Resting Energy Expenditure Is Not Altered in Children and Adolescents with Obesity. Effect of Age and Gender and Association with Serum Leptin Levels

In children and adolescents, obesity does not seem to depend on a reduction of resting energy expenditure (REE). Moreover, in this young population, the interactions between either age and obesity or between age and gender, or the role of leptin on REE are not clearly understood. To compare the levels of REE in children and adolescents we studied 181 Caucasian individuals (62% girls) classified on the basis of age- and sex-specific body mass index (BMI) percentile as healthy weight (n = 50), with overweight (n = 34), or with obesity (n = 97) and in different age groups: 8–10 (n = 38), 11–13 (n = 50), and 14–17 years (n = 93). REE was measured by indirect calorimetry and body composition by air displacement plethysmography. Statistically significant differences in REE/fat-free mass (FFM) regarding obesity or gender were not observed. Absolute REE increases with age (p < 0.001), but REE/FFM decreases (p < 0.001) and there is an interaction between gender and age (p < 0.001) on absolute REE showing that the age-related increase is more marked in boys than in girls, in line with a higher FFM. Interestingly, the effect of obesity on absolute REE is not observed in the 8–10 year-old group, in which serum leptin concentrations correlate with the REE/FFM (r = 0.48; p = 0.011). In conclusion, REE/FFM is not affected by obesity or gender, while the effect of age on absolute REE is gender-dependent and leptin may influence the REE/FFM in 8–10 year-olds.     

Anthropometric measured fat-free mass as essential determinant of resting energy expenditure for pregnant and non-pregnant women

Objective

There is conflicting evidence as to whether anthropometric parameters are related to resting energy expenditure (REE) during pregnancy. The aim of this prospective longitudinal study was to precisely assess a major anthropometric determinant of REE for pregnant and non-pregnant women with verification of its use as a possible predictor.

Methods

One hundred fifty-two randomly recruited, healthy, pregnant Czech women were divided into groups G1 and G2. G1 (n = 31) was used for determination of the association between anthropometric parameters and REE. G2 (n = 121) and a group of non-pregnant women (G0; n = 24) were used for verification that observed relations were suitable for the prediction of REE during pregnancy. The women in the study groups were measured during four periods of pregnancy for REE by indirect calorimetry and anthropometric parameters after 12 h of fasting.

Results

Associations were found in all groups between measured REE by indirect calorimetry and anthropometric parameters such as weight, fat mass, fat-free mass (FFM), body surface area, and body mass index (P < 0.0001). The best derived predictor, REE/FFM (29.5 kcal/kg, r = 0.70, P < 0.0001), in group G1 was statistically verified in group G2 and compared with G0.

Conclusion

Anthropometrically measured FFM with its metabolically active components is an essential determinant of REE in pregnancy. REE/FFM can be used for the prediction of REE in pregnant and non-pregnant woman.     

Total and regional body composition and energy expenditure in multiple symmetric lipomatosis

AIMS: The aim of the present study was to investigate possible alterations in body composition and resting energy expenditure (REE) in type 1 multiple symmetric lipomatosis (MSL). SUBJECTS AND METHODS: Thirteen men aged from 40 to 78 years affected by type I MSL were compared with 13 healthy control subjects. Fat mass (FM) and fat-free mass (FFM) were determined by DEXA using both standard analysis and specifically for the lipomatous region. REE was measured by indirect calorimetry. RESULTS: FM was higher in MSL subjects at proximal arm level, but significantly lower at distal leg level than in controls (left 1.63+/-0.55 vs. 2.26+/-0.49 kg, P<0.05; right 1.63+/-0.53 vs. 2.40+/-0.54 kg, P<0.01). Arm FFM was similar in the two groups, while distal leg FFM was significantly lower in MSL cases (left: 7.8+/-1.3 vs. 8.7+/-0.8 kg, P<0.05; right: 8.0+/-1.5 vs. 9.2+/-0.9 kg, P<0.05). FFM strongly correlated with REE (r:0.86;P<0.001). REE, expressed as an absolute value and adjusted for FFM (1830+/-215 vs. 1675+/-120 kcal, P<0.05) was higher in MSL patients. CONCLUSION: In conclusion, MSL patients had a marked FFM and FM atrophy in the lower segments of the legs and an altered energy expenditure (hypermetabolism).     

