[Correlation of equations for energy expenditure with indirect calorimetry in critically ill patients]. / Correlación de fórmulas para gasto energético con calorimetría indirecta en pacientes críticos.

Background: Nutrition in the Intensive Care Unit (ICU) is a cornerstone; however, energy requirements are a controversial issue that has not yet been resolved. Calorimetry is the gold standard for calculating energy expenditure, but it is expensive and not available in all ICU areas. Formulas have been developed to calculate basal energy expenditure (BAE) and make the process easier. Objective: To validate the predictive formulas of BAE compared to that obtained with ventilatory indirect calorimetry (IC) within the nutritional assessment in ICU patients. Material and methods: Analytical cross-sectional retrolective study. We performed BAE measurement on patients in the ICU of a third level hospital with ventilatory indirect calorimetry and compared the results obtained with those of the Harris Benedict, Muffin-St. Jeor, Institute of Medicine, and Faisy equations. Results: A total of 49 patients were included; a moderate correlation with statistical significance was found between the BAE measurements obtained by indirect calorimetry, with those obtained by four predictive equations that were studied. The Faisy equation obtained the strongest correction with r = 0.461 (p = 0.001). Conclusion: The correlation between the BAE obtained by predictive equations and by IC goes from mild to moderate, due to the heterogeneity of critical patients and their changing nature throughout their disease.

Introducción: la nutrición en la unidad de cuidados intensivos (UCI) es una piedra angular; sin embargo, los requerimientos energéticos son un tema controversial aún no resuelto. La calorimetría es el estándar de oro para calcular el gasto energético, pero es costosa y no está disponible en todas las áreas de las UCI. Se han desarrollado fórmulas para calcular el gasto energético basal (GEB) y hacer el proceso más sencillo. Objetivo: validar las fórmulas predictivas de GEB comparado con el obtenido con calorimetría indirecta (CI) ventilatoria dentro de la valoración nutricia en los pacientes de UCI. Material y métodos: estudio transversal analítico retrolectivo. Realizamos medición de GEB a los pacientes de la UCI de un hospital de tercer nivel con calorimetría indirecta ventilatoria y se compararon los resultados obtenidos con los de las fórmulas de Harris Benedict, Muffin-St. Jeor, Institute of Medicine y Faisy. Resultados: se incluyeron un total de 49 pacientes; se encontró correlación moderada con significación estadística entre las medidas de GEB obtenidas por calorimetría indirecta, con las obtenidas por cuatro fórmulas predictivas que se estudiaron. La fórmula de Faisy obtuvo la corrección más fuerte con una r = 0.461 (p = 0.001). Conclusión: la correlación entre el GEB obtenido por fórmulas predictivas y por CI es de ligera a moderada, debido a la heterogeneidad del paciente crítico y su naturaleza cambiante a lo largo de su enfermedad.

Accuracy of equations for estimating resting energy expenditure in children and adolescents living with phenylketonuria.

BACKGROUND: Measuring resting energy expenditure (REE) in individuals living with phenylketonuria (PKU) using indirect calorimetry (IC) is unusual in healthcare facilities because it requires specific protocols and expensive equipment. Considering that determining REE is crucial for devising nutritional strategies for the management of PKU, the aim of this study was to identify the predictive equations that provide the best estimates of REE in children and adolescents living with PKU and to propose a predictive equation for determining REE in this population. METHODS: An REE concordance study was conducted with children and adolescents living with PKU. Anthropometric and body composition assessments using bioimpedance and REE assessment using IC were performed. The results were compared to 29 predictive equations. RESULTS: Fifty-four children and adolescents were evaluated. The REE obtained using IC differed from all estimated REE, except Henry's equation for male children (p = 0.058). Only this equation showed good agreement (0.900) with IC. Eight variables were associated with the REE obtained using IC with emphasis on fat-free mass (kg) (r = 0.786), weight (r = 0.775), height (r = 0.759) and blood phenylalanine (r = 0.503). With these variables, three REE equations were suggested, with R2 = 0.660, 0.635 and 0.618, respectively, and the third equation, which involves weight and height, showed adequate sample size for a statistical power of 0.942. CONCLUSION: Most equations, not specific for individuals living with PKU, overestimate the REE of this population. We propose a predictive equation for assessing REE for children and adolescents living with PKU to be used in settings where IC is not available.

Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women.

Resting metabolic rate (RMR) depends on body fat-free mass (FFM) and fat mass (FM), whereas abdominal fat distribution is an aspect that has yet to be adequately studied. The objective of the present study was to analyze the influence of waist circumference (WC) in predicting RMR and propose a specific estimation equation for older Chilean women. This is an analytical cross-sectional study with a sample of 45 women between the ages of 60 and 85 years. Weight, height, body mass index (BMI), and WC were evaluated. RMR was measured by indirect calorimetry (IC) and %FM using the Siri equation. Adequacy (90% to 110%), overestimation (>110%), and underestimation (<90%) of the FAO/WHO/UNU, Harris−Benedict, Mifflin-St Jeor, and Carrasco equations, as well as those of the proposed equation, were evaluated in relation to RMR as measured by IC. Normal distribution was determined according to the Shapiro−Wilk test. The relationship of body composition and WC with RMR IC was analyzed by multiple linear regression analysis. The RMR IC was 1083.6 ± 171.9 kcal/day, which was significantly and positively correlated with FFM, body weight, WC, and FM and inversely correlated with age (p < 0.001). Among the investigated equations, our proposed equation showed the best adequacy and lowest overestimation. The predictive formulae that consider WC improve RMR prediction, thus preventing overestimation in older women.

New Predictive Resting Metabolic Rate Equations for High-Level Athletes: A Cross-Validation Study.

PURPOSE: The present study aims a) to assess the agreement between the measured resting metabolic rate (RMR) using indirect calorimetry and different predictive equations (predicted RMR), and b) to propose and cross-validate two new predictive equations for estimating the RMR in high-level athletes. METHODS: The RMR of 102 athletes (44 women) was assessed using indirect calorimetry, whereas the body composition was assessed using skinfolds. Comparisons between measured and predicted RMR values were performed using one-way ANOVA. Mean difference, root mean square error (RMSE), simple linear regression, and Bland-Altman plots were used to evaluate the agreement between measured and predicted RMR. The accuracy of predictive equations was analyzed using narrower and wider accuracy limits (±5% and ±10%, respectively) of measured RMR. Multiple linear regression models were employed to develop the new predictive equations based on traditional predictors (equation 1) and the stepwise method (equation 2). RESULTS: The new equations 1 and 2 presented good agreement based on the mean difference (3 and -15 kcal·d -1 ), RMSE (200 and 192 kcal·d -1 ), and R2 (0.71 and 0.74), respectively, and accuracy (61% of subjects between the limit of ±10% of measured RMR). Cunningham's equation provided the best performance for males and females among the existing equations, whereas Jagim's equation showed the worst performance for males (mean difference = -335 kcal·d -1 ; RMSE = 386 kcal·d -1 ). Compared with measured RMR, most predictive equations showed heteroscedastic distribution (linear regression's intercept and slope significantly different from zero; P ≤ 0.05), mainly in males. CONCLUSIONS: The new proposed equations can estimate the RMR in high-level athletes accurately. Cunningham's equation is a good option from existing equations, and Jagim's equation should not be used in high-level male athletes.

Predictive equations for resting metabolic rate are not appropriate to use in Brazilian male adolescent football athletes.

