912 resultados para Calorimetry, indirect


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The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

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To evaluate the validity of the ActiGraph accelerometer for the measurement of physical activity intensity in children and adolescents with cerebral palsy (CP) using oxygen uptake (VO 2) as the criterion measure. Thirty children and adolescents with CP (mean age 12.6 ± 2.0 years) wore an ActiGraph 7164 and a Cosmed K4b 2 portable indirect calorimeter during four activities; quiet sitting, comfortable paced walking, brisk paced walking and fast paced walking. VO 2 was converted to METs and activity energy expenditure and classiWed as sedentary, light or moderate-to-vigorous intensity according to the conventions for children. Mean ActiGraph counts min -1 were classiWed as sedentary, light or moderate-to-vigorous (MVPA) intensity using four diVerent sets of cut-points. VO 2 and counts min¡1 increased signiWcantly with increases in walking speed (P < 0.001). Receiver operating characteristic (ROC) curve analysis indicated that, of the four sets of cut-points evaluated, the Evenson et al. (J Sports Sci 26(14):1557-1565, 2008) cut-points had the highest classiWcation accuracy for sedentary (92%) and MVPA (91%), as well as the second highest classiWcation accuracy for light intensity physical activity (67%). A ROC curve analysis of data from our participants yielded a CP-speciWc cut-point for MVPA that was lower than the Evenson cut-point (2,012 vs. 2,296 counts min¡1), however, the diVerence in classiWcation accuracy was not statistically signiWcant 94% (95% CI = 88.2-97.7%) vs. 91% (95% CI = 83.5-96.5%). In conclusion, among children and adolescents with CP, the ActiGraph is able to diVerentiate between diVerent intensities of walking. The use of the Evenson cut-points will permit the estimation of time spent in MVPA and allows comparisons to be made between activity measured in typically developing adolescents and adolescents with CP. © 2011 Springer-Verlag.

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Background: Paediatric onset inflammatory bowel disease (IBD) may cause alterations in energy requirements and invalidate the use of standard prediction equations. Our aim was to evaluate four commonly used prediction equations for resting energy expenditure (REE) in children with IBD. Methods: Sixty-three children had repeated measurements of REE as part of a longitudinal research study yielding a total of 243 measurements. These were compared with predicted REE from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict equations using the Bland-Altman method. Results: Mean (±SD) age of the patients was 14.2 (2.4) years. Mean measured REE was 1566 (336) kcal per day compared with 1491 (236), 1441 (255), 1481 (232), and 1435 (212) kcal per day calculated from Schofield, Oxford, FAO/WHO/UNU, and Harris-Benedict, respectively. While the Schofield equation demonstrated the least difference between measured and predicted REE, it, along with the other equations tested, did not perform uniformly across all subjects, indicating greater errors at either end of the spectrum of energy expenditure. Smaller differences were found for all prediction equations for Crohn's disease compared with ulcerative colitis. Conclusions: Of the commonly used equations, the equation of Schofield should be used in pediatric patients with IBD when measured values are not able to be obtained. (Inflamm Bowel Dis 2010;) Copyright © 2010 Crohn's & Colitis Foundation of America, Inc.

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Background: Better understanding of body composition and energy metabolism in pediatric liver disease may provide a scientific basis for improved medical therapy aimed at achieving optimal nutrition, slowing progression to end-stage liver disease (ESLD), and improving the outcome of liver transplantation. Methods: Twenty-one children less than 2 years of age with ESLD awaiting liver transplantation and 15 healthy, aged-matched controls had body compartment analysis using a four compartment model (body cell mass, fat mass, extracellular water, and extracellular solids). Subjects also had measurements of resting energy expenditure (REE) and respiratory quotient (RQ) by indirect calorimetry. Nine patients and 15 control subjects also had measurements of total energy expenditure (TEE) using doubly labelled water. Results: Mean weights and heights were similar in the two groups. Compared with control subjects, children with ESLD had higher relative mean body cell mass (33 ± 2% vs 29 ± 1% of body weight, P < 0.05), but had similar fat mass, extracellular water, and extracellular solid compartments (18% vs 20%, 41% vs 38%, and 7% vs 13% of body weight respectively). Compared with control subjects, children with ESLD had 27% higher mean REE/body weight (0.285 ± 0.013 vs 0.218. ± 0.013 mJ/kg/24h, P < 0.001), 16% higher REE/unit cell mass (P < 0.05); and lower mean RQ (P < 0.05). Mean TEE of patients was 4.70 ± 0.49 mJ/24h vs 3.19 ± 0.76 in controls, (P < 0.01). Conclusions: In children, ESLD is a hypermetabolic state adversely affecting the relationship between metabolic and non-metabolic body compartments. There is increased metabolic activity within the body cell mass with excess lipid oxidation during fasting and at rest. These findings have implications for the design of appropriate nutritional therapy.

