Measured and Predicted Resting Energy Expenditure in Malnourished Older Hospitalized Patients: A Cross-Sectional and Longitudinal Comparison.

A number of equations have been proposed to predict resting energy expenditure (REE). The role of nutritional status in the accuracy and validity of the REE predicted in older patients has been paid less attention. We aimed to compare REE measured by indirect calorimetry (IC) and REE predicted by the Harris-Benedict formula in malnourished older hospitalized patients. Twenty-three malnourished older patients (age range 67-93 years, 65% women) participated in this prospective longitudinal observational study. Malnutrition was defined as Mini Nutritional Assessment Long Form (MNA-SF) score of less than 17. REE was measured (REEmeasured) and predicted (REEpredicted) on admission and at discharge. REEpredicted within ±10% of the REEmeasured was considered as accuracy. Nutritional support was provided to all malnourished patients during hospitalization. All patients were malnourished with a median MNA-LF score of 14. REEmeasured and REEpredicted increased significantly during 2-week nutritional therapy (+212.6 kcal and +19.5 kcal, respectively). Mean REEpredicted (1190.4 kcal) was significantly higher than REEmeasured (967.5 kcal) on admission (p < 0.001). This difference disappeared at discharge (p = 0.713). The average REEpredicted exceeded the REEmeasured on admission and at discharge by 29% and 11%, respectively. The magnitude of difference between REEmeasured and REEpredicted increased along with the degree of malnutrition (r = 0.42, p = 0.042) as deviations ranged from -582 to +310 kcal/day in severe to mildly malnourished patients, respectively. REEpredicted by the Harris-Benedict formula is not accurate in malnourished older hospitalized patients. REE measured by IC is considered precise, but it may not represent the true energy requirements to recover from malnutrition. Therefore, the effect of malnutrition on measured REE must be taken into account when estimating energy needs in these patients.

Usefulness of Modern Activity Trackers for Monitoring Exercise Behavior in Chronic Cardiac Patients: Validation Study.

BACKGROUND: Improving physical activity (PA) is a core component of secondary prevention and cardiac (tele)rehabilitation. Commercially available activity trackers are frequently used to monitor and promote PA in cardiac patients. However, studies on the validity of these devices in cardiac patients are scarce. As cardiac patients are being advised and treated based on PA parameters measured by these devices, it is highly important to evaluate the accuracy of these parameters in this specific population. OBJECTIVE: The aim of this study was to determine the accuracy and responsiveness of 2 wrist-worn activity trackers, Fitbit Charge 2 (FC2) and Mio Slice (MS), for the assessment of energy expenditure (EE) in cardiac patients. METHODS: EE assessed by the activity trackers was compared with indirect calorimetry (Oxycon Mobile [OM]) during a laboratory activity protocol. Two groups were assessed: patients with stable coronary artery disease (CAD) with preserved left ventricular ejection fraction (LVEF) and patients with heart failure with reduced ejection fraction (HFrEF). RESULTS: A total of 38 patients were included: 19 with CAD and 19 with HFrEF (LVEF 31.8%, SD 7.6%). The CAD group showed no significant difference in total EE between FC2 and OM (47.5 kcal, SD 112 kcal; P=.09), in contrast to a significant difference between MS and OM (88 kcal, SD 108 kcal; P=.003). The HFrEF group showed significant differences in EE between FC2 and OM (38 kcal, SD 57 kcal; P=.01), as well as between MS and OM (106 kcal, SD 167 kcal; P=.02). Agreement of the activity trackers was low in both groups (CAD: intraclass correlation coefficient [ICC] FC2=0.10, ICC MS=0.12; HFrEF: ICC FC2=0.42, ICC MS=0.11). The responsiveness of FC2 was poor, whereas MS was able to detect changes in cycling loads only. CONCLUSIONS: Both activity trackers demonstrated low accuracy in estimating EE in cardiac patients and poor performance to detect within-patient changes in the low-to-moderate exercise intensity domain. Although the use of activity trackers in cardiac patients is promising and could enhance daily exercise behavior, these findings highlight the need for population-specific devices and algorithms.

Accuracy of the Multisensory Wristwatch Polar Vantage's Estimation of Energy Expenditure in Various Activities: Instrument Validation Study.