High accuracy in estimating energy expenditure is essential for enhancing sports performance. The resting metabolic rate (RMR), as a primary component of total energy expenditure (TEE), is commonly estimated using predictive equations. However, these references may not be applicable to adolescent athletes. The purpose of this cross-sectional study was to analyse the differences between predicted RMR in relation to energy expenditure measured by indirect calorimetry (IC) among 45 Brazilian male adolescent football athletes. Indirect calorimetry (IC) and anthropometric (bioimpedance) measurements were recorded at a single visit to the laboratory after fasting overnight. The mean age was 15.6 ± 1.14 years, body mass was 63.05 ± 7.8 kg, and height was 172 ± 7.5 cm. The RMR values predicted by equations proposed by the Food and Agriculture Organization (FAO) (United Nations), Henry and Rees (HR), Harris Benedict (HB), and Cunningham (CUN) were compared with IC RMR values, by correlation analysis. The FAO and HR predictive equations yielded different values from IC (IC: 1716.26 ± 202.58, HR: 1864.87 ± 147.78, FAO: 1854.28 ± 130.19, p = 0.001). A moderate correlation of 0.504 was found between the results of HB and IC. In the survival-agreement model, the CUN equation showed low disagreement with the IC RMR, with error values between 200 and 300 kcal/day. The results showed that HB and CUN yielded similar values as IC, with the CUN equation showing low disagreement with IC; hence, adolescent athletes should undergo evaluation with precise laboratory methods to ensure that accurate information about RMR is recorded.

Energy expenditure, growth, and nutritional therapy in appropriate and small for gestational age preterm infants / Gasto energético, crescimento e terapia nutricional em recém-nascidos pré-termo adequados e pequenos para idade gestacional

Abstract Objective: To evaluate the resting energy expenditure, growth, and quantity of energy and macronutrients intake in a group of preterm newborns. Methods: The cohort study was performed with appropriate and small for gestational age preterm infants (birth weight lower than 1500 g or gestational age < 32 weeks). Resting energy expenditure was measured using indirect calorimetry on the 7th, 14th, 21st, and 28th days of life, and at discharge. Length, head circumference and body weight were assessed weekly. Nutritional therapy was calculated during the hospital stay and the information for each type of food was recorded in software that calculates the total amount of energy and macronutrients. Results: 61 preterm infants were followed; 43 appropriate and 18 small for gestational age infants. There was no statistical difference for resting energy expenditure between the groups, and it increased from the first to the fourth week of life (appropriate: 26.3% and small: 21.8%). Energy intake in the first two weeks of life was well below the energy requirement. Conclusion: Considering that the results demonstrate high energy expenditure during the first weeks of life, there is an evident need to provide the best quality of nutrition for each child in the first weeks of life so that preterm infants with or without intrauterine growth restriction can achieve their maximum potential for growth and development.

Resumo Objetivo: Avaliar o gasto energético de repouso, o crescimento e a quantidade ofertada de energia e macronutrientes em um grupo de recém-nascidos pré-termo. Método: Foi feito estudo de coorte com recém-nascidos pré-termo adequados e pequenos para a idade gestacional (peso de nascimento inferior a 1.500 gramas ou idade gestacional < 32 semanas). O gasto energético foi avaliado com a calorimetria indireta nos dias 7°, 14°, 21°, 28° dias de vida e alta hospitalar. Medidas do comprimento, perímetro cefálico e peso corporal foram avaliadas semanalmente. A terapia nutricional foi calculada durante a internação do recém-nascido e as informações de cada tipo de alimentação foram registradas em um software que calcula a quantidade total de energia e macronutrientes. Resultados: Foram acompanhados 61 recém-nascidos, sendo 43 adequados e 18 pequenos para idade gestacional. O gasto energético de repouso não apresentou diferença estatística entre os grupos e aumentou entre a primeira e quarta semana de vida (adequados: 26,3% e pequenos: 21,8%). O aporte energético nas duas primeiras semanas de vida mostrou-se bem abaixo do requerimento energético mensurado pela calorimetria. Conclusão: Considerando os resultados que demonstram um gasto energético alto ao longo das primeiras semanas de vida, fica evidente a necessidade de fornecer ao recém-nascido pré-termo um melhor aporte energético já nas primeiras semanas de vida, para que os neonatos com ou sem restrição intrauterina possam atingir o seu potencial máximo de crescimento e desenvolvimento.

Accurate determination of energy requirements in hospitalised patients with parenteral nutrition.