Energy requirements in frail elderly people: a review of the literature

This review collates studies of healthy, sick, underweight (BMI < or = 21 kg/m2) and very elderly people (> or = 90 yr), in whom resting energy expenditure (REE) was measured using indirect calorimetry. We have observed the following: (1) REE, when adjusted for differences in both body weight and fat-free mass (FFM), is similar in healthy and in sick elderly people being 20 and 28 kcal/kg of FFM per day, respectively, (2) their nutritional status influences their energy requirements given that weight-adjusted REE increases in line with a decrease in BMI, (3) total energy expenditure is lower in sick elderly people given that their physical activity level, i.e. the ratio of total energy expenditure to REE, is reduced during disease averaging at 1.36, (4) energy intake (EI) being only 1.23 x REE is insufficient to cover energy requirements in sick elderly patients, whereas the EI of healthy elderly people appears sufficient to cover requirements, and finally, (5) gender ceases to be a determinant of REE in people aged 60 yr or over, with the Harris & Benedict equation capable of accurately predicting mean REE in this population, whether healthy or sick.     

Resting energy expenditure can be assessed by fat-free mass in female athletes regardless of body size

Energy requirements can be estimated from resting energy expenditure (REE). However, little is known about factors influencing REE in Japanese female athletes. This study was performed to evaluate the relationship between REE and body composition in Japanese female athletes with a wide range of body sizes. Ninety-three athletes (age 20.3±1.2 y, height 162.8±6.4 cm, body weight (BW) 57.0±9.2 kg, fat-free mass (FFM) 45.4±6.2 kg) were classified into three groups according to BW: small-size (S) (n=34), medium-size (M) (n=34), and large-size (L) (n=25). Systemic and regional body compositions (skeletal muscle (SM), fat mass (FM), bone mass (BM), and residual mass (RM)) were estimated by dual energy X-ray absorptiometry (DXA). Measured resting energy expenditure (REEm) was evaluated by indirect calorimetry. Marked differences were found in REEm (S: 1,111±150, M: 1,242±133, L: 1,478±138 kcal/d), and systemic and regional body compositions among the three groups. REEm was strongly correlated with FFM, and absolute values of RM and SM increased significantly according to body size. There was good agreement between REEm and estimated REE (REEe) from the specific metabolic rates of four major organ tissue level compartments. These data indicate that REE for female athletes can be attributed to changes in organ tissue mass, and not changes in organ tissue metabolic rate. That is, change in REE can be explained mainly by the change in FFM, and REE can be assessed by FFM in female athletes regardless of body size.     

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.     

Energy prediction equations are inadequate for obese Hispanic youth

Assessing energy requirements is a fundamental activity in clinical dietetics practice. A study was designed to determine whether published linear regression equations were accurate for predicting resting energy expenditure (REE) in fasted Hispanic children with obesity (aged 7 to 15 years). REE was measured using indirect calorimetry; body composition was estimated with whole-body air displacement plethysmography. REE was predicted using four equations: Institute of Medicine for healthy-weight children (IOM-HW), IOM for overweight and obese children (IOM-OS), Harris-Benedict, and Schofield. Accuracy of the prediction was calculated as the absolute value of the difference between the measured and predicted REE divided by the measured REE, expressed as a percentage. Predicted values within 85% to 115% of measured were defined as accurate. Participants (n=58; 53% boys) were mean age 11.8±2.1 years, had 43.5%±5.1% body fat, and had a body mass index of 31.5±5.8 (98.6±1.1 body mass index percentile). Measured REE was 2,339±680 kcal/day; predicted REE was 1,815±401 kcal/day (IOM-HW), 1,794±311 kcal/day (IOM-OS), 1,151±300 kcal/day (Harris-Benedict), and, 1,771±316 kcal/day (Schofield). Measured REE adjusted for body weight averaged 32.0±8.4 kcal/kg/day (95% confidence interval 29.8 to 34.2). Published equations predicted REE within 15% accuracy for only 36% to 40% of 58 participants, except for Harris-Benedict, which did not achieve accuracy for any participant. The most frequently accurate values were obtained using IOM-HW, which predicted REE within 15% accuracy for 55% (17/31) of boys. Published equations did not accurately predict REE for youth in the study sample. Further studies are warranted to formulate accurate energy prediction equations for this population.     

