Validity of four commercially available metabolic carts for assessing resting metabolic rate and respiratory exchange ratio in non-ventilated humans

Durability and Underlying Physiological Factors: How Do They Change Throughout a Cycling Season in Semiprofessional Cyclists?

PURPOSE

To investigate how cycling time-trial (TT) performance changes over a cycling season, both in a "fresh" state and in a "fatigued" state (durability). Additionally, the aim was to explore whether these changes are related to changes in underlying physiological factors such as gross efficiency, energy expenditure (EE), and substrate oxidation (fat oxidation [FatOx] and carbohydrate oxidation [CarbOx]).

METHODS

Sixteen male semiprofessional cyclists visited the laboratory on 3 occasions during a cycling season (PRE, START, and IN) and underwent a performance test in both fresh and fatigued states (after 38.1 [4.9] kJ/kg), containing a submaximal warm-up for the measurement of gross efficiency, EE, FatOx, and CarbOx and a maximal TT of 1 (TT1min) and 10 minutes (TT10min). Results were compared across states (fresh vs fatigued) and periods (PRE, START, and IN).

RESULTS

The average power output (PO) in TT1min decreased (P < .05) from fresh to fatigued state across all observed periods, whereas there was no change in the PO in TT10min. Over the course of the season, the PO in TT1min in the fatigued state improved more compared with the PO in TT1min in the fresh state. Furthermore, while EE did not significantly change, there was an increase in FatOx and a decrease in CarbOx toward the fatigued state. These changes diminished during the cycling season (IN), indicating a greater contribution of CarbOx in the fatigued state.

CONCLUSIONS

TT1min performance is more sensitive to fatigue compared with TT10min. Also, during a cycling season, durability improves more when compared with fresh maximal POs, which is also observed in the changes in substrate oxidation.

Evaluating Airflow Sensor Methods: Precision in Indirect Calorimetry

This study assesses the impact of three volumetric gas flow measurement methods-turbine (fT); pneumotachograph (fP), and Venturi (fV)-on predictive accuracy and precision of expired gas analysis indirect calorimetry (EGAIC) across varying exercise intensities. Six males (Age: 38 ± 8 year; Height: 178.8 ± 4.2 cm;V ̇ O 2 peak $$ \dot{V}{\mathrm{O}}_2\mathrm{peak} $$ : 42 ± 2.8 mL O2 kg-1 min-1) and 14 females (Age = 44.6 ± 9.6 year; Height = 164.6 ± 6.9 cm;V ̇ O 2 peak $$ \dot{V}{\mathrm{O}}_2\mathrm{peak} $$ = 45 ± 8.6 mL O2 kg-1 min-1) were recruited. Participants completed physical exertion on a stationary cycle ergometer for simultaneous pulmonary minute ventilation (V ̇ $$ \dot{V} $$ ) measurements and EGAIC computations. Exercise protocols and subsequent conditions involved a 5-min cycling warm-up at 25 W min-1, incremental exercise to exhaustion (V ̇ O 2 $$ \dot{V}{\mathrm{O}}_2 $$ ramp test), then a steady-state exercise bout induced by a constant Watt load equivalent to 80% ventilatory threshold (80% VT). A linear mixed model revealed that exercise intensity significantly affectedV ̇ O 2 $$ \dot{V}{\mathrm{O}}_2 $$ measurements (p < 0.0001), whereas airflow sensor method (p = 0.97) and its interaction with exercise intensity (p = 0.91) did not. Group analysis of precision yielded aV ̇ O 2 $$ \dot{V}{\mathrm{O}}_2 $$ CV % = 21%; SEM = 5 mL O2 kg-1 min-1. Intra- and interindividual analysis of precision via Bland-Altman revealed a 95% confidence interval (CI) precision benchmark of 3-5 mL kg-1 min-1. Agreement among methods decreased at power outputs elicitingV ̇ $$ \dot{V} $$ up to 150 L min-1, indicating a decrease in precision and highlighting potential challenges in interpreting biological variability, training response heterogeneity, and test-retest comparisons. These findings suggest careful consideration of airflow sensor method variance across metabolic cart configurations.

