Advances in the understanding of specific metabolic rates of major organs and tissues in humans.

PURPOSE OF REVIEW: To present recent evidence on organ and tissue metabolic rates in humans to explain the variance in resting energy expenditure (REE). RECENT FINDINGS: In humans, present knowledge on specific metabolic activities (i.e. ki-values) refers to seven organs and tissues - brain, heart, liver, kidneys, skeletal muscle, adipose tissue and residual mass - with ki-values of 240, 440, 200, 440, 13, 4.5 and 12 kcal/kg/day, provided by Elia in 1992. Detailed body composition data, as derived from whole body MRI together with measurements of whole body REE, were used to validate ki-values in nonobese, healthy and middle-aged adults. There is no sex difference, but minor, that is 2 and 3% deviations are found for age above 55 years and obesity, respectively. By contrast, in adolescents, differences of about 100 kcal/day or 7.3% of measured REE were observed. There is first evidence for changes in ki-values with either weight loss or weight regain after weight loss. Altogether these data suggest that in adolescence and at age above 55 years, in the obese and with weight change, organ and tissue masses differ in cellularity and/or their specific metabolic rates. Presently, direct assessment of specific organ and tissue metabolic rates in humans by either NMR spectroscopy or PET, together with detailed body composition analysis, has not been performed systematically. SUMMARY: We need to become more skilled in methods and models used for detailed body composition analysis together with detailed assessment of energy expenditure in humans.

Estimation of total body skeletal muscle mass in Chinese adults: prediction model by dual-energy X-ray absorptiometry.

BACKGROUND: There are few reports on total body skeletal muscle mass (SM) in Chinese. The objective of this study is to establish a prediction model of SM for Chinese adults. METHODOLOGY: Appendicular lean soft tissue (ALST) was measured by dual energy X-ray absorptiometry (DXA) and SM by magnetic resonance image (MRI) in 66 Chinese adults (52 men and 14 women). Images of MRI were segmented into compartments including intermuscular adipose tissue (IMAT) and IMAT-free SM. Regression was used to fit the prediction model SM = c + k × ALST. Age and gender were adjusted in the fitted model. The piece-wise linear function was performed to further explore the effect of age on SM. 'Leave-One-Out Cross Validation' was utilized to evaluate the prediction performance. The significance of observed differences between predicted and actual SM was tested by t test and the level of agreement was assessed by the method of Bland and Altman. RESULTS: Men had greater ALST and IMAT-free SM than women. ALST was the primary predictor and highly correlated with IMAT-free SM (R(2) = 0.94, SEE = 1.11 kg, P<0.001). Age was an additional predictor (SM prediction model with age adjusted R(2) = 0.95, SEE = 1.05 kg, P<0.001). There was a piece-wise linear relationship between age and IMAT-free SM: IMAT-free SM = 1.21×ALST-0.98, (Age <45 years) and IMAT-free SM = 1.21×ALST-0.98-0.04× (Age-45), (Age ≥45 years). The prediction performance of this age-adjusted model was good due to 'Leave-One-Out Cross Validation'. No significant difference between measured and predicted IMAT-free SM was detected. CONCLUSION: Previous SM prediction model developed in multi-ethnic groups underestimated SM by 2.3% and 3.4% for Chinese men and women. A new prediction model by DXA has been established to predict SM in Chinese adults.

New insights into scaling of fat-free mass to height across children and adults.