Body composition in 98 patients awaiting kidney transplantation

ObjectiveRecent data suggest that the nutritional status of patients who are on the waiting list for kidney transplantation, influence outcomes after renal transplantation. Body composition (BC) analysis is rarely included in pretransplant evaluation. The aim of this study was to determine how alteration of the BC of these patients could influence pretransplant and post-transplant care.MethodsWe compared the BC of French patients on a waiting list for kidney transplantation to a sex- and age-matched healthy, European control population. Patients were included when listed for kidney grafting in a prospective longitudinal study (CORPOS). Biological nutritional parameters, fat free mass (FFM) and fat mass (FM) estimated by dual-energy x-ray absorptiometry (DXA) were assessed on the day of wait-list registration. FFM and FM index (FFMi - FMi) are the ratio of FFM and FM to height squared. Results are expressed as median (range). These indexes were compared with previous study values used as a normal range in nutritional assessment and clinical practice.ResultsThe study included 28 women and 70 men aged 25.3 to 65.9 y. Body mass index ranged from 16.8 kg/m² to 39.4 kg/m². Compared with controls, FMi was higher in women (10.6 kg/m² [3.7–18.6 kg/m²]) than in men (8.1 kg/m² [3.5–13.3 kg/m²] in M) and FFMi was lower in women (14.3 kg/m² [11.8–21.4 kg/m²]) than in men (17.9 kg/m² [13.9-24.2 kg/m²]) (P < 0.01), reflecting an abnormal distribution of body compartments. All biological parameters were within the normal range.ConclusionBC abnormalities, which can only be detected with the use of DXA, are present in patients on a kidney transplantation waiting list. Detection of these abnormalities could influence the post-transplantation survey in order to prevent the frequent risk for developing metabolic complications after the procedure.     

Estimation of Resting Energy Expenditure: Validation of Previous and New Predictive Equations in Obese Children and Adolescents

Objective: Accurate estimation of resting energy expenditure (REE) in childrenand adolescents is important to establish estimated energy requirements. The aim of the present study was to measure REE in obese children and adolescents by indirect calorimetry method, compare these values with REE values estimated by equations, and develop the most appropriate equation for this group.

Methods: One hundred and three obese children and adolescents (57 males, 46 females) between 7 and 17 years (10.6 ± 2.19 years) were recruited for the study. REE measurements of subjects were made with indirect calorimetry (COSMED, FitMatePro, Rome, Italy) and body compositions were analyzed.

Results: In females, the percentage of accurate prediction varied from 32.6 (World Health Organization [WHO]) to 43.5 (Molnar and Lazzer). The bias for equations was ?0.2% (Kim), 3.7% (Molnar), and 22.6% (Derumeaux-Burel). Kim's (266 kcal/d), Schmelzle's (267 kcal/d), and Henry's equations (268 kcal/d) had the lowest root mean square error (RMSE; respectively 266, 267, 268 kcal/d). The equation that has the highest RMSE values among female subjects was the Derumeaux-Burel equation (394 kcal/d). In males, when the Institute of Medicine (IOM) had the lowest accurate prediction value (12.3%), the highest values were found using Schmelzle's (42.1%), Henry's (43.9%), and Müller's equations (fat-free mass, FFM; 45.6%). When Kim and Müller had the smallest bias (?0.6%, 9.9%), Schmelzle's equation had the smallest RMSE (331 kcal/d). The new specific equation based on FFM was generated as follows: REE = 451.722 + (23.202 * FFM). According to Bland-Altman plots, it has been found out that the new equations are distributed randomly in both males and females.

Conclusion: Previously developed predictive equations mostly provided unaccurate and biased estimates of REE. However, the new predictive equations allow clinicians to estimate REE in an obese children and adolescents with sufficient and acceptable accuracy.     

Effects of habitual physical activity on the resting metabolic rates and body compositions of women aged 35 to 50 years.

