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The accuracy of methods to determine resting energy expenditure (REE) contributes towards the adequate provision of nutritional support to hospitalized patients. Indirect calorimetry (IC) is considered the gold standard method to determine REE. The aim of this study is evaluated the degree of agreement between the REE measured by IC (REE-IC) and REE estimated by predictive equations in the intensive care unit patients, showing which could be used as an alternative METHODS: : The sample is made up of intensive care unit patients over the age of 18, both male and female, and undergoing nutritional therapy. The predictive equations to estimate REE was the Harris Benedict (HB), Ireton Jones (IJ) and practical method (PM). Degree of agreement between REE-predictive equations and REE-IC was analyzed by the interclass correlation coefficient and the Bland-Altman test RESULTS: : Average energy obtained by IC was significantly different from HB and IJ equations (p

Summary Background Accurate measurements of resting energy expenditure (REE) are important for determining nutritional needs in HIV patients. Indirect calorimetry (IC) is a noninvasive method that reflects REE but can be costly and is frequently calculated with predictive equations. Research suggests that REE obtained by predictive equations in people living with HIV/AIDS (PLWH) is inaccurate. The aim of the study is to develop and validate a new predictive equation of REE based on a population of PLWH. Methods Cross-sectional study including 164 PLWH (82 to develop and 82 to validate the equation). Multiple linear regression was used to determine the relationship between variables and to develop the new predictive equation. Intraclass correlation coefficient (ICC) and Bland–Altman methods were used to evaluate agreement between the new predictive equation and indirect calorimetry. Results A new predictive equation with an accuracy of 67% when compared with IC was developed. This equation included as covariates: fat free mass, antiretroviral therapy status and age. Conclusion A new equation to predict energy expenditure in PLWH was developed and validated. This formula can be used to estimate REE if IC is not available.

To individualize nutritional interventions for the prevention and treatment of malnutrition and sarcopenia, it is required to understand the nutritional needs of older adults. This study explores the nutritional needs of geriatric outpatients. We hypothesized that inadequate energy and protein intake is common in geriatric outpatients. Data were retrieved from 2 cohort studies encompassing community-dwelling older adults referred to geriatric outpatient mobility clinics in Amsterdam, The Netherlands and Melbourne, Australia. Indirect calorimetry and a food diary, respectively, were used to assess resting metabolic rate (RMR) and energy and protein intake. Total energy expenditure (TEE) was calculated by the RMR multiplied by an activity factor of 1.4. An energy deficit was defined as a relative difference >10% between TEE and energy intake. A protein deficit was defined as protein intake

Summary Background and aims: Caloric prescription based on resting energy expenditure (REE) measured with indirect calorimetry (IC) improves outcome and is the gold standard in nutritional therapy of critically ill patients. Until now continuous renal replacement therapy (CRRT) precluded the use of IC due to several mechanisms. We investigated the impact of CRRT on VCO2, VO2 and REE to facilitate indirect calorimetry during CRRT. Methods In 10 critically ill ventilated patient in need of continuous veno-venous hemofiltration (CVVH) using citrate predilution we performed IC in 4 different states: baseline, high dose, baseline with NaCl predilution and without CVVH. CO2 content of effluent fluid was measured by a point of care blood gas analyzer. Carbon dioxide production (VCO2) measured with IC was adapted by adding the CO2 flow of effluent and deducing CO2 flow in postdilution fluid to calculate a true VCO2. True REE was calculated with the Weir equation using the true VCO2. Results CO2 removal in effluent during baseline, high dose and NaCl predilution was respectively 24 mL/min, 38 mL/min and 23 mL/min. Together with the CO2 delivery by the postdilution fluid this led to an adaptation of REE respectively by 34 kcal/d or 2% (p = 0,002), 44 kcal/d or 3% (p = 0,002) and 33 kcal/d or 2% (p = 0,002). Compared to the true REE during baseline of 1935 ± 921 kcal/d, true REE during high dose was 1723 ± 752 kcal/d (p = 0.65), during NaCl predilution it was 1604 ± 633 kcal/d (p = 0.014) and without CRRT it was 1713 ± 704 kcal/d (p = 0.193). Conclusions CO2 alterations due to CVVH are clinically of no importance so no correction factor of REE is needed with or without CVVH. IC must be performed during CVVH as CVVH seems to alter metabolism. These changes may be mainly explained by the use of citrate predilution.

The activPAL is a valid measure of step counts and posture, but its ability to determine physical activity intensity is unclear. This study tested the criterion validity of the activPAL using its built-in linear cadence-metabolic equivalents (METs) equation (activPAL-linear) versus an individualized height-adjusted curvilinear cadence-METs equation (activPAL-curvilinear) to estimate intensity-related physical activity. Forty adults (25±6 years, 23.3±4.1 kg/m

Background: Smartphones with embedded sensors, such as accelerometers, are promising tools for assessing physical activity (PA), provided they can produce valid and reliable indices. The authors aimed to summarize studies on the PA measurement properties of smartphone accelerometers compared with research-grade PA monitors or other objective methods across the intensity spectrum, and to report the effects of different smartphone placements on the accuracy of measurements. Methods: A systematic search was conducted on July 1, 2019 in PubMed, Embase, SPORTDiscus, and Scopus, followed by screening. Results: Nine studies were included, showing moderate-to-good agreements between PA indices derived from smartphone accelerometers and research-grade PA monitors and/or indirect calorimetry. Three studies investigated measurement properties across smartphone placements, with small differences. Large heterogeneity across studies hampered further comparisons. Conclusions: Despite moderate-to-good agreements between PA indices derived from smartphone accelerometers and research-grade PA monitors and/or indirect calorimetry, the validity of smartphone monitoring is currently challenged by poor intermonitor reliability between smartphone brands/versions, heterogeneity in protocols used for validation, the sparsity of studies, and the need to address the effects of smartphone placement.

Background: Over 50% of adults in Latin America and the Caribbean have a body mass index (BMI) ≥ 25 suggesting excess energy intakes relative to energy expenditure. Accurate estimation of resting metabolic rate (RMR), the largest component of total energy requirements, is crucial to strategies aimed at reducing the prevalence and incidence of overweight and obesity. Aim: We evaluated the accuracies of established and locally developed RMR prediction equations (RMRP) among adults. Methods: Four hundred adult volunteers ages 20 to 65 years had RMR measured (RMRM) with a MedGem® indirect calorimeter according to recommended procedures. RMRP were compared to RMRM with values ± 10% of RMRM deemed accurate. Anthropometry was measured using standard procedure. Linear regression with bootstrap analyses was used to develop local RMRP equations based on anthropometric and demographic variables. The University of the West Indies Ethics Committee approved the study. Results: Males had higher mean absolute RMR ( p < 0.001) but similar mean age-adjusted measured RMR per kg of body (20.9 vs. 21.5 kcals/day; p = 0.1) to females. The top performing established anthropometry-based RMRP among participants by sex, physical activity (PA) level and BMI status subgroups were Mifflin-St Jeor, Owen, Korth, Harris–Benedict, and Livingston, while Johnstone, Cunningham, Müller (body composition (BC)), Katch and McArdle, Mifflin-St Jeor (BC) were the most accurate BC-based RMRP. Locally developed RMRP had accuracies comparable to their top-ranked established RMRP counterparts. Conclusions: Accuracies of established RMRP depended on habitual PA level, BMI status, BC and sex. Furthermore, locally developed RMRP provide useful alternatives to established RMRP.