BACKGROUND: Sport watches and fitness trackers provide a feasible way of obtaining energy expenditure (EE) estimations in daily life as well as during exercise. However, today's popular wrist-worn technologies show only poor-to-moderate EE accuracy. Recently, the invention of optical heart rate measurement and the further development of accelerometers in wrist units have opened up the possibility of measuring EE. OBJECTIVE: This study aimed to validate the new multisensory wristwatch Polar Vantage and its EE estimation in healthy individuals during low-to-high-intensity activities against indirect calorimetry. METHODS: Overall, 30 volunteers (15 females; mean age 29.5 [SD 5.1] years; mean height 1.7 [SD 0.8] m; mean weight 67.5 [SD 8.7] kg; mean maximal oxygen uptake 53.4 [SD 6.8] mL/min·kg) performed 7 activities-ranging in intensity from sitting to playing floorball-in a semistructured indoor environment for 10 min each, with 2-min breaks in between. These activities were performed while wearing the Polar Vantage M wristwatch and the MetaMax 3B spirometer. RESULTS: After EE estimation, a mean (SD) of 69.1 (42.7) kcal and 71.4 (37.8) kcal per 10-min activity were reported for the MetaMax 3B and the Polar Vantage, respectively, with a strong correlation of r=0.892 (P<.001). The systematic bias was 2.3 kcal (3.3%), with 37.8 kcal limits of agreement. The lowest mean absolute percentage errors were reported during the sitting and reading activities (9.1%), and the highest error rates during household chores (31.4%). On average, 59.5% of the mean EE values obtained by the Polar Vantage were within ±20% of accuracy when compared with the MetaMax 3B. The activity intensity quantified by perceived exertion (odds ratio [OR] 2.028; P<.001) and wrist circumference (OR -1.533; P=.03) predicted 29% of the error rates within the Polar Vantage. CONCLUSIONS: The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent. During sitting and reading activities, the EE estimation is very good, whereas during nonsteady activities that require wrist and arm movement, the EE accuracy is only moderate. However, compared with other available wrist-worn EE monitors, the Polar Vantage can be recommended, as it performs among the best.

Estimating resting energy expenditure of patients on dialysis: Development and validation of a predictive equation.

OBJECTIVES: The aims of this study were to develop and validate a resting energy expenditure (REE) predictive equation in a cohort of patients on dialysis and to test the accuracy of two previously developed specific equations to estimate REE of these patients. METHODS: A database with REE measured by indirect calorimetry (IC) of 189 patients on hemodialysis and peritoneal dialysis was used to develop and validate the new equation. The sample including only patients on hemodialysis (n = 131) was used to test the accuracy of the specific REE dialysis equations by Vilar and Byham-Gray. RESULTS: Multiple regression analysis generated two equations: REE (kcal/d) = 957.02 - 8.08 × age + 11.07 × body weight + 136.4 (if men) (R2 = 0.515) (1) REE (kcal/d) = 624.6-4.8 × age + 20.6 × fat-free, ass-fat-free mass-8.65 (if men) (R2 = 0.512) (2) In the validation group, REE by both equations did not differ from the REE measured by IC. No bias was found in the Bland-Altman analysis and the intraclass correlation coefficient and P20 test showed good reliability with measured REE. Vilar's equation overestimated REE; whereas REE generated by Byham-Gray's equation did not differ from measured REE. Proportional and systematic biases were significant for both equations. CONCLUSIONS: The new equations developed showed good accuracy and can be valuable to estimate energy needs of patients on dialysis. Byham-Gray's and Vilar's equations presented low to moderate performance to estimate REE of the patients on dialysis.

Accelerometry-based method for assessing energy expenditure in patients with diabetes during walking.