BACKGROUND: The prescription of parenteral nutrition (PN) in hospitalised patients requires an estimation of the energy requirements. Most studies employing prediction equations (PEs) to estimate energy requirements have focused on critically ill patients. The present study aimed to evaluate several PEs of the resting energy expenditure (REE) to identify the most accurate equation for estimating the REE required for PN. METHODS: This cross-sectional and descriptive study included patients hospitalised with medical or surgical diagnoses, making them candidates for PN. Epidemiological data, the reason for hospital admission, nutritional screening results, characteristics of the PN administered and REE by indirect calorimetry (IC) were recorded and, subsequently, PEs were calculated. RESULTS: In total, 116 patients were recruited with a mean (SD) age of 56.7 (13.8) years and body mass index of 21.3 (4.25) kg m-2 . The diagnosis was medical in 52% of patients and surgical in 48%. The mean (SD) REEs of patients, according to IC, were: 6.11 (1.18) MJ [1461 (281) kcal]; and according to PEs: Mifflin, 5.07 (1.05) MJ [1212 (252) kcal]; Owen, 5.43 (0.72) MJ [1298 (172) kcal]; Harris-Benedict, 5.38 (0.85) MJ [1285 (204) kcal]; Ireton-Jones, 6.20 (1.69) MJ [1481 (403) kcal]; and short equation, 6.12 (0.92) MJ [1464 (220) kcal]. A comparison of the results obtained for the REE by IC and with PEs indicated that the short equation had less bias than the other equations, with an accuracy of 54% CONCLUSIONS: In hospitalised patients who receive PN, determination of the REE should ideally be made by IC. PEs are acceptable but not exact and so their estimation could overfeed or underfeed the patient.

Energy expenditure, growth, and nutritional therapy in appropriate and small for gestational age preterm infants.

OBJECTIVE: To evaluate the resting energy expenditure, growth, and quantity of energy and macronutrients intake in a group of preterm newborns. METHODS: The cohort study was performed with appropriate and small for gestational age preterm infants (birth weight lower than 1500g or gestational age<32 weeks). Resting energy expenditure was measured using indirect calorimetry on the 7th, 14th, 21st, and 28th days of life, and at discharge. Length, head circumference and body weight were assessed weekly. Nutritional therapy was calculated during the hospital stay and the information for each type of food was recorded in software that calculates the total amount of energy and macronutrients. RESULTS: 61 preterm infants were followed; 43 appropriate and 18 small for gestational age infants. There was no statistical difference for resting energy expenditure between the groups, and it increased from the first to the fourth week of life (appropriate: 26.3% and small: 21.8%). Energy intake in the first two weeks of life was well below the energy requirement. CONCLUSION: Considering that the results demonstrate high energy expenditure during the first weeks of life, there is an evident need to provide the best quality of nutrition for each child in the first weeks of life so that preterm infants with or without intrauterine growth restriction can achieve their maximum potential for growth and development.

Difference between Methods for Estimation of Basal Metabolic Rate and Body Composition in Pediatric Patients with Osteogenesis Imperfecta.

BACKGROUND/AIMS: Osteogenesis Imperfecta (OI) is a bone disease characterized by bone fragility, deformities, and multiple fractures. The aim of this study was to compare the different methods of measuring the basal metabolic rate (BMR) and body composition (BC) in pediatric patients with OI. METHODS: This cross-sectional study included 52 individuals with a median age of 9 (5.25-12.7) years. BMR was calculated by bioelectrical impedance analyses (BIA), predictive values according to age from the World Health Organization (WHO), a kcal/cm formula, and indirect calorimetry (IC). BC was assessed using the anthropometric calculation of percentage body fat (%BF) and lean mass (kg), BIA, and dual-energy X-ray absorptiometry (DEXA). Agreement among the methods was assessed using the Bland-Altman technique. RESULTS: IC estimates of BMR were greater than BIA and lower than values obtained using the WHO and kcal/cm methods. Better agreement was observed using the WHO values for mild forms of OI and the kcal/cm formula for moderate-to-severe forms. For BC, DEXA estimates of %BF were higher and the lean mass was lower than the values obtained using BIA and anthropometry. Neither method agreed with the DEXA method results. CONCLUSIONS: Significant differences exist among the various methods used for measuring BMR and BC with regard to phenotypic differences between OI types.

