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.     

A longitudinal comparison of body composition by total body water and bioelectrical impedance in adolescent girls

Previous studies have assessed the ability of bioelectrical impedance analysis (BIA) to estimate body composition cross-sectionally, but less is known about the ability of BIA to detect changes in body composition longitudinally over the adolescent growth period. Body composition was assessed by isotopic dilution of H(2)(18)O and BIA in 196 initially nonobese girls enrolled in a longitudinal study. Two prediction equations for use in our population of girls were developed, one for use premenarcheally and one for use postmenarcheally. We compared estimates from our equation with those derived from several published equations. Using longitudinal data analysis techniques, we estimated changes in fat-free mass (FFM) and percentage body fat (%BF) over time from BIA, compared with changes in FFM and % BF estimated by H(2)(18)O. A total of 422 measurements from 196 girls were available for analysis. Of the participants, 26% had one measurement of body composition, 43% had two measurements of body composition and 31% had three or more measurements of body composition. By either H(2)(18)O or BIA, the mean %BF at study entry was 23% (n = 196) and the mean %BF at 4 y postmenarche was 27% (n = 133). In our cohort, the best predictive equations to estimate FFM by BIA were: PREMENARCHE: FFM = -5.508 + (0.420 x height(2)/resistance) + (0.209 x weight) + (0.08593 x height) + (0.515 x black race) - (0.02273 x other race). POSTMENARCHE: FFM = -11.937 + (0.389 x height(2)/resistance) + (0.285 x weight) + (0.124 x height) + (0.543 x black race) + (0.393 x other race). Overall, we found that BIA provided accurate estimates of the change in both FFM and %BF over time.     

World Health Organization equations have shortcomings for predicting resting energy expenditure in persons from a modern, affluent population: generation of a new reference standard from a retrospective analysis of a German database of resting energy expenditure

BACKGROUND: Reference standards for resting energy expenditure (REE) are widely used. Current standards are based on measurements made in the first part of the past century in various races and locations. OBJECTIVE: The aim of the present study was to investigate the application of the World Health Organization (WHO) equations from 1985 in healthy subjects living in a modern, affluent society in Germany and to generate a new formula for predicting REE. DESIGN: The study was a cross-sectional and retrospective analysis of data on REE and body composition obtained from 2528 subjects aged 5-91 y in 7 different centers between 1985 and 2002. RESULTS: Mean REE varied between 5.63 and 8.07 MJ/d in males and between 5.35 and 6.46 MJ/d in females. WHO prediction equations systematically overestimated REE at low REE values but underestimated REE at high REE values. There were significant and independent effects of sex, age, body mass or fat-free mass, and fat mass on REE. Multivariate regression analysis explained up to 75% of the variance in REE. Two prediction formulas including weight, sex, and age or fat-free mass, fat mass, sex, and age, respectively, were generated in a subpopulation and cross-validated in another subpopulation. Significant deviations were still observed for underweight and normal-weight subjects. REE prediction formulas for specific body mass index groups reduced the deviations. The normative data for REE from the Institute of Medicine underestimated our data by 0.3 MJ/d. CONCLUSIONS: REE prediction by WHO formulas systematically over- and underestimates REE. REE prediction from a weight group-specific formula is recommended in underweight subjects.     

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   

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.     

Calculating energy requirements for men with HIV/AIDS in the era of highly active antiretroviral therapy

