Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass

Gallagher, Dympna; Belmonte, Daniel García; Deurenberg, P.; Wang, Z.M.; Krasnow, Norman; Pi‐Sunyer, F. Xavier; Heymsfield, Steven B.

doi:10.1152/ajpendo.1998.275.2.e249

Cited by 341 publications

(457 citation statements)

References 28 publications

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“…However, neither with the results of our investigation in which weights of the brain, heart, liver and kidneys were calculated by regression equations according to Garby et al (1993) nor with the results of Gallagher et al (2000), who measured the volumes of the organs and tissues by magnetic resonance imaging, can it be explained whether the decline in RMR independently of changes in body composition relates to a reduction in the organs' metabolic rate or whether this is due, for example, to morphological changes like infiltration of the organs with fat, oedema or cystic structures (Gallagher et al, 1998). Future studies should focus therefore on oxygen consumption of specific organs and its relation to respective anatomical, physiological or biochemical changes in these tissues associated with age.…”

Section: Discussionmentioning

confidence: 99%

“…One approach to investigate this question is to calculate RMR on the basis of individual tissue masses and their specific metabolic rates and to compare calculated RMR to RMR assessed by indirect calorimetry (Gallagher et al, 1998). Gallagher et al (2000) employed this approach of calculated and measured RMR in a small sample of seven elderly women and six elderly men.…”

Section: Introductionmentioning

confidence: 99%

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Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

et al. 2004

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Objective: To investigate whether or not the lower resting metabolic rate (RMR) in the elderly is entirely due to changes in body composition. Design: Cross-sectional data of 132 female (age 69.975.5 y, body mass index (BMI) 26.574.0 kg/m 2 ) and 84 male (age 68.975.1 y, BMI 26.172.8 kg/m 2 ) participants of the longitudinal study on nutrition and health status in an aging population of Giessen, Germany, as well as that of 159 young women (age 24.873.0 y, BMI 21.172.5 kg/m 2 ) and 67 young men (age 26.873.4 y, BMI 23.372.4 kg/m 2 ) were analysed. RMR was measured by indirect calorimetry after an overnight fast and body composition was estimated by bioelectrical impedance analysis and predictive equations from the literature. Analysis of covariance was used to adjust RMR for body composition, body fat distribution and smoking habits. Additionally, RMR that is to be expected theoretically, was calculated on the basis of the subjects' body composition and the specific metabolic rate of the different organs and was compared to measured RMR. Results: Compared to young subjects adjusted RMR was significantly lower in elderly women (5432782 vs 5809770 kJ/day, Po0.01) and men (6971799 vs 75587121 kJ/day, Po0.001). In both elderly women and men, measured RMR was markedly lower than calculated RMR (À6257404, À5157570 kJ/day). By contrast, measured and calculated RMR were nearly the same in young men (1597612 kJ/day); in young women the difference between measured and calculated RMR was only À3007457 kJ/day. In both sexes, these differences are significantly larger in the elderly when compared to young adults. Conclusion: These results support the point of view that the decline in RMR with advancing age cannot be totally due to changes in body composition.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

et al. 2004

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“…Ideally RMR data have to be corrected for differences in FFM (Deurenberg, 1994), although it can be argued that such a correction is only a very crude one. Gallagher et al (1998) recently showed that the FFM is not one entity in that different components of the FFM have different contributions to the RMR. Based on their data it can be argued that obese subjects will have a lower RMR per kg body mass or even per kg fat-free mass, as their organ contribution per kg body weight or per kg FFM will be relatively lower.…”

Section: Discussionmentioning

confidence: 99%

Measured and predicted resting metabolic rate in Italian males and females, aged 18–59 y

et al. 2001

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Objectives: To determine the resting metabolic rate in a sample of the Italian population, and to evaluate the validity of predictive equations for resting metabolic rate (RMR) from the literature in normal and obese subjects. Design: Cross-sectional observational study. Settings: Department of Human Physiology and Nutrition, University`Tor Vergata', Rome. Subjects: A total of 320 healthy subjects, 127 males and 193 females, aged 18 ± 59 y. Methods: Weight, height and resting metabolic rate by indirect calorimetry were measured. Resting metabolic rate was also predicted using equations from the literature. Results: Resting metabolic rate (mean AE s.d.) in normal weight subjects was 7983 AE 1007 kJa24 h (males) and 6127 AE 907 kJa24 h (females). Measured RMR and predicted RMR values using various equations from the literature were signi®cantly different in males and females, except for the Harris ± Benedict equation and the Scho®eld equations. Also, in overweight and obese subjects the prediction error was generally larger compared to normal-weight subjects for all formulas except for the Harris ± Benedict and Scho®eld formulas. In overweight and obese males but not in females, RMR was lower than in normal-weight subjects after correcting for weight and age differences. Stepwise multiple regression of resting metabolic rate against weight, height and age in males and females did not reveal a prediction formula with a lower prediction error than the Harris ± Benedict or Scho®eld formulas and thus was not further explored. Conclusions: The Harris ± Benedict formula and the Scho®eld formula provide a valid estimation of resting metabolic rate at a group level in both normal-weight and overweight Italians. However, the individual error can be so high that for individual use a measured value has to be preferred over an estimated value.