OBJECTIVE: To examine the effect habitual physical activity has on resting metabolic rate (RMR) and body composition (fat-free mass[FFM], fat mass, and percent body fat) in active compared to sedentary adult women. DESIGN: RMR was measured (by indirect calorimetry) twice after a 12-hour fast at the same point of the menstrual cycle and 48 hours after exercise. FFM, fat mass and percent body fat were measured using whole body air displacement plethysmography. Energy intake and expenditure were determined using 7-day weighed-food records and activity logs. SUBJECTS: Healthy, weight-stable premenopausal women aged 35 to 50 years classified as either active (approximately 9 hours per week of physical activity for 10 or more years) (n= 18) or sedentary (approximately 1 hour per week of physical activity) (n= 14). STATISTICAL ANALYSES: Analysis of covariance was used to investigate differences in mean RMR (kcal/day) between the groups adjusted for FFM, and independent t tests were used to determine differences in demographic, energy expenditure, and diet variables. RESULTS: Percent body fat and fat mass were lower (P<.0005) and RMR (adjusted for FFM) was significantly higher in the active women (P=.045) compared with sedentary controls. In the active and sedentary groups respectively, mean adjusted RMR was 1,510 kcal/day and 1,443 kcal/day, body fat was 18.9% and 28.8%, and fat mass was 11.1 kg and 18.8 kg. Groups were similar in body mass, FFM, body mass index, and age. Mean energy balance appeared to be more negative in the active group (P=.0059) due to significantly higher mean self-reported energy expenditures (P=.0001) and similar mean self-reported energy intakes (P=.52) compared with sedentary controls. These data indicate that active women who participate in habitual physical activity can maintain lower body fat and a higher RMR than sedentary controls with similar body mass, FFM, and body mass index. APPLICATIONS/CONCLUSIONS: This research supports and emphasizes the benefits of habitual physical activity in maintaining RMR and lower body fat levels in middle-aged women.     

Resting Energy Expenditure and the Effects of Muscle Wasting in Patients With Chronic Heart Failure: Results From the Studies Investigating Comorbidities Aggravating Heart Failure (SICA-HF)

Objectives

Muscle wasting is common in patients with chronic heart failure (HF) and worsens functional status. Protein catabolism is characteristic of muscle wasting and contributes to resting energy expenditure (REE). Glucagonlike peptide 1 (GLP-1) is linked to REE in healthy individuals. We aimed to evaluate (1) whether REE is elevated in patients with HF with muscle wasting, and (2) whether basal GLP-1 levels are linked to REE in HF.

Design

Cross-sectional study.

Setting

Ambulatory patients with HF were recruited at the Charité Medical School, Campus Virchow-Klinikum, Berlin, Germany.

Participants

A total of 166 patients with HF and 27 healthy controls participating in the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF) were enrolled. GLP-1 was measured in 55 of these patients.

Measurements

Body composition was measured by dual-energy X-ray absorptiometry (DEXA). Muscle wasting was defined as appendicular lean mass of at least 2 SDs below values of a healthy young reference group. REE was measured by indirect calorimetry. GLP-1 was assessed by ELISA.

Results

Thirty-four of 166 patients (mean age 67.4 ± 10.2 years, 77.7% male, New York Heart Association class 2.3 ± 0.6) presented with muscle wasting. REE in controls and patients with muscle wasting was significantly lower than in patients without muscle wasting (1579 ± 289 and 1532 ± 265 vs 1748 ± 359 kcal/d, P = .018 and P = .001, respectively). REE normalized for fat-free mass (FFM) using the ratio method (REE/FFM) and analysis of covariance was not different (P = .23 and .71, respectively). GLP-1 did not significantly correlate with REE (P = .49), even not after controlling for FFM using multivariable regression (P = .15).

Conclusions

Differences in REE are attributable to lower FFM. GLP-1 does not relate to REE in patients with HF, possibly because of HF-related effects on REE.     

Body composition and energy expenditure in Duchenne muscular dystrophy

OBJECTIVE: To investigate the relationship between resting energy expenditure (REE) and body composition in Duchenne Muscular Dystrophy (DMD). DESIGN: An observational study. SETTING: University Research Centre. SUBJECTS: Nine Duchenne children (age range 6-12 y), mean relative weight 128%, agreed to undergo the investigation and all of them completed the study; INTERVENTIONS: Assessment of body composition (total body fat and skeletal muscle mass) by magnetic resonance imaging and resting energy expenditure by indirect calorimetry. MAIN OUTCOME MEASURES: Fat mass (FM; kg and percentage weight), fat-free mass (FFM; kg and percentage weight), muscle mass (kg and percentage weight), resting energy expenditure (kJ/kg body weight and kJ/kg fat-free mass). RESULTS:: In Duchenne children fat mass averages 32% and total skeletal muscle mass 20% of body weight. Resting energy expenditure per kg of body weight falls within the normal range for children of the same age range, while when expressed per kg of FFM is significantly higher than reference values. No relationship was found between REE and total skeletal muscle mass. CONCLUSIONS: Our results do not demonstrate a low REE in DMD boys; on the contrary REE per kg of FFM is higher than normal, probably due to the altered FFM composition. We suggest that the development of obesity in DMD children is not primarily due to a low REE but to other causes such as a reduction in physical activity and or overfeeding.     