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Objective: To compare measurements of sleeping metabolic rate (SMR) in infancy with predicted basal metabolic rate (BMR) estimated by the equations of Schofield. Methods: Some 104 serial measurements of SMR by indirect calorimetry were performed in 43 healthy infants at 1.5, 3, 6, 9 and 12 months of age. Predicted BMR was calculated using the weight only (BMR-wo) and weight and height (BMR-wh) equations of Schofield for 0-3-y-olds. Measured SMR values were compared with both predictive values by means of the Bland-Altman statistical test. Results: The mean measured SMR was 1.48 MJ/day. The mean predicted BMR values were 1.66 and 1.47 MJ/day for the weight only and weight and height equations, respectively. The Bland-Altman analysis showed that BMR-wo equation on average overestimated SMR by 0.18 MJ/day (11%) and the BMR-wh equation underestimated SMR by 0.01 MJ/day (1%). However the 95% limits of agreement were wide: -0.64 to + 0.28 MJ/day (28%) for the former equation and -0.39 to + 0.41 MJ/day (27%) for the latter equation. Moreover there was a significant correlation between the mean of the measured and predicted metabolic rate and the difference between them. Conclusions: The wide variation seen in the difference between measured and predicted metabolic rate and the bias probably with age indicates there is a need to measure actual metabolic rate for individual clinical care in this age group.

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Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.

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PURPOSE: The purpose of this study was to develop a mathematical model (sine model, SIN) to describe fat oxidation kinetics as a function of the relative exercise intensity [% of maximal oxygen uptake (%VO2max)] during graded exercise and to determine the exercise intensity (Fatmax) that elicits maximal fat oxidation (MFO) and the intensity at which the fat oxidation becomes negligible (Fatmin). This model included three independent variables (dilatation, symmetry, and translation) that incorporated primary expected modulations of the curve because of training level or body composition. METHODS: Thirty-two healthy volunteers (17 women and 15 men) performed a graded exercise test on a cycle ergometer, with 3-min stages and 20-W increments. Substrate oxidation rates were determined using indirect calorimetry. SIN was compared with measured values (MV) and with other methods currently used [i.e., the RER method (MRER) and third polynomial curves (P3)]. RESULTS: There was no significant difference in the fitting accuracy between SIN and P3 (P = 0.157), whereas MRER was less precise than SIN (P < 0.001). Fatmax (44 +/- 10% VO2max) and MFO (0.37 +/- 0.16 g x min(-1)) determined using SIN were significantly correlated with MV, P3, and MRER (P < 0.001). The variable of dilatation was correlated with Fatmax, Fatmin, and MFO (r = 0.79, r = 0.67, and r = 0.60, respectively, P < 0.001). CONCLUSIONS: The SIN model presents the same precision as other methods currently used in the determination of Fatmax and MFO but in addition allows calculation of Fatmin. Moreover, the three independent variables are directly related to the main expected modulations of the fat oxidation curve. SIN, therefore, seems to be an appropriate tool in analyzing fat oxidation kinetics obtained during graded exercise.

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The aim of this study was to determine whether breath 13CO2 measurements could be used to assess the compliance to a diet containing carbohydrates naturally enriched in 13C. The study was divided into two periods: Period 1 (baseline of 4 days) with low 13C/12C ratio carbohydrates. Period 2 (5 days) isocaloric diet with a high 13C/12C ratio (corn, cane sugar, pineapple, millet) carbohydrates. Measurements were made of respiratory gas exchange by indirect calorimetry, urinary nitrogen excretion and breath 13CO2 every morning in post-absorptive conditions, both in resting state and during a 45-min low intensity exercise (walking on a treadmill). The subjects were 10 healthy lean women (BMI 20.4 +/- 1.7 kg/m2, % body fat 24.4 +/- 1.3%), the 13C enrichment of oxidized carbohydrate and breath 13CO2 were compared to the enrichment of exogenous dietary carbohydrates. At rest the enrichment of oxidized carbohydrate increased significantly after one day of 13C carbohydrate enriched diet and reached a steady value (103 +/- 16%) similar to the enrichment of exogenous carbohydrates. During exercise, the 13C enrichment of oxidized carbohydrate remained significantly lower (68 +/- 17%) than that of dietary carbohydrates. The compliance to a diet with a high content of carbohydrates naturally enriched in 13C may be assessed from the measurement of breath 13CO2 enrichment combined with respiratory gas exchange in resting, postabsorptive conditions.