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“…Total body adipose tissue volume, SM volume, and ATFM were evaluated by whole-body MRI in Asian men age Ն18 yr at the NY Obesity Research Center. Compartment volumes were converted to mass using previously reported (7,37) densities for adipose tissue (0.92 kg/l), SM (1.04 kg/l), and ATFM (1.04 kg/l). Bone mineral content (BMC) was measured by DXA on the same day and results were converted to bone mass as BMC/0.54 (12,37).…”

Section: Experimental Design and Rationalementioning

confidence: 99%

“…Since brain is a high-metabolic-rate organ (ϳ240 kcal⅐kg Ϫ1 ⅐day Ϫ1 ; Ref. 7), a relatively smaller brain mass may provide a partial mechanistic explanation for the lower REE/ body weight observed in taller men.…”

mentioning

confidence: 99%

Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults

Heymsfield¹,

Chirachariyavej²,

Rhyu³

et al. 2009

Journal of Applied Physiology

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Heymsfield SB, Chirachariyavej T, Rhyu IJ, Roongpisuthipong C, Heo M, Pietrobelli A. Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults. J Appl Physiol 106: 40 -48, 2009. First published November 13, 2008 doi:10.1152/japplphysiol.91123.2008.-Adult resting energy expenditure (REE) scales as height ϳ1.5 , whereas body weight (BW) scales as height ϳ2 . Mass-specific REE (i.e., REE/BW) is thus lower in tall subjects compared with their shorter counterparts, the mechanism of which is unknown. We evaluated the hypothesis that high-metabolic-rate brain mass scales to height with a power significantly less than that of BW, a theory that if valid would provide a potential mechanism for height-related REE effects. The hypothesis was tested by measuring brain mass on a large (n ϭ 372) postmortem sample of Thai men. Since brain mass-body size relations may be influenced by age, the hypothesis was secondarily explored in Thai men age Յ45 yr (n ϭ 299) and with brain magnetic resonance imaging (MRI) studies in Korean men (n ϭ 30) age Ն20Ͻ30 yr. The scaling of large body compartments was examined in a third group of Asian men living in New York (NY, n ϭ 28) with MRI and dual-energy X-ray absorptiometry. Brain mass scaled to height with a power (mean Ϯ SEE; 0.46 Ϯ 0.13) significantly smaller (P Ͻ 0.001) than that of BW scaled to height (2.36 Ϯ 0.19) in the whole group of Thai men; brain mass/BW scaled negatively to height (Ϫ1.94 Ϯ 0.20, P Ͻ 0.001). Similar results were observed in younger Thai men, and results for brain mass/BW vs. height were directionally the same (P ϭ 0.09) in Korean men. Skeletal muscle and bone scaled to height with powers similar to that of BW (i.e., ϳ2-3) in the NY Asian men. Models developed using REE estimates in Thai men suggest that brain accounts for most of the REE/BW height dependency. Tall and short men thus differ in relative brain mass, but the proportions of BW as large compartments appear independent of height, observations that provide a potential mechanistic basis for related differences in REE and that have implications for the study of adult energy requirements. body composition; nutritional requirements ENERGY REQUIREMENTS ARE LARGELY determined by subject body weight (5b, 23). Since adult body weight increases as a function of height ϳ2 (33), taller subjects weigh more and have a greater energy requirement than their shorter counterparts (5b). The largest component of energy requirements in most adults is related to resting energy expenditure (REE), and REE scales as height ϳ1.5 (13). Accordingly, mass-specific resting energy requirements, defined as REE/body weight, decrease as height Ϫ0.5 . Tall subjects thus appear to have a smaller magnitude mass-specific REE and from the energetic perspective can be considered relatively more "efficient" at rest. Greater stature and associated body weight are thus not accompanied by a proportionally larger resting energy need.The mechanism leadin...

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Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass

Cited by 341 publications

References 28 publications

Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

Measured and predicted resting metabolic rate in Italian males and females, aged 18–59 y

Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults

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