Profiling Determinants of Resting Energy Expenditure in Colorectal Cancer

Abstract

Background: Understanding resting energy expenditure (REE) is important for determining energy requirements; REE might be altered in individuals with cancer. The objective of this study was to characterize determinants of REE in patients with stages II–IV colorectal cancer (CRC).

Methods: REE was measured via indirect calorimetry in patients with newly diagnosed CRC. Computerized tomography images from medical records ascertained skeletal muscle and total adipose tissue cross-sectional areas, which were then transformed to lean soft tissue (LST) and fat mass (FM) values (in kg). Linear regression assessed determinants of REE.

Results: 86 patients were included (n?=?55, 64.0% male; 60?±?12?years old; median body mass index: 27.6, interquartile range: 24.3–31.2?kg/m²), with most (n?=?40) having stage III disease. Age, sex, and weight were significant predictors of REE [R² = 0.829, standard error of the estimate (SEE): 128?kcal/day, P?<?0.001]. Replacing weight with LST and FM yielded a similar model, with age, sex, LST, and FM predictive of REE (R² = 0.820, SEE: 129?kcal/day, p?<?0.001).

Conclusion: Age, sex, weight, LST, and FM were the main contributors to REE. Further investigation of REE changes over time and its relationship to total energy expenditure, dietary intake, and clinical outcomes should be explored.     

Associations of Growth Impairment and Body Composition among South African School-Aged Children Enrolled in the KaziAfya Project

(1) Background: Early childhood malnutrition may result in increased fat mass (FM) among school-aged children in low- and middle-income countries (LMICs). We explored whether South African children with shorter stature have greater overall and abdominal FM compared to normal stature children. (2) Methods: Baseline assessments of body composition and weight were determined among school-aged children enrolled in a randomized controlled trial in Port Elizabeth, South Africa, using bioelectrical impedance analysis. Multiple linear regression models tested associations of children’s height and degree of stunting with FM, fat free mass (FFM), truncal fat mass (TrFM), and truncal fat free mass (TrFFM) overall and by sex. (3) Results: A total of 1287 children (619 girls, 668 boys) were assessed at baseline. Reduced child height was associated with higher FM and lower FFM and TrFFM, but these associations were reversed with increases in height. Girls classified as mildly or moderately/severely stunted had higher FM and TrFM but lower FFM and TrFFM, while no association was found for boys. (4) Conclusions: Our study suggests that efforts to reduce the non-communicable disease burden in LMICs should target growth-impaired children who may have greater overall FM and greater abdominal FM.     

Hand-Held Indirect Calorimeter Offers Advantages Compared with Prediction Equations, in a Group of Overweight Women, to Determine Resting Energy Expenditures and Estimated Total Energy Expenditures during Research Screening

Objective

To compare standardized prediction equations to a hand-held indirect calorimeter in estimating resting energy and total energy requirements in overweight women.

Design

Resting energy expenditure (REE) was measured by hand-held indirect calorimeter and calculated by prediction equations Harris-Benedict, Mifflin-St Jeor, World Health Organization/Food and Agriculture Organization/United Nations University (WHO), and Dietary Reference Intakes (DRI). Physical activity level, assessed by questionnaire, was used to estimate total energy expenditure (TEE).

Subjects

Subjects (n=39) were female nonsmokers older than 25 years of age with body mass index more than 25.

Statistical analyses

Repeated measures analysis of variance, Bland-Altman plot, and fitted regression line of difference. A difference within ±10% of two methods indicated agreement.

