Evaluating steady-state resting energy expenditure using indirect calorimetry in adults with overweight and obesity

Multiple factor assessment for determining resting metabolic rate in young adults

Existing formulas cannot fully explain the variation of resting metabolic rate (RMR). This study aims to examine potential influencing factors beyond anthropometric measurements and develop more accurate equations using accessible parameters. 324 healthy adults (230 females; 18-32 years old) participated in the study. Height, fat-free mass (FFM), fat mass (FM) and RMR were measured. Menstrual cycle, stress levels, living habits, and frequency of consuming caffeinated foods were collected. Measured RMR were compared with predictive values of the new equations and previous 11 equations. Mean RMR for men and women was 1825.2 ± 248.8 and 1345.1 ± 178.7 kcal/day, respectively. RMR adjusted for FFM0.66FM0.066 was positively correlated with BMI. The multiple regression model showed that RMR can be predicted in this population with model 1 (with FFM, FM, age, sex and daily sun exposure duration) or model 2 (with weight and height replacing FFM and FM). The accuracy was 75.31% in the population for predictive model 1 and 70.68% for predictive model 2. The new equations had overall improved performance when compared with existing equations. The predictive formula that consider daily sun exposure duration improve RMR prediction in young adults. Additional investigation is required among individuals in the middle-aged and elderly demographic.

Intermittent normobaric hypoxia alters substrate partitioning and muscle oxygenation in individuals with obesity: implications for fat burning

This single-blind, crossover study aimed to measure and evaluate the short-term metabolic responses to continuous and intermittent hypoxic patterns in individuals with obesity. Indirect calorimetry was used to quantify changes in resting metabolic rate (RMR), carbohydrate (CHOox, %CHO), and fat oxidation (FATox, %FAT) in nine individuals with obesity pre and post: 1) breathing normoxic air [normoxic sham control (NS-control)], 2) breathing continuous hypoxia (CH), or 3) breathing intermittent hypoxia (IH). A mean peripheral oxygen saturation ([Formula: see text]) of 80-85% was achieved over a total of 45 min of hypoxia. Throughout each intervention, pulmonary gas exchanges, oxygen consumption (V̇o2) carbon dioxide production (V̇co2), and deoxyhemoglobin concentration (Δ[HHb]) in the vastus lateralis were measured. Both RMR and CHOox measured pre- and postinterventions were unchanged following each treatment: NS-control, CH, or IH (all P > 0.05). Conversely, a significant increase in FATox was evident between pre- and post-IH (+44%, P = 0.048). Although the mean Δ[HHb] values significantly increased during both IH and CH (P < 0.05), the greatest zenith of Δ[HHb] was achieved in IH compared with CH (P = 0.002). Furthermore, there was a positive correlation between Δ[HHb] and the shift in FATox measured pre- and postintervention. It is suggested that during IH, the increased bouts of muscle hypoxia, revealed by elevated Δ[HHb], coupled with cyclic periods of excess posthypoxia oxygen consumption (EPHOC, inherent to the intermittent pattern) played a significant role in driving the increase in FATox post-IH.

Measured versus estimated energy requirement in hospitalized patients

BACKGROUND & AIM

Failure to identify a patient's energy requirement has a variety of consequences both physiological and economical. Previous studies have shown that predictive formulas, including the Harris Benedict equation (HB), both over- and underestimates energy requirement in severely ill patients and healthy younger adults, compared to the golden standard, indirect calorimetry (IC). The comparison between measured and estimated energy requirements in hospitalized patients in regular wards is underreported. The aim of this study was to assess the agreement between measured energy requirements and requirements estimated by HB in the individual hospitalized patients, and to investigate whether those findings were associated with other specific patient characteristics.

METHODS

IC (n = 86) was used to measure resting energy expenditure (REE) and bioimpedance analysis (BIA) (n = 67) was used for body composition in patients admitted to Aalborg University Hospital. Furthermore, height, weight, body mass index, calf circumference, while information regarding hospital ward, vital values, dieticians estimated energy requirements and blood samples were collected in the patients' electronic medical records. Bland-Altman plots, multiple linear regression analysis, and Chi2 tests were performed.