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To test the dose response effect of infused fish oil (FO) rich in n-3 PUFAs on the inflammatory response to endotoxin (LPS) and on membrane incorporation of fatty acids in healthy subjects. Prospective, sequential investigation comparing three different FO doses. Three groups of male subjects aged 26.8 +/- 3.2 years (BMI 22.5 +/- 2.1). One of three FO doses (Omegaven10%) as a slow infusion before LPS: 0.5 g/kg 1 day before LPS, 0.2 g/kg 1 day before, or 0.2 g/kg 2 h before. Temperature, hemodynamic variables, indirect calorimetry and blood samples (TNF-alpha, stress hormones) were collected. After LPS temperature, ACTH and TNF-alpha concentrations increased in the three groups: the responses were significantly blunted (p < 0.0001) compared with the control group of the Pluess et al. trial. Cortisol was unchanged. Lowest plasma ACTH, TNF-alpha and temperature AUC values were observed after a single 0.2 g/kg dose of FO. EPA incorporation into platelet membranes was dose-dependent. Having previously shown that the response to LPS was reproducible, this study shows that three FO doses blunted it to various degrees. The 0.2 g/kg perfusion immediately before LPS was the most efficient in blunting the responses, suggesting LPS capture in addition to the systemic and membrane effects.

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Obesity is fundamentally a problem of energy balance that develops when the energy intake is greater than the total energy expenditure (TEE). TEE is composed by the sum of resting energy expenditure (REE), thermal effect of foods and thermal effect of physical activity. Many factors can affect energy expenditure and energy homeostasis. Historically, the energy expenditure has been measured by indirect calorimetry. However, more recently, the use of doubly labeled water has allowed the assessment of energy expenditure in a 24 hour period, which expanded the knowledge on energy metabolism. Factors such as gender, age, thyroid disorders, physical activity and body composition affect REE as already established in the literature. However, there has been speculation whether other factors, such as adipocytokines and diet composition, which might be involved in the genesis of obesity by decreasing the REE. So, this paper aims to review the factors that can alter the energy metabolism.

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Background & aims: Little is known about energy requirements in brain injured (TBI) patients, despite evidence suggesting adequate nutritional support can improve clinical outcomes. The study aim was to compare predicted energy requirements with measured resting energy expenditure (REE) values, in patients recovering from TBI.

Methods: Indirect calorimetry (IC) was used to measure REE in 45 patients with TBI. Predicted energy requirements were determined using FAO/WHO/UNU and Harris–Benedict (HB) equations. Bland– Altman and regression analysis were used for analysis.

Results: One-hundred and sixty-seven successful measurements were recorded in patients with TBI. At an individual level, both equations predicted REE poorly. The mean of the differences of standardised areas of measured REE and FAO/WHO/UNU was near zero (9 kcal) but the variation in both directions was substantial (range 591 to þ573 kcal). Similarly, the differences of areas of measured REE and HB demonstrated a mean of 1.9 kcal and range 568 to þ571 kcal. Glasgow coma score, patient status, weight and body temperature were signi?cant predictors of measured REE (p < 0.001; R2= 0.47).

Conclusions: Clinical equations are poor predictors of measured REE in patients with TBI. The variability in REE is substantial. Clinicians should be aware of the limitations of prediction equations when estimating energy requirements in TBI patients.

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Objective: This study aimed to determine the energy expenditure (EE) in terms of caloric cost and metabolic equivalents (METs) of two sessions of an exercise protocol. Methods: Fifteen subjects (51.0 ± 5.5years) performed the exercise sessions (80min), which were composed by (warming, walking and flexibility exercises; Session A) and (warming, walking and local muscular endurance exercises; Session B). Heart hate (HR) was measured during each part of the sessions. In laboratory environment, maximal oxygen consumption (VO2max) and oxygen uptake in rest and exercise conditions (using mean HR obtained in classes) were measured on different days, using indirect calorimetry. Exercise METs were obtained by dividing VO2 in exercise (mL.kg-1.min-1) by VO2 in rest (mL.kg-1.min-1). The EE of the exercises was calculated by the formula: MET x Weight(kg) x Time(min)/60. The results were analyzed by ANOVA with Tuckey post hoc test (p < 0.05). Results: One MET for this group was 2.7 ± 0.1mL.kg-1.min-1. The mean METs of exercises were 4,7 ± 0,8 (warming), 5,8 ± 0,9 (walking) and 3,6 ± 0,7 (flexibility) on session A, and 4,6 ± 1,2 (warming), 5,6 ± 1,0 (walking) and 4.8 ± 1,0 (local muscular endurance exercises) on Session B. The training sessions showed similar energy cost (A: 398 ± 86.72 kcal and B: 404 ± 38.85 kcal; p > 0,05). None of activities were classified into vigorous intensity (> 7 METs). There were no differences on VO2 between walking (15,6 ± 2,8 or 15,4 ± 2,6 mL.kg-1.min-1) and local muscular endurance exercises (13,2 ± 2,9 mL.kg-1.min-1), although both were higher (p > 0.05) than flexibility exercises (10.1 ± 2.2 mL.kg-1.min-1). Conclusion: The proposed protocol achieves the physical activity needed by healthy adults to improve and maintain health, by their structure, moderate intensity, duration, frequency and caloric expenditure.