Pediatric inflammatory bowel disease (IBD) is often associated with growth retardation due to malnutrition. However, knowledge on total energy expenditure (TEE), active-induced energy expenditure (AEE) and physical activity remains limited in children with IBD. Assessment of TEE using the doubly labelled water (DLW) method, resting energy expenditure (REE) using indirect calorimetry, and physical activity level using the actigraph GT3X+ in children with IBD (in remission) and healthy controls. TEE, REE, AEE and physical activity were measured in 21 children with IBD and 24 healthy controls at baseline. IBD children parameters were monitored further after 6 and 12 months. Predicted REE and TEE values (using Schoefield and the actigraph GT3X+, for REE and TEE respectively) were compared to measured values. Mean ages at baseline were 14.8 ± 1.5 and 13.2 ± 2 years in children with IBD and in healthy control children, respectively. Measured TEE DLW was significantly lower (P < 0.001) in children with IBD compared to the healthy control group. REE corrected by FFM 0.5 , REE and AEE were also significantly lower in children with IBD. Children with IBD had AEE of 17.5% of TEE and had a significantly higher sedentary behaviour as compared to healthy children. This study suggests that TEE and AEE are reduced in children with IBD in clinical remission which may result in a reduced moderate and vigorous physical activity level. Our result also highlights that the actigraph GT3X + might give good prediction of TEE in children with IBD at group level but it remains highly variable at individual level.

Purpose This study assessed how individuals compensate for energy expended during a 12-wk aerobic exercise intervention, elucidating potential mechanisms and the role exercise dose plays in the compensatory response. Participants and Design Three-arm, randomized controlled trial among sedentary adults age 18 to 40 yr, body mass index of 25 to 35. Groups included six exercise sessions per week, two sessions per week, and sedentary control. Methods Rate of exercise energy expenditure was calculated from a graded exercise test averaged across five heart rate zones. Energy compensation was calculated as the difference between expected weight loss (based on exercise energy expenditure) and changes in fat and fat-free mass (DXA). Resting energy expenditure was assessed via indirect calorimetry and concentrations of acylated ghrelin, leptin, insulin, and Glucagon-like peptide 1 (GLP-1) were assessed fasting and postprandial (six timepoints over 2 h). Results The 6-d·wk−1 group expended more energy (2753.5 kcal) and exercised longer (320.5 min) per week than the 2-d·wk−1 group (1490.7 kcal, 1888.8 min, P < 0.05), resulting in greater fat loss compared with the 2-d or control groups (P < 0.05). Exercise groups did not differ in the % or total kcal compensated. Greater decreases in area under the curve (AUC) for acylated ghrelin predicted greater fat loss, regardless of group, energy expended per week, exercise duration, or exercise intensity. Changes in leptin AUC was the only independent predictor for energy compensation, with a greater decrease in leptin AUC predicting less energy compensation. Exercise frequency, energy expended, duration, or intensity did not influence energy compensation. Conclusions Leptin is an important factor in successful weight loss through exercise, with greater postprandial decreases promoting less compensation. Greater amounts of exercise do not influence the compensatory response to an exercise-induced energy deficit.

AIMS/HYPOTHESIS: Growth hormone (GH) causes insulin resistance that is linked to lipolysis, but the underlying mechanisms are unclear. We investigated if GH-induced insulin resistance in skeletal muscle involves accumulation of diacylglycerol (DAG) and ceramide as well as impaired insulin signalling, or substrate competition between fatty acids and glucose.METHODS: Nine GH-deficient male participants were randomised and examined in a 2 × 2 factorial design with and without administration of GH and acipimox (an anti-lipolytic compound). As-treated analyses were performed, wherefore data from three visits from two patients were excluded due to incorrect GH administration. The primary outcome was insulin sensitivity, expressed as the AUC of the glucose infusion rate (GIRAUC), and furthermore, the levels of DAGs and ceramides, insulin signalling and the activity of the active form of pyruvate dehydrogenase (PDHa) were assessed in skeletal muscle biopsies obtained in the basal state and during a hyperinsulinaemic-euglycaemic clamp (HEC).RESULTS: Co-administration of acipimox completely suppressed the GH-induced elevation in serum levels of NEFA (GH versus GH+acipimox, p CONCLUSIONS/INTERPRETATION: GH-induced insulin resistance in skeletal muscle is: (1) causally linked to lipolysis; (2) not associated with either accumulation of DAGs and ceramides or impaired insulin signalling; (3) likely to involve substrate competition between glucose and lipid intermediates.TRIAL REGISTRATION: ClinicalTrials.gov NCT02782208 FUNDING: The work was supported by the Grant for Growth Innovation (GGI), which was funded by Merck KGaA, Darmstadt, Germany. Graphical abstract.

Background Data on the influence of age and body mass index (BMI) on energy metabolism of the critically ill are heterogeneous. Due to the increasingly aging critically ill population, investigation on age- and BMI-specific energy metabolism is relevant. Methods A total of 394 indirect calorimetry measurements were conducted on 348 critically ill adult medical patients, including 46 repeat measurements after 3.6 ± 4.3 days. Measured resting energy expenditure (MREE) was compared for age groups, BMI, and gender. Predicted energy expenditure (PEE) using the Penn State, Swinamer, and Ireton-Jones equations and the ACCP recommendations was also compared with MREE. Results The patients were 65.6 ± 14.5 years old. Their mean Acute Physiology and Chronic Health Evaluation II score was 27.6 ± 7.8. Mean BMI was 27.8 ± 8.4 kg/m2, and 25.6% were obese. MREE adjusted for ideal body weight decreased with increasing age, while it increased with increasing BMI. Age, BMI, and gender are independent determinants of MREE after adjusting for clinical factors (R2 = 0.34). All four prediction equations showed a proportional bias, with the Penn State equation performing acceptably. In 46 patients with repeat indirect calorimetry, there was no significant difference between the first and second MREE (p = 0.62). Conclusions Age, BMI, and gender are independent determinants of resting energy expenditure in critically ill adults. Variations between measured and predicted energy expenditure are considerable. Should prediction equations be used, their performance in the specific population should be taken into consideration. Repeat indirect calorimetry may not always be necessary. However, this may depend on the length of stay and the extent of stress.

Energy expenditure (EE) is the sum of metabolic activity within the body at a given time and comprises basal EE, diet-induced thermogenesis, and physical activity. In the intensive care unit, EE is most often assessed to determine a patient’s caloric requirements. Energy expenditure also may be useful to understand disease states and the metabolic impact of interventions. Several methods for estimating EE are relevant for clinical use, including indirect calorimetry, predictive equations, exhaled carbon dioxide volume, and the Fick method. Indirect calorimetry is the preferred method for evaluating EE and is considered the gold standard for estimating EE in hospitalized patients. However, use of indirect calorimetry is not always practical or possible. Therefore, other methods of estimating EE must be considered. In this review, methods of evaluating EE in critically ill adults are examined and the benefits and limitations of each method are discussed, with practical considerations for use.

Background LI85008F is a proprietary combination of leaf extracts of Moringa oleifera, Murraya koeingii, and extract of Curcuma longa rhizome. This herbal extract combination is an effective weight loss supplement for overweight and obese subjects. The present study aimed to investigate the thermogenic potential of the LI85008F in high-fat diet (HFD)-induced obese Sprague Dawley rats. Methods Seven rats received a regular diet (RD), and twenty-one rats received a high-fat diet (HFD) for 56 days. On day 28, the HFD-fed rats were randomized into three groups (n = 7). Starting from day 29 through day 56, one HFD-fed group received daily oral gavage of 0.5% Carboxymethylcellulose Sodium (CMC) alone (HFD), and the remaining two groups received 100 and 250 mg/kg LI85008F (LI85008F-100 and LI85008F-250, respectively). Body weight, fat mass, fat cell size, liver weight, liver triglyceride were measured. The energy metabolism parameters were measured using indirect calorimetry. In serum, the metabolic and endocrine markers were analyzed. The adipogenic and thermoregulatory proteins expression in the white adipose tissue (WAT) were analyzed using an immunoblot assay. Results Supplementation with both doses of LI85008F significantly increased resting energy expenditure (REE) in the obese rats. The LI85008F-250 rats showed significant up-regulation of uncoupling protein-1 (UCP-1) expression, as compared with the HFD rats. LI85008F significantly reduced body weight gain, fat mass, fat cell size, liver weight, and hepatic triglycerides. Serum triglyceride, total cholesterol, glucose, leptin, and fat cell markers were significantly reduced in LI85008F-supplemented rats compared to the HFD rats. Conclusion The present data suggest that LI85008F reduces body fat mass and controls body weight gain via increasing energy metabolism in combination with reduced lipogenesis in diet-fed obese rats.