Influence of a Gas Exchange Correction Procedure on Resting Metabolic Rate and Respiratory Quotient in Humans.

OBJECTIVE: The aim of this study was to determine the influence of a gas exchange correction protocol on resting metabolic rate (RMR) and respiratory quotient (RQ), assessed by a Vmax Encore 29n metabolic cart (SensorMedics Co., Yorba Linda, California) in overnight fasted and fed humans, and to assess the predictive power of body size for corrected and uncorrected RMR. METHODS: Healthy participants (23 M/29 F; 34 ± 9 years old; 26.3 ± 3.7 kg/m2 ) ingested two 3-hour-apart glucose loads (75 g). Indirect calorimetry was conducted before and hourly over a 6-hour period. Immediately after indirect calorimetry assessment, gas exchange was simulated through high-precision mass-flow regulators, which permitted the correction of RMR and RQ values. RESULTS: Uncorrected and corrected RMR and RQ were directly related at each time over the 6-hour period. However, uncorrected versus corrected RMR was 6.9% ± 0.5% higher (128 ± 7 kcal/d; P < 0.0001), while RQ was 14.0 ± 0.4% lower (-0.114 ± 0.003; P < 0.0001) when compared throughout the whole period. Body weight, sex, and age explained a larger fraction of the variance when corrected RMR was considered (adjusted R2 = 0.71; P < 0.0001) versus uncorrected RMR (adjusted R2 = 0.59; P < 0.0001). CONCLUSIONS: Applying a protocol to correct gas exchange in humans over a 6-hour period is feasible and provides information of improved accuracy.

Energy expenditure in the immediate postpartum period: Indirect calorimetry versus predictive equations.

OBJECTIVE: The aim of this study was to evaluate the resting energy expenditure (REE) of postpartum women by indirect calorimetry and to provide the most appropriate predictive equations to estimate it. METHODS: This was a cross-sectional study with 79 women in the maternity unit of a Brazilian city hospital. Information regarding age, income, gestational age, and breastfeeding was collected. Height, weight, and body composition were measured. We measured REE by indirect calorimetry and predicted REE using eight equations. Analysis of comparison, correlation, agreement, and accuracy was performed. RESULTS: The median of measured REE was 1224 kcal (95% confidence interval [CI], 1157.4-1330), and the predicted REE ranged from 1213.8 (95% CI, 1207.3-1261.9) to 1553.1 kcal (95% CI, 1430.8-1488.5). No difference was found in REE between mothers who breastfed and those who did not (P = 0.994); however, there was a positive correlation with lean mass (r = 0.336; P = 0.003) and weight (r = 0.237; P = 0.036). The best predictor of REE was the Harris Benedict equation, with lower difference (P = 0.876), better median of adequacy (99.8%), and better interclass correlation coefficient (0.289). The Schofield equation was next, with greater percentage of accuracy (33.3%) and lower opposite agreement (7.6%). CONCLUSIONS: All predictive equations showed low agreement and accuracy, and, in most cases, the results were overestimated. These findings indicate the need for continued studies to propose more suitable methods to determine the energy requirements for this population.

Applicability of predictive equations for resting energy expenditure in obese patients with obstructive sleep apnea

ABSTRACT Objective To investigate the applicability of predictive equations for resting energy expenditure (REE) in obese individuals with obstructive sleep apnea (OSA) and the effects of OSA severity on REE. Materials and methods Twenty-nine obese men, 41.5 ± 7 years old, with moderate and severe OSA were recruited. All subjects were submitted to a clinical polysomnography, body composition, and indirect calorimetry measurements. REE was also predicted by three different equations: Harris and Benedict (1919), Cunningham (1990), and DRI (2002). Results No effects of OSA severity on REE were found. The measured REE (2416.0 ± 447.1 kcal/day) and the REE predicted by equations were different from each other (F = 2713.88; p < 0.05): Harris and Benedict (2128.0 ± 245.8 kcal/day), Cunningham (1789.1 ± 167.8 kcal/day) and DRI (2011.1 ± 181.4 kcal/day). Pearson correlations showed a moderate positive correlation between the REE measured and predicted by all equations. Conclusion Our findings suggest that predictive equations for REE underestimate the energy expenditure in obese patients with sleep apnea. Also, no effects of OSA severity on REE were found.