OBJECTIVES: 1. To determine if resting energy expenditure (REE) adjusted for body composition is elevated in HIV-positive males when compared with healthy controls in the era of highly active antiretroviral therapy. 2. To examine the accuracy of prediction equations for estimating REE in people with HIV. 3. To determine if REE adjusting for body composition is significantly different between those HIV-positive subjects reporting lipodystrophy (LD) or weight loss (>or=5%) and those who are weight stable when compared to controls. DESIGN: Cross-sectional study. SETTING: Tertiary referral hospital HIV unit and an outpatient clinic specializing in HIV care. SUBJECTS: HIV-positive males (n=70) and healthy male controls (n=16). METHODS: REE was measured using indirect calorimetry. Body composition was assessed using bioelectrical impedance analysis. RESULTS: 1. REE when adjusted for fat-free mass and fat mass using the general linear model (analysis of covariance) was greater in HIV-positive subjects than controls (7258+/-810 kJ, n=70 vs 6615+/-695 kJ, n=16, P<0.05). 2. The Harris and Benedict, Schofield, Cunningham and the two equations previously published by Melchior and colleagues in HIV-positive subjects all gave an estimate of REE significantly different from the measured REE in the HIV-positive subjects, therefore a new prediction equation was developed. The inability of the published equations to predict REE in the different HIV-positive subgroups reflected the heterogeneity in body composition. 3. REE adjusted for fat-free and fat mass was significantly greater in the both the HIV patients who were weight stable and those with lipodystrophy compared with the healthy controls. CONCLUSION: REE is significantly higher in HIV-positive males when compared with healthy controls. Body composition abnormalities common in HIV render the use of standard prediction equations for estimating REE invalid. When measuring REE in HIV-positive males adjustment steps should include fat-free and fat mass.     

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.     

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.     

Energy balance in children and young adults receiving haemodialysis for chronic renal failure

This study was designed to determine the contribution of energy expenditure to the energy imbalance seen in uraemic children. Resting energy expenditure (REE) was measured using open-circuit indirect calorimetry in eight uraemic haemodialysed subjects aged 9.3-20.4 years and in 10 healthy children. Linear correlations between REE and both body weight and fat-free mass as measured by anthropometry were found in both controls and uraemic subjects (respectively: r = 0.76 and r = 0.88 for body weight and r = 0.73 and r = 0.90 for fat-free mass). Measured REE in uraemic patients was not different from the value predicted by using actual body weight and fat-free mass in the regression equation of REE on body weight and fat-free mass in controls (paired t test: p = 0.70 and p = 0.19 respectively). These data suggest that the energy imbalance seen in uraemic children is not due to increased energy expenditure and is therefore probably due to decreased food intake.     

Assessment of body composition by bioelectrical impedance in a population aged greater than 60 y

Body composition was measured in a group of 35 healthy men and 37 healthy women aged 60-83 y. Body mass index (BMI) in men was 25.0 +/- 2.2 kg/m2 (means +/- SD) and in women, 25.9 +/- 3.2 kg/m2. BMI was low in relation to body fat percentage as determined by skinfold-thickness measurements or densitometry in comparison with the relation found in younger adults. Mean body fat percentage of the male subjects (aged 70.4 +/- 5.2 y) as determined by densitometry was 31.0 +/- 4.5%, whereas in women (aged 68.0 +/- 5.2 y) it was 43.9 +/- 4.3%. Body impedance correlated with fat-free mass (FFM). The best prediction formulas for the FFM from body impedance and anthropometric variables were 1) FFM (kg) = (0.671 x 10(4) x H2/R) + 3.1S + 3.9 where H is body height (m), R is resistance (omega), and S is gender (females, 0; males, 1) (r = 0.94; SEE = 3.1 kg) and 2) FFM (kg) = (0.360 x 10(4) x H2/R) + 0.359BW + 4.5S - 20T + 7.0 where BW is body weight (kg) and T is thigh circumference (m) (r = 0.96; SEE = 2.5 kg). The prediction equations from the literature, generally determined in younger populations, overestimated FFM in elderly subjects by approximately 6 kg and are not applicable to elderly subjects.     

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.     

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.     