To evaluate a) the magnitude of the increase in caloric consumption due to early mobilisation of patients with mechanical ventilation (MV) in Intensive Care Units (ICU) as part of routine care, b) whether there are differences in caloric consumption due to active or passive mobilisation, and c) whether early mobilisation in routine care would lead to additional nutritional requirements.Prospective, observational, multi-centre study.Medical, surgical and neurological ICUs from three centres.Patients on MV in ICU who were mobilised out of bed as part of routine care.Caloric consumption was assessed in 66 patients by indirect calorimetry at six time points: (1) lying in bed 5-10 min prior to mobilisation, (2) sitting on the edge of the bed, (3) standing beside the bed, (4) sitting in a chair, (5) lying in bed 5-10 min after mobilisation, and (6) 2 h after mobilisation. Differences in caloric consumption in every mobilisation level vs. the baseline of lying in bed were measured for 5 min and found to have increased significantly by: +0.4 (Standard Deviation (SD) 0.59) kcal while sitting on the edge of the bed, +1.5 (SD 1.26) kcal while standing in front of the bed, +0.7 (SD 0.63) kcal while sitting in a chair (all p 0.001). Active vs. passive transfers showed a higher, but non-significant consumption. A typical sequence of mobilisation including sitting on edge of the bed, standing beside the bed, sitting in a chair (20 min) and transfer back into bed, would require an additional 4.56 kcal compared to caloric consumption without mobilisation.Based on this data, routine mobilisation of MV patients in ICU increases caloric consumption, especially in active mobilisation. Nevertheless, an additional caloric intake because of routine mobilisation does not seem to be necessary.

NEW FINDINGS What is the central question of this study? Repeated heat exposure during the summer months can enhance heat loss in humans (seasonal heat acclimatisation), but does the magnitude of that enhancement differ between young and older adults when assessed during passive heat exposure? What is the main finding and its importance? While seasonal heat acclimatisation enhanced evaporative heat loss (i.e. sweating) in both young and older adults, those improvements led to a greater reduction in body heat storage in older adults. These outcomes indicate that heat acclimatisation may confer greater thermoregulatory benefits with increasing age. ABSTRACT Repeated heat exposure throughout summer can enhance heat loss in humans (seasonal heat acclimatisation), although the effect of ageing on those improvements remains unclear. We therefore sought to assess thermoregulatory function in young and older adults during environmental heat exposure prior to and following seasonal heat acclimatisation, hypothesizing that the magnitude of adaptation would be greater in older relative to young adults. To achieve this, 14 young (19-27 years) and 10 older adults (55-72 years), who resided in a temperate humid-continental climate, completed a 3 h resting heat exposure (44°C, ∼30% relative humidity) in the winter-spring months as part of a larger investigation (pre-acclimatisation), before being re-evaluated using the same heat stress test following the summer months (post-acclimatisation). Whole-body dry and evaporative heat exchange, and metabolic rate were measured throughout using direct and indirect calorimetry (respectively), and used to quantify body heat storage (metabolic rate + dry heat gain - evaporative heat loss). Evaporative heat loss increased in both groups following acclimatisation, but those improvements led to a decrease in body heat storage in older (mean difference (95% CI); 213 (295, 131) kJ; P

Abstract. Some studies have reported inaccuracy of predicting basal metabolic rate (BMR) by using common equations for Asian people. Thus, this study was undertaken to develop new predictive equations for the Iranian community and also to compare their accuracy with the commonly used formulas. Anthropometric measures and thyroid function were evaluated for 267 healthy subjects (18–60 y). Indirect calorimetry (InCal) was performed only for those participants with normal thyroid function tests (n = 252). Comparison of predicted RMR (both kcal/d and kcal.kg.wt−1.d−1) using current predictive formulas and measured RMR revealed that Harris-Benedict and FAO/WHO/UNU significantly over-estimated and Mifflin-St. Jeor significantly under-estimated RMR as compared to InCal measurements. In stepwise regression analysis for developing new equations, the highest r2 (=0.89) was from a model comprising sex, height and weight. However, further analyses revealed that unlike the subjects under 30 y, the association between age and the measured RMR in subjects 30 y and plus was negative (r = −0.241, p = 0.001). As a result, two separate equations were developed for these two age groups. Over 80 percent of variations were covered by the new equations. In conclusion, there were statistical significant under- and over-estimation of RMR using common predictive equations in our subjects. Using the new equations, the accuracy of the calculated RMR increased remarkably.

Purpose of review The prevalence and burden of obesity has reached alarming levels. The assessment of human energy expenditure enables the identification of obesity-prone and obesity-resistant individuals and helps to explain the short and long-term success of weight loss treatments. In this review, we describe the state-of-the-art methods used in the assessment of human energy expenditure and the impact of dietary intake on the interpretation of the data. Recent findings The reference techniques to assess energy expenditure in humans have not significantly changed during the last century. Today, indirect calorimetry, either using a metabolic chamber or a metabolic cart, is the favored method to assess human energy expenditure and is the only method enabling the assessment of macronutrient oxidation. The doubly labeled water method however provides accurate assessment of human energy expenditure under free living conditions. Summary Although energy expenditure and macronutrient oxidation can be assessed by simple calculations from oxygen consumption and carbon dioxide production, these calculations can provide erroneous results or require corrections and/or more complex interpretation when several biochemical pathways are simultaneously engaged. Such physiological mechanisms are often elicited by dietary interventions including, among other, gluconeogenesis, lipogenesis, ketogenesis, alcohol oxidation and under or overfeeding.

Interrupting sedentary behaviour with regular activity breaks benefits glycaemic control; however, the influence of the energy utilised during these activity breaks on postprandial metabolic response is relatively unknown. Therefore, the aim of this study was to investigate whether the energy utilisation of regular (every 30 min) short (1 min 40 s or 2 min) activity breaks was associated with the lowering of postprandial glycaemia, insulinemia and lipidemia. Using separate data from two previously performed studies (ALPhA Study n = 65, age 25.7 (5.2) y, 40% male, BMI 23.6 (4.1) kg · m−2. ABPA study n = 35, age 25.1 (3.7) y, 31% male, BMI 23.4 (3.2) kg · m−2) we investigated the association between energy utilisation (measured by indirect calorimetry) and postprandial glucose, insulin and triglycerides during prolonged sitting, and regular activity breaks.Results Mixed effects regression models indicated that energy utilisation was not consistently associated with postprandial glucose, insulin or triglyceride responses (p > 0.05 for all). Additionally, there was some indication that energy utilisation was obscuring (mildly suppressing) the effects of regular activity breaks on glucose, insulin and triglyceride iAUC.Conclusions If energy utilisation does not mediate the association between regular activity breaks and postprandial glycaemic response, it is possible that it is the frequency of the activity breaks that is beneficial.

