component of FFM comprises 40-50% of total body weight (or 51% of FFM) and accounts for only 18-25% of REE. REE varies in relation to body size across mammalian species. Within humans, REE per kg of body weight or FFM is highest in newborns (^56 kcal kg-1 day-1), declines sharply until 4 years, and slowly thereafter reaching adult values (~25kcalkg-1day-1). Among adults,

REE is lower in the later adult years, to an extent beyond that explained by changes in body composition. That is, the loss of FFM cannot fully explain the decrease (5-25%) in REE in healthy elderly persons.

Recent attention has been given to modeling REE based on available information on organ- and tissue-specific metabolic rates combined (Table 3) with the mass of these tissues as determined by MRI. Whole-body REE can be calculated from organ- tissue mass (REEc) and then compared to REE measured using indirect calorimetry (REEm) for individuals or groups. REE (in kJday-1) of each organ- tissue component (subscript i) can be calculated using the following equation:

where OMR (organ metabolic rate) is the metabolic rate constant (in kJ per kg per day) for each organ-tissue component (Table 3) and M is the mass of the corresponding organ/tissue (in kg). Whole-body REE (in kJ per day) is calculated as the sum of the seven individual organ-tissue REE

The whole-body REE equation is: REEc = 1008 x Mbrain + 840 x Mliver

Mresidual [3 ]

This approach has allowed for the hypothesis to be tested that the proportion of FFM as certain

Table 3 Organ and tissue coefficients used in developing models

Weight

Density

Metabolic rate

(kg)a

(kg-1)a

(kJkg-1day-1)b

Skeletal muscle

28.0

1.04

55

Adipose tissue

15.0

0.92

19

Liver

1.8

1.05

840

Brain

1.4

1.03

1008

Heart

0.3

1.03

1848

Kidneys

0.3

1.05

1848

Residual

23.2

*

50

aAdapted from Snyder WS, Cook MJ, Nasset ES et al. (1975) Report of the task group on reference men. International Commission on Radiological Protection 23. Oxford: Pergamon. bAdapted from Elia M (1992) Organ and tissue contribution to metabolic rate. In: Kinney JM and Tucker HN (eds.) Energy Metabolism. Tissue Determinants and Cellular Corollaries, pp. 61-77. New York: Raven Press.

Residual mass was not assigned a density but was calculated as body mass minus sum of other measured mass components.

aAdapted from Snyder WS, Cook MJ, Nasset ES et al. (1975) Report of the task group on reference men. International Commission on Radiological Protection 23. Oxford: Pergamon. bAdapted from Elia M (1992) Organ and tissue contribution to metabolic rate. In: Kinney JM and Tucker HN (eds.) Energy Metabolism. Tissue Determinants and Cellular Corollaries, pp. 61-77. New York: Raven Press.

Residual mass was not assigned a density but was calculated as body mass minus sum of other measured mass components.

-3.7 ± 0.5%*

-3.3 ± 0.9%-

6.2 ± 1.3%**

0.8 ± 0.1% 0.5 ± 0.2%

51.0 ± 9.4%

52.5 ± 4.2%

37.8 ± 9.4%

39.9 ± 3.4%

Children

Adults

□ Liver □ Brain □ Heart ■ Kidneys □ SM □ Residual

Figure 4 Proportional contribution of each organ/tissue to Adipose Tissue Free Mass (ATFM). Liver (i i). brain (□), heart (□), kidneys (h), skeletal muscle mass (i i), residual mass (□), * p <0.01 and ** p <0.001 for children vs. adults. Reproduced with permission from Hsu A, Heshka S, Janumala I, Song MY, Horlick M, Krasnow N, and Gallagher D (2003) Larger mass of high-metabolic-rate organs does not explain higher resting energy expenditure in children. American Journal of Ciinical Nutrition 77: 1506-11.

high metabolic rate organs, specifically liver and brain, is greater in children compared to young adults (Figure 4). Findings thus far have shown that after accounting for this disproportion, the specific organ/tissue metabolic constants available in the literature (Table 3) are not adequate to account for REE in children. These results therefore imply that the decline in REE per kilogram body weight (or per kilogram FFM) during the growth years is likely due to both changes in body composition and changes in the metabolic rate of individual organs/tissues. When this approach was applied to young adults (31.2 ± 7.2 years), REEc and REEm were highly correlated, with no significant differences between them. When this approach was applied to persons over 70 years, both older men and women had significantly lower REEm compared to REEc, and the magnitude of the differences were 13% and 9.5%, respectively, for men and women. These findings suggest that even after adjustment for age-related organ and tissue atrophy in the elderly, whole body REE by indirect calorimetry continues to be lower than expected. The latter suggests that the metabolic rate constants used (Table 3) for specific organs and tissues may not be appropriate in the elderly.

At the individual or clinic level, the measurement of REE by indirect calorimetry is frequently unavailable. An alternate approach has been to estimate REE

based on body weight, height, age, and sex. Many studies have examined the association between these basic and easily acquired measures and REE. A small number of studies have included FFM in their REE prediction equations. Table 4 lists published equations for the prediction of REE in healthy individuals.

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