RESULTS

On average a difference between IC compared with the HB (6.2%), dietitians' estimation (7.8%) and BIA (4.50%) was observed (p < 0.05). Association between REE and skeletal muscle mass (SMM) (R2 = 0.58, β = 149.0 kJ), body fat mass (BFM) (R2 = 0.51, β = 59.1 kJ), and weight (R2 = 0.62, β = 45.6 kJ) were found (p < 0.05). A positive association between measured REE and HB were found in the following variables (p < 0.05): CRP, age, surgical patients, and respiratory rate.

CONCLUSION

This study found a general underestimation of estimated energy expenditure compared to measured REE. A positive correlation between measured REE and SMM, BRM and weight was found. Lastly, the study found a greater association between CRP, age, surgical patients, and respiratory rate and a general greater than ±10% difference between measured and estimation of energy requirements.

Impact of methods for data selection on the day-to-day reproducibility of resting metabolic rate assessed with four different metabolic carts

BACKGROUND AND AIMS

Accomplishing a high day-to-day reproducibility is important to detect changes in resting metabolic rate (RMR) and respiratory exchange ratio (RER) that may be produced after an intervention or for monitoring patients' metabolism over time. We aimed to analyze: (i) the influence of different methods for selecting indirect calorimetry data on RMR and RER assessments; and, (ii) whether these methods influence RMR and RER day-to-day reproducibility.

METHODS AND RESULTS

Twenty-eight young adults accomplished 4 consecutive RMR assessments (30-min each), using the Q-NRG (Cosmed, Rome, Italy), the Vyntus CPX (Jaeger-CareFusion, Höchberg, Germany), the Omnical (Maastricht Instruments, Maastricht, The Netherlands), and the Ultima CardiO2 (Medgraphics Corporation, St. Paul, Minnesota, USA) carts, on 2 consecutive mornings. Three types of methods were used: (i) short (periods of 5 consecutive minutes; 6-10, 11-15, 16-20, 21-25, and 26-30 min) and long time intervals (TI) methods (6-25 and 6-30 min); (ii) steady state (SSt methods); and, (iii) methods filtering the data by thresholding from the mean RMR (filtering methods). RMR and RER were similar when using different methods (except RMR for the Vyntus and RER for the Q-NRG). Conversely, using different methods impacted RMR (all P ≤ 0.037) and/or RER (P ≤ 0.009) day-to-day reproducibility in all carts. The 6-25 min and the 6-30 min long TI methods yielded more reproducible measurements for all metabolic carts.

CONCLUSION

The 6-25 min and 6-30 min should be the preferred methods for selecting data, as they result in the highest day-to-day reproducibility of RMR and RER assessments.

Obesity and Overweight: Probing Causes, Consequences, and Novel Therapeutic Approaches Through the American Heart Association's Strategically Focused Research Network

As the worldwide prevalence of overweight and obesity continues to rise, so too does the urgency to fully understand mediating mechanisms, to discover new targets for safe and effective therapeutic intervention, and to identify biomarkers to track obesity and the success of weight loss interventions. In 2016, the American Heart Association sought applications for a Strategically Focused Research Network (SFRN) on Obesity. In 2017, 4 centers were named, including Johns Hopkins University School of Medicine, New York University Grossman School of Medicine, University of Alabama at Birmingham, and Vanderbilt University Medical Center. These 4 centers were convened to study mechanisms and therapeutic targets in obesity, to train a talented cadre of American Heart Association SFRN-designated fellows, and to initiate and sustain effective and enduring collaborations within the individual centers and throughout the SFRN networks. This review summarizes the central themes, major findings, successful training of highly motivated and productive fellows, and the innovative collaborations and studies forged through this SFRN on Obesity. Leveraging expertise in in vitro and cellular model assays, animal models, and humans, the work of these 4 centers has made a significant impact in the field of obesity, opening doors to important discoveries, and the identification of a future generation of obesity-focused investigators and next-step clinical trials. The creation of the SFRN on Obesity for these 4 centers is but the beginning of innovative science and, importantly, the birth of new collaborations and research partnerships to propel the field forward.

