Growth velocity, fat-free mass and energy intake are inversely related to viral load in HIV-infected children

The study objectives were to assess the relationships among human immunodeficiency virus (HIV) replication, energy balance, body composition and growth in children with HIV-associated growth failure (GF). Energy intake and expenditure, body composition and level of HIV RNA were measured in 16 HIV-infected children with growth failure (HIV+/GF+), defined as a 12-mo height velocity 相似文献   

Resting energy expenditure is increased in stable, malnourished HIV-infected patients

Resting energy expenditure (REE) was measured by reference to body composition in 50 malnourished patients with human immunodeficiency virus (HIV) infection and compared with that of 14 healthy subjects. Among HIV patients, 40 had acquired immune deficiency syndrome (AIDS) and 10 had AIDS-related complex (ARC). All were in stable condition and had a previous history of progressive wasting, ie, a mean body weight loss of 14.2 +/- 8.1 kg over 16.6 mo (range 2-49 ms). The mean REE was 14% higher than estimated basal energy expenditure (EBEE), according to the Harris and Benedict formula. Thirty-four patients (68%) were classified as hypermetabolic (REE greater than 110% EBEE). The best predictable variable for REE was fat-free mass (FFM), as determined by an anthropometric method (r = 0.72; P less than 0.001). The mean REE was 12% higher in HIV patients than in the control group FFM (156 +/- 19 vs 124 +/- 17 kJ.kg FFM-1.d-1). We concluded that in stable and malnourished HIV patients, the progressive wasting may be partly related to an increase in REE. The mechanism of this hypermetabolic state remains to be established.     

Resting and sleeping energy expenditure in the elderly

An estimate of a patient's energy needs is usually derived from equations, which predict energy expenditure (EE) by considering sex, age and body weight. Due to the increasing number of elderly people in a hospital population, more data on energy requirements in this age-group are needed. In this study resting energy expenditure (REE) of 40 healthy men and women, aged 51-82 years, was measured using a ventilated hood system. The results showed that some commonly used prediction equations underestimated REE by approximately 6 per cent. REE was highly correlated with fat free mass (FFM) (r = 0.88; P less than 0.001) and body weight (r = 0.85; P less than 0.001). A stepwise multiple regression analysis showed that the combination of body weight, sex and age resulted in the best prediction for REE; REE (kcal) = 1641 + 10.7 weight (kg)--9.0 age (years)--203 sex (1 = male, 2 = female) (r = 0.92). However, REE of an individual may be over- or underestimated by +/- 225 kcal (10-20 per cent) due to large between-subject variations. We suggest therefore that the energy requirements of elderly people should be measured rather than predicted. Due to small within-subject variations (including measurement error) a single REE measurement would suffice. Sleeping energy expenditure (SEE) was 7 per cent lower than REE.     

Resting energy expenditure and nutritional state in patients with liver cirrhosis before and after liver transplantation

Resting energy expenditure (REE), body composition, and the biochemical parameters of liver function were measured in 26 patients before and 432 days (range: 103-1022 days) after liver transplantation (LTX). PreLTX REE was variable (mean: 1638 +/- 308 kcal/day, range: 1220-2190 kcal/day or +10 +/- 11% of Harris Benedict = HB prediction, range: -19 - +33%) and was closely related to body cell mass (r = 0.66, p < 0.0003). PostLTX REE was variable (mean: 1612 +/- 358 kcal/day, range: 1010-2490 kcal/day or +5 +/- 15% of HB prediction, range: -20 - +37%) and was closely related to body cell mass (r = 0.65, p < 0.0006). When compared with preLTX values only small changes in mean REE (-71 +/- 43 kcal/day) and a close correlation between pre and postLTX REE (r = 0.82, p < 0.001) were observed. In contrast to REE, changes in body weight were highly variable (-16.5 - +32.7 kg/year). This variance was not explained by the number of postoperative complications, pre and postLTX liver function, possible graft rejection and/or hepatitis reinfection. Pre-operative hypermetabolism (i.e. REE >+20% of HB prediction) was associated with postoperative hypermetabolism and a reduced liver function before and after LTX. Hypermetabolic patients had a poorer nutritional outcome after LTX (weight change: 0 +/- 8.4 kg/year) when compared with normometabolic controls (weight change: +5.7 +/- 7.4 kg/year; p < 0.05). There was no significant association between deviations in pre and postLTX REE and changes in body weight. When corrected for changes in the nutritional state our data provide evidence for the persistence of resting energy expenditure in liver transplant patients.     

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).     

An evaluation of resting energy expenditure in hospitalized, severely underweight patients.

A prospective trial was conducted with 14 hospitalized patients who were severely underweight with a mean weight of 40.9+/-5.1 kg and 70.7+/-7.8% of ideal body weight, to compare estimates of resting energy expenditure (REE) with measured values. The 9 women and 3 men, whose mean age was 66.5+/-13.9 y, underwent nutritional assessment and measurement of their REE by indirect calorimetry using the Sensormedics Deltatrac MBM100 indirect calorimeter. Their REE was also estimated by the Harris-Benedict formula (mean 1032+/-66 kcal/d) as well as a previously established empirical formula where REE = 25 x body weight in kg (mean 1023+/-129 kcal/d). Results by both estimates were significantly lower than the measured resting energy expenditure (MREE) in this group of patients (P<0.0001). The percentage difference between MREE and estimated REE by the Harris-Benedict formula was 18.4+/-9.4% and 20.9+/-7.5% by the empirical formula. The MREE exceeded the estimated REE in each individual. The correlation between MREE and body weight (r2 = 0.558, r = 0.005) was better than that between MREE and estimated REE by Harris-Benedict formula (r2 = 0.275, P = 0.08) suggesting that weight was the principal determinant rather than the other components (height, age, sex) of the Harris-Benedict formula. Our data shows that commonly employed formulae routinely underestimate the energy needs of severely underweight patients below 50 kg in body weight. The Harris-Benedict equation had limited predictive value for the individual, explaining approximately 25% of the variance in energy expenditure. Given the particular importance of matching energy intake to needs in this group of patients with limited reserves, many of whom are critically ill, we suggest an empirical equation using 30-32 kcal/kg be used to estimate the energy requirements of severely underweight patients when direct measurements are unavailable or clinically less imperative.     

Measured energy expenditure of tube-fed patients with severe neurodevelopmental disabilities

OBJECTIVE: To determine measured resting energy expenditure (REE) of nonambulatory tube-fed patients with severe neurological neurodevelopmental disabilities. METHODS: Twenty patients were prospectively studied. Only steady state indirect calorimetry measurements were taken. All measurements were conducted using a canopy system. Nutritional needs were met entirely by enteral feedings via a permanent ostomy. RESULTS: REE was widely distributed from 16 kcals/kg/day to 39 kcals/kg/day. The mean REE (888+/-176 kcals/day) of the patients was significantly (p<0.01) lower than predicted as estimated by the Harris-Benedict equations (1081+/-155 kcals/day) and World Health Organization equations (1194+/-167 kcals/day). Fat-free mass (FFM) was the best parameter for predicting REE. Two predictive equations were developed that are not significantly biased and more precise (< or =15% error) than conventional predictive formulas. CONCLUSION: Conventional formulas for estimating energy expenditure are inaccurate and generally overestimate measured energy expenditure of nonambulatory patients with severe developmental disabilities.     

Validation study of energy expenditure and intake during calorie restriction using doubly labeled water and changes in body composition

BACKGROUND: Clinical trials involving calorie restriction (CR) require an assessment of adherence to a prescribed CR with the use of an objective measure of energy intake (EI). OBJECTIVE: The objective was to validate the use of energy expenditure (EE) measured by doubly labeled water (DLW), in conjunction with precise measures of body composition, to calculate an individual's EI during 30% CR. DESIGN: Ten participants underwent 30% CR for 3 wk. During the last week (7 d), 24-h EE was measured in a respiratory chamber and simultaneously by DLW (EEDLW). EI was calculated from 7-d EE measured by DLW and from changes in energy stores (ES) (weight and body composition). Calculated EI was then compared with the actual EI measured in the chamber by using the following equations: calculated EI (kcal/d) = EEDLW + DeltaES, where DeltaESFM/FFM (kcal/d) = (9.3 x DeltaFM, g/d) + (1.1 x DeltaFFM, g/d), FM is fat mass, and FFM is fat-free mass. RESULTS: We found close agreement (R = 0.88) between EE measured in the metabolic chamber and EEDLW during CR. Using the measured respiratory quotient, we found that the mean (+/-SD) EE(DLW) was 1934 +/- 377 kcal/d and EE measured in the metabolic chamber was 1906 +/- 327 kcal/d, ie, a 1.3 +/- 8.9% overestimation. EI calculated from EEDLW and from changes in ES was 8.7 +/- 36.7% higher than the actual EI provided during the chamber stay (1596 +/- 656 kcal/d). CONCLUSIONS: DLW methods can accurately estimate 24-h EE during CR. Although the mean difference between actual and calculated EIs for the group was small, we conclude that the interindividual variability was too large to provide an assessment of CR adherence on an individual basis.     

Factors associated with the increase in resting energy expenditure during refeeding in malnourished anorexia nervosa patients

BACKGROUND: In malnourished anorexia nervosa (AN) patients, body-weight gain during refeeding is slowed by an increase in resting energy expenditure (REE). OBJECTIVE: The objective of the study was to identify factors associated with the increase in REE during refeeding. DESIGN: Before and 8, 30, and 45 d after the beginning of refeeding, REE was studied by indirect calorimetry in 87 female AN patients [x +/- SD age: 23.4 +/- 7.9 y; body mass index (in kg/m2) 13.2 +/- 1.3]. Energy intake, body composition (by bioelectrical impedance analysis), physical activity, smoking behavior, abdominal pain, anxiety, depressive mood, serum thyrotropin and thyroid hormone, and urinary catecholamines were measured. REE was also evaluated in 18 patients after 1 y of recovery. RESULTS: By day 8, REE increased from 3.84 +/- 0.6 to 4.36 +/- 0.59 MJ/d (P < 0.01). This increase (13.4%) was significantly (P <0.01) greater than that expected on the basis of the increase in fat-free mass (FFM; 1.6%). Thereafter, the ratio of REE to FFM remained high and, in multivariate analysis, was significantly related to 4 factors: energy intake (P <0.01), anxiety (P <0.01), abdominal pain (P <0.05), and depressive mood (P <0.05). The ratio also increased significantly with physical activity (P <0.01) and cigarette smoking (P <0.02). This rise in REE leveled off after recovery from AN. CONCLUSION: In AN patients, the rise in REE observed during refeeding was independently linked to anxiety level, abdominal pain, physical activity, and cigarette smoking, and it contributed to resistance to weight gain.     

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.     

Sex differences in resting energy expenditure and their relation to insulin resistance in children (EarlyBird 13)

BACKGROUND: Insulin resistance is believed to be the process underlying type 2 diabetes and premature cardiovascular disease. We have established that a relation between body mass and insulin resistance calculated by homeostasis model assessment (HOMA-IR) exists by 5 y of age in contemporary UK children. Resting energy expenditure (REE) is variable among individuals and is one of many factors controlling body mass. OBJECTIVE: The objective was to investigate the relations between REE, body mass, and HOMA-IR in young children. DESIGN: EarlyBird is a nonintervention prospective cohort study of 307 healthy 5-y-olds that asks the question: Which children develop insulin resistance and why? REE by indirect calorimetry and HOMA-IR were measured in addition to total body mass, fat-free mass (FFM) by bioimpedance, body mass index (BMI; in kg/m(2)), and skinfold thickness when the mean age of the cohort was 5.9 +/- 0.2 y. RESULTS: Whereas the BMI of the boys was lower than that of the girls (x +/- SD: boys, 15.9 +/- 1.9; girls, 16.5 +/- 1.9; P = 0.03), their REE was higher by 6% (x +/- SD: 4724 +/- 615 compared with 4469 +/- 531 kJ/d; P = 0.002). This difference persisted after adjustment for FFM and other anthropometric variables (P = 0.04). In boys, there was a weak, although significant, inverse correlation between REE and HOMA-IR, independent of fat mass and FFM (boys: r = -0.21, P = 0.03; girls: r = 0.12, P = 0.34). CONCLUSION: There is a sex difference in REE at 6 y of age that cannot be explained by body composition. The difference appears to be intrinsic, and its contribution to sex differences in adiposity and HOMA-IR in children merits further exploration.     

Relationship between blood adipocytokines and resting energy expenditure in young and elderly women

It has been demonstrated in a previous study that resting energy expenditure (REE) is associated with adiponectin levels in the blood. However, body composition was not taken into consideration in that study. The purpose of the present study was to again investigate the relationship between blood adipocytokines and REE, adjusted by body composition, in both young and elderly women. REE and blood adipocytokines were measured in 115 young (age: 22.3+/-2.1 y, BMI: 21.3+/-1.9 kg/m(2)) and 71 elderly (63.4+/-6.5 y, 22.9+/- 2.3 kg/m(2)) women. Dual energy X-ray absorptiometry was used to measure percent body fat. Fat mass and fat free mass (FFM) were calculated. REE (kcal/d and kcal/kg BW/d) was lower in elderly women than in young women, but no significant difference was observed in REE, expressed as kcal/kg FFM/d, between the two groups. Although elderly women had a higher percent body fat and higher serum leptin concentrations than young women, plasma adiponectin concentrations did not differ between young and elderly women. In elderly women, REE (kcal/d) was significantly and inversely correlated with plasma adiponectin concentration (r=-0.386, p<0.001), but REE expressed per kilogram of BW or FFM was not significantly correlated. Furthermore, no significant correlation was observed between REE (kcal/d) and concentrations of plasma adiponectin or serum leptin, after adjusting for potential confounders such as body composition and hormones, in either age group. These results suggest that adipocytokines do not influence REE in adult women.     

Resting energy expenditure in patients with chronic obstructive pulmonary disease

Resting energy expenditure (REE) was measured in 68 patients with stable chronic obstructive pulmonary disease (COPD) and in 34 weight-stable, age-matched (65 +/- 8 y; means +/- SD) healthy control subjects. Fat-free mass (FFM) determined by bioelectrical resistance explained 84% of the variation in REE in the control group but only 34% in the COPD patients. REE could not reliably be predicted from regression equations either developed in healthy subjects or in COPD patients. REE adjusted for FFM was significantly higher (P less than 0.05) in weight-losing (n = 34) than in weight-stable (n = 34) patients (6851 +/- 781 and 6495 +/- 650 kJ/d, respectively). Pulmonary function was more compromised in weight-losing patients. Adjusted REE in weight-stable patients was significantly higher (P less than 0.01) than in the healthy control group (6131 +/- 405 kJ/d). In patients with COPD, factors in addition to FFM are important determinants of REE. A disease-related increase in REE develops, which may contribute to weight loss in COPD in combination with a lack of an adaptive response to undernutrition in weight-losing patients.     

Energy expenditure measured by doubly labeled water,activity recall,and diet records in the rural elderly

OBJECTIVE: The purpose of this study was to determine whether energy expenditure estimated from physical activity and energy intake were equivalent to total daily energy expenditure in an elderly rural population. METHODS: Twenty-seven elderly male (n = 14) and female (n = 13) subjects (mean age, 74 y) were recruited from a rural Pennsylvania population. Over a 2-wk period, total daily energy expenditure was measured by doubly labeled water (TEE) and estimated from 7-d physical activity recall factors multiplied by weight (PA(WT)), estimated basal metabolic rate (PA(BMR)) and resting energy expenditure from indirect calorimetry (PA(REE)), and energy intake from 3-d self-reported diet records (EI). Analysis of variance was used to determine significant within-subject differences in physical activity, energy intake, and energy expenditure. RESULTS: PA(REE) (men: 13.69 +/- 3.23 MJ, women: 9.51 +/- 2.40 MJ) and PA(BMR) (men: 13.69 +/- 2.99 MJ, women: 10.15 +/- 2.21 MJ) were not significantly different from TEE (men: 12.43 +/- 1.63 MJ, women: 9.44 +/- 0.90 MJ). EI (men: 8.66 +/- 2.34 MJ, women: 7.12 +/- 0.93 MJ) was significantly less than TEE, and PA(WT) (men: 17.03 +/- 4.07 MJ, women: 12.86 +/- 3.41 MJ) was significantly greater than TEE. CONCLUSIONS: Whereas 7-d physical activity recall determined with an age- and gender-specific estimate of resting metabolic rate or measured using indirect calorimetry accurately estimated TEE for this group of rural elderly, self-reported diet records consistently underestimated and physical activity recall determined with weight alone consistently overestimated energy expenditure measured by doubly labeled water.     

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.     

A new predictive equation for resting energy expenditure in healthy individuals

A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371.     

Comparison of energy intakes estimated by weighed dietary record and diet history questionnaire with total energy expenditure measured by accelerometer in young Japanese women

In Western countries underestimation of energy intake (EI) is considered a serious problem in dietary surveys, but information on the accuracy of EI among Japanese people is sparse. We compared estimated EI with measured total energy expenditure (TEE) in 21 Japanese women aged 20-22 y. Dietary intake was estimated by 7-d weighed dietary records (7dWR) and a self-administered diet history questionnaire (DHQ). TEE was measured for 25+/-3 d (mean+/-standard deviation, range: 16-27 d) by a uniaxial accelerometer. Both EI by 7dWR (1,498+/-305 kcal/d) and EI by DHQ (1,599+/-331 kcal/d) were significantly lower than TEE (1,865+/-179 kcal/d) (p<0.001 and p<0.01, respectively), but neither estimated EI nor the magnitude of EI underestimation (20+/-15% for 7dWR and 13+/-23% for DHQ) was significantly different between two methods (p=0.25 and p=0.22, respectively). The Spearman correlation (r) between TEE and EI was 0.51 (p=0.2) for 7dWR and 0.09 (p=0.71) for DHQ, indicating better ranking of individuals by 7dWR. The accuracy of EI (EI/TEE) was negatively associated with the percentage of EI from protein in 7dWR (r=-0.44, p=0.049) and positively associated with the percentage of EI from fat in both 7dWR (r=0.45, p=0.04) and DHQ (r=0.62, p<0.01), suggesting selective overestimation of protein and selective underestimation of fat. These results indicate not only underestimation of habitual EI but also selective under- and/or overestimation of macronutrients in both 7dWR and DHQ.     

Influence of sibutramine on energy expenditure in African American women

OBJECTIVE: African American women have a high prevalence of obesity, which partially may be explained by their lower rates of resting energy expenditure (REE). The aim of this study was to examine the influence of acute sibutramine administration on REE and post-exercise energy expenditure in African American women. RESEARCH METHODS AND PROCEDURES: A total of 15 premenopausal, African American women (age, 29 +/- 5 years; body fat, 38 +/- 7%) completed a randomized, double-blind cross-over design with a 30-mg ingestion of sibutramine or a placebo. Each trial was completed a month apart in the follicular phase and included a 30-minute measurement of REE 2.5 hours after sibutramine or placebo administration. This was followed by 40 minutes of cycling at approximately 70% of peak aerobic capacity and a subsequent 2-hour measurement of post-cycling energy expenditure. RESULTS: There was no difference (p > 0.05) in REE (23.70 +/- 2.81 vs. 23.69 +/- 2.95 kcal/30 min), exercise oxygen consumption (1.22 +/- 0.15 vs. 1.25 +/- 0.15 liter/min), and post-cycling energy expenditure (104.2 +/- 12.7 vs. 104.9 +/- 11.4 kcal/120 min) between the sibutramine and placebo trials, respectively. Cycling heart rate was significantly higher (p = 0.01) during the sibutramine (158 +/- 14 beats/min) vs. placebo (150 +/- 12 beats/min) trials. DISCUSSION: These data demonstrate that acute sibutramine ingestion does not increase REE or post-exercise energy expenditures but does increase exercising heart rate in overweight African American women. Sibutramine may, therefore, impact weight loss through energy intake and not energy expenditure mechanisms.     

Energy balance in relation to cancer cachexia

The aim of the current study was to determine the contribution of increased resting energy expenditure (REE) and/or decreased energy intake (EI) to the development of weight loss in gastric and colorectal (GCR) and lung cancer patients. REE was measured in 22 GCR cancer patients and 17 lung cancer patients and was compared with REE values in 40 apparently healthy controls. REE in lung cancer patients expressed per kg fat free mass (REE/FFM) was significantly increased when compared to healthy controls (33.5 +/- 5.4 and 29.6 +/- 2.9 kcal, respectively; p < 0.01). GCR cancer patients had no elevated REE compared to these healthy controls. No significant differences in EI were established between the three groups. Eight GCR cancer patients reported a decrease in food intake compared to pre-disease intake, in contrast to only one lung cancer patient. Semi-starving GCR cancer patients showed a significant weight loss (8.7 +/- 8.1%), a low respiratory quoteint (RQ) (0.76 +/- 0.04) and a high beta-hydroxybutyrate level (259 +/- 192 mumol/l), but they showed no difference in REE compared to patients with a normal EI. The current study suggests that weight loss in GCR cancer patients is initiated by decreased food intake, whereas weight loss in lung cancer patients represents a combination of an increased REE and a relatively low EI.     

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.