OBJECTIVE: Forbes expressed fat-free mass (FFM, in kg) as the cube of height (H, in m): FFM = 10.3 × H(3). Our objective is to examine the potential influence of gender and population ancestry on the association between FFM and height. METHODS: This is a cross-sectional analysis involving an existing dataset of 279 healthy subjects (155 males and 124 females) with age 5-59 years and body mass index (BMI) 14-28 kg/m(2). FFM was measured by a four-component model as the criterion. RESULTS: Nonlinear regression models were fitted: FFM = 10.8 × H(2.95) for the males and FFM = 10.1 × H(2.90) for the females. The 95% confidence intervals for the exponential coefficients were (2.83, 3.07) for the males and (2.72, 3.08) for the females, both containing hypothesized value 3.0. Population ancestry adjustment was considered in the H-FFM model. The coefficient of the H-FFM model for male Asians is smaller than that for male Caucasians (P = 0.006), while there is no statistically significant difference among African-Americans, Caucasians and Hispanics: 10.6 for the males (10.1 for Asians, 10.8 for African-Americans, 10.7 for Caucasians and 10.4 for Hispanics) and 9.6 for the females (9.3 for Asians, 9.8 for African-Americans, 9.6 for Caucasians and 9.5 for Hispanics). Age adjustment was unnecessary for the coefficient of the H-FFM model. CONCLUSION: Height is the most important factor contributing to the magnitude of FFM across most of the lifespan, though both gender and ancestry effects are significant in the H-FFM model. The proposed H-FFM model can be further used to develop a mechanistic model to explain why population ancestry, gender and age influence the associations between BMI and %Fat.

High ratio of resting energy expenditure to body mass in childhood and adolescence: a mechanistic model.

BACKGROUND: Children have lower resting energy expenditure (REE) but higher ratio of resting energy expenditure to body mass (REE/BM) than do adults. This well-known observation has never been quantitatively explained. OBJECTIVES: The aim of the present study is to understand the high REE/BM in childhood and adolescence. DESIGN: A mechanistic REE/BM model is proposed. Literature data on REE, BM and the masses of four high metabolic rate organs (i.e., liver, brain, heart and kidneys) of 1-18 y boys and girls were used to evaluate the proposed REE/BM model. Specifically, we tested the hypothesis that the magnitude and variation of the REE/BM can be predicted by a combination of four variables, including relative cellularity, growth energy expenditure for constructing new cells, fraction of body mass as individual organs/tissues, and their specific resting energy expenditure. RESULTS: The REE/BM provided by the literature is 54 kcal/kg per day at 1 year, decreasing to 26.0 kcal/kg per day at 18 years. Model-predicted REE/BM can account for 97.0% and 100.7% of the literature-reported REE/BM in males and females, respectively. The average differences between literature-reported and model-predicted REE/BM are 1.1 kcal/kg per day in boys and -0.3 kcal/kg per day in girls. CONCLUSION: The high REE/BM ratio in childhood results from two model variables: the high fraction of body mass as liver, brain, heart, and kidneys, and their high specific resting metabolic rates. The proposed REE/BM model promotes understanding of the REE, and allows a rational establishment of energy requirements for children and adolescents.

Evaluation of specific metabolic rates of major organs and tissues: comparison between nonobese and obese women.

Elia (1992) identified the specific resting metabolic rates (K(i)) of major organs and tissues in young adults with normal weight: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue and 12 for residual mass (all units in kcal/kg per day). The aim of the present study was to assess the applicability of Elia's K(i) values for obese adults. A sample of young women (n = 80) was divided into two groups, nonobese (BMI <29.9 kg/m(2)) and obese (BMI 30.0-43.2 kg/m(2)). This study was based on the 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. For each organ/tissue, the corresponding Elia's K(i) value was analyzed respectively for nonobese and obese groups by using stepwise univariate regression analysis. Elia's K(i) values were within the range of 95% confidence intervals (CIs) in the nonobese group. However, Elia's K(i) values were outside the right boundaries of 95% CIs in the obese group and a corresponding obesity-adjusted coefficient was calculated as 0.98, indicating that Elia's values overestimate K(i) by 2.0% in obese adults. Obesity-adjusted K(i) values were 196 for liver, 235 for brain, 431 for heart and kidneys, 12.7 for skeletal muscle, 4.4 for adipose tissue, and 11.8 for residual mass. In conclusion, although Elia's K(i) values were validated in nonobese women, obesity-adjustments are appropriate for application in obese women.

Evaluation of specific metabolic rates of major organs and tissues: comparison between men and women.