Associations between Intra-Assessment Resting Metabolic Rate Variability and Health-Related Factors

In humans, the variation in resting metabolic rate (RMR) might be associated with health-related factors, as suggested by previous studies. This study explored whether the intra-assessment RMR variability (expressed as a coefficient of variation (CV; %)) is similar in men and women and if it is similarly associated with diverse health-related factors. The RMR of 107 young, and relatively healthy adults, was assessed using indirect calorimetry. Then, the CV for volumes of oxygen consumption (VO2) and carbon dioxide production (VCO2), respiratory exchange ratio (RER), and resting energy expenditure (REE) were computed as indicators of intra-assessment RMR variability. Body composition, cardiorespiratory fitness (peak VO2 uptake), circulating cardiometabolic risk factors, and heart rate and its variability (HR and HRV) were assessed. Men presented higher CVs for VO2, VCO2, and REE (all p ≤ 0.001) compared to women. Furthermore, in men, the intra-assessment RER variability was associated with vagal-related HRV parameters and with mean HR (standardized β = −0.36, −0.38, and 0.41, respectively; all p < 0.04). In contrast, no associations were observed in women. In conclusion, men exhibited higher variability (CVs for VO2, VCO2, and REE) compared to women. The CV for RER could be a potential marker of cardiometabolic risk in young men.

Soluble Receptor for Advanced Glycation End Products (sRAGE) Isoforms Predict Changes in Resting Energy Expenditure in Adults with Obesity during Weight Loss

Background

Accruing evidence indicates that accumulation of advanced glycation end products (AGEs) and activation of the receptor for AGEs (RAGE) play a significant role in obesity and type 2 diabetes. The concentrations of circulating RAGE isoforms, such as soluble RAGE (sRAGE), cleaved RAGE (cRAGE), and endogenous secretory RAGE (esRAGE), collectively sRAGE isoforms, may be implicit in weight loss and energy compensation resulting from caloric restriction.

Objectives

We aimed to evaluate whether baseline concentrations of sRAGE isoforms predicted changes (∆) in body composition [fat mass (FM), fat-free mass (FFM)], resting energy expenditure (REE), and adaptive thermogenesis (AT) during weight loss.

Methods

Data were collected during a behavioral weight loss intervention in adults with obesity. At baseline and 3 mo, participants were assessed for body composition (bioelectrical impedance analysis) and REE (indirect calorimetry), and plasma was assayed for concentrations of sRAGE isoforms (sRAGE, esRAGE, cRAGE). AT was calculated using various mathematical models that included measured and predicted REE. A linear regression model that adjusted for age, sex, glycated hemoglobin (HbA1c), and randomization arm was used to test the associations between sRAGE isoforms and metabolic outcomes.

Results

Participants (n = 41; 70% female; mean ± SD age: 57 ± 11 y; BMI: 38.7 ± 3.4 kg/m2) experienced modest and variable weight loss over 3 mo. Although baseline sRAGE isoforms did not predict changes in ∆FM or ∆FFM, all baseline sRAGE isoforms were positively associated with ∆REE at 3 mo. Baseline esRAGE was positively associated with AT in some, but not all, AT models. The association between sRAGE isoforms and energy expenditure was independent of HbA1c, suggesting that the relation was unrelated to glycemia.

Conclusions

This study demonstrates a novel link between RAGE and energy expenditure in human participants undergoing weight loss.This trial was registered at clinicaltrials.gov as NCT03336411.

Metabolic Low-Frequency Oscillation and Abbreviated Protocol for Estimating REE by Indirect Calorimetry in Healthy Adults

OBJECTIVES

The aim of this study is to propose a new wave protocol to identify low-frequency oscillations for evaluating resting energy expenditure (REE) and compare its performance with the 5-minute interval abbreviated protocol and standard protocol.

RESEARCH METHODS & PROCEDURES

Consecutive 20-minute indirect calorimetry (IC) was used to collect metabolic data from 23 women and 37 men (between 23 and 43 years old). Sliding window filter algorithms were used to eliminate noise. Three protocols were used to evaluate REE: averaging the data between two consecutive waves (wave protocol), averaging the second 5-minute intervals (interval protocol), and averaging the last 15-minute REE (standard protocol).

