Article
Resting energy expenditure in children and adolescents: agreement between calorimetry and prediction equations.
Departamento de Pediatría, Facultad de Medicina, Universidad de Zaragoza, Zaragoza, Spain.
Clinical Nutrition (impact factor:
3.73).
07/2002;
21(3):255-60.
pp.255-60
Source: PubMed
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Citations (0)
- Cited In (4)
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Article: Validation of predictive equations for resting energy expenditure in obese adolescents.
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ABSTRACT: When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation. The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents. Predictive equations based on weight, height, sex, age, fat-free mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE). Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (+/-SD) body mass index SD score of 2.93 +/- 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: -1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10-18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d). Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12-18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398.American Journal of Clinical Nutrition 03/2010; 91(5):1244-54. · 6.67 Impact Factor -
Article: [Validation of the equations that estimate the resting metabolic rate in adolescent girls].
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ABSTRACT: The objective of the study is to analyze the validity of the prediction equations for the resting metabolic rate (RMR) proposed by Harris and Benedicti (1919), Schofield (1985), WHO/FAO/ UNU (1985), Henry and Rees (1991), Molnár and cols. (1995), Tverskaya and cols. (1998) and Müller and cols. (2004) in adolescent girls (51 girls between 10 and 17 years of age). The following anthropometric variables were measured: body weight, stature, body fat mass (absolute and percentage), body lean mass (absolute and percentage) as well as the consumption ofVO2 and production ofVCO2 that were substituted in Weir's (1949) equation which was considered the RMR standard method in this study. The following statistical procedures were carried out: paired t-test (p < 0.05); constant error (CE) with a less than 5% difference and Bland and Altman's (1986) graphical analysis. The equations proposed by Tverskaya and cols. (1998) and Müller and cols. (2004) were the only equations that presented significant differences between the averages. However, only the equations proposed by Henry and Rees (1991) and Molnár and cols. (1995) produced a constant error of less than 5%. However, Bland and Altman's (1986) graphical analysis showed that independently of the equation there is no agreement between the equations and the standard method. The study indicates that none of the equations meet all the stipulated criteria and that thus have no validity in the calculation of the RMR.Arquivos brasileiros de endocrinologia e metabologia 02/2010; 54(1):30-6. · 0.68 Impact Factor -
Article: Variable dietary management of methylmalonic acidemia: metabolic and energetic correlations.
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ABSTRACT: Isolated methylmalonic acidemia (MMA) is managed by dietary protein restriction and medical food supplementation. Resting energy expenditure (REE) can be depressed in affected individuals for undefined reasons. The objective was to document the spectrum of nutritional approaches used to treat patients with MMA, measure REE, and analyze the dependence of REE on body composition, biochemical, and nutritional variables. Twenty-nine patients with isolated MMA (22 mut, 5 cblA, 2 cblB; 15 males, 14 females; age range: 2-35 y) underwent evaluation. REE was measured with open-circuit calorimetry and compared with predicted values by using age-appropriate equations. Nutritional regimens were as follows: protein restriction with medical food (n = 17 of 29), protein restriction with medical food and supplemental isoleucine or valine (n = 5 of 29), or the use of natural protein alone for dietary needs (n = 7 of 29). Most mut patients had short stature and higher percentage fat mass compared with reference controls. Measured REE decreased to 74 ± 13.6% of predicted (P < 0.001) in the ≤ 18-y group (n = 22) and to 83 ± 11.1% (P = 0.004) in patients aged >18 y (n = 7). Linear regression modeling suggested that age (P = 0.001), creatinine clearance (P = 0.01), and height z score (P = 0.04) accounted for part of the variance of measured REE per kilogram of fat-free mass (model R² = 0.66, P < 0.0001). There is wide variation in the dietary treatment of MMA. Standard predictive equations overestimate REE in this population primarily due to their altered body composition and decreased renal function. Defining actual energy needs will help optimize nutrition and protect individuals from overfeeding. This trial is registered at clinicaltrials.gov as NCT00078078.American Journal of Clinical Nutrition 11/2010; 93(1):47-56. · 6.67 Impact Factor
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Keywords
95% confidence interval
accurate prediction equations
agreement -293
Agriculture/World Health Organization/United Nations University
calorimetry
calorimetry results
entire cohort group
FAO/WHO/UNU equation
indirect calorimetry
mixed population
MREE-PREE difference
non-statistic differences
open-circuit indirect calorimetry
PREE
REE studies
resting energy expenditure
Schofield-HW equation
Schofield-HW equations
Schofield-W
Schofield-W equation