Association of metabolic flexibility indexes after an oral glucose tolerance test with cardiometabolic risk factors

BACKGROUND & AIMS

Metabolic flexibility (MetF) is considered a metabolic health biomarker, as excess body weight is associated with lower MetF. We aimed to identify whether MetF indexes were associated with cardiometabolic risk factors before and after adjustment for body size-related factors (body weight, fat-free mass, and resting metabolic rate).

METHODS

We studied 51 participants (55% women; 33.6 ± 8.7 years; 26.3 ± 3.8 kg/m²) who consumed a 75-g glucose load. We measured gas exchange before (fasting) and for 3 h after glucose ingestion. MetF indexes were assessed, including the change after each hour and the 3-hour incremental area under the curve (iAUC) in respiratory exchange ratio (RER). These indexes were then related to cardiometabolic risk factors before and after adjusting for body size-related factors.

RESULTS

MetF indexes correlated with each other (r ≥ 0.51; P < 0.001) and related to body weight (adjusted R2 ≥ 0.09; P < 0.03). A similar pattern was noted for fat-free mass and resting metabolic rate. MetF, regardless of the index, was not related to cardiometabolic risk factors except to BMI and high-density lipoprotein-cholesterol (HDL-C). The association between BMI and MetF disappeared after adjusting for body size-related factors. Similar adjustments did not modify the association between HDL-C and MetF, especially when approached by the change in RER after the first hour (adjusted R2 = 0.20-0.22; all P < 0.02).

CONCLUSIONS

Inter-individual body size differences fully accounted for the associations between BMI and MetF. However, variability in body size-related factors appeared less relevant in affecting the associations of other cardiometabolic risk factors with MetF.

Resting energy metabolism and sweet taste preference during the menstrual cycle in healthy women

Differences in blood concentration of sex hormones in the follicular (FP) and luteal (LP) phases may influence energy metabolism in women. We compared fasting energy metabolism and sweet taste preference on a representative day of the FP and LP in twenty healthy women (25·3 (sd 5·1) years, BMI: 22·2 (sd 2·2) kg/m2) with regular self-reported menses and without the use of hormonal contraceptives. From the self-reported duration of the three prior menstrual cycles, the predicted FP and LP visits were scheduled for days 5-12 and 20-25 after menses, respectively. The order of the FP and LP visits was randomly assigned. On each visit, RMR and RQ by indirect calorimetry, sweet taste preference by the Monell two-series forced-choice tracking procedure, serum fibroblast growth factor 21 by a commercial ELISA (FGF21, a liver-derived protein with action in energy balance, fuel oxidation and sugar preference) and dietary food intake by a 24-h dietary recall were determined. Serum progesterone and oestradiol concentrations displayed the expected differences between phases. RMR was lower in the FP v. LP (5042 (sd 460) v. 5197 (sd 490) kJ/d, respectively; P = 0·04; Cohen effect size, d rm = 0·33), while RQ showed borderline significant higher values (0·84 (sd 0·05) v. 0·81 (sd 0·05), respectively; P = 0·07; d rm = 0·62). Also, in the FP v. LP, sweet taste preference was lower (12 (sd 8) v. 16 (sd 9) %; P = 0·04; d rm = 0·47) concomitant with higher serum FGF21 concentration (294 (sd 164) v. 197 (sd 104) pg/ml; P < 0·01; d rm = 0·66). The menstrual cycle is associated with changes in energy expenditure, sweet taste preference and oxidative fuel partitioning.

Impact of Equation Choice on Resting Metabolic Rate Ratio in High-Level Men and Women Athletes

Objective: To examine the impact of the RMR ratio cutoff point selected on the categorization of prevalence/absence of low energy availability among predictive equations in high-level athletes (n = 241 [99 women]; 52% competed at the World Championship and Olympic Games), and whether this categorization is influenced by sex and the predictive equation used.Methods: We assessed RMR using indirect calorimetry, predicted the RMR using the equations proposed by Harris-Benedict, FAO/WHO/UNU, de Lorenzo, ten Haaf and Wejis, Wong, Jagim, Cunningham, and Freire, and computed the RMR ratio for each equation.Results: We observed that the cumulative percentage of RMR ratio values increased at a faster rate using Jagim, ten Haaf and Wejis, and Cunningham equations compared to the other equations. At the 0.90 value (the most used cutoff point in literature), the Jagim equation categorized ≥ 50% of the athletes into "low energy availability". No Sex × Equation × Sport interaction effect was observed (F = 0.10, p = 1.0). There was a significant main effect to Sex (F = 11.7, p < 0.001, ES = 0.05), Sport (F = 16.4, p < 0.001, ES = 0.01), and Equation (F = 64.1, p < 0.001, ES = 0.19). Wong and FAO/WHO/UNU equations yielded the largest errors (assessed vs. predicted RMR) in men and women, respectively.Conclusion: The selected RMR ratio cutoff point influences the prevalence/absence of low energy availability characterization in high-level athletes and suggests that certain equations could bias its assessment.

Accuracy of respiratory gas variables, substrate, and energy use from 15 CPET systems during simulated and human exercise

PURPOSE

Various systems are available for cardiopulmonary exercise testing (CPET), but their accuracy remains largely unexplored. We evaluate the accuracy of 15 popular CPET systems to assess respiratory variables, substrate use, and energy expenditure during simulated exercise. Cross-comparisons were also performed during human cycling experiments (i.e., verification of simulation findings), and between-session reliability was assessed for a subset of systems.

METHODS

A metabolic simulator was used to simulate breath-by-breath gas exchange, and the values measured by each system (minute ventilation [V̇E], breathing frequency [BF], oxygen uptake [V̇O2 ], carbon dioxide production [V̇CO2 ], respiratory exchange ratio [RER], energy from carbs and fats, and total energy expenditure) were compared to the simulated values to assess the accuracy. The following manufacturers (system) were assessed: COSMED (Quark CPET, K5), Cortex (MetaLyzer 3B, MetaMax 3B), Vyaire (Vyntus CPX, Oxycon Pro), Maastricht Instruments (Omnical), MGC Diagnostics (Ergocard Clinical, Ergocard Pro, Ultima), Ganshorn/Schiller (PowerCube Ergo), Geratherm (Ergostik), VO2master (VO2masterPro), PNOĒ (PNOĒ), and Calibre Biometrics (Calibre).

RESULTS

Absolute percentage errors during the simulations ranged from 1.15%-44.3% for V̇E, 1.05-3.79% for BF, 1.10%-13.3% for V̇O2 , 1.07%-18.3% for V̇CO2 , 0.62%-14.8% for RER, 5.52%-99.0% for Kcal from carbs, 5.13%-133% for Kcal from fats, and 0.59%-12.1% for total energy expenditure. Between-session variation ranged from 0.86%-21.0% for V̇O2 and 1.14%-20.2% for V̇CO2 , respectively.

CONCLUSION

The error of respiratory gas variables, substrate, and energy use differed substantially between systems, with only a few systems demonstrating a consistent acceptable error. We extensively discuss the implications of our findings for clinicians, researchers and other CPET users.

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.

Predicting resting energy expenditure: a critical appraisal

BACKGROUND

The most commonly used prediction models for resting energy expenditure (REE) are Harris-Benedict (1919), Schofield (1985), Owen (1986), and Mifflin-St Jeor (1990), based on height, weight, age and gender, and Cunningham (1991), based on body composition.

METHODS

Here, the five models are compared with reference data, consisting of individual REE measurements (n = 353) from 14 studies, covering a large range of participant characteristics.

RESULTS

For white adults, prediction of REE with the Harris-Benedict model approached measured REE most closely, with estimates within 10% for more than 70% of the reference population.

DISCUSSION

Sources of differences between measured and predicted REE include measurement validity and measurement conditions. Importantly, a 12- to 14-h overnight fast may not be sufficient to reach post-absorptive conditions and may explain differences between predicted REE and measured REE. In both cases complete fasting REE may not have been achieved, especially in participants with high energy intake.

CONCLUSION

In white adults, measured resting energy expenditure was closest to predicted values with the classic Harris-Benedict model. Suggestions for improving resting energy expenditure measurements, as well as prediction models, include the definition of post-absorptive conditions, representing complete fasting conditions with respiratory exchange ratio as indicator.

2023 International Olympic Committee's (IOC) consensus statement on Relative Energy Deficiency in Sport (REDs)

Relative Energy Deficiency in Sport (REDs) was first introduced in 2014 by the International Olympic Committee's expert writing panel, identifying a syndrome of deleterious health and performance outcomes experienced by female and male athletes exposed to low energy availability (LEA; inadequate energy intake in relation to exercise energy expenditure). Since the 2018 REDs consensus, there have been >170 original research publications advancing the field of REDs science, including emerging data demonstrating the growing role of low carbohydrate availability, further evidence of the interplay between mental health and REDs and more data elucidating the impact of LEA in males. Our knowledge of REDs signs and symptoms has resulted in updated Health and Performance Conceptual Models and the development of a novel Physiological Model. This Physiological Model is designed to demonstrate the complexity of either problematic or adaptable LEA exposure, coupled with individual moderating factors, leading to changes in health and performance outcomes. Guidelines for safe and effective body composition assessment to help prevent REDs are also outlined. A new REDs Clinical Assessment Tool-Version 2 is introduced to facilitate the detection and clinical diagnosis of REDs based on accumulated severity and risk stratification, with associated training and competition recommendations. Prevention and treatment principles of REDs are presented to encourage best practices for sports organisations and clinicians. Finally, methodological best practices for REDs research are outlined to stimulate future high-quality research to address important knowledge gaps.

Methodology for studying Relative Energy Deficiency in Sport (REDs): a narrative review by a subgroup of the International Olympic Committee (IOC) consensus on REDs

In the past decade, the study of relationships among nutrition, exercise and the effects on health and athletic performance, has substantially increased. The 2014 introduction of Relative Energy Deficiency in Sport (REDs) prompted sports scientists and clinicians to investigate these relationships in more populations and with more outcomes than had been previously pursued in mostly white, adolescent or young adult, female athletes. Much of the existing physiology and concepts, however, are either based on or extrapolated from limited studies, and the comparison of studies is hindered by the lack of standardised protocols. In this review, we have evaluated and outlined current best practice methodologies to study REDs in an attempt to guide future research.This includes an agreement on the definition of key terms, a summary of study designs with appropriate applications, descriptions of best practices for blood collection and assessment and a description of methods used to assess specific REDs sequelae, stratified as either Preferred, Used and Recommended or Potential Researchers can use the compiled information herein when planning studies to more consistently select the proper tools to investigate their domain of interest. Thus, the goal of this review is to standardise REDs research methods to strengthen future studies and improve REDs prevention, diagnosis and care.

Resting Metabolic Rate of Individuals

The resting metabolic rate (RMR) represents the energy required to sustain normal body functions and homeostasis in an awake individual under ambient thermoneutral conditions and during rest [...].

Current insights in ICU nutrition: tailored nutrition

PURPOSE OF REVIEW

To summarize recent research on critical care nutrition focusing on the optimal composition, timing, and monitoring of enteral feeding strategies for (post)-ICU patients. We provide new insights on energy and protein recommendations, feeding intolerance, and describe nutritional practices for coronavirus disease 2019 ICU patients.