We sought to assess the accuracy of current or developing new prediction equations for resting metabolic rate (RMR) in adolescent athletes. RMR was assessed via indirect calorimetry, alongside known predictors (body composition via dual-energy X-ray absorptiometry, height, age, and sex) and hypothesized predictors (race and maturation status assessed via years to peak height velocity), in a diverse cohort of adolescent athletes (n = 126, 77% male, body mass = 72.8 ± 16.6 kg, height = 176.2 ± 10.5 cm, age = 16.5 ± 1.4 years). Predictive equations were produced and cross-validated using repeated k-fold cross-validation by stepwise multiple linear regression (10 folds, 100 repeats). Performance of the developed equations was compared with several published equations. Seven of the eight published equations examined performed poorly, underestimating RMR in >75% to >90% of cases. Root mean square error of the six equations ranged from 176 to 373, mean absolute error ranged from 115 to 373 kcal, and mean absolute error SD ranged from 103 to 185 kcal. Only the Schofield equation performed reasonably well, underestimating RMR in 51% of cases. A one- and two-compartment model were developed, both r2 of .83, root mean square error of 147, and mean absolute error of 114 ± 26 and 117 ± 25 kcal for the one- and two-compartment model, respectively. Based on the models’ performance, as well as visual inspection of residual plots, the following model predicts RMR in adolescent athletes with better precision than previous models; RMR = 11.1 × body mass (kg) + 8.4 × height (cm) − (340 male or 537 female).

Decline in skeletal muscle mitochondrial oxidative capacity (MOC) is associated with reduced aerobic capacity and increased risk of cardiovascular and metabolic disease. Measuring skeletal muscle MOC may be an alternative method to assess aerobic capacity, especially for individuals unable to perform a whole-body maximum oxygen uptake protocol. In this study, linear regression analysis in two leg muscles was performed to determine whether MOC values could be used to predict whole-body peak oxygen uptake. MOC was measured with near infrared spectroscopy (NIRS) in the medial gastrocnemius (MG) and vastus lateralis (VL) muscles of 26 participants (age, 27.1 ± 5.8 years old). Whole-body peak oxygen uptake (VO2 peak) was determined by indirect calorimetry during a continuous ramp protocol on a cycle ergometer. VO2 peak values were significantly correlated with the muscle recovery rate constant (k) of the MG (kMG, r = 0.59; p

PURPOSE This study aimed to develop cadence-based metabolic equations (CME) for predicting the intensity of level walking and evaluate these CME against the widely adopted American College of Sports Medicine (ACSM) Metabolic Equation, which predicts walking intensity from speed and grade. METHODS Two hundred and thirty-five adults (21-84 yr of age) completed 5-min level treadmill walking bouts between 0.22 and 2.24 m·s, increasing by 0.22 m·s for each bout. Cadence (in steps per minute) was derived by dividing directly observed steps by bout duration. Intensity (oxygen uptake; in milliliters per kilogram per minute) was measured using indirect calorimetry. A simple CME was developed by fitting a least-squares regression to the cadence-intensity relationship, and a full CME was developed through best subsets regression with candidate predictors of age, sex, height, leg length, body mass, body mass index (BMI), and percent body fat. Predictive accuracy of each CME and the ACSM metabolic equation was evaluated at normal (0.89-1.56 m·s) and all (0.22-2.24 m·s) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL·kg·min). RESULTS On average, the simple CME predicted intensity within ~1.8 mL·kg·min (~0.5 METs) at normal walking speeds and with negligible (

BACKGROUND Nutrition therapies in children with congenital heart disease (CHD) after cardiopulmonary bypass (CPB) is crucial, but energy and protein requirements remain undefined. We assessed energy and protein requirements, with nitrogen kinetics and clinical outcomes, in infants with complex CHD following CPB. METHODS Infants were randomized to control (1.3 g/kg/d), moderate protein (MP, 2.5 g/kg/d), or high protein (HP, 4 g/kg/d) groups. Resting energy expenditure (REE) was measured 6 hours post-CPB and then at 24-hour intervals, using indirect calorimetry to formulate energy intakes. Enteral formula feeding was initiated 6 hours post-CPB and continued for 5 days. Nitrogen balance (NB); urea nitrogen waste and nitrogen retention; serum prealbumin level; and hepatic, renal, and cardiac function were measured daily. Mid-upper arm circumference and triceps skinfold were measured preoperatively and 5 days after CPB. Adverse outcomes (bacterial infection, reintubation, and cardiac intensive care unit (CICU) stay > 8 days) were recorded. RESULTS REE was not different across the 3 groups (P = .37). It declined from 62 ± 6 to 57 ± 7 kcal/kg/d over 5 days post-CPB (P = .02). NB and nitrogen retention became positive by day 3 in the HP group but remained negative in the other 2 groups (P = .045-.003), despite higher urea nitrogen waste in the HP group (P < .0001). The HP group had a greater increase in serum prealbumin level and anthropometric measures (P = .009-.03). Other measures were not significantly different across the 3 groups. CONCLUSIONS In infants with complex CHD in the first 5 days post-CPB, protein and energy intakes of ≈4 g/kg/d and 60 kcal/kg/d, respectively, led to improved nutrition outcomes without increased adverse events.

Summary Background & aims Indirect calorimetry (IC) is the only way to measure in real time energy expenditure (EE) and to optimize nutrition support in acutely and chronically ill patients. Unfortunately, most of the commercially available indirect calorimeters are rather complex to use, expensive and poorly accurate and precise. Therefore, an innovative device (Q-NRG®, COSMED, Rome, Italy) that matches clinicians’ needs has been developed as part of the multicenter ICALIC study supported by the two academic societies ESPEN and ESICM. The aim of this study was to evaluate the accuracy and intra- and inter-unit precision of this new device in canopy dilution mode in vitro and in spontaneously breathing adults. Methods Accuracy and precision of oxygen consumption (VO2) and carbon dioxide production (VCO2) measurements were evaluated in vitro and in 15 spontaneously breathing healthy adults by interchanging three Q-NRG® units in a random order. In vitro validation was performed by gas exchange simulation using high-precision gas mixture and mass flow controller. Accuracy was calculated as error of measured values against expected ones based on volume of gas infused. Respiratory coefficient (RQ) accuracy was furthermore assessed using the ethanol-burning test. To evaluate the intra- and inter-unit precisions, the coefficient of variation (CV% = SD/Mean*100) was calculated, respectively, from the mean ± SD or the mean ± SD of the three mean values of VO2, VCO2, RQ and EE measured by each Q-NRG® units. In vivo accuracy measurement of the Q-NRG® was assessed by simultaneous comparison with mass spectrometry (MS) gas analysis, using Bland-Altman plot, Pearson correlation and paired t-test (significance level of p = 0.05). Results In vitro evaluation of the Q-NRG® accuracy showed measurement errors Conclusion Both in vitro and in vivo measurements of VO2, VCO2, RQ and EE on three Q-NRG® units showed minimal differences compared to expected values and MS and very low intra- and inter-unit variability. These results confirm the very good accuracy and precision of the Q-NRG® indirect calorimeter in canopy dilution mode in spontaneously breathing adults.

