Effect of weight reduction on resting energy expenditure, substrate utilization, and the thermic effect of food in moderately obese women.

It is not known whether the decrease in the thermic effect of food (TEF) in obesity is a consequence of obesity or a factor contributing to the development of obesity. The resting energy expenditure (REE) of 24 obese, nondiabetic, postmenopausal women was 5481 +/- 110 kJ/24 h (1310 +/- 26.4 kcal/24 h). After weight loss (12.7 +/- 0.45 kg) the REE was significantly decreased (4858 +/- 94 kJ/24 h, or 1161 +/- 22.4 kcal/24 h) and equivalent to the REE of 4866 +/- 119 kJ/24 h (1163 +/- 28.5 kcal/24 h) in 24 never-obese, postmenopausal women. The TEF, expressed as a percentage of the calories ingested, was 8.2 +/- 0.50% for obese subjects, 8.7 +/- 0.57% for postobese subjects, and 9.8 +/- 0.54% for never-obese subjects. Compared with never-obese subjects, the TEF was significantly reduced in obese subjects (P = 0.043) and remained unchanged after weight loss (P = 0.341). These findings indicate that the lower TEF in the obese subjects is uncorrected by weight loss, and thus it is a contributor to obesity rather than a consequence of obesity.     

Effect of acclimation on resting energy expenditure measurements.

BACKGROUND: Development of an acclimation protocol for use when measuring resting energy expenditure (REE) would simplify and standardize data collection. The purpose of this study was to determine if our 2 metabolic carts could be used interchangeably and to determine if excluding the first 3 or 5 minutes of data collected as an acclimation period would significantly improve the coefficients of variation (CVs) for oxygen consumed (VO(2)) and carbon dioxide produced (VCO(2)) when performing REE assessments with our metabolic cart systems. METHODS: Thirteen healthy, nonsmoking adults ranging in age from 32 to 45 years, with activity levels ranging from sedentary to highly active, participated. Indirect calorimetry was performed twice in the morning after 30 minutes of supine resting. Subjects had fasted for 12 hours, and did not exercise within the last 24 hours. The system order for testing was randomized for the first measurement. When the first measurement was completed, subjects were crossed over for measurement using a second metabolic cart. RESULTS: The CVs for VO(2) and VCO(2) were significantly lower when excluding the first 3 (VO(2), p = .0005), (VCO(2), p = .0024) or 5 minutes (VO(2), p = .0001, VCO(2), p = .0021) of data compared with no exclusions. No significant differences in CVs between the 3- and 5-minute exclusions were found for VO(2) (p = .3224) or VCO(2) (p = .2255). CONCLUSIONS: Clearly, our machines cannot be used interchangeably within a study. An acclimation period improves CVs of VO(2) and VCO(2.) The similarities in CVs led us to adopt a 3-minute acclimation period for measuring REE.     

The influence of nutritional intervention on resting energy expenditure in obese adolescents aged 15-18 years

The aim of this research was to assess the influence of dietary intervention on weight loss and resting energy expenditure (REE) in 20 obese and overweight adolescents (BMI = 29 +/- 3,8 kg/m2) aged 15-18 years. Nutritional habits and nutritional status were estimated before and after the introduction of low-calorie diet. Measurements of REE were carried out by indirect calorimetry in a respiratory chamber Nutritional intervention had a significant influence in decreasing body weight (from 85 +/- 14.3 kg to 82.5 +/- 12.8 kg), BMI and fat mass. Muscle mass was found to be significantly elevated (p < 0.050). REE did not decline significantly due to nutritional intervention (p > 0.05; p = 0.84).     

Development and cross-validation of prediction equations for estimating resting energy expenditure in severely obese Caucasian children and adolescents

The objectives of the present study were to develop and cross-validate new equations for predicting resting energy expenditure (REE) in severely obese children and adolescents, and to determine the accuracy of new equations using the Bland-Altman method. The subjects of the study were 574 obese Caucasian children and adolescents (mean BMI z-score 3.3). REE was determined by indirect calorimetry and body composition by bioelectrical impedance analysis. Equations were derived by stepwise multiple regression analysis using a calibration cohort of 287 subjects and the equations were cross-validated in the remaining 287 subjects. Two new specific equations based on anthropometric parameters were generated as follows: (1) REE=(Sex x 892.68)-(Age x 115.93)+(Weight x 54.96)+(Stature x 1816.23)+1484.50 (R(2) 0.66; se 1028.97 kJ); (2) REE=(Sex x 909.12)-(Age x 107.48)+(fat-free mass x 68.39)+(fat mass x 55.19)+3631.23 (R(2) 0.66; se 1034.28 kJ). In the cross-validation group, mean predicted REE values were not significantly different from the mean measured REE for all children and adolescents, as well as for boys and for girls (difference <2 %) and the limits of agreement (+/-2 sd) were +2.06 and -1.77 MJ/d (NS). The new prediction equations allow an accurate estimation of REE in groups of severely obese children and adolescents. These equations might be useful for health care professionals and researchers when estimating REE in severely obese children and adolescents.     

The effect of a high protein-low calorie diet on the energy expenditure of obese adolescents.

Resting energy expenditure (REE), and body composition, as fat-free mass (FFM) and fat mass, were determined in seven obese adolescents before and after weight loss of a mean 13.5 kg on an approximately 800 kcal/d (3349 kJ), high protein reducing diet regimen. Ideal body weight decreased from 166% to 142% in 8 weeks. There were no significant changes in total body potassium (TBK), extracellular water (ECW), intracellular water (ICW) or total body water (TBW) with weight loss. The REE (kcal/d) fell from 2034 +/- 392 (8514 +/- 1641 kJ) to 1762 +/- 453 (7376 +/- 1896 kJ) with weight loss (P < 0.05). However, when the REE was expressed as kcal/body weight there was no difference between before and after weight loss, 21.4 +/- 2.8 (90 +/- 21 kJ) and 21.6 +/- 4.5 (90 +/- 19 kJ). Similarly, when REE was examined in relation to FFM (kcal/kg) before and after weight loss, there were also no significant differences: 34.6 +/- 5.1 (145 +/- 21 kJ) and 32.1 +/- 7.9 (134 +/- 33 kJ).     

Whole-body protein turnover and resting energy expenditure in obese, prepubertal children

BACKGROUND: Obesity is becoming more frequent in children; understanding the extent to which this condition affects not only carbohydrate and lipid metabolism but also protein metabolism is of paramount importance. OBJECTIVE: We evaluated the kinetics of protein metabolism in obese, prepubertal children in the static phase of obesity. DESIGN: In this cross-sectional study, 9 obese children (x +/- SE: 44+/-4 kg, 30.9+/-1.5% body fat) were compared with 8 lean (28+/-2 kg ,16.8+/-1.2% body fat), age-matched (8.5+/-0.2 y) control children. Whole-body nitrogen flux, protein synthesis, and protein breakdown were calculated postprandially over 9 h from 15N abundance in urinary ammonia by using a single oral dose of [15N]glycine; resting energy expenditure (REE) was assessed by indirect calorimetry (canopy) and body composition by multiple skinfold-thickness measurements. RESULTS: Absolute rates of protein synthesis and breakdown were significantly greater in obese children than in control children (x +/- SE: 208+/-24 compared with 137+/-14 g/d, P < 0.05, and 149+/-20 compared with 89+/-13 g/d, P < 0.05, respectively). When these variables were adjusted for fat-free mass by analysis of covariance, however, the differences between groups disappeared. There was a significant relation between protein synthesis and fat-free mass (r = 0.83, P < 0.001) as well as between protein synthesis and REE (r = 0.79, P < 0.005). CONCLUSIONS: Obesity in prepubertal children is associated with an absolute increase in whole-body protein turnover that is consistent with an absolute increase in fat-free mass, both of which contribute to explaining the greater absolute REE in obese children than in control children.     

Validating predictive factors for resting energy expenditure of adolescents in Indonesia

Our objectives were to (1) compare the measured and predicted resting energy expenditure (REE) using 18 equations in normal-weight and obese adolescents, and (2) examine potential predictive factors for accurately estimating REE in obese adolescents. The subjects chosen were 41 obese and 35 normal-weight adolescents living in an urban area in Indonesia. REE was measured using indirect calorimetry and compared with predicted REE determined via 18 equations. New predictive equations were developed via stepwise multiple regression analysis. Mean differences between the predicted and measured REE were within ±?5% with 13 equations tested in normal-weight subjects, and only six equations in obese subjects. New predicted REE derived from our new equations was significantly correlated with measured REE (P?相似文献   

Effect of energy and protein intake and exercise intensity on the thermic effect of food

The effect of energy content and protein concentration of a test meal and exercise intensity on the thermic effect of food (TEF) was examined. TEF was measured in eight men in response to meals representing 15, 30, and 45% of daily energy requirement; protein concentrations of 15, 30, and 45% of energy of the meal, and exercise intensities of 35, 50, and 65% of maximum capacity. In response to energy content of the meals, total 3-h TEF (mean +/- SEM) 4.0 +/- 0.83, 9.7 +/- 1.15, and 10.8 +/- 0.79 1 O2 for the 15, 30, and 45% meals, respectively, indicating a positive linear and a negative quadratic relationship. Although the 15% protein meal resulted in the smallest TEF, 150-270 min after the meal, total 5-h increase in oxygen consumption did not differ among the three protein meals. Exercise intensity did not alter TEF. Energy content of the test meal had the greatest effect on TEF.     

Prediction of resting energy expenditure in a large population of obese children

BACKGROUND: Recommendations for energy intake in obese children rely on accurate methods for measuring energy expenditure that cannot be assessed systematically. OBJECTIVE: The aim was to establish and validate new equations for predicting resting energy expenditure (REE), specifically in obese children. DESIGN: REE (indirect calorimetry) and body composition (bioelectrical impedance analysis) were measured in 752 obese subjects aged 3-18 y. The first cohort (n=471) was used to establish predictive equations, the second (and independent) cohort (n=211) was used to validate these equations, and the third cohort, a follow-up group of children who lost weight (n=70), was used to examine predictive REE in the postobese period. REE values predicted with the use of various published equations and the new established equation were compared with measured REE by using the Bland-Altman method and Student's t tests. RESULTS: In cohort 1, significant determinants of the new prediction equations were fat-free mass in boys (model R2=0.79) and age and fat-free mass in girls (model R2=0.76). External validation conducted by using the Bland-Altman method and Student's t tests, in cohort 2, showed no significant difference between measured REE and predicted REE with the new equation. When already published equations were applied, systematical bias appeared with all published equations except for that of the World Health Organization. In cohort 3, the children who lost weight, almost all equations significantly underestimated REE. CONCLUSIONS: These new predictive equations allow clinicians to estimate REE in an obese pediatric population with sufficient and acceptable accuracy. This estimation may be a strong basis for energy recommendations in childhood obesity.     

Influence of resting energy expenditure on weight gain in adolescents taking second-generation antipsychotics

Background & aims

: Weight gain is an undesirable side effect of second-generation antipsychotics (SGAs). We performed this study to examine the influence of SGAs on resting energy expenditure (REE) and the relationship of REE to weight gain in adolescent patients.

Methods

Antipsychotic-naïve or quasi-naïve (<72 h of exposure to antipsychotics) adolescent patients taking olanzapine, quetiapine, or risperidone in monotherapy were followed up for one year. We performed a prospective study (baseline, 1, 3, 6, and 12 months after treatment) based on anthropometric measurements, bioelectrical impedance analysis, and indirect calorimetry (Deltatrac™ II MBM-200) to measure REE. We also analyzed metabolic and hormonal data and adiponectin concentrations.

Results

Forty-six out of the 54 patients that started treatment attended at least 2 visits, and 16 completed 1 year of follow-up. Patients gained 10.8 ± 6.2 kg (60% in the form of fat mass) and increased their waist circumference by 11.1 ± 5.0 cm after 1 year of treatment. The REE/kg body mass ratio decreased (p = 0.027), and the REE/percentage fat-free mass (FFM) ratio increased (p = 0.007) following the fall in the percentage of FFM during treatment. Weight increase was significantly correlated with the REE/percentage FFM ratio at all the visits (1–3–6–12 months) (r = 0.69, p = 0.004 at 12 months).

Conclusions

SGAs seem to induce a hypometabolic state (reflected as decreased REE/kg body mass and increased REE/percentage FFM). This could explain, at least in part, the changes in weight and body composition observed in these patients.     