Results

Significant proportional bias was present between hand-held indirect calorimeter and prediction equations for REE and TEE (P<0.01); prediction equations overestimated at lower values and underestimated at higher values. Mean differences (±standard error) for REE and TEE between hand-held indirect calorimeter and Harris-Benedict were −5.98±46.7 kcal/day (P=0.90) and 21.40±75.7 kcal/day (P=0.78); between hand-held indirect calorimeter and Mifflin-St Jeor were 69.93±46.7 kcal/day (P=0.14) and 116.44±75.9 kcal/day (P=0.13); between hand-held indirect calorimeter and WHO were −22.03±48.4 kcal/day (P=0.65) and −15.8±77.9 kcal/day (P=0.84); and between hand-held indirect calorimeter and DRI were 39.65±47.4 kcal/day (P=0.41) and 56.36±85.5 kcal/day (P=0.51). Less than 50% of predictive equation values were within ±10% of hand-held indirect calorimeter values, indicating poor agreement.

Conclusions

A significant discrepancy between predicted and measured energy expenditure was observed. Further evaluation of hand-held indirect calorimeter research screening is needed.     

Cross-Validation of Prediction Equations for Resting Energy Expenditure in Young, Healthy Children

Objective To examine the accuracy of several prediction equations for resting energy expenditure (REE) in children.Design REE was measured in 113 prepubertal children (60 girls and 53 boys aged 3.9 to 7.8 years old, weighing 14.7 to 30.0 kg) using indirect calorimetry and compared with values estimated from the prediction equations of Altman and Dittmer, The Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU), Maffeis et al, and Harris and Benedict.Statistical analysis Measured REE (MREE) was compared with predicted REE (FREE) by means of regression analysis. Prediction equations were considered accurate if the regression of MREE vs FREE was not significantly different from the line of identity (slope=l.0; INTERCEPT=0). Precision was assessed by the multiple correlation coefficient of the regression of MREE vs FREE.Results MREE was 938±119 kcal/day, and FREE was 1,057+224 kcal/day for the Altman and Dittmer equations, 956±84 kcal/day for the FAO/WHO/UNU equations, 948±64 kcal/day for the equations of Maffeis et al, and 954+102 kcal/day for the Harris-Benedict equations. The regression of MREE vs FREE was significantly different from the line of identity for all prediction equations except the FAO/WHO/UNU equations (slope=0.96, P=.735; INTERCEPT=–15 kcal/day, P=.885 for girls and SLOPE=1.08, P=.635; INTERCEPT=-62 kcal/day, P=.635 for boys). None of the equations was precise for MREE vs FREE (for all, R²<.6). For the FAO/WHO/UNU equations, less than half of the predictions were within ±50 kcal/day but 99% were within 200 kcal/day.Conclusion Most prediction equations for REE in children do not accurately or precisely estimate REEs. The exception is the FAO/WHO/UNU equations, which are reasonably accurate and precise for practical purposes. J Am Diet Assoc. 1997;97: 140–145.     

Controlled trial of the metabolic effects of a very-low-calorie diet: short- and long-term effects

Resting energy expenditure (REE), weight, and body composition were measured up to seven times in 13 obese women during a 24-wk study. Patients were randomly assigned to a very-low-calorie diet (VLCD, 500 kcal/d) or a balanced-deficit diet (BDD, 1200 kcal/d). After 8 wk of supplemented fasting, REE of the VLCD patients decreased by 17% whereas that of the BDD patients was virtually unchanged. REE of the VLCD patients increased during 12 subsequent weeks of realimentation such that differences in REE between the two groups were not statistically significant at week 24 (VLCD = -11%, BDD = -2%). Reductions in weight and fat-free mass (FFM) were 12.1% and 3.6% for the VLCD patients and 10.6% and 4.1% for the BDD patients, respectively. There were no significant differences between the groups in pre- to posttreatment changes in REE normalized to FFM. Results suggest that REE recovers partially after consumption of a VLCD. They also provide evidence of a possible metabolic advantage of weight loss by a more moderate restriction.     

Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation

Differences in body composition have often been examined in conjunction with measurements of energy expenditure in men and women. Numerous studies during the past decade examined the relationship between resting energy expenditure (REE) and the components of a two-compartment model of composition, namely the fat-free mass (FFM) and the fat mass (FM). A synthetic review of these studies confirms a primary correlation between REE and FFM in adults over a broad range of body weights. A generalized prediction equation is proposed as REE = 370 +/- 21.6 x FFM. This equation explains 65-90% of the variation in REE. Several studies suggest, further, that FFM predicts total daily energy expenditure (TDEE) equally well. An independent contribution by FM to the prediction of either REE or TDEE is not supported for the general population, perhaps reflecting the relative constancy of the absolute FM in nonobese individuals. In the subset of obese women, FM may be a significant predictor.     