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 balance in children and young adultsreceiving haernodialysis for chronic renal failure

This study was designed to determine the contribution of energy expenditure tothe energy imbalance seen in uraemic children. Resting energy expenditure (REE) was measured using open-circuit indirect calorimetry in eight uraemic haemodialysed subjects aged 9.3–20.4 years and in 10 healthy children. Linear correlations between REE and both body weight and fat-free mass as measured by anthropometry were found in both controls and uraemic subjects (respectively: r = 0.76 and r = 0.88 for body weight and r = 0.73 and r = 0.90 for fat-free mass). Measured REE in uraemic patients was not different from the value predicted by using actual body weight and fat-free mass in the regression equation of REE on body weight and fat-free mass in controls (paired t test: p = 0.70 and p = 0.19 respectively). These data suggest that the energy imbalance seen in uraemic children is not due to increased energy expenditure and is therefore probably due to decreased food intake.     

The relationship between body fat mass and fat-free mass

It has been suggested that there is a curvilinear relationship between lean body or fat-free mass and body fat mass. In order to confirm this relationship, body composition was measured by determining body density and total body water using deuterium-labeled water in subjects varying widely in body fat mass. There were 29 males and 75 females with body mass index ranging from 20 to 66 kg/m2. The relationship between fat-free mass and fat mass appeared to be linear over the range of body fat from 10 to 90 kg: males R2 = 0.67 (p less than 0.0001) and females, R2 = 0.47 (p less than 0.0001). The amount of variance explained was not greater when the log of fat mass was used in place of fat mass alone. Multiple regression analysis demonstrated that the relationship between fat-free mass and fat mass remained significant (p less than 0.001) after adjusting for body height, age, and fat distribution. It is concluded that over the range of body fat extending from 10 to 90 kg there is a positive and linear relationship between fat-free body mass and fat mass.     

Air displacement plethysmography can detect moderate changes in body composition

OBJECTIVES: To determine the sensitivity of air displacement plethysmography (APD) for evaluation of changes in body composition in normal subjects. DESIGN: Comparison of measurements with and without oil or water loads. SUBJECTS AND METHODS: Ten healthy volunteers were analyzed, without and with 1 l and 2 l of oil or water. The measured and true changes in fat mass and fat-free mass were compared by paired t-tests. A correlation study and a Bland & Altman procedure was performed on the 60 measurements of adiposity changes in 30 subjects carrying 0.5 l (n=8 x 2), 1 l (n=10 x 2) and 2 l (n=12 x 2) oil and water loads. RESULTS: Fat-free mass increased when the 10 subjects were carrying water. When they carried oil, fat mass increased, however, a approximately 0.5 kg increase of fat-free mass was also detected. Two liters loads led to distinct changes: +1.49+/-0.59 kg fat and +0.50+/-0.60 kg fat-free with oil and +0.37+/-0.57 kg fat and +1.70+/-0.56 kg fat-free with water (both P<0.001). Mixed loads (+1 l oil and 1 l water) led to detect +0.85+/-0.48 kg fat and +1.09+/-0.45 kg fat-free (both P<0.005 vs without load). For the 30 subjects analyzed thrice, measured changes in fat and fat-free mass were slightly underestimated (-15%, NS) but correlated with the true changes. Measured changes in adiposity were correlated with the true changes, with no bias as indicated by the Bland & Altman procedure. CONCLUSION: APD detects approximately 2 kg changes in fat or fat-free mass in small populations.     

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.     

Relative influences of sex, race, environment, and HIV infection on body composition in adults