OBJECTIVES: The specific resting metabolic rates (K(i) , in kcal/kg per day) of major organs and tissues in the Reference Man were suggested in 1992 by Elia: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue and 12 for the residual mass. However, it is unknown whether gender influences the K(i) values. The aim of the present study was to compare the K(i) values observed in nonelderly nonobese men to the corresponding values in women. METHODS: Elia's K(i) values were evaluated based on 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 major organs and tissues measured by magnetic resonance imaging. Marginal 95% confidence intervals (CIs) for the model-estimated K(i) values were calculated by stepwise univariate regression analysis. Subjects were nonelderly (age 20-49 years) nonobese (BMI 18.5-29.9 kg/m(2) ) men (n = 49) and women (n = 57). RESULTS: The measured REE (REEm) and the mass of major organs and skeletal muscle were all greater in the men than in women. The predicted REE by Elia's K(i) values were correlated with REEm in men (r = 0.87) and women (r = 0.86, both P < 0.001). Elia's K(i) values were within the range of 95% CIs for both men and women groups, revealing that gender adjustment is not necessary. CONCLUSIONS: Elia's proposed adult K(i) values are valid in both nonelderly nonobese men and women. Further studies are needed to explore the potential influences of age and obesity on K(i) values in humans.

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

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.

Total body carbon and oxygen masses: evaluation of dual-energy x-ray absorptiometry estimation by in vivo neutron activation analysis.

Oxygen and carbon are the first and second abundant elements, respectively, in the human body by mass. Although many physiological and pathological processes are accompanied with alteration of total body oxygen (TBO) and carbon (TBC) masses, in vivo measurements of the two elements are limited. Up to now, almost all available information of TBC and TBO is based on in vivo neutron activation (IVNA) analysis which is very expensive and involves moderate radiation exposure. The aim of the present study was to develop and evaluate an alternative strategy for TBC and TBO estimation. Mechanistic models were derived for predicting TBC and TBO masses from dual-energy x-ray absorptiometry (DXA) and total body water (TBW). Twenty-eight adult subjects were studied. IVNA-measured TBC and TBO masses were used as the criterion. TBC masses predicted by DXA-alone and by DXA-TBW models were 20.8 ± 7.1 kg and 20.6 ± 6.8 kg, respectively, close to the IVNA-measured value (19.5 ± 6.3 kg). There were strong correlations (both with r > 0.95, P < 0.001) between the predicted and measured TBC masses. TBO masses predicted by DXA-alone and by DXA-TBW models were 46.0 ± 9.8 kg and 46.5 ± 9.9 kg, respectively, close to the IVNA-measured value (48.0 ± 10.4 kg). Correlations (both with r > 0.97, P < 0.001) were strong between the predicted and measured TBO masses. Bland-Altman analysis validated the applicability of DXA-based models to predict TBC and TBO masses. As both DXA and TBW dilutions are widely available, low-risk, low-cost techniques, the present study provides a safe and practical method for estimating elemental composition in vivo.

Estimation of percentage body fat by dual-energy x-ray absorptiometry: evaluation by in vivo human elemental composition.

Dual-energy x-ray absorptiometry (DXA) is widely applied for estimating body fat. The percentage of body mass as fat (%fat) is predicted from a DXA-estimated R(ST) value defined as the ratio of soft tissue attenuation at two photon energies (e.g., 40 keV and 70 keV). Theoretically, the R(ST) concept depends on the mass of each major element in the human body. The DXA R(ST) values, however, have never been fully evaluated by measured human elemental composition. The present investigation evaluated the DXA R(ST) value by the total body mass of 11 major elements and the DXA %fat by the five-component (5C) model, respectively. Six elements (i.e. C, N, Na, P, Cl and Ca) were measured by in vivo neutron activation analysis, and potassium (i.e. K) by whole-body (40)K counting in 27 healthy adults. Models were developed for predicting the total body mass of four additional elements (i.e. H, O, Mg and S). The elemental content of soft tissue, after correction for bone mineral elements, was used to predict the R(ST) values. The DXA R(ST) values were strongly associated with the R(ST) values predicted from elemental content (r = 0.976, P < 0.001), although there was a tendency for the elemental-predicted R(ST) to systematically exceed the DXA-measured R(ST) (mean +/- SD, 1.389 +/- 0.024 versus 1.341 +/- 0.024). DXA-estimated %fat was strongly associated with 5C %fat (24.4 +/- 12.0% versus 24.9 +/- 11.1%, r = 0.983, P < 0.001). DXA R(ST) is evaluated by in vivo elemental composition, and the present study supports the underlying physical concept and accuracy of the DXA method for estimating %fat.

A cellular level approach to predicting resting energy expenditure: Evaluation of applicability in adolescents.

We previously derived a cellular level approach for a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging (MRI) combined with their individual cellularity and assumed stable-specific resting metabolic rates. Although this approach predicts REE well in both young and elderly adults, there were no studies in adolescents that specifically evaluated REE in relation to organ-tissue mass. It is unclear whether the approach can be applied to rapidly growing adolescents. The aim of the present study was to evaluate the applicability of the previous developed REE prediction model in adolescents, and to compare its applicability in young and elderly adults. Specifically, we tested the hypothesis that measured REE can be predicted from a combination of individual organ and tissue mass and their related cellularity. This was a 2-year longitudinal investigation. Twenty healthy male subjects with a mean age of 14.7 years had REE, organ and tissue mass, body cell mass, and fat-free mass (FFM) measured by indirect calorimetry, whole-body MRI, whole-body (40)K counting and dual-energy X-ray absorptiometry, respectively. The predicted REE (REEp; mean +/- SD, 1,487 +/- 238 kcal/day) was correlated with the measured REE (REEm, 1,606 +/- 237 kcal/day, r = 0.76, P < 0.001). The mean difference (118 +/- 165 kcal/day) between REEm and REEp was significant (P = 0.0047), accounting for 7.3% of REEm for the entire group. The present study, the first of its type in adolescents, does not support the applicability of the organ-tissue-based REE prediction model during rapid adolescent growth. A modified general REE prediction model is thus suggested which may account for the higher REE/FFM ratio observed in adolescents.

Ethnicity-related skeletal muscle differences across the lifespan.

Despite research and clinical significance, limited information is available on the relations between skeletal muscle (SM) and age in adults, specifically among Hispanics, African Americans (AA), and Asians. The aim was to investigate possible sex and ethnic SM differences in adults over an age range of 60 years. Subjects were 468 male and 1280 female adults (> or =18 years). SM was estimated based on DXA-measured appendicular lean-soft tissue using a previously reported prediction equation. Locally weighted regression smoothing lines were fit to examine SM trends and to localize age cutoffs; piecewise multiple linear regression models were then applied, controlling for weight and height, to identify age cutoffs for sex-specific changes in SM among the ethnic groups. The age of 27 years was identified for women and men as the cut-off after which SM starts to show a negative association with age. Both sexes had a similar ethnic pattern for expected mean SM at the age cutoff, with AA presenting the highest SM values, followed by Whites, Hispanics, and Asians. After the age cutoffs, the lowering of SM differed by ethnicity and sex: AA women showed the greatest SM lowering whereas Hispanic women had the least. Hispanic men tended to show a higher negative association of SM with age followed by AA and Whites. To conclude, significant sex and ethnic differences exist in the magnitude of negative associations of SM with age >27 years. Further studies using a longitudinal design are needed to explore the associations of ethnicity-related decline of SM with health risks.

Evaluation of between-methods agreement of extracellular water measurements in adults and children.

BACKGROUND: Extracellular water (ECW), a relevant molecular level component for clinical assessment, is commonly obtained by 2 methods that rely on assumptions that may not be possible to test at the time the measurements are made. OBJECTIVE: The aim of the current study was to evaluate the degree of agreement between ECW assessment by the sodium bromide dilution (ECW(NaBr)) and total body potassium (TBK; whole-body (40)K counting) to total body water (TBW; isotope dilution) methods (ECW(TBK-TBW)) in an ethnically mixed group of children and adults. DESIGN: ECW was measured with the ECW(NaBr) and ECW(TBK-TBW) methods in 526 white and African American males and females (86 nonobese children, 193 nonobese adults, and 247 obese adults). Fat mass was assessed with dual-energy X-ray absorptiometry. Multiple regression analysis was used to examine the variables related to between-ECW method differences. RESULTS: Significant but generally small group mean (+/-SD) differences in ECW were found in the obese adults (1.28 +/- 2.54 kg) and children (-0.71 +/- 1.78 kg). The magnitude of the differences was related to mean ECW in obese adults, children, and nonobese adults, and the relations between these variables were modified by sex for nonobese adults. ECW differences were also dependent on age, weight, sex, and race or on interactions between these variables. CONCLUSIONS: Overall, although good between-method agreement was found across the 3 groups, the degree of agreement varied according to subject characteristics, particularly at the extremes of ECW and body weight. We advance a possible mechanism that may link subject characteristics with the degree of agreement between ECW measurement methods and their underlying assumptions.

Dual-energy X-ray absorptiometry is a valid tool for assessing skeletal muscle mass in older women.

Assessing skeletal muscle mass (SMM) is critical in studying and detecting sarcopenia. Direct measurements by MRI or computerized tomography are expensive or high in radiation exposure. Dual-energy X-ray absorptiometry (DXA) is promising for body composition assessments, but the validity of DXA for predicting SMM in the elderly is still under investigation. The objective of this study was to assess the relationship between DXA-derived measurements of lean soft tissue mass (LSTM) and SMM in older women. Study participants were postmenopausal women (n = 101) recruited in southern Arizona. Total and regional body composition was measured using MRI and DXA (QDR4500w). The participants' mean age was 70.7 +/- 6.4 y and their mean BMI was 27.4 +/- 5.1 kg/m2. DXA-derived LSTM was highly correlated with MRI-derived SMM for the whole body (r = 0.94; P < 0.001) and leg region (r = 0.91; P < 0.001). In multivariate models, adjusting for age and DXA-derived percent fat slightly increased the amount of variance in SMM that can be explained by the DXA-derived LSTM assessments for the leg region but not for the total body. In conclusion, although the relationships between DXA measures and MRI-derived SMM vary by region of interest, the overall prediction of SMM by DXA is excellent. We conclude that DXA is a reliable method for cross-sectional assessments of SMM in older women.

A new total body potassium method to estimate total body skeletal muscle mass in children.

A whole body skeletal muscle [(SM); kg] mass estimation model, based on total body potassium [(TBK); mmol] measured by whole body (40)K counting (WBC) was developed (SM = 0.0082.TBK) and validated in adults in a previous study. It is unknown whether the adult TBK SM prediction model is applicable for pediatric use. The aim of this study was to derive and validate a pediatric TBK SM prediction equation. SM measured by MRI was used as the criterion and TBK was measured by WBC. The protocol was completed in 116 healthy children, 66 males and 50 females, 11.7 +/- 3.5 y (mean +/- SD, range = 5-17 y). A strong linear correlation was observed between TBK and SM (r = 0.984; P < 0.001). The SM:TBK ratio was 0.0071 +/- 0.0008 kg/mmol in the children studied, much lower than the corresponding value of 0.0082 kg/mmol in adults. An empirical SM prediction equation was developed using TBK alone: SM = 0.0085.TBK - 2.83, r(2) = 0.97, SEE = 1.39 kg. Bland-Altman analysis did not disclose a significant bias in the prediction of SM. When biological factors entered along with TBK in the general linear model, another prediction equation was developed: SM = 5.52 + 0.001.TBK (mmol) + 0.081.weight (kg) - 0.049.height (cm) + 0.00004.TBK . height + race (-0.60 for Caucasian, 0.49 for African-American, and 0 for Hispanic). Because the adult TBK SM prediction model is not applicable for pediatric use, this study provides new empirical TBK SM prediction equations that should prove useful for studies on nutrition, growth, and development in children.

Extracellular water across the adult lifespan: reference values for adults.

Extracellular water (ECW) is a large and clinically important body compartment that varies widely in volume both in health and disease. Interpretation of ECW measurements in the clinical setting requires consideration of potential influencing factors such as age, race, sex and other variables that influence fluid status. An important gap in physiological research is a lack of normative ECW values against which to reference perturbations in fluid homeostasis. The current study's aim was to develop conditional quantile equations for ECW based on weight, height, age, sex and race using a large (n = 1538, 854 females and 684 males) healthy adult multi-ethnic (African American, Asian, European American, Hispanic) sample. ECW was derived from total body water and potassium measured by isotope dilution and whole-body 40K counting, respectively. Quantile regression methods were used to identify five percentile levels (10th, 25th, 50th, 75th, 90th). Weight and height were significant variables at each quantile in both males and females; age made a significant contribution in the male but not the female sample. These regression equations provide ECW quantile reference values based on a large multi-ethnic adult population that should not only prove useful in clinical settings and physiological research, but serve as a model approach for developing body composition normative ranges.

Metabolically active portion of fat-free mass: a cellular body composition level modeling analysis.

The proportion of fat-free mass (FFM) as body cell mass (BCM) is highly related to whole body resting energy expenditure. However, the magnitude of BCM/FFM may have been underestimated in previous studies. This is because Moore's equation [BCM (kg) = 0.00833 x total body potassium (in mmol)], which was used to predict BCM, underestimates BCM by approximately 11%. The aims of the present study were to develop a theoretical BCM/FFM model at the cellular level and to explore the influences of sex, age, and adiposity on the BCM/FFM. Subjects were 112 adults who had the following measurements: total body water by (2)H(2)O or (3)H(2)O dilution; extracellular water by NaBr dilution; total body nitrogen by in vivo neutron activation analysis; and bone mineral by dual-energy X-ray absorptiometry. FFM was calculated using a multicomponent model and BCM as the difference between FFM and the sum of extracellular fluid and solids. The developed theoretical model revealed that the proportion of BCM to FFM is mainly determined by water distribution (i.e., E/I, the ratio of extracellular to intracellular water). A significant correlation (r = 0.90, P < 0.001) was present between measured and model-predicted BCM/FFM for all subjects pooled. Measured BCM/FFM [mean (SD)] was 0.584 +/- 0.041 and 0.529 +/- 0.041 for adult men and women (P < 0.001), respectively. A multiple linear regression model showed that there are independent significant associations of sex, age, and fat mass with BCM/FFM.

Total-body skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in children and adolescents.

BACKGROUND: Skeletal muscle (SM) is an important compartment but is difficult to quantify in children and adolescents. OBJECTIVE: We investigated the potential of dual-energy X-ray absorptiometry (DXA) for measuring total-body SM in pediatric subjects. DESIGN: A previously published adult DXA SM prediction formula was evaluated in children and adolescents aged 5-17 y (n = 99) who varied in pubertal maturation stage. SM estimated by whole-body magnetic resonance imaging (MRI) was used as the reference. The adult SM model was not accurate for subjects below Tanner stage 5 (n = 65; aged 5-14 y). New pediatric SM prediction models were therefore developed and validated in a separate group (n = 18). RESULTS: The adult DXA SM prediction model was valid in subjects at Tanner stage 5 but significantly (P < 0.001) overestimated SM in subjects below Tanner stage 5. New SM prediction formulas were developed with appendicular lean soft tissue (ALST) estimates by DXA as the main predictor variable (eg, model 1, ALST alone: R(2) = 0.982, SEE = 0.565 kg, P < 0.001). The new models were validated by the leave-one-out method and were cross-validated in a separate validation group. CONCLUSIONS: A previously reported adult DXA SM prediction model is applicable in children and adolescents late in pubertal development (Tanner stage 5). A new DXA SM prediction model was developed for prepubertal and pubertal subjects (Tanner stage /=5 y. DXA thus provides an important opportunity for quantifying total-body SM mass across most of the human life span.

Total body protein mass: validation of total body potassium prediction model in children and adolescents.

