External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis.

OBJECTIVE: To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. DESIGN: Individual participant data meta-analysis. SETTING: 19 countries. PARTICIPANTS: 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). MAIN OUTCOME MEASURES: The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. RESULTS: The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (-0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. CONCLUSION: The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

Nutrition Assessment and Dietary Interventions in Heart Failure: JACC Review Topic of the Week.

Despite the high prevalence of nutrition disorders in patients with heart failure (HF), major HF guidelines lack specific nutrition recommendations. Because of the lack of standardized definitions and assessment tools to quantify nutritional status, nutrition disorders are often missed in patients with HF. Additionally, a wide range of dietary interventions and overall dietary patterns have been studied in this population. The resulting evidence of benefit is, however, conflicting, making it challenging to determine which strategies are the most beneficial. In this document, we review the available nutritional status assessment tools for patients with HF. In addition, we appraise the current evidence for dietary interventions in HF, including sodium restriction, obesity, malnutrition, dietary patterns, and specific macronutrient and micronutrient supplementation. Furthermore, we discuss the feasibility and challenges associated with the implementation of multimodal nutrition interventions and delineate potential solutions to facilitate addressing nutrition in patients with HF.

Resting Energy Expenditure and Organ-Tissue Body Composition 5 Years After Bariatric Surgery.

INTRODUCTION: Bariatric surgery-induced weight loss may reduce resting energy expenditure (REE) and fat-free mass (FFM) disproportionately thereby predisposing patients to weight regain and sarcopenia. METHODS: We compared REE and body composition of African-American and Caucasian Roux-en-Y gastric bypass (RYGB) patients after surgery with a group of non-operated controls (CON). REE by indirect calorimetry; skeletal muscle (SM), trunk organs, and brain volumes by MRI; and FFM by DXA were measured at post-surgery visits and compared with CON (N = 84) using linear regression models that adjusted for relevant covariates. Ns in RYGB were 50, 42, and 30 for anthropometry and 39, 27, 17 for MRI body composition at years 1, 2, and 5 after surgery, respectively. RESULTS: Regression models adjusted for age, weight, height, ethnicity, and sex showed REE differences (RYGB minus CON; mean ± s.e.): year 1 (43.2 ± 34 kcal/day, p = 0.20); year 2 (- 27.9 ± 37.3 kcal/day, p = 0.46); year 5 (114.6 ± 42.3 kcal/day, p = 0.008). Analysis of FFM components showed that RYGB had greater trunk organ mass (~ 0.4 kg) and less SM (~ 1.34 kg) than CON at each visit. REE models adjusted for FFM, SM, trunk organs, and brain mass showed no between-group differences in REE (- 15.9 ± 54.8 kcal/day, p = 0.8; - 46.9 ± 64.9 kcal/day, p = 0.47; 47.7 ± 83.0 kcal/day, p = 0.57, at years 1, 2, and 5, respectively). CONCLUSIONS: Post bariatric surgery patients maintain a larger mass of high-metabolic rate trunk organs than non-operated controls of similar anthropometrics. Interpreting REE changes after weight loss requires an accurate understanding of fat-free mass composition at both the organ and tissue levels. CLINICAL TRIAL REGISTRATION: Long-term Effects of Bariatric Surgery (LABS-2) NCT00465829.

Normalising birth for women with a disability: the challenges facing practitioners.

UNLABELLED: Previous research on pregnant women with a disability and their experience of maternity care demonstrated that these mothers perceived themselves to be the 'perennial outsiders' with midwives automatically categorising them as 'high risk' because of their disability. They also felt that their ability to make choices, stay in control and have continuity of care was not considered to be part of the mainstream maternity care for them because they did not fit the 'normal' category. OBJECTIVE: this research was undertaken to explore the perceptions of two multiprofessional teams in Irish hospitals as to how maternity services to these mothers can be improved. PARTICIPANTS: nineteen health-care professionals from midwifery, social work and public health nursing were recruited. SETTING: two from two major maternity hospitals, one in the North and one in the South of Ireland. were featured. DESIGN: the method chosen was a qualitative approach, using focus group interviews in which case studies depicting a range and breadth of women's birthing experiences were presented and discussed. Newell and Burnard's (2006) six stage approach to thematic content analysis was used. FINDINGS: the professionals found the disabled women's stories believable, upsetting and challenging. KEY CONCLUSIONS: Staff acknowledged their 'lack of competence, knowledge and skill' regarding disability and felt that, on reflection, their failure to consult and collaborate with disabled women contributed to their failing to provide individualised woman centred care to women with a disability. IMPLICATIONS OF PRACTICe: A series of recommendations for improved practice was agreed.

MRI assessment of lean and adipose tissue distribution in female patients with Cushing's disease.

OBJECTIVE: Chronic hypercortisolemia due to Cushing's disease (CD) results in abnormal adipose tissue (AT) distribution. Whole-body magnetic resonance imaging (MRI) was used to examine lean and AT distribution in female patients with CD to further understand the role of glucocorticoid excess in the development of abnormal AT distribution and obesity. DESIGN: Cross-sectional and case-control study. PATIENTS: Fifteen women with CD and 12 healthy controls. MEASUREMENTS: Mass of skeletal muscle (SM) and AT in the visceral (VAT), subcutaneous (SAT), and intermuscular (IMAT) compartments from whole-body MRI and serum levels of insulin, glucose, and leptin were measured. RESULTS: CD patients had leptin values that correlated to total AT (TAT) and SAT (P < 0.05) but not to VAT. CD patients had higher VAT/TAT ratios (P < 0.01) and lower SAT/TAT ratios (P < 0.05) compared to controls. TAT, VAT, and trunk SAT (TrSAT) were greater in CD patients (P < 0.01). SM was less in CD (P < 0.001) but IMAT was not different. CONCLUSIONS: TAT, VAT, trSAT, and the proportion of AT in the visceral depot were greater in CD although the proportion in the subcutaneous depot was less. SM was less but IMAT was not different. These findings have implications for understanding the role of cortisol in the abnormal AT distribution and metabolic risk seen in patients exposed to chronic excess glucocorticoids.

Brain and high metabolic rate organ mass: contributions to resting energy expenditure beyond fat-free mass.

BACKGROUND: The degree to which interindividual variation in the mass of select high metabolic rate organs (HMROs) mediates variability in resting energy expenditure (REE) is unknown. OBJECTIVE: The objective was to investigate how much REE variability is explained by differences in HMRO mass in adults and whether age, sex, and race independently predict REE after adjustment for HMRO. DESIGN: A cross-sectional evaluation of 55 women [30 African Americans aged 48.7 +/- 22.2 y (mean +/- SD) and 25 whites aged 46.4 +/- 17.7 y] and 32 men (8 African Americans aged 34.3 +/- 18.2 y and 24 whites aged 51.3 +/- 20.6 y) was conducted. Liver, kidney, spleen, heart, and brain masses were measured by magnetic resonance imaging, and fat and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry. REE was measured by indirect calorimetry. RESULTS: REE estimated from age (P = 0.001), race (P = 0.006), sex (P = 0.31), fat (P = 0.001), and FFM (P < 0.001) accounted for 70% (adjusted (2)) of the variability in REE. The addition of trunk HMRO (P = 0.001) and brain (P = 0.006) to the model increased the explained variance to 75% and rendered the contributions of age, sex, and race statistically nonsignificant, whereas fat and FFM continued to make significant contributions (both P < 0.05). The addition of brain to the model rendered the intercept (69 kcal . kg(-1) . d(-1)) consistent with zero, which indicated zero REE for zero body mass. CONCLUSIONS: Relatively small interindividual variation in HMRO mass significantly affects REE and reduces the role of age, race, and sex in explaining REE. Decreases in REE with increasing age may be partly related to age-associated changes in the relative size of FFM components.

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.

Assessment methods in human body composition.

PURPOSE OF REVIEW: The present study reviews the most recently developed and commonly used methods for the determination of human body composition in vivo with relevance for nutritional assessment. RECENT FINDINGS: Body composition measurement methods are continuously being perfected with the most commonly used methods being bioelectrical impedance analysis, dilution techniques, air displacement plethysmography, dual energy X-ray absorptiometry, and MRI or magnetic resonance spectroscopy. Recent developments include three-dimensional photonic scanning and quantitative magnetic resonance. Collectively, these techniques allow for the measurement of fat, fat-free mass, bone mineral content, total body water, extracellular water, total adipose tissue and its subdepots (visceral, subcutaneous, and intermuscular), skeletal muscle, select organs, and ectopic fat depots. SUMMARY: There is an ongoing need to perfect methods that provide information beyond mass and structure (static measures) to kinetic measures that yield information on metabolic and biological functions. On the basis of the wide range of measurable properties, analytical methods and known body composition models, clinicians and scientists can quantify a number of body components and with longitudinal assessment, can track changes in health and disease with implications for understanding efficacy of nutritional and clinical interventions, diagnosis, prevention, and treatment in clinical settings. With the greater need to understand precursors of health risk beginning in childhood, a gap exists in appropriate in-vivo measurement methods beginning at birth.

How useful is waist circumference for assessment of abdominal obesity in Korean pre-menopausal women during weight loss?

Asian women are known to have a larger amount of abdominal fat (AF) for the same level of BMI compared with Caucasian and African-American women. This study was aimed to determine whether waist circumference (WC) could be useful as an index of AF compared with AF measured by dual energy x-ray absorptiometry (DXA) before and after a weight-loss program in Asian women. Thirty-eight healthy, pre-menopausal obese Korean women (body fat percent>30%) were enrolled and followed during a 6-week weight-loss program including herbal formula, calorie restriction, and exercise. Anthropometry and DXA measurements were performed before and after weight-loss. A specific region of interest (ROI, L2-iliac crest) by DXA was correlated with anthropometry at baseline: WC (gamma=0.91)>BMI (gamma=0.87)>Waist-Height ratio (WHtR, gamma=0.82)>WHR (gamma=0.46); and after weight loss: BMI (gamma=0.88)>WC (gamma=0.84)>WHtR (gamma=0.82), all p<0.01. The change in DXA ROI showed a reasonable correlation with change in anthropometry: BMI (gamma=0.63, p<0.01)>WC (gamma=0.39, p<0.05)>WHtR (gamma=0.37, p<0.05). A stepwise multiple regression analysis revealed that 83% of the variance in DXA derived AF was explained by WC at baseline, WC and BMI at follow-up, respectively. This study suggests that WC could be a good predictor of AF for Korean pre-menopausal women.

Estimating whole body intermuscular adipose tissue from single cross-sectional magnetic resonance images.

Intermuscular adipose tissue (IMAT), a novel fat depot linked with metabolic abnormalities, has been measured by whole body MRI. The cross-sectional slice location with the strongest relation to total body IMAT volume has not been established. The aim was to determine the predictive value of each slice location and which slice locations provide the best estimates of whole body IMAT. MRI quantified total adipose tissue of which IMAT, defined as adipose tissue visible within the boundary of the muscle fascia, is a subcomponent. Single-slice IMAT areas were calculated for the calf, thigh, buttock, waist, shoulders, upper arm, and forearm locations in a sample of healthy adult women, African-American [n = 39; body mass index (BMI) 28.5 +/- 5.4 kg/m2; 41.8 +/- 14.8 yr], Asian (n = 21; BMI 21.6 +/- 3.2 kg/m2; 40.9 +/- 16.3 yr), and Caucasian (n = 43; BMI 25.6 +/- 5.3 kg/m2; 43.2 +/- 15.3 yr), and Caucasian men (n = 39; BMI 27.1 +/- 3.8 kg/m2; 45.2 +/- 14.6 yr) and used to estimate total IMAT groups using multiple-regression equations. Midthigh was the best, or near best, single predictor in all groups with adjusted R2 ranging from 0.49 to 0.84. Adding a second and third slice further increased R2 and reduced the error of the estimate. Menopausal status and degree of obesity did not affect the location of the best single slice. The contributions of other slice locations varied by sex and race, but additional slices improved predictions. For group studies, it may be more cost-effective to estimate IMAT based on one or more slices than to acquire and segment for each subject the numerous images necessary to quantify whole body IMAT.

Small organs with a high metabolic rate explain lower resting energy expenditure in African American than in white adults.

BACKGROUND: African Americans have a lower resting energy expenditure (REE) relative to fat-free mass (FFM) than do whites. Whether the composition of FFM at the organ-tissue level differs between African Americans and whites and, if so, whether that difference could account for differences by race in REE are unknown. OBJECTIVE: The objectives were to quantify FFM in vivo in women and men at the organ-tissue level and to ascertain whether the mass of specific high-metabolic-rate organs and tissues differs between African Americans and whites and, if so, whether that difference can account for differences in REE. DESIGN: The study was a cross-sectional evaluation of 64 women (n = 34 African Americans, 30 whites) and 35 men (n = 8 African Americans, 27 whites). Magnetic resonance imaging measures of liver, kidney, heart, spleen, brain, skeletal muscle, and adipose tissue and dual-energy X-ray absorptiometry measures of fat and FFM were acquired. REE was measured by using indirect calorimetry. RESULTS: The mass of selected high-metabolic-rate organs (sum of liver, heart, spleen, kidneys, and brain) after adjustment for fat, FFM, sex, and age was significantly (P < 0.001) smaller in African Americans than in whites (3.1 and 3.4 kg, respectively; x +/- SEE difference: 0.30 +/- 0.06 kg). In a multiple regression analysis with fat, FFM, sex, age, and race as predictors of REE, the addition of the total mass rendered race nonsignificant. CONCLUSIONS: Racial differences in REE were reduced by >50% and were no longer significant when the mass of specific high-metabolic-rate organs was considered. Differences in FFM composition may be responsible for the reported REE differences.

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.

Larger mass of high-metabolic-rate organs does not explain higher resting energy expenditure in children.

BACKGROUND: Children have a high resting energy expenditure (REE) relative to their body weight. The decline in REE during growth may be due to changes in body composition or to changes in the metabolic rate of individual organs and tissues. OBJECTIVES: The goals were to quantify body-composition components in children at the organ-tissue level in vivo and to determine whether the observed masses 1) account for the elevated REE in children and 2) account, when combined with specific organ-tissue metabolic constants, for children's REE. DESIGN: This was a cross-sectional evaluation of 15 children (aged 9.3 +/- 1.7 y) and 13 young adults (aged 26.0 +/- 1.8 y) with body mass indexes (in kg/m(2)) < 30. Magnetic resonance imaging-derived in vivo measures of brain, liver, kidney, heart, skeletal muscle, and adipose tissue were acquired. REE was measured by indirect calorimetry (REE(m)). Previously published organ-tissue metabolic rate constants were used to calculate whole-body REE (REE(c)). RESULTS: The proportion of adipose-tissue-free mass as liver (3.7 +/- 0.5% compared with 3.1 +/- 0.5%; P < 0.01) and brain (6.2 +/- 1.2% compared with 3.3 +/- 0.9%; P < 0.001) was significantly greater in children than in young adults. The addition of brain and liver mass significantly improved the model but did not eliminate the role of age. REE(c) with published metabolic coefficients underestimated REE(m) (REE(c) = 3869 +/- 615 kJ/d; REE(m) = 5119 +/- 769 kJ/d; P < 0.001) in children. CONCLUSION: The decline in REE during growth is likely due to both a decrease in the proportion of some of the more metabolically active organs and tissues and changes in the metabolic rate of individual organs and tissues.