Metabolic heat production and evaporation of poultry.

Accurate measurements of gas exchange between an animal and its environment is critical in determining metabolic heat production and respiratory functions of broilers. Information on non-invasive methods to measure gas exchange of broiler chicks and chickens under uncontrolled environmental conditions is lacking in the literature. The aims of this study were: (1) to develop an indirect calorimetric system including a hood that allows gas exchange for chickens, (2) to measure gas exchange and respiratory functions (respiration rate, ventilation rate, and tidal volume) of broiler chickens weighing greater than 250 g, and (3) to calculate heat production and respiratory evaporation of the birds based on measured gas and vapor exchanges. We conducted two trials. The first trial involved 6 broiler chicks evaluated for 6 days in 6 different schedules (6 × 6 Latin square). The chicks were kept inside a heat exchanger with a continuous air flow of 150 mL min-1. The second trial involved 12 birds evaluated for 12 days in 12 different schedules (12 × 12 Latin square). Metabolic heat production and evaporation were influenced by live weight of chicks, varying between evaluation days (P < 0.05). The respiratory functions (tidal volume, ventilation rate, and respiratory rate) varied between days, and were strongly influenced by live weight of the broilers (P < 0.05).

Applicability of predictive equations for resting energy expenditure in obese patients with obstructive sleep apnea.

OBJECTIVE: To investigate the applicability of predictive equations for resting energy expenditure (REE) in obese individuals with obstructive sleep apnea (OSA) and the effects of OSA severity on REE. MATERIALS AND METHODS: Twenty-nine obese men, 41.5 ± 7 years old, with moderate and severe OSA were recruited. All subjects were submitted to a clinical polysomnography, body composition, and indirect calorimetry measurements. REE was also predicted by three different equations: Harris and Benedict (1919), Cunningham (1990), and DRI (2002). RESULTS: No effects of OSA severity on REE were found. The measured REE (2416.0 ± 447.1 kcal/day) and the REE predicted by equations were different from each other (F = 2713.88; p < 0.05): Harris and Benedict (2128.0 ± 245.8 kcal/day), Cunningham (1789.1 ± 167.8 kcal/day) and DRI (2011.1 ± 181.4 kcal/day). Pearson correlations showed a moderate positive correlation between the REE measured and predicted by all equations. CONCLUSION: Our findings suggest that predictive equations for REE underestimate the energy expenditure in obese patients with sleep apnea. Also, no effects of OSA severity on REE were found.

Minimum Time to Achieve the Steady State and Optimum Abbreviated Period to Estimate the Resting Energy Expenditure by Indirect Calorimetry in Healthy Young Adults.

BACKGROUND: The optimum abbreviated period for measurement by indirect calorimetry (IC) to estimate the resting energy expenditure (REE), including the acclimation period, in healthy individuals has not been established. This study aimed to determine the acclimation time required to achieve the REE steady state during a 30-minute IC measurement and to define the optimum abbreviated measurement period in the steady state to estimate the REE in healthy young adults. METHODS: Thirty-nine volunteers (27 men and 12 women; age, 18-31 years) were recruited. The REE was obtained by IC over 30 minutes. Friedman's test was used to compare the coefficient of variation (CV%) among all 5-minute intervals (REE5). To compare the REE values obtained during the first REE5 interval in the steady state with the REE average values of the subsequent measurements, Student paired t test, linear regression, and Bland-Altman test were used. RESULTS: The CV% of the first REE5 (mean ± standard deviation: 19.9% ± 13.2%) was significantly higher (P < .0001) than that of all other REE5 (second REE5: 7.4% ± 3.8%; third: 7.8% ± 5.2%; fourth: 7.1% ± 3.9%; fifth: 8.0% ± 5.7%; sixth: 8.0% ± 4.5%). No significant difference was found between the second REE5 and the REE average values of the last 20 minutes. The second REE5 explained 90% of the REE average of the last 20 minutes, with the 95% limits of agreement by the Bland-Altman test ranging from -142.92 to 150.44 kcal/d. CONCLUSION: Ten minutes can be used as an abbreviated alternative for IC measurements in healthy young adults, and values of the first 5-minute interval should be discarded.

Overweight postmenopausal women with different plasma estradiol concentrations present with a similar pattern of energy expenditure and substrate oxidation rate before and after a fatty meal challenge.

Menopause-related withdrawal of ovarian estrogens is associated with reduced energy metabolism and overall impairment of substrate oxidation. Estradiol's withdrawal after menopause is associated with a reduction in energy metabolism and impaired substrate oxidation, which contributes to weight gain and visceral fat accumulation. Here we aimed to investigate the association between plasma estradiol concentrations and energy expenditure (EE)/substrate oxidation in a group of overweight postmenopausal women before and after a fatty meal challenge. Women were divided into three groups according to their plasma estradiol concentrations (E2): group 1 - E2 ≤ 39, group 2 - 40 ≤ E2 ≤ 59, and group 3 - E2 ≥ 60 pg/mL. VO2 and VCO2 volumes were collected following indirect calorimetry 5 h following a single lipid overload meal (1100 kcal, 72% of fat). For comparisons between groups and within the same group, a linear regression model with mixed effects was applied (P < 0.05). Forty-four women aged 55 ± 0.7 years-old, 8 ± 1.1 years following menopause, with a BMI of 30.5 ± 0.5 kg/m2, and 41.9 ± 0.7% of body fat were enrolled the study. Plasma E2 concentrations were: group 1 - 30.4 ± 1.9, group 2 - 46.9 ± 1.5, and group 3 - 91.3 ± 12.0 pg/mL (P < 0.0001). EE at baseline and in the resting state was 1320 ± 24.3 kcal/d, and increased to 1440 ± 27.0 kcal/d 30 min following ingestion of the fatty meal (P < 0.0001), and rose again to an average of 1475 ± 30.3 kcal/d at the completion of experiment (P < 0.0001). Carbohydrate oxidation (Chox) was 0.155 ± 0.01 g/min at resting, maintained as 0.133 ± 0.00 g/min 30 min after ingestion of the fatty meal, and was 0.123 ± 0.01 g/min at the end of the testing period. Lipid oxidation (Lipox) was 0.041 ± 0.003 g/min at resting, increasing to 0.054 ± 0.003 g/min at 30 min (P = 0.01), and reaching 0.063 ± 0.003 g/min at the end of the experiment (P < 0.0001). There was no difference between groups for EE, Chox or Lipox. Our data suggest that EE and substrate oxidation were modulated following a lipid-meal challenge equally in all groups and this did not differ with plasma E2 concentrations.

Basal Metabolic Rate of Adolescent Modern Pentathlon Athletes: Agreement between Indirect Calorimetry and Predictive Equations and the Correlation with Body Parameters.

PURPOSE: The accurate estimative of energy needs is crucial for an optimal physical performance among athletes and the basal metabolic rate (BMR) equations often are not well adjusted for adolescent athletes requiring the use of specific methods, such as the golden standard indirect calorimetry (IC). Therefore, we had the aim to analyse the agreement between the BMR of adolescents pentathletes measured by IC and estimated by commonly used predictive equations. METHODS: Twenty-eight athletes (17 males and 11 females) were evaluated for BMR, using IC and the predictive equations Harris and Benedict (HB), Cunningham (CUN), Henry and Rees (HR) and FAO/WHO/UNU (FAO). Body composition was obtained using DXA and sexual maturity data were retrieved through validated questionnaires. The correlations among anthropometric variables an IC were analysed by T-student test and ICC, while the agreement between IC and the predictive equations was analysed according to Bland and Altman and by survival-agreement plotting. RESULTS: The whole sample average BMR measured by IC was significantly different from the estimated by FAO (p<0.05). Adjusting data by gender FAO and HR equations were statistically different from IC (p <0.05) among males, while female differed only for the HR equation (p <0.05). CONCLUSION: The FAO equation underestimated athletes' BMR when compared with IC (T Test). When compared to the golden standard IC, using Bland and Altman, ICC and Survival-Agreement, the equations underestimated the energy needs of adolescent pentathlon athletes up to 300kcal/day. Therefore, they should be used with caution when estimating individual energy requirements in such populations.

Energy Expenditure in Adolescents With Cerebral Palsy: Comparison of the SenseWear Armband and Indirect Calorimetry.

BACKGROUND: Inactivity and overweight are major health concerns in children and adolescents with disabilities. Methods for the assessment of activity and energy expenditure may be affected negatively by the underlying disability, especially when motor function is impaired. The purpose of this study was to assess the validity of the SenseWear Armband in adolescents with cerebral palsy and hemiparesis. METHODS: Ten volunteers (age: 13.4 ± 1.6 years) were equipped with SenseWear Armbands on the hemiparetic and nonhemiparetic side of the body. Energy expenditure was measured at rest and during treadmill exercise (speed range: 0.85 to 2.35 m/s). Indirect calorimetry served as independent reference method. RESULTS: The mean error was between -0.6 and 0.8 kcal/min and there were no significant differences between SenseWear and indirect calorimetry at any speed. Differences between body sides in expenditure (mean: -0.2 to 0.0 kcal/min) and step count (mean: -3.4 to 9.7 steps/min) were not significant. CONCLUSIONS: The validity of the SenseWear Armband does not appear to be negatively affected by cerebral palsy during laboratory treadmill exercise. Future field studies are necessary to assess the validity and practicability energy expenditure and physical activity in children and adolescents with physical disabilities.

Estimating energy expenditure using heat flux measured at a single body site.

INTRODUCTION: The Personal Calorie Monitor (PCM) is a portable direct calorimeter that estimates energy expenditure (EE) from measured heat flux (i.e., the sum of conductive, convective, radiative, and evaporative heat). PURPOSE: The primary aim of this study was to compare EE estimated from measures of heat flux with those measured using indirect calorimetry in a thermoneutral environment (26°C). A secondary aim was to determine whether exposure to ambient temperature below thermoneutral condition (19°C) influences the accuracy of the PCM. METHODS: Thirty-four adults (mean ± SD: age, 28 ± 5 yr; body mass index, 22.9 ± 2.6 kg · m(-2)) were studied for 5 h in a whole-room indirect calorimeter (IC) in thermoneutral and cool conditions. Participants wore the PCM on their upper arm and completed two 20-min treadmill walking bouts (0% grade, 3 mph). The remaining time was spent sedentary (e.g., watching television, using a computer). RESULTS: In thermoneutral conditions, EE values (mean (95% confidence interval)) measured by IC and PCM were 560.0 (526.5-593.5) and 623.3 (535.5-711.1) kcal, respectively. In cool conditions, EE values measured by IC and PCM were 572.5 (540.9-604.0) and 745.5 (668.1-822.8) kcal, respectively. Under thermoneutral conditions, mean PCM minute-by-minute EE tracked closely with IC, resulting in a small nonsignificant bias (63 kcal (-5.8 to 132.4)). During cool conditions, mean PCM minute-by-minute EE did not track IC, resulting in a large bias (173.0 kcal (93.9-252.1)) (P <; 0.001). CONCLUSIONS: This study demonstrated the validity of using measured heat flux to estimate EE. However, accuracy may be impaired in cool conditions possibly because of excess heat loss from the exposed limbs.

Predicted and measured resting energy expenditure in children with spinal muscular atrophy 2.

We investigated in children with spinal muscular atrophy type 2 the consistency of 4 different equations for predicting resting energy expenditure (REE) compared with measured REE by using indirect calorimetry. In patients with spinal muscular atrophy type 2, measured REE was lower than predicted. We also found a correlation between energy consumption and motor skills.