BACKGROUND: The factors that control body composition in disease are uncertain. OBJECTIVE: We planned to compare the relative influences of HIV infection, sex, race, and environment on body composition. METHODS: We analyzed results of body composition studies performed by bioelectrical impedance analysis in 1415 adults from 2 cohorts: white and African American men and women from the United States, and African men and women (279 HIV-infected and 1136 control). The effects of sex and HIV infection on weight, body cell mass, and fat-free mass were analyzed by using both unadjusted and age-, weight-, and height-adjusted data. RESULTS: Control men weighed more and had more body cell mass and fat-free mass than did control women, although control women had more fat. The strongest correlates with body composition were height and weight, followed by sex. HIV infection, age, environment, and race. Control men and women weighed more and had more body cell mass, fat-free mass, and fat than did HIV-infected men. However, differences in body composition between HIV-infected and control groups were strongly influenced by sex. Of the differences in weight between HIV-infected and uninfected subjects, fat-free mass accounted for 51% in men but only 18% in women, in whom the remainder was fat. Sex effects were similar in African and American groups. CONCLUSIONS: Sex has a marked effect on the changes in body composition during HIV infection, with women losing disproportionately more fat than men. Sex-related differences in body composition were narrower in the HIV-infected groups. Race and environment had smaller effects than sex and HIV infection.     

Assessment of resting energy expenditure in mechanically ventilated patients

BACKGROUND: Usual equations for predicting resting energy expenditure (REE) are not appropriate for critically ill patients, and indirect calorimetry criteria render its routine use difficult. OBJECTIVE: Variables that might influence the REE of mechanically ventilated patients were evaluated to establish a predictive relation between these variables and REE. DESIGN: The REE of 70 metabolically stable, mechanically ventilated patients was prospectively measured by indirect calorimetry and calculated with the use of standard predictive models (Harris and Benedict's equations corrected for hypermetabolism factors). Patient data that might influence REE were assessed, and multivariate analysis was conducted to determine the relations between measured REE and these data. Measured and calculated REE were compared by using the Bland-Altman method. RESULTS: Multivariate analysis retained 4 independent variables defining REE: body weight (r(2) = 0.14, P < 0.0001), height (r(2) = 0.11, P = 0.0002), minute ventilation (r(2) = 0.04, P = 0.01), and body temperature (r(2) = 0.07, P = 0.002): REE (kcal/d) = 8 x body weight + 14 x height + 32 x minute ventilation + 94 x body temperature - 4834. REE calculated with this equation was well correlated with measured REE (r(2) = 0.61, P < 0.0001). Bland-Altman plots showed a mean bias approaching zero, and the limits of agreement between measured and predicted REE were clinically acceptable. CONCLUSION: Our results suggest that REE estimated on the basis of body weight, height, minute ventilation, and body temperature is clinically more relevant than are the usual predictive equations for metabolically stable, mechanically ventilated patients.     

Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y

BACKGROUND: Individual energy requirements of overweight and obese adults can often not be measured by indirect calorimetry. OBJECTIVE: The objective was to analyze which resting energy expenditure (REE) predictive equation was the best alternative to indirect calorimetry in US and Dutch adults aged 18-65 y with a body mass index (in kg/m(2)) of 25 to 40. DESIGN: Predictive equations based on weight, height, sex, age, fat-free mass, and fat mass were tested. REE in Dutch adults was measured with indirect calorimetry, and published data from the Institute of Medicine were used for US adults. The accuracy of the equations was evaluated on the basis of the percentage of subjects predicted within 10% of the REE measured, the root mean squared prediction error (RMSE), and the mean percentage difference (bias) between predicted and measured REE. RESULTS: Twenty-seven predictive equations (9 of which were based on FFM) were included. Validation was based on 180 women and 158 men from the United States and on 154 women and 54 men from the Netherlands aged <65 y with a body mass index (in kg/m(2)) of 25 to 40. Most accurate and precise for the US adults was the Mifflin equation (prediction accuracy: 79%; bias: -1.0%; RMSE: 136 kcal/d), for overweight Dutch adults was the FAO/WHO/UNU weight equation (prediction accuracy: 68%; bias: -2.5%; RMSE: 178), and for obese Dutch adults was the Lazzer equation (prediction accuracy: 69%; bias: -3.0%; RMSE: 215 kcal/d). CONCLUSIONS: For US adults aged 18-65 y with a body mass index of 25 to 40, the REE can best be estimated with the Mifflin equation. For overweight and obese Dutch adults, there appears to be no accurate equation.