Protein is an important body component for monitoring growth, development, and nutritional status. We previously developed a total body potassium (TBK, in mmol) and bone mineral (Mo, in kg) model for predicting total body protein (TBPro, in kg) in adults (TBPro = 0.00252 x TBK + 0.732 x Mo). However, the applicability of the TBK-Mo model for children is unknown. The study aims were to develop a TBK-independent 6-component (6-C) TBPro approach as the criterion, and then to validate the TBK-Mo model in children. The following measurements were made in adolescents and children (n = 62, 38 boys and 24 girls, aged 5-17 y): body weight (BW, in kg), body volume (BV, in liters) by air displacement plethysmography, total body water (TBW, in kg) by 2H2O dilution, Mo by dual-energy X-ray absorptiometry, and TBK by whole-body counting. A 6-C model was derived as TBPro = 2.922 x BW - 0.301 x TBW - 2.039 x Mo - 2.632 x BV. The TBPro estimates did not differ between the 6-C and TBK-Mo models (mean +/- SD, 0.20 +/- 0.86 kg). There was a significant correlation between TBPro by the 6-C and TBK-Mo models (r = 0.94, P < 0.001). Bland-Altman analysis indicated that the differences between TBPro by 6-C and TBK-Mo models were not significantly correlated with the mean TBPro estimates by the 2 models (r = 0.032, P > 0.05). The TBK-Mo model can thus be used to estimate TBPro in healthy adults, adolescents, and children > 5 y old.

The end of body composition methodology research?

PURPOSE OF REVIEW: Over one century of research has led to methods for measuring all major body components at the atomic, molecular, cellular, and tissue-system levels. These remarkable developments have fueled a rapid and sustained increase in 'body composition' biological findings and related publications. Other than small, incremental improvements in available methods, is there no longer a need for developing new body composition methods? This review examines the question: are we approaching the 'end' of body composition methodology research? RECENT FINDINGS: Emerging and rapidly growing areas outside of 'traditional' body composition research are highlighting the need for new and innovative method development. Recently introduced technologies such as positron emission tomography and functional magnetic resonance imaging extend 'mass' estimates to corresponding 'function' and physiology in humans. Although all major components are now measurable in humans, large gaps remain when considering factors such as radiation exposure, invasiveness, static versus dynamic measurements, and laboratory versus clinic and field assessments. SUMMARY: The end of the first phase of body composition method development has now arrived: all major components are measurable in vivo. The accessibility of these methods is stimulating rapid advances in biological knowledge surrounding human body composition from in utero to old age. Sustaining advances in new body composition method development will require extending the boundaries of the field as it now exists.

A cellular-level approach to predicting resting energy expenditure across the adult years.

BACKGROUND: We previously derived a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging combined with assumed stable, specific resting metabolic rates of individual organs and tissues. Although the model predicted REE well in young persons, it overpredicted REE by approximately 11% in elderly adults. This overprediction may occur because of a decline in the fraction of organs and tissues as cell mass with aging. OBJECTIVE: The aim of the present study was to develop a cellular-level REE prediction model that would be applicable across the adult age span. Specifically, we tested the hypothesis that REE can be predicted from a combination of organ and tissue mass, the specific resting metabolic rates of individual organs and tissues, and the cellular fraction of fat-free mass. DESIGN: Fifty-four healthy subjects aged 23-88 y had REE, organ and tissue mass, body cell mass, and fat-free mass measured by indirect calorimetry, magnetic resonance imaging, whole-body (40)K counting, and dual-energy X-ray absoptiometry, respectively. RESULTS: REE predicted by the cellular-level model was highly correlated with measured REE (r = 0.92, P < 0.001). The mean difference between measured REE (x+/- SD: 1487 +/- 294 kcal/d) and predicted REE (1501 +/- 300 kcal/d) for the whole group was not significant, and the difference between predicted and measured REE was not associated with age (r = 0.009, NS). CONCLUSION: The present approach establishes an REE-body composition link with the use of a model at the cellular level. The combination of 2 aging-related factors (ie, decline in both the mass and the cellular fraction of organs and tissues) may account for the lower REE observed in elderly adults.