RESULTS

Based on 60 healthy participants' metabolic data, compared with the interval protocol, the wave protocol showed better consistency with the standard protocol. The mean bias (limits of agreement) using the wave protocol was 0.3458% (-7.817% to 8.509%), and that using the interval protocol was -1.720% (-16.06% to 12.62%). The time required to evaluate REE with the wave protocol and interval protocol was measured. The measurement time for the interval protocol was 10 minutes, while the average measurement time for the wave protocol was 9.75 minutes.

CONCLUSIONS

We recommend the wave protocol for estimating REE in healthy people. This abbreviated protocol can identify low-frequency oscillations and consider individual differences to more accurately reflect the baseline REE compared to the interval protocol. Compared with the standard protocol, the measurement time of the wave protocol was reduced by nearly half (from 20 minutes (standard protocol) to 9.75 minutes).

Resting Energy Expenditure Is Elevated in Asthma

Background: Asthma physiology affects respiratory function and inflammation, factors that may contribute to elevated resting energy expenditure (REE) and altered body composition. Objective: We hypothesized that asthma would present with elevated REE compared to weight-matched healthy controls. Methods: Adults with asthma (n = 41) and healthy controls (n = 20) underwent indirect calorimetry to measure REE, dual-energy X-ray absorptiometry (DEXA) to measure body composition, and 3-day diet records. Clinical assessments included spirometry, fractional exhaled nitric oxide (FENO), and a complete blood count. Results: Asthmatics had greater REE than controls amounting to an increase of ~100 kcals/day, even though body mass index (BMI) and body composition were similar between groups. Inclusion of asthma status and FENO in validated REE prediction equations led to improved estimates. Further, asthmatics had higher white blood cell (control vs. asthma (mean ± SD): 4.7 ± 1.1 vs. 5.9 ± 1.6, p < 0.01) and neutrophil (2.8 ± 0.9 vs. 3.6 ± 1.4, p = 0.02) counts that correlated with REE (both p < 0.01). Interestingly, despite higher REE, asthmatics reported consuming fewer calories (25.1 ± 7.5 vs. 20.3 ± 6.0 kcals/kg/day, p < 0.01) and carbohydrates than controls. Conclusion: REE is elevated in adults with mild asthma, suggesting there is an association between REE and the pathophysiology of asthma.

Design of a randomised controlled trial: does indirect calorimetry energy information influence weight loss in obesity?

INTRODUCTION

Respiratory quotient (RQ) provides an indication of the relative balance of carbohydrate and fat oxidation. RQ could serve as an early biomarker of negative energy balance during weight loss. Restriction of energy intake relative to total daily energy requirements produces a negative energy balance which can lead to a fall in RQ, accompanied by a decrease in resting energy expenditure (REE). However, the net change in body weight does not usually match predicted weight change due to intraindividual metabolic adaptations. Our aim is to determine the effectiveness of utilising EE information from indirect calorimetry during weight loss intervention.

METHODS AND ANALYSIS

We will undertake an assessor-blinded, parallel-group randomised controlled trial of 105 adults with obesity randomised in 1:1 ratio to receive either standard weight management care (SC) or EE information plus SC (INT) during a 24-week multicomponent weight management programme. The primary outcome is difference in weight loss between INT and SC group at 24 weeks. Secondary outcomes include: change in RQ, REE, glycaemic variability, and appetite-relating gut hormones (glucagon-like peptide 1, gastric inhibitory polypeptide, peptide YY). Generalised linear mixed models (intention to treat) will assess outcomes for treatment (INT vs SC), time (baseline, 24 weeks) and the treatment-by-time interaction. This will be the first study to evaluate impact of utilising measured REE and RQ on the lifestyle-based intensive intervention programme.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Health Research Authority and the North West Research Ethics Committee (18/NW/0645). Results from this trial will be disseminated through publication in peer-reviewed journals, national and international presentations.

TRIAL REGISTRATION NUMBERS

NCT03638895; UoL001379.