Equation to estimate resting energy expenditure in adolescents with sickle cell anemia

BACKGROUND: Basal energy requirements are higher in adolescents with sickle cell anemia (SCA) than in healthy control subjects. However, no equation is available to accurately predict their energy needs. OBJECTIVE: Our objective was to develop a clinically useful equation to estimate resting energy expenditure (REE) in adolescents with SCA. DESIGN: REE and other components of total energy expenditure were measured in adolescents with SCA (n = 37) and in control subjects (n = 23) for 24 h in a whole-room indirect calorimeter. Multiple linear regression analysis was used to describe the relations of REE with independent variables such as sex, weight, height, fat-free mass, fat mass, age, and hemoglobin concentration in adolescents with SCA. The Bland-Altman comparison technique was used to compare values predicted by existing equations with measured REE values. RESULTS: Mean (+/-SD) measured REEs were 7746 +/- 974 and 6332 +/- 869 kJ/d in the male and female subjects with SCA, respectively, and these values were 16% higher than those in the healthy control subjects. Standard equations underestimated REE by 12% (P 相似文献   

Effect of meal frequency on the thermic effect of food in women

The effect of meal frequency on the thermic effect of food (TEF), also referred to as dietary induced thermogenesis (DIT), was investigated in eighteen non-obese female subjects. Their metabolic rate before and after consuming the test meal was measured by open circuit indirect calorimetry using the Douglas bag technique, while the subjects were in the resting state (lying down). Eight subjects consumed a high carbohydrate-low fat (HCLF) meal providing 70, 19 and 11 per cent of the energy content from carbohydrate, fat and protein, respectively, and ten other subjects consumed a low carbohydrate-high fat (LCHF) meal providing 24, 65 and 11 per cent of the energy from carbohydrate, fat and protein, respectively. On two separate occasions, each subject consumed the appropriate diet either as one large meal containing 5040 kJ (1200 kcal) or as two smaller meals each containing 2520 kJ (600 kcal). TEF values were calculated for 6 h after the test meal and the mean values after consuming the HCLF meal were 377.0 +/- 30.0 kJ (90 +/- 7.2 kcal) and 381.0 +/- 26.5 kJ (91.0 +/- 6.3 kcal) for the one meal and the two meals, respectively. The mean TEF values for the subjects who consumed the LCHF meal wre 356.0 +/- 23.0 kJ (85.0 +/- 5.5 kcal) and 340 +/- 15.9 kJ (81.0 +/- 3.8 kcal) for the one meal and the two meals, respectively. No significant differences were found between the two feeding regimens (HCLF, P = 0.94; LCHF, P = 0.64) as well as between the compositions (P = 0.57). Thus, meal frequency and meal composition did not seem to influence the TEF.     

Age, sex, ethnicity, body composition, and resting energy expenditure of obese African American and white children and adolescents

BACKGROUND: African Americans may have a lower resting energy expenditure (REE) than do whites, although the data are limited for obese children and adolescents and for boys. Differences in bone density and trunk lean body mass may account for some of these measured differences in REE. OBJECTIVE: We assessed the REE and body composition of obese African American and white children and adolescents. DESIGN: Obese, 5-17-y-old children and adolescents were evaluated (n = 203). Body composition was assessed by dual-energy X-ray absorptiometry. REE was measured by open-circuit calorimetry. African American and white children were compared. The relation between REE and the independent variables (age, sex, ethnic group, fat mass, and fat-free mass or lean tissue mass) was assessed. RESULTS: Of those evaluated, 66% were girls and 34% were African American. Age, sex, pubertal status, and body composition did not differ significantly by ethnic group. All the independent variables were significantly associated with REE. Using lean tissue mass to account for differences in bone density did not significantly alter the results. REE decreased with age and was lower in the girls than in the boys and in the African Americans than in the whites. When trunk fat-free mass was included in the model in place of whole-body fat-free mass, the ethnic difference in REE decreased. CONCLUSIONS: Adjustment for trunk lean tissue mass partially explains the lower REE of obese African American children and adolescents. The lower relative REE of older obese children suggests the importance of early intervention in the prevention of childhood obesity. The lower REE of girls and of African Americans may contribute to the difficulty in weight management in these groups.     

Effect of meal size and frequency on the thermic effect of food

Results from previous studies suggest that energy content and frequency of meals may affect total daily thermic effect of food (TEF). TEF response to 2 large meals, each representing 50% of daily energy needs, was compared to the TEF response to 4 small meals, each representing 25% of daily energy needs. Total 10-hour TEF, measured as increase in oxygen consumption from rest, did not differ between the large and small meal patterns (43.43 ±5.01 vs. 43.42±4.72 liters, respectively). Measured TEF was significantly greater than predicted response due to a more complete measurement period. An optimum pattern for energy intake to either maximize or minimize TEF was not observed.