Summary Background and aims Cervical spinal cord injuries (CSCI) are frequently complicated by respiratory failure requiring prolonged invasive mechanical ventilation in the intensive care unit (ICU). Providing adequate nutrition may be an important factor in the recovery of respiratory muscle function for ventilator weaning. The aim of this study was to examine the practical implementation of a multi-disciplinary approach to nutrition combining indirect calorimetry and the modified Harris Benedict equation to achieve target rates of nutrition for patients with CSCI. Materials and methods A retrospective observational study was performed by collecting data of normal nutrition practice in a series of adult ventilated patients with CSCI admitted between 2014 and 2017 to the ICU. Administered calories by enteral nutrition and measured total energy expenditure (TEE) by indirect calorimetry were recorded for the first 3-weeks. Calculations were performed to measure the adequacy of calorie administration relative to TEE. Average daily temperatures and minute ventilation were recorded to support evidence for hypermetabolism. TEE estimates using the modified Harris Benedict equation were compared to indirect calorimetry measures for each patient. Results Sixteen patients were included in the study. Calorie administration rapidly increased to a plateau of 2300–2400 kcal per day over the first four days. The median measured TEE by indirect calorimetry was initially high, starting at 3472 kcal/day and decreasing to 2784 kcal/day at three weeks. However, there was wide variation in energy expenditure amongst patients. Average daily temperatures and minute ventilation were high supporting hypermetabolism. Adequacy of calorie administration to TEE ranged between 76 and 86 percent through the study period. There was relatively wide variation when comparing estimates of TEE using the modified Harris Benedict equation versus indirect calorimetry. Conclusions A multi-disciplinary approach to nutrition in ventilated patients with CSCI, incorporating indirect calorimetry, achieves target rates of nutrition. Our findings suggest that a hypermetabolic response may be common but variable in this population and subsequently both under and over feeding may be a risk if nutrition targets are not guided by indirect calorimetry. Further prospective research using protocoled indirect calorimetry measures would be beneficial to ascertain accurate energy requirements for this group of patients and also determine whether feeding to target influences weaning off the ventilator.

Due to the nature of micro-electromechanical systems, the vector magnitude (VM) activity of accelerometers varies depending on the wearing position and does not identify different levels of physical fitness. Without an appropriate energy expenditure (EE) estimation equation, bias can occur in the estimated values. We aimed to amend the EE estimation equation using heart rate reserve (HRR) parameters as the correction factor, which could be applied to athletes and non-athletes who primarily use ankle-mounted devices. Indirect calorimetry was used as the criterion measure with an accelerometer (ankle-mounted) equipped with a heart rate monitor to synchronously measure the EE of 120 healthy adults on a treadmill in four groups. Compared with ankle-mounted accelerometer outputs, when the traditional equation was modified using linear regression by combining VM with body weight and/or HRR parameters (modified models: Model A, without HRR; Model B, with HRR), both Model A (r: 0.931 to 0.972; ICC: 0.913 to 0.954) and Model B (r: 0.933 to 0.975; ICC: 0.930 to 0.959) showed the valid and reliable predictive ability for the four groups. With respect to the simplest and most reasonable mode, Model A seems to be a good choice for predicting EE when using an ankle-mounted device.

An adverse maternal in utero environment can program offspring for increased risk for metabolic disease. The aim of this study was to determine whether N-acetylcysteine (NAC), an anti-inflammatory antioxidant, attenuates programmed susceptibility to obesity and insulin resistance in high fat diet (HFD) offspring. CD1 female mice were acutely fed a standard breeding chow or HFD. NAC was added to the drinking water (1g/kg) of the treatment cohorts from embryonic day 0.5 (e0.5) until the end of lactation. NAC treatment normalized HFD-induced maternal weight gain and oxidative stress, improved the maternal lipidome and prevented maternal leptin resistance. These favorable changes in the in utero environment normalized postnatal growth, decreased white adipose tissue (WAT) and hepatic fat, improved glucose and insulin tolerance and antioxidant capacity, reduced leptin and insulin and increased adiponectin in HFD offspring. The lifelong metabolic improvements in the offspring were accompanied by reductions in pro-inflammatory gene expression in liver and WAT and increased thermogenic gene expression in brown adipose tissue (BAT). These results, for the first time, provide a mechanistic rationale for how NAC can prevent the onset of metabolic disease in the offspring of mothers who consume a typical Western HFDs.

Maternal stress during pregnancy exposes fetuses to hyperglucocorticoids, which increases the risk of metabolic dysfunctions in offspring. Despite being a key tissue for maintaining metabolic health, the impacts of maternal excessive glucocorticoids (GC) on fetal brown adipose tissue (BAT) development and its long-term thermogenesis and energy expenditure remain unexamined. For testing, pregnant mice were administered dexamethasone (DEX), a synthetic GC, in the last trimester of gestation, when BAT development is the most active. DEX offspring had glucose, insulin resistance, and adiposity and also displayed cold sensitivity following cold exposure. In BAT of DEX offspring, Ppargc1a expression was suppressed, together with reduced mitochondrial density, and the brown progenitor cells sorted from offspring BAT demonstrated attenuated brown adipogenic capacity. Increased DNA methylation in Ppargc1a promoter had a fetal origin; elevated DNA methylation was also detected in neonatal BAT and brown progenitors. Mechanistically, fetal GC exposure increased GC receptor/DNMT3b complex in binding to the Ppargc1a promoter, potentially driving its de novo DNA methylation and transcriptional silencing, which impaired fetal BAT development. In summary, maternal GC exposure during pregnancy increases DNA methylation in the Ppargc1a promoter, which epigenetically impairs BAT thermogenesis and energy expenditure, predisposing offspring to metabolic dysfunctions.

PURPOSE A reduced resting metabolic rate (RMR) ratio and suppressed total triiodothyronine (TT3 ) have been demonstrated to reflect metabolic compensation to chronic energy deficiency. However, it is unknown whether the relationship between RMR ratio and TT3 remains constant over time. OBJECTIVE To examine the relationship between RMR ratio and TT3 in free-living exercising, ovulatory, weight-stable women (n = 14) for a 12-month observational period. METHODS Dual-energy X-ray absorptiometry (DXA) and indirect calorimetry provided data on anthropometrics and energy expenditure. Harris-Benedict, DXA, and Cunningham (1980 and 1991) equations estimated RMR and RMR ratio (measured RMR/predicted RMR). Repeated measures analysis assessed changes over time (ANOVA and Friedman). Generalized linear modeling tested whether RMR ratio threshold predicted TT3 > 73.2 ng/dL or TT3 > 80 ng/dL over 12-months. RESULTS Women were 25.9 ± 5.4 years, weighed 59.6 ± 5.2 kg with BMI 22.3 ± 1.4 kg/m2 at baseline, which remained constant throughout the study (weight: P = .523; BMI: P = .511). There was no significant effect of time for RMR (P = .886), TT3 (P = .890), energy availability (P = .212), and RMR ratio (Harris-Benedict: P = .852; DXA: P = .607; Cunningham1980 : P = .754; Cunningham1991 : P = .739). When TT3 > 73.2 ng/dL, each RMR ratio threshold (Harris-Benedict: P = .021; DXA: P = .019; Cunningham1980 : P = .019; Cunningham1991 : P = .016) significantly predicted participants as energy replete; however, when using a more lenient clinical TT3 threshold of >80 ng/dL, only the DXA ratio threshold yielded a significant prediction of TT3 (P

The purpose of the present study was to compare next-morning responses of RMR and appetite to pre-sleep consumption of casein protein (CP) in pre- and postmenopausal women. The study was a randomised, crossover, double-blind, placebo-controlled trial. Seven sedentary premenopausal (age: 19·9 (sd 1·2) years; BMI: 23·1 (sd 2·6) kg/m2) and seven sedentary postmenopausal (age: 56·4 (sd 4·9) years; BMI: 26·3 (sd 3·5) kg/m2) women participated. During visit one, anthropometrics and body composition were measured. Following visit one, subjects consumed either CP (25 g) or placebo (PL) ≥2 h after their last meal and ≤30 min prior to sleep on the night before visits two and three. Visits two and three occurred ≥1 week after visit one and were 48 h apart. During visits two and three, RMR (VO2), RER and appetite were measured via indirect calorimetry and visual analogue scale, respectively. Anthropometrics and body composition were analysed by one-way ANOVA. RMR and measures of appetite were analysed using a 2 × 2 (menopause status × CP/PL) repeated-measures ANOVA. Significance was accepted at P ≤ 0·05. RMR was significantly lower in postmenopausal compared with premenopausal women under both conditions (P = 0·003). When consumed pre-sleep CP did not alter RMR, RER or appetite compared with PL when assessed next morning in pre- and postmenopausal women. These data contribute to growing evidence that pre-sleep consumption of protein is not harmful to next-morning metabolism or appetite. In addition, these data demonstrate that menopause may not alter next-morning RMR, RER or appetite after pre-sleep consumption of CP.

A study using indirect calorimetry and 12 lactating multiparous Jersey cows (53 ± 23 d in milk at the beginning of the experiment; mean ± standard deviation) was conducted to evaluate the utilization of energy in cattle consuming diets containing increasing hydrolyzed feather meal (HFM). A triplicated 4 × 4 Latin square design with 35-d periods (28-d adaption and 4-d collections) was used to compare 4 different dietary treatments. Treatments contained (DM basis) HFM at 0% (0HFM), 3.3% (3.3HFM), 6.7% (6.7MFM), and 10.0% (10HFM). Diets were formulated such that HFM replaced blood meal and nonenzymatically browned soybean meal. With increasing HFM, linear increases were observed for dietary NEL content (1.61, 1.64, 1.69, and 1.70 ± 0.042 Mcal/kg of DM for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), and the efficiency of converting ME to NEL (0.708, 0.711, 0.717, and 0.719). Apparent total-tract digestibility of CP linearly decreased with increasing HFM (63.4, 61.1, 59.9, and 58.6 ± 1.46% for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), whereas long-chain fatty acid digestibility increased with increasing HFM (77.2, 77.7, 78.5, and 80.6 ± 1.30%). With increased inclusion of HFM, fecal N excretion increased (199, 230, 239, 237 ± 12.1 g/d for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), whereas urinary N excretion decreased (166, 151, 155, and 119 ± 14.8 g/d). Increasing the concentration of HFM resulted in a quadratic effect on DMI (19.6, 20.2, 20.3, and 19.1 ± 0.79 kg/d for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively) and milk yield (31.7, 32.0, 31.9, and 29.7 ± 1.32 kg/d). Increasing HFM linearly decreased the milk protein concentration (3.34, 3.29, 3.23, and 3.23 ± 0.158 for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively) and yield (1.05, 1.05, 1.02, and 0.96 ± 0.040 kg). The inclusion of HFM did not affect energy-correct milk yield (average of 39.3 ± 1.54). Results of this study suggest that HFM can increase dietary NEL content compared with blood meal and nonenzymatically browned soybean meal and maintained energy-corrected milk yield; however, feeding HFM at greater than 6.7% of diet DM decreased DMI, and protein availability may have been reduced with increased HFM, leading to a linear decrease in milk protein concentration and yield.

Aims/Introduction In Japan, an ideal bodyweight (IBW) calculated by 22 × height (m)2 has commonly been used in the planning of medical nutrition therapy (MNT). However, there have been concerns regarding calorie deficits in fulfilling resting energy expenditure (REE) for patients with type 2 diabetes undergoing MNT as defined by 25 kcal/kg IBW/day. The objective of the present study was to measure REE in patients with type 2 diabetes and verify the validity of MNT with 25 kcal/kg IBW/day. Materials and Methods A retrospective cross‐sectional study was carried out in 52 patients with type 2 diabetes (mean age was 65.9 ± 7.3 years, bodyweight 65.0 ± 11.3 kg, body mass index 24.9 ± 3.8 kg/m2). REE was measured by indirect calorimetry. Results The mean REE was 1,601.0 ± 253.1 kcal/day. Assuming that all patients strictly observed daily energy intake as 25 kcal/kg IBW/day, 41 of 52 patients (78.9%) did not reach their REE. The greater the bodyweight, the greater the difference between assumed energy intake as 25 kcal/kg IBW and REE. Conclusions We call attention to the potential risk of total dietary energy intake set to 25 kcal/kg IBW/day. Clinicians should carefully plan MNT to not fall below a patient’s REE to prevent sarcopenia and ensure MNT continuity., Assuming that all patients with type 2 diabetes strictly observed daily energy intake as 25 kcal/kg ideal bodyweight/day, 41 of 52 patients (78.9%) did not reach their REE. The greater the bodyweight, the greater the difference between assumed energy intake as 25 kcal/kg ideal bodyweight and REE.

The basal metabolic rate (BMR) of children aged

Background and Aim:An accurate estimation of Resting Energy Expenditure (REE) in patients with obesity is crucial. Therefore, our aim was to assess the validity of REE predictive equations based on body composition variables in treatment-seeking Arab adults with obesity.Methods:Body composition and REE were measured by Tanita BC-418 bioimpedance and Vmax Encore 229 IC, respectively, and predictive equations based on fat mass and fat-free mass were used in REE estimations among 87 adults of both genders, in the Outpatient Clinic in the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). The mean differences between the measured and estimated REE values were calculated to assess the accuracy, and the Bland-Altman method was used to assess the level of agreement.Results:Ten predictive equations were included. In males, all the predictive equations gave significantly different estimates of REE when compared to that measured by IC. On the other hand, in females, the mean difference between the REE value estimated by Huang and Horie-Waitzberg equations and that measured using IC was not significant, and the agreement was confirmed using Bland-Altman plots.Conclusion:Huang and Horie-Waitzberg equations are suggested for accurate REE estimation in females; however, new validated REE estimation equations for males in this population are still needed.

Background Nutrition therapy plays a major role in the perioperative management of surgical patients. Understanding energy metabolism and correctly establishing the adequate energy needs is a crucial step to provide optimal nutrition care. The aim of this study was to assess the resting energy expenditure (REE) after major abdominal procedures and its associated factors. Methods This was a prospective observational study conducted at a single center. REEs of patients admitted for gastrointestinal surgical procedures were measured by indirect calorimetry 24 hours prior to the procedure and reassessed at least once within the fifth postoperative day. Substrate oxidation was calculated according to the Frayn equation. Nutrition status was evaluated using subjective global assessment. Results There were no significant changes in the REEs throughout the study period; however, there was a decrease in the respiratory quotient during the postoperative period, as well as a decrease in carbohydrate oxidation and an increase in lipid oxidation. Only 33.3% of the patients presented a postoperative increase in REE > 10%. Those patients presented higher blood-monocyte levels. Conclusion Postoperative REE is not increased in most of the patients. In patients who had increased REE, associated factors included higher levels of monocytes.

Weight homeostasis is complex in Parkinson's disease (PD) and body weight changes substantially throughout the course of the disease. We designed a case-control study to i) investigate whether PD is associated with changes in resting energy expenditure (REE), ii) to assess the accuracy of REE predictive equations for healthy people in PD and iii) to eventually construct a new formula. Measured REE (mREE) was compared between 122 PD patients and 122 gender and body mass index (BMI)-matched controls. The accuracy of estimated REE by 5 common equations (Harris/Benedict-1919, Harris/Benedict-1984, Mifflin St. Jeor, WHO/FAO and aggregate formula) was investigated in PD using Bland-Altman analysis and reported as the frequency of accurate predictions (±10%). Concordance correlation coefficients (CCC) were also calculated. Then, we regressed a new REE equation - using gender, age, weight, height and Hoehn-Yahr stage - and validated it in an independent sample (N=100). No significant difference in mREE was recorded between the whole PD sample and healthy controls. However, mREE was increased in patients with BMI≥30 kg/m2 and Hoehn-Yahr stage≥3. Available REE equations showed limited accuracy (accurate prediction [±10%] frequency, PD patients are not commonly characterized by an increase in REE. This is limited to patients suffering from obesity and more severe disease. Common REE equations appear to be inaccurate. The new formula provided better REE estimates and its use can be proposed.

Context: The impact of mechanical ventilation on energy expenditure after spinal cord injury (SCI) is sparse. The objective of this case-series is to measure 15-minutes resting metabolic rate (RMR) to determine 24-hours measured-RMR (m-RMR) using QUARK indirect calorimeter (IC) and; compare the m-RMR with estimated RMR (e-RMR) using four commonly used predictive equations (Harris-Benedict, Mifflin St-Jeor, Henry and Schofield). Findings: We measured the RMR of four patients with SCI (one male and three female; mean age: 58.3 years) all with complete tetraplegia (ISNCSCI A) twice in a one-week interval using an IC with two sampling flow settings during a six month period. The median (IQ) of all m-RMRs was 1094 (340.2) kcal/day. The median m-RMR was 40.1% lower than the median calculated with four different e-RMRs using predictive equations. All four predictive equations overestimated RMR in SCI patients requiring mechanical ventilation by 4.1–61.1% (Harris-Benedict: 28.8–60.6%; Mifflin St-Jeor: 6.9–61.1%; Henry: 4.1–58.9% and; Schofield: 6–54.6%). Conclusion/clinical relevance: There is a high variability of e-RMR and m-RMR in patients with SCI who are dependent on mechanical ventilation. The use of predictive equations may lead to over-estimation of energy requirements. To avoid overfeeding we recommended measuring RMR using IC wherever possible. A further study with a larger sample size is needed due to the small number of subjects in our case-series. Development of a validated RMR equation in the SCI population is warranted

The authors would like to thank all the participants that took part of the study for their time and effort. This study is part of a Ph.D. Thesis conducted in the Biomedicine Doctoral Studies of the University of Granada, Spain. We are grateful to Dr. Ángel Gutiérrez and Alejandro De la O for all their support in the study. We are grateful to Ms. Ana Yara Postigo-Fuentes for her assistance with the English language., The aim of the present study was to investigate the relationship of sleep quality and time with basal metabolic rate (BMR) and fuel oxidation in basal conditions and during exercise in sedentary middleaged adults. We also studied the mediation role of dietary intake and adherence to the traditional Mediterranean Diet in the relationship between sleep parameters and energy metabolism parameters.A secondary analysis of the FIT-AGEING study was undertaken. 70 middle-aged sedentary adults (40–65 years old) participated in the present study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and wrist accelerometers (ActiSleep, Actigraph, Pensacola, Florida, USA) for 7 consecutive days. BMR was measured with indirect calorimetry and fuel oxidation was estimated through stoichiometric equations. Maximal fat oxidation was determined by a walking graded exercise test and dietary intake with 24 h recalls. Adherence to the traditional Mediterranean diet was assessed through the PREDIMED questionnaire. PSQI global score (poor sleep quality) was associated with lower basal fat oxidation (BFox), both expressed in g/min and as a percentage of BMR, independently of confounders. We did not find any association between other sleep and energy metabolism parameters. No mediating role of the dietary intake or PREDIMED global score was observed in the association of PSQI and BFox. In conclusion, our study showed that a subjective poor sleep quality was associated with lower BFox, which is not mediated by dietary intake in sedentary adults., The study was supported by the Spanish Ministry of Education (FPU14/04172 and FPU15/03960), by the University of Granada UGR Research and Knowledge Transfer Fund (PPIT) 2016 (Excellence Actions Programme. Units of Scientific Excellence: Scientific Unit of Excellence on Excercise and Health [UCEES]) and Plan Propio de Investigación 2019 - Programa Contratos-Puente, by the Regional Government of Andalusia, Regional Ministry of Economy, Knowledge, Entreprises and University, by the European Regional Development Fund (ERDF), ref. SOMM17/6107/UGR and by Redes Temáticas de Investigación Cooperativa RETIC grant Red SAMID RD16/0022.

Indirect calorimetry probes the relationship between fuel consumed and energy produced, and in doing so provides an estimation of whole-body energy expenditure and fuel preference. When assayed continuously in real-time, rhythms appear and illuminate the temporal regulation of energy metabolism by the circadian clock. Here we describe a method for recording circadian energy metabolism in mice using indirect calorimetry-enabled metabolic cages, encompassing mouse entrainment, experimental design, data acquisition and analysis, troubleshooting of common problems, and important considerations. This method is adaptable to the end user's equipment and serves as an effective tool to study, for example, mutant mice, dietary interventions, drug treatments, or circadian disruption.

ContextEnergy expenditure predictive equations can generate inaccurate estimates for overweight or obese individuals.ObjectiveThe objective of this review was to determine which predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) have the lowest bias and the highest precision in adults with overweight and obesity.Data SourcesSearches were performed in January 2022 in MEDLINE, Web of Science, Scopus, CENTRAL, and the gray literature databases.Data ExtractionMeta-analyses were performed with equations included in more than 1 study. The DerSimonian and Laird random-effects model and the I2 statistic were used to quantify heterogeneity in the quantitative analyses. The Egger test was performed to assess potential publication biases, and metaregressions were conducted to explore the heterogeneity. Findings were presented separated by participants’ body mass index classification (overweight and obesity).Data AnalysisSixty-one studies were included. The FAO/WHO/UNU (1985) equation, which uses only body weight in its formula, showed the lowest bias in estimating REE (mean difference [MD] = 8.97 kcal; 95% CI = –26.99; 44.94). In the subgroup analysis for individuals with obesity, the Lazzer (2007) equation showed the lowest bias (MD = 4.70 kcal; 95% CI = –95.45; 104.86). The Harris–Benedict equation (1919) showed the highest precision values for individuals with overweight (60.65%) and for individuals with obesity (62.54%). Equations with body composition data showed the highest biases. The equation proposed by the Institute of Medicine (2005) showed the lowest bias (MD = –2.52 kcal; 95% CI = –125.94; 120.90) in estimating the TEE. Most analyses showed high heterogeneity (I2 > 90%). There was no evidence of publication bias.ConclusionFor individuals with overweight, the FAO/WHO/UNU (1985) and the Harris–Benedict equations (1919) showed the lowest bias and the highest precision in predicting the REE, respectively. For individuals with obesity, the Harris–Benedict equation (1919) showed the highest precision and the Lazzer equation (2007) showed the lowest bias. More studies are needed on predictive equations to estimate the TEE.Systematic Review RegistrationPROSPERO registration no. CRD42021262969.

Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure. Energy expenditure (EE) estimated by ventilator-derived carbon dioxide consumption (EEVCORetrospective study of a cohort of critically ill adult patients with COVID-19 requiring mechanical ventilation and artificial nutrition to compare energy estimations by three methods through the calculation of bias and precision agreement, reliability, and accuracy rates.In 58 mechanically ventilated patients, a total of 117 paired measurements were obtained. The mean estimated energy derived from weight-based calculations was 2576 ± 469 kcal/24 h, as compared with 1507 ± 499 kcal/24 h when EE was estimated by IC, resulting in a significant bias of 1069 kcal/day (95% CI [-2158 to 18.7 kcal]; P 0.001). Similarly, estimated mean EEVCOThe energy estimated with EEVCO

Drosophila melanogaster is a leading genetic model for studying the neural regulation of sleep. Sleep is associated with changes in behavior and physiological state that are largely conserved across species. The investigation of sleep in flies has predominantly focused on behavioral readouts of sleep because physiological measurements, including changes in brain activity and metabolic rate are less accessible. We have previously used stop-flow indirect calorimetry to measure whole body metabolic rate in single flies and have shown that in flies, like mammals, metabolic rate is reduced during sleep. Here, we describe a modified version of this system that allows for efficient and highly sensitive acquisition of CO(2) output from single flies. In this modified system, we show that sleep-dependent changes in metabolic rate are diminished in aging flies, supporting the notion that sleep quality is reduced as flies age. We also describe a modification that allows for simultaneous acquisition of CO(2) and O(2) levels, providing a respiratory quotient that quantifies how metabolic stores are utilized. We find that the respiratory quotient identified in flies on an all-sugar diet is suggestive of lipogenesis, where the dietary sugar provided to the flies is being converted to fat. Taken together, the measurement of metabolic rate via indirect calorimetry not only provides a physiological readout of sleep depth, but also provides insight the metabolic regulation of nutrient utilization, with broad applications to genetic studies in flies.

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.The RMR of 102 athletes (44 women) was assessed using indirect calorimetry, while 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, 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 regressions models were employed to develop the new predictive equations based on traditional predictors (Equation 1) and the stepwise method (Equation 2).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 HarrisBenedict's equation showed the worst performance for males (mean difference = 406 kcal.d-1; RMSE = 473 kcal.d-1). Compared to measured RMR, most predictive equations showed heteroscedastic distribution (linear regression's intercept and slope significantly different from zero; p ≤ 0.05), mainly in males.The new proposed equations can estimate the RMR in high-level athletes accurately. Cunningham's equation is a good option from existing equations, and HarrisBenedict's equation should not be used in high-level male athletes.

Increased adiposity is associated with dysregulation of the endothelin system, both of which increase the risk of cardiovascular disease (CVD). Preclinical data indicate that endothelin dysregulation also reduces resting energy expenditure (REE). The objective was to test the hypothesis that endothelin receptor antagonism will increase REE in people with obesity compared with healthy weight individuals. Using a double blind, placebo-controlled, crossover design, 32 participants [healthy weight (HW): n = 16, BMI: 21.3 ± 2.8 kg/m(2), age: 26 ± 7 yr and overweight/obese (OB): n = 16, BMI: 33.5 ± 9.5 kg/m(2), age: 31 ± 6 yr] were randomized to receive either 125 mg of bosentan (ET(A/B) antagonism) or placebo twice per day for 3 days. Breath-by-breath gas exchange data were collected and REE was assessed by indirect calorimetry. Venous blood samples were analyzed for concentrations of endothelin-1 (ET-1). Treatment with bosentan increased plasma ET-1 in both OB and HW groups. Within the OB group, the changes in absolute REE (PLA: −77.6 ± 127.6 vs. BOS: 72.2 ± 146.6 kcal/day; P = 0.046). The change in REE was not different following either treatment in the HW group. Overall, absolute plasma concentrations of ET-1 following treatment with bosentan were significantly associated with kcal/day of fat (r = 0.488, P = 0.005), percentage of fat utilization (r = 0.415, P = 0.020), and inversely associated with the percentage of carbohydrates (r = −0.419, P = 0.019), and respiratory exchange ratio (r = −0.407, P = 0.023). Taken together, these results suggest that modulation of the endothelin system may represent a novel therapeutic approach to increase both resting metabolism and caloric expenditure, and reduce CVD risk in people with increased adiposity. NEW & NOTEWORTHY Findings from our current translational investigation demonstrate that dual endothelin A/B receptor antagonism increases total REE in overweight/obese individuals. These results suggest that modulation of the endothelin system may represent a novel therapeutic target to increase both resting metabolism and caloric expenditure, enhance weight loss, and reduce CVD risk in seemingly healthy individuals with elevated adiposity.

For individuals receiving maintenance dialysis, estimating accurate resting energy expenditure (REE) is essential for achieving energy balance, and preventing protein-energy wasting. Dialysis-specific, predictive energy equations (PEEs) offer a practical way to calculate REE. Three PEEs have been formulatedThis analysis comprised of 113 individuals from the Rutgers Nutrition and Kidney Database. Estimated REE (eREE) was calculated for each PEE, and agreement with mREE was set at50% of values within the limits of ±10%. Reliability and accuracy were determined using intraclass correlation (ICC) and a Bland Altman plot, which analysed the percentage difference of eREE form mREE.Participants were 58.4% male and 81.4% African American. Mean age was 55.8 ± 12.2 years, and the median BMI was 28.9 (IQR = 25.3 - 34.4) kg/mDialysis-specific energy equations showed variable accuracy. When categorized by BMI, the equations performed poorly at the extremes, where individuals are most vulnerable. Innovation is needed to understand these variances and correct the imprecision in PEEs for clinical practice.KEY MESSAGESPotentially impacting over millions of patients worldwide, our long-term goal is to understand energy expenditure (EE) across the spectrum of CKD (stages 1-5) in adults and children being treated with dialysis or transplantation, with the intent of providing tools for the health professional that will improve the delivery of quality care.Our research has identified and focussed on disease-specific factors which account for 60% of the variance in predicting EE in patients on MHD, but significant gaps remain.Thus, our central hypotheses are that (1) there are unique disease-specific determinants of EE and (2) prediction of EE for individuals diagnosed with CKD can be vastly improved with a model that combines these factors with more sophisticated approaches.

The present study investigated the time needed to achieve a steady state for an accurate assessment of resting energy expenditure (REE) in adolescents with healthy weight and obesity.Thirty adolescents aged 12-17 years were assigned to a group with healthy weight (GHW; n = 12, body mass index [BMI] 22.5 ± 3.6 kg/mA significant change occurred during the 30 min in REE. Significant differences existed between consecutive means until the 20The following recommendations are provided to promote accurate assessment of REE among adolescents: a) initiate the REE assessment with 10 min of acclimation to decrease restlessness; b) determine REE for a minimum of 20 min if healthy weight and 25 min if obesity; c) determine REE for a further 5 min, with the average of this last 5 min of REE data being regarded as the REE.

The oral

Humans acquire energy from the environment for survival. A central question for nutritional sciences is how much energy is required to sustain cellular work while maintaining an adequate body mass. Because human energy balance is not exempt from thermodynamic principles, the energy requirement can be approached from the energy expenditure. Conceptual and technological advances have allowed understanding of the physiological determinants of energy expenditure. Body mass, sex, and age are the main factors determining energy expenditure. These factors constitute the basis for predictive equations for resting (REE) and total (TEE) energy expenditure in healthy adults. These equations yield predictions that differ up to ~400 kcal/d for REE and ~550 kcal/d for TEE. Identifying additional factors accounting for such variability and the most valid equations appears relevant. This review used novel approaches based on mathematical modeling of REE and analyses of the data from which REE predictive equations were generated. As for TEE, R

Obesity caused by caloric overload has assumed epidemic proportions. Obesity is frequently associated with metabolic dysfunctions, such as type 2 diabetes, non-alcoholic steatohepatitis (NASH), cardiovascular diseases, and cancer. Metabolic phenotyping is a set of techniques for studying metabolic dysfunction and behavior information including energy expenditure, body weight gain, glucose homeostasis, and lipid profile. Among different metabolic phenotyping methods, indirect calorimetry is an indispensable tool for quantifying the energy balance/imbalance in various mouse models, which enables researchers to probe the development of disease and to evaluate the therapeutic benefit from different interventions. In this chapter, we will describe the procedures of metabolic phenotyping using indirect calorimetry in db/db mouse, a metabolic disorder mouse model which develops NASH.