DXA: potential for creating a metabolic map of organ-tissue resting energy expenditure components.

OBJECTIVE: This study tested the hypothesis that tissue-organ components can be derived from DXA measurements, and in turn, resting energy expenditure (REE) can be calculated from the summed heat productions of DXA-estimated brain, skeletal muscle mass (SM), adipose tissue, bone, and residual mass (RM). RESEARCH METHODS AND PROCEDURES: Subjects were divided into five groups of adults <50 years of age. The specific metabolic rate of RM was developed in 13 Group I healthy subjects and a DXA-brain mass prediction formula in 52 Group II subjects. SM, adipose tissue, and bone models were developed based on earlier reports. The composite REE prediction model (REEp) was tested in 154 Group III subjects in whom REEp was compared with measured REE (REEm). Features of the developed model were determined in 94 normal-weight men and women (Group IV) and seven spinal cord injury patients and healthy matched controls (Group V). RESULTS: REEp and REEm in Group III were highly correlated (y = 0.85x + 233; r = 0.82, p < 0.001), and no bias was detected. Both REEm (mean +/- SD, 1,579 +/- 324 kcal/d) and REEp (1,585 +/- 316 kcal/d) were also highly correlated (r values = 0.85 to 0.98; p values < 0.001) and provided similar group values to REE estimated by the Harris-Benedict equations (1,597 +/- 279 kcal/d) and Wang's composite fat-free mass-based REE equation (1,547 +/- 248 kcal/d). New insights into the sources and distribution of REE were provided by analysis of the demonstration groups. DISCUSSION: This approach offers a new practical and educational opportunity to examine REE in subject groups using modeling strategies that reveal the magnitude and distribution of fundamental somatic heat-producing units.

Body-size dependence of resting energy expenditure can be attributed to nonenergetic homogeneity of fat-free mass.

An enduring enigma is why the ratio of resting energy expenditure (REE) to metabolically active tissue mass, expressed as the REE/fat-free mass (FFM) ratio, is greater in magnitude in subjects with a small FFM than it is in subjects with a large FFM. This study tested the hypothesis that a higher REE/FFM ratio in subjects with a small body mass and FFM can be explained by a larger proportion of FFM as high-metabolic-rate tissues compared with that observed in heavier subjects. REE was measured by indirect calorimetry, FFM by dual-energy X-ray absorptiometry (DEXA), and tissue/organ contributions to FFM by whole body magnetic resonance imaging (MRI) in healthy adults. Four tissue heat-producing contributions to FFM were evaluated, low-metabolic-rate fat-free adipose tissue (18.8 kJ/kg), skeletal muscle (54.4 kJ/kg), and bone (9.6 kJ/kg); and high-metabolic-rate residual mass (225.9 kJ/kg). Initial evaluations in 130 men and 159 women provided strong support for two key, developed models, one linking DEXA FFM with MRI FFM estimates and the other linking REE predicted from the four MRI-derived components with measured REE. There was an inverse association observed between measured REE/FFM and FFM (r(2) = 0.17, P < 0.001). Allometric models revealed a similar pattern of tissue change relative to body mass across males and females with greater proportional increases in fat-free adipose tissue and skeletal muscle than in FFM and a smaller proportional increase in residual mass than in FFM. When examined as a function of FFM, positive slopes were observed for skeletal muscle/FFM and pooled low-metabolic-rate components, and a negative slope for residual mass. Our linked REE-body composition models and associations strongly support the hypothesis that FFM varies systematically in the proportion of thermogenic components as a function of body mass and FFM. These observations have important implications for the interpretation of between-individual differences in REE expressed relative to metabolically active tissue mass.