Influence of methods used in body composition analysis on the prediction of resting energy expenditure

OBJECTIVE: There are considerable differences in published prediction algorithms for resting energy expenditure (REE) based on fat-free mass (FFM). The aim of the study was to investigate the influence of the methodology of body composition analysis on the prediction of REE from FFM. DESIGN: In a cross-sectional design measurements of REE and body composition were performed. SUBJECTS: The study population consisted of 50 men (age 37.1+/-15.1 years, body mass index (BMI) 25.9+/-4.1 kg/m2) and 54 women (age 35.3+/-15.4 years, BMI 25.5+/-4.4 kg/m2). INTERVENTIONS: REE was measured by indirect calorimetry and predicted by either FFM or body weight. Measurement of FFM was performed by methods based on a 2-compartment (2C)-model: skinfold (SF)-measurement, bioelectrical impedance analysis (BIA), Dual X-ray absorptiometry (DXA), air displacement plethysmography (ADP) and deuterium oxide dilution (D2O). A 4-compartment (4C)-model was used as a reference. RESULTS: When compared with the 4C-model, REE prediction from FFM obtained from the 2C methods were not significantly different. Intercepts of the regression equations of REE prediction by FFM differed from 1231 (FFM(ADP)) to 1645 kJ/24 h (FFM(SF)) and the slopes ranged between 100.3 kJ (FFM(SF)) and 108.1 kJ/FFM (kg) (FFM(ADP)). In a normal range of FFM, REE predicted from FFM by different methods showed only small differences. The variance in REE explained by FFM varied from 69% (FFM(BIA)) to 75% (FFM(DXA)) and was only 46% for body weight. CONCLUSION: Differences in slopes and intercepts of the regression lines between REE and FFM depended on the methods used for body composition analysis. However, the differences in prediction of REE are small and do not explain the large differences in the results obtained from published FFM-based REE prediction equations and therefore imply a population- and/or investigator specificity of algorithms for REE prediction.     

Energy expenditure and estimated caloric intake in asthmatic adolescents with excess body weight

ObjectiveTo measure resting energy expenditure (REE) and to estimate caloric intake of asthmatic adolescents with excess body weight and compare results with those groups of eutrophic asthmatic adolescents and non-asthmatic adolescents with excess body weight.MethodsThis cross-sectional study categorized 69 adolescents aged 10 to 18 y into three matched groups. Nutritional status was assessed using anthropometric and body composition measurements. Indirect calorimetry was used to measure energy expenditure, and caloric intake was estimated from dietary recalls.ResultsIn each group, there were 23 adolescents (10 girls) aged 12.39 ± 2.40 y. Results for each group were as follows. For asthmatic adolescents with excess body weight, body mass index (BMI) was 24.83 ± 2.73 kg/m², REEs were 1550.24 ± 547.23 kcal/d and 27.69 ± 11.33 kcal · kg^?1 · d^?1, and estimated caloric intake was 2068.75 ± 516.66 kcal/d; for eutrophic asthmatic adolescents, BMI was 19.01 ± 2.10 kg/m², REEs were 1540.82 ± 544.22 kcal/d and 36.65 ± 15.04 kcal · kg^?1 · d^?1, and estimated caloric intake was 2174.05 ± 500.55 kcal/d; and for non-asthmatic adolescents with excess body weight, BMI was 25.35 ± 3.66 kg/m², REEs were 1697.24 ± 379.84 kcal/d and 28.18 ± 6.70 kcal · kg^?1 · d^?1, and estimated caloric intake was 1673.17 ± 530.68 kcal/d. Absolute REE values between groups were not statistically different, even after correction for lean mass and fat mass (F = 0.186, P = 0.831). REE (kilocalories per kilogram per day) was significantly higher in the group of eutrophic asthmatic adolescents (P = 0.016). Estimated caloric intake was greater than REE only in the group of adolescents with asthma.ConclusionThe REE was not significantly different among groups, and REE (kilocalories per kilogram per day) was higher in the group of eutrophic asthmatic adolescents. Estimated caloric intake was greater than REE in the group of adolescents with asthma.