BACKGROUND: Monitoring activity-related energy expenditure (EE) is essential in the management of daily activity and the dietary programme in patients with type 2 diabetes (T2D) and must be estimated accurately. Accelerometry-based equations have frequently used to estimate EE, although the validity of these methods has not been confirmed in patients with T2D. The present study aimed to test the validity of an accelerometry-based method (Bouten's method) to assess EE during walking in patients with T2D. METHODS: The study included 20 patients with controlled T2D [mean (SD) duration: 10.6 (6.1) years; age: 57.5 (8.4) years; body mass index: 26.4 (2.6) kg m- ²]. All participants performed five 6-min periods of walking at different speeds (0.5-1.5 m s-1 ) on a treadmill. Mechanical data were recorded using an inertial measurement unit placed on the lower back with gas exchange being simultaneously monitored. RESULTS: Values of EE during walking estimated by the accelerometer method did not differ significantly from those measured by indirect calorimetry. Bias and root mean square error were -1.17 and 2.93 kJ min-1 , respectively, on average across speeds. CONCLUSIONS: Our results suggest that EE during walking may be accurately estimated in patients with diabetes mellitus using an accelerometer.

Energy Balance in Critically Ill Children With Severe Sepsis Using Indirect Calorimetry: A Prospective Cohort Study.

OBJECTIVES: Energy needs in critically ill children are dynamic and variable. Data on energy balance in children with severe sepsis using indirect calorimetry (IC) is lacking. Thus, we planned to study the energy needs and balance of this cohort. METHODS: Prospective observational study conducted in ventilated children aged 5 to 12 years, admitted in pediatric intensive care unit with severe sepsis from May 2016 to June 2017. Measured resting energy expenditure (mREE) was measured with IC (Quark RMR, COSMED) till 7 days or pediatric intensive care unit discharge. Predicted energy expenditure (pREE) was estimated using Schofield, Harris and Benedict, and FAO/WHO/UNU equations. Primary outcome was to study the daily energy balance. Secondary outcome was to determine nitrogen balance and agreement of mREE with pREE. RESULTS: Forty children (24 boys) with median age of 7 (5.2, 10) years were enrolled. All received enteral nutrition; 35 (87.5%) received inotropic support. Median ventilation-free days were 19 days and 4 children died (10%). A total of 176 IC measurements were obtained with an average of 4 per patient. The mean mREE was 51 ±â€Š17 kcal/kg and mean respiratory quotient was 0.77 ±â€Š0.07. There was persistent negative energy balance from days 1 to 7 and negative nitrogen balance from days 1 to 5. There was poor agreement of pREE with mREE using Bland Altman plots. None of severity of illness scores (PRISM III, daily Sequential Organ Function Assessment, daily Vasoactive Inotropic Score) showed correlation with mREE. CONCLUSIONS: Persistent negative energy and nitrogen balance exist during acute phase of severe sepsis. Predictive equations are inaccurate compared with IC as the criterion standard.

Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90⁻110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris⁻Benedict equation, with an underestimation of 54 (95% CI: 30⁻137) kcal/d. The pooled analysis was associated with significant heterogeneity (I2 = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data.

Predicting ambulatory energy expenditure in lower limb amputees using multi-sensor methods.

PURPOSE: To assess the validity of a derived algorithm, combining tri-axial accelerometry and heart rate (HR) data, compared to a research-grade multi-sensor physical activity device, for the estimation of ambulatory physical activity energy expenditure (PAEE) in individuals with traumatic lower-limb amputation. METHODS: Twenty-eight participants [unilateral (n = 9), bilateral (n = 10) with lower-limb amputations, and non-injured controls (n = 9)] completed eight activities; rest, ambulating at 5 progressive treadmill velocities (0.48, 0.67, 0.89, 1.12, 1.34m.s-1) and 2 gradients (3 and 5%) at 0.89m.s-1. During each task, expired gases were collected for the determination of [Formula: see text] and subsequent calculation of PAEE. An Actigraph GT3X+ accelerometer was worn on the hip of the shortest residual limb and, a HR monitor and an Actiheart (AHR) device were worn on the chest. Multiple linear regressions were employed to derive population-specific PAEE estimated algorithms using Actigraph GT3X+ outputs and HR signals (GT3X+HR). Mean bias±95% Limits of Agreement (LoA) and error statistics were calculated between criterion PAEE (indirect calorimetry) and PAEE predicted using GT3X+HR and AHR. RESULTS: Both measurement approaches used to predict PAEE were significantly related (P<0.01) with criterion PAEE. GT3X+HR revealed the strongest association, smallest LoA and least error. Predicted PAEE (GT3X+HR; unilateral; r = 0.92, bilateral; r = 0.93, and control; r = 0.91, and AHR; unilateral; r = 0.86, bilateral; r = 0.81, and control; r = 0.67). Mean±SD percent error across all activities were 18±14%, 15±12% and 15±14% for the GT3X+HR and 45±20%, 39±23% and 34±28% in the AHR model, for unilateral, bilateral and control groups, respectively. CONCLUSIONS: Statistically derived algorithms (GT3X+HR) provide a more valid estimate of PAEE in individuals with traumatic lower-limb amputation, compared to a proprietary group calibration algorithm (AHR). Outputs from AHR displayed considerable random error when tested in a laboratory setting in individuals with lower-limb amputation.