RECENT FINDINGS

The use of indirect calorimetry to establish individual energy requirements for ICU patients is considered the gold standard. The limited research on optimal feeding targets in the early phase of critical illness suggests avoiding overfeeding. Protein provision based upon the absolute lean body mass is rational. Therefore, body composition measurements should be considered. Body impedance analysis and muscle ultrasound seem reliable, affordable, and accessible methods to assess body composition at the bedside. There is inadequate evidence to change our practice of continuous enteral feeding into intermittent feeding. Finally, severe acute respiratory syndrome coronavirus 2 patients are prone to underfeeding due to hypermetabolism and should be closely monitored.

SUMMARY

Nutritional therapy should be adapted to the patient's characteristics, diagnosis, and state of metabolism during ICU stay and convalescence. A personalized nutrition plan may prevent harmful over- or underfeeding and attenuate muscle loss. Despite novel insights, more research is warranted into tailored nutrition strategies during critical illness and convalescence.

Determination of energy expenditure in professional cyclists using power data: Validation against doubly labeled water

INTRODUCTION

Accurate determination of total daily energy expenditure (TDEE) in athletes is important for optimal performance and injury prevention, but current approaches are insufficiently accurate. We therefore developed an approach to determine TDEE in professional cyclists based on power data, basal metabolic rate (BMR), and a non-exercise physical activity level (PAL) value, and compared energy expenditure (EE) between multi-day and single-day races.

METHODS

Twenty-one male professional cyclists participated. We measured: (1) BMR, (2) the relationship between power output and EE during an incremental cycling test, which was used to determine EE during exercise (EE_E ), and (3) TDEE using doubly labeled water (DLW). A non-exercise PAL-value was obtained by subtracting EE_E from TDEE and dividing this by BMR.

RESULTS

Measured BMR was 7.9 ± 0.8 MJ/day, which was significantly higher than predicted by the Oxford equations. A new BMR equation for elite endurance athletes was therefore developed. Mean TDEE was 31.7 ± 2.8 and 27.3 ± 2.8 MJ/day during the Vuelta a España and Ardennes classics, while EE_E was 17.4 ± 1.8 and 10.1 ± 1.4 MJ/day, respectively. Non-exercise PAL-values were 1.8 and 2.0 for the Vuelta and Ardennes classics, respectively, which is substantially higher than currently used generic PAL-values.

CONCLUSION

We show that the proposed approach leads to a more accurate estimation of non-exercise EE than the use of a generic PAL-value in combination with BMR predictive equations developed for non-elite athletes, with the latter underestimating non-exercise EE by ~28%. The proposed approach may therefore improve nutritional strategies in professional cyclists.

Reproducibility of the energy metabolism response to an oral glucose tolerance test: influence of a postcalorimetric correction procedure

PURPOSE

Metabolic flexibility (MetF), which is a surrogate of metabolic health, can be assessed by the change in the respiratory exchange ratio (RER) in response to an oral glucose tolerance test (OGTT). We aimed to determine the day-to-day reproducibility of the energy expenditure (EE) and RER response to an OGTT, and whether a simulation-based postcalorimetric correction of metabolic cart readouts improves day-to-day reproducibility.

METHODS

The EE was assessed (12 young adults, 6 women, 27 ± 2 years old) using an Omnical metabolic cart (Maastricht Instruments, Maastricht, The Netherlands) after an overnight fast (12 h) and after a 75-g oral glucose dose on 2 separate days (48 h). On both days, we assessed EE in 7 periods (one 30-min baseline and six 15-min postprandial). The ICcE was performed immediately after each recording period, and capillary glucose concentration (using a digital glucometer) was determined.

RESULTS

We observed a high day-to-day reproducibility for the assessed RER (coefficients of variation [CV] < 4%) and EE (CVs < 9%) in the 7 different periods. In contrast, the RER and EE areas under the curve showed a low day-to-day reproducibility (CV = 22% and 56%