Prognostic value of respiratory quotients in severe polytrauma patients with nutritional support.

OBJECTIVE: The association between energy metabolism and prognosis in polytrauma patients has not yet been defined. The aim of this study was to describe energy metabolism and analyze the prognostic value of respiratory quotient (RQ) and nonprotein respiratory quotient (npRQ) in fasting polytrauma patients (fPP) and polytrauma patients with nutritional support (nsPP). METHODS: Twenty-two polytrauma patients (before and after parenteral nutrition administration) and 22 healthy controls (after overnight fasting) were examined on day 4 (median) after admission to the intensive care unit. To evaluate energy expenditure in nsPP and resting energy expenditure in fPP and controls with RQ and npRQ in all groups, we used indirect calorimetry. With regression analysis, the descriptive models of intensive care unit (ICU) length of stay (LOS) and mechanical ventilation time (VT) were derived. RESULTS: RQ and npRQ were significantly lower in fPP than in controls (P < 0.05 and P < 0.01, respectively) and in nsPP (P < 0.05). In nsPP, relationships between RQ or npRQ and the ICU LOS or mechanical VT were demonstrated (P < 0.0001, r = -0.78 for RQ and VT; P < 0.0001, r = -0.78 for npRQ and VT; P < 0.001, r = -0.69 for RQ and LOS; P < 0.001, r = -0.72 for npRQ and LOS). CONCLUSIONS: RQ and npRQ parameters measured by indirect calorimetry in polytrauma patients with parenteral nutrition on the fourth day of ICU stay related to clinical outcomes such as duration of mechanical ventilation and ICU LOS.

A new resting metabolic rate equation for women with class III obesity.

OBJECTIVE: Resting metabolic rate (RMR) is an important parameter to guide the nutritional therapy of class III obese patients. The aims of the present study were to develop a predictive equation for RMR estimation in class III obese women using anthropometric indicators and to compare indirect calorimetry with other predictive equations. METHODS: This was a cross-sectional study on women with class III obesity (body mass index >40 kg/m2). Weight, height, fat-free mass, fat mass, and RMR of all individuals were measured. Multiple linear regression was used to determine the new RMR equation and the Bland-Altman plot was used to analyze the agreement between indirect calorimetry and the results of predictive equations. RESULTS: We evaluated 101 women with obesity class III and a mean age of 36.3 ± 10 y. The anthropometric and body composition variables used in the new equation had a coefficient of determination of 0.80, and a significant influence on RMR (P = 0.01). Harris-Benedict and World Health Organization equations showed similar bias and limits (181.6, +2 SD = 765.5, -2 SD = -402.2; 156.4, +2 SD = 799.4, -2 SD = -486.6, respectively). The Mifflin-St Jeor and Owen equations showed large clinical bias (mean, 239.2 and 463.9, respectively), and a tendency to overestimate RMR. CONCLUSION: The prediction equations tested in the study had low accuracy in estimating RMR of women with class III obesity. However, our equation was developed specifically for this population, using variables known to influence their energy expenditure.

Relative validity of an indirect calorimetry device for measuring resting energy expenditure and respiratory quotient.

BACKGROUND AND OBJECTIVES: Resting energy expenditure (REE) and respiratory quotient (RQ) are important for optimal nutritional care. The purpose of this study was to assess the accuracy and repeatability of an indirect calorimetry device (IIM-IC-100) in the measurement of REE and RQ in healthy Chinese adults. METHODS AND STUDY DESIGN: A total of 38 healthy adults (19 male and 19 female) aged 18-52 years (25±6 years) were enrolled in this study. REE and RQ were measured by IIM-IC-100 and by VO2000, alternately and in duplicate. RESULTS: There was a highly significant correlation between IIM-IC-100 REE and VO2000 REE (r=0.906, p<0.001), with mean IIM-IC-100 REE significantly higher than that of VO2000 (1475±269 vs 1394±313 kcal/d, p=0.002). Bland- Altman analysis revealed that the mean difference between IIM-IC-100 REE and VO2000 REE was 81.3 kcal/d, with limits of agreement of -185 to +347 kcal/d. There was no significant difference in RQ between the two devices. No significant differences were observed between the repeated measurements for both devices. Intrasubject coefficients of variation (CVs) of REE were smaller for IIM-IC-100 (5.8%) than for VO2000 (10.5%), while CVs of RQ were similar for IIM-IC-100 (7.2%) and VO2000 (6.9%). CONCLUSIONS: These preliminary data indicated that the IIM-IC-100 showed promise as an accurate and precise tool in the assessment of REE and RQ in healthy Chinese adults.

Assessing resting energy expenditure in overweight and obese adolescents in a clinical setting: validity of a handheld indirect calorimeter.

BACKGROUND: Accurately determining energy requirements is key for nutritional management of pediatric obesity. Recently, a portable handheld indirect calorimeter, MedGem (MG) has become available to measure resting energy expenditure (REE). Our work aims to determine the clinical validity and usefulness of MG to measure REE in overweight and obese adolescents. METHODS: Thirty-nine overweight and obese adolescents (16 male (M): 23 female (F), 15.2 ± 1.9 y, BMI percentile: 98.6 ± 2.2%) and 15 normal weight adolescents (7M: 8F, age 15.2 ± 2.0 y, BMI percentile: 39.2 ± 20.9%) participated. REE was measured with both MG and standard indirect calorimeter (VMax) in random order. RESULTS: MG REE (1,600 ± 372 kcal/d) was lower than VMax REE (1,727 ± 327 kcal/) in the overweight and obese adolescents. Bland Altman analysis (MG -VMax) showed a mean bias of -127 kcal/d (95% CI = -72 to -182 kcal/d, P < 0.001), and a proportional bias existed such that lower measured REE by VMax was underestimated by MG, and higher measured REE by VMax were overestimated by MG. CONCLUSION: MG systematically underestimates REE in the overweight and adolescent population, thus the MG portable indirect calorimeter is not recommended for routine use. Considering that it is a systematic underestimation of REE, MG may be clinically acceptable, only if used with caution.

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.

Assessing Resting Metabolic Rate in Overweight and Obese Adolescents With a Portable Indirect Calorimeter: A Pilot Study for Validation and Reliability.

BACKGROUND: Indirect calorimetry measured via the traditional indirect calorimeter is considered the "gold standard" for determining resting metabolic rate (RMR). Portable devices for assessing RMR are a less expensive option for measuring RMR in the clinical setting. This pilot study tested the reliability and validity of a portable device for measuring RMR, specifically in overweight and obese adolescents. MATERIALS AND METHODS: Participants aged 17-19 years (n = 19) and ≥85th percentile on the Centers for Disease Control and Prevention body mass index growth curves for age and sex were recruited from a university campus. Participants completed testing on a traditional indirect calorimeter and a portable indirect calorimeter in a randomized order on 2 separate testing days. RESULTS: A paired samples t test comparing the means of the portable device and the traditional indirect calorimeter found no significant difference (P = .22). The test-retest intraclass correlation coefficient for assessing RMR was 0.91, indicating reliability of the portable indirect calorimeter. Compared with measured RMR, the Mifflin-St Jeor equation demonstrated 37% accuracy, and the Molnar equation demonstrated 57% accuracy. CONCLUSION: This pilot study found portable indirect calorimetry to be reliable and valid for assessing RMR in an overweight and obese adolescent population. In addition, this study indicates that portable indirect calorimetry may be an acceptable option for assessing RMR in this population compared with the traditional indirect calorimeter or predictive equations.

Energy Balance in Huntington's Disease.

INTRODUCTION: Little is known about the energy needs in Huntington's disease (HD). The aims of this study are to analyze and compare the total energy expenditure (TEE) and energy balance (EB) in a representative sample of HD patients with healthy controls. METHODS: This is an observational, case-control single-center study. Food caloric energy intake (EI) and TEE were considered for estimating EB. A dietary recall questionnaire was used to assess the EI. TEE was computed as the sum of resting energy expenditure (REE), measured by indirect calorimetry and physical activity (PA) monitored by an actigraph. RESULTS: A total of 22 patients were included (36% men, mean age 50.3 ± 15.6 years, motor Unified Huntington's Disease Scale 27.9 ± 23.7, total functional capacity 11.0 (7.0-13.0), EI 38.6 ± 10.0 kcal/kg, PA 5.3 (3.0-7.4) kcal/kg, REE 30.9 ± 6.4 kcal/kg, TEE 2,023.4 (1,592.0-2,226.5) kcal/day) and 18 controls (50% men, mean age 47.4 ± 13.8 years, EI 38.6 ± 10.3 kcal/kg, PA 8.4 (5.0-13.8) kcal/kg, REE 30.8 ± 6.6 kcal/kg, TEE 2,281.0 (2,057.3-2,855.3) kcal/day). TEE was significantly lower in patients compared to controls (p = 0.03). PA was lower in patients compared to controls (p = 0.02). CONCLUSIONS: Although patients with HD appeared to have lower energy expenditure, mainly due to decreased voluntary PA, they were still able to maintain their energy needs with an adequate food intake. © 2015 S. Karger AG, Basel.

Concordancia entre calorimetría indirecta y modelos predictivos en una población sana española / Agreement between indirect calorimetry and predictive equations in a sample of Spanish healthy adults

Objetivo: estudiar la concordancia entre el gasto energético en reposo (GER) obtenido mediante calorimetría indirecta (CI), y las ecuaciones de estimación más utilizadas en población adulta sana española. Métodos: estudio transversal en el que se determinó el GER en 95 sujetos sanos con normopeso mediante calorimetría indirecta y modelos predictivos (se seleccionaron 45 fórmulas desarrolladas en adultos de características similares a la muestra estudiada que incluían peso, talla, sexo y/o composición corporal). La concordancia entre ambos métodos se analizó mediante el Coeficiente de Correlación Intraclase (CCI) y la prueba de Bland-Altman. La significación se alcanzó con p< 0,05. Resultados: la edad media fue de 42 años (rango: 23,0– 63,2). El GER medio estimado por CI en la muestra fue de 1589 (312) kcal/día [1822,3 (224,3) kcal/día en varones y 1379,3 (216,1) kcal/día en mujeres; p< 0,05]. Las fórmulas que mejor se ajustaron a la muestra fueron las de De-Lorenzo, Harris-Benedict, Schofield y, especialmente, Korth. Conclusiones: existen grandes variaciones en la estimación del gasto energético en reposo en función de la ecuación predictiva utilizada. Las fórmulas de De-Lorenzo, Harris-Benedic y Schofield se comportan adecuadamente en la muestra evaluada; sin embargo, la de Korth demostró ser la más apta. Los modelos que incluyen peso y/o talla obtuvieron mejores resultados que los que contienen variables de composición corporal (AU)

Objective: the aim of this study was to analyze the agreement between the resting energy expenditure (REE) obtained by indirect calorimetry (IC) and that obtained by prediction equations in a sample of healthy adults from Spain. Méthods: a descriptive cross-sectional study was conducted in 95 healthy, normal-weight adults. REE was determined by IC and 45 population-specific prediction equations which were based on weight, height, sex and/or body composition (BC). The Intraclass Correlation Coefficient (ICC) and Bland-Alman plots were used to analyze the agreement between the REE obtained by IC and that obtained by prediction equations. The level of signification was reached at p< 0,05. Results: mean age was 42 years (range: 23.0–63.2). Mean REE determined by CI was 1589 (312) kcal/d [1822.3 (224.3) kcal/d in men and 1379.3 (216.1) kcal/d in women; p< 0.05]. The De-Lorenzo, Harris-Benedict, Schofield, and especially the Korth equations showed the greatest level of agreement with respect to IC. Conclusions: there is high variability in the estimates of REE depending on the prediction equation used. The De Lorenzo, Harris-Benedict, and the Schofield equations showed a good level of agreement in our sample; however, the Korth equation was the most appropriate. Equations based on weight and/or height were more accurate than those which included body composition variables (AU)

Eight weeks of exercise training improves fitness measures in methamphetamine-dependent individuals in residential treatment.

OBJECTIVES: Physical exercise has been shown to benefit diverse medical and behavioral conditions. This study assesses the feasibility and efficacy of an 8-week endurance and resistance training program on fitness measures in individuals undergoing residential treatment for methamphetamine (MA) dependence. METHODS: A total of 39 MA-dependent individuals were randomized to 3 days/week of exercise training (ET, n = 15) or health education without training (equal attention [EA], n = 14) over 8 weeks. Aerobic performance ((Equation is included in full-text article.)VO2max) was measured by indirect calorimetry, body composition by skinfolds, muscle strength by 1-repetition maximum (1-RM), and endurance at 85% of 1-RM for both leg press (LP) and chest press (CP). RESULTS: A total of 29 individuals completed the study for a 74% adherence rate. Baseline characteristics (mean ± SD) were balanced between groups: age 31 ± 7 years; height = 1.74 ± 0.07 m; weight 82.0 ± 15.0 kg. The ET group significantly improved (Equation is included in full-text article.)O2max by 0.63 ± 0.22 L/min (+21%), LP strength by 24.4 ± 5.6 kg (+40%), and CP strength by 20.6 ± 5.7 kg (+49%). The ET group increased LP and CP endurance by 120% and 96%, respectively and showed significant reductions in body weight of 1.7 ± 2.4 kg (-2%), % body fat of 2.8 ± 1.3% (-15%), and fat weight 2.8 ± 1.8 kg (-18%). All changes were significant (P < 0.001) for ET, and no changes were seen for the EA group. CONCLUSIONS: Individuals recovering from MA dependence showed substantial improvements in aerobic exercise performance, muscle strength and endurance, and body composition with ET. These findings demonstrate the feasibility of an ET intervention in these participants and also show excellent responsiveness to the exercise stimulus resulting in physiological changes that might enhance recovery from drug dependency.

Validade da equação de Henry e Rees que estima a taxa metabólica de repouso em adolescentes masculinos / Validity of the equation of Henry and Rees that estimates the resting metabolic rate in male adolescents

OBJETIVO: Analisar a validade da equação de predição da taxa metabólica de repouso proposta por Henry e Rees (1991) em adolescentes do sexo masculino. MÉTODOS: Estudo transversal, com amostra de conveniência constituída de 52 meninos, entre dez e 17 anos, sendo mensuradas a massa corporal e a calorimetria indireta. A massa corporal foi substituída na equação de Henry e Rees para determinar a taxa metabólica de repouso predita. A calorimetria indireta foi determinada pelos valores do consumo de O2 e produção de CO2, e usada na equação de Weir (1949), considerada método padrão para o cálculo da taxa metabólica de repouso. Todas as medidas foram realizadas pela manhã, com o indivíduo em jejum de seis horas, em posição supina e em repouso muscular. Realizaram-se os seguintes procedimentos estatísticos: teste t pareado; erro constante (com diferença aceita entre as médias <5 por cento) e, para análise da concordância entre os dois métodos, o procedimento gráfico de Bland e Altman. RESULTADOS: A equação proposta por Henry e Rees não apresentou diferença significativa em relação ao método padrão, assim como o erro constante entre as médias foi <5 por cento. Porém, a análise gráfica de Bland e Altman revelou que não há concordância entre a equação e o método padrão. CONCLUSÕES: A equação de Henry e Rees deve ser utilizada com prudência no cálculo da taxa metabólica de respouso para adolescentes com características similares as do grupo estudado.

OBJETCTIVE: To evaluate the validity of the equation proposed by Henry and Rees (1991) to predict resting metabolic rate in adolescent boys. METHODS: This cross-sectional study enrolled 52 boys aged ten to 17 years on a random convenience sample. The variables measured were: body mass and indirect calorimetry. Body mass was replaced in the equation of Henry and Rees to determine the predicted resting metabolic rate. The indirect calorimetry was determined by the values of O2 consumption and CO2 productions, in order to calculate Weir's equation (1949), considered in this study as the standard method to calculate resting metabolic rate. All measurements were performed in the supine position and at rest, in the morning after a six-hour fast. Statistical analysis included paired t-test; constant error (with a tolerable difference between the means <5 percent) and Bland and Altman graphic analysis. RESULTS: The equation proposed by Henry and Rees did not show significant difference in relation to the standard method and the constant error between the means was <5 percent. However, Bland and Altman analysis did not show agreement between the studied equation and the standard method. CONCLUSIONS: Henry and Rees equation should be used with caution to calculate resting metabolic rate in adolescent boys with similar characteristics of the studied group.

OBJETIVO: Analizar la validez de la ecuación de predicción de la tasa metabólica de reposo (TMR) propuesta por Henry y Rees (1991) en adolescentes del sexo masculino. MÉTODOS: Estudio transversal, con muestra de conveniencia constituida por 52 niños, entre 10 y 17 años, siendo medidas las variables a continuación: masa corporal y calorimetría indirecta (CI). La masa corporal fue sustituida en la ecuación de Henry y Rees (1991) para determinar la TMR predicha. La CI fue determinada por los valores del consumo de O2 y producción de CO2 y usada en la ecuación de Weir (1949), considerada como método estándar de la TMR. Todas las medidas fueron realizadas por la mañana, con el individuo en ayuno de 6 horas, en posición supina y en reposo muscular. Se realizaron los siguientes procedimientos estadísticos: prueba “t” pareada; error constante (EC - con diferencia aceptada entre los promedios menor que 5 por ciento) y, para análisis de la concordancia entre los dos métodos, el procedimiento gráfico de Bland y Altman. RESULTADOS: La ecuación propuesta por Henry y Rees (1991) no presentó diferencia significativa respecto al método estándar, así como el error constante entre los promedios fue inferior a 5 por ciento. Sin embargo, el análisis gráfico de Bland y Altman revela que no hay concordancia entre la ecuación y el método estándar. CONCLUSIONES: La ecuación de Henry y Rees (1991) debe ser utilizada con prudencia en el cálculo de la TMR para adolescentes semejantes al grupo estudiado.

A new method to estimate energy expenditure from abdominal and rib cage distances.

The aim of this paper is to validate a new method of energy expenditure (EE) estimation stemming solely from the measurement of rib cage, abdominal and chest wall distances. We set out to prove that the variations of these distances, measured by two pairs of electromagnetic coils, lead to the estimation of the ventilation (VE) and the EE. Eleven subjects were recruited to take part in this study (27.6 ± 5.4 years; 73.7 ± 9.7 kg). Each subject participated in two tests. The objective of Test 1 was to determine the individual and group equations between the VE and EE during light to moderate activities while Test 2 compared the two pairs of electromagnetic coils with the indirect calorimetry so as to estimate EE in upright sitting and standing positions and during walking exercises. During Test 2, we compared EE measured by indirect calorimetry (EE(IC-Val-REF)) with EE estimated by the two pairs of electromagnetic coils through the application of: (1) the individual equation (EE(mag-Val-INDIV)) and (2) the group equation (EE(mag-val-GROUP)). The results show that there is no significant difference between EE(IC-Val-REF) and EE(mag-Val-INDIV) and between EE(IC-Val-REF) and EE(mag-val-GROUP) for each activity. Furthermore, the mean difference seems to show that the estimation of EE is better with the group equation. In conclusion, on the proven basis of this study we are able to validate this new method which permits the estimation of EE from abdominal and rib cage distances. This study also highlights the advantage of using a group equation to the estimate EE.

Utility of the actiheart accelerometer for estimating exercise energy expenditure in female adolescent runners.

There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors' purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner's training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal × kg-1 × min-1 during recovery, tempo, and race pace, respectively (p < .0001). Bland-Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner's recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal × kg-1 × min-1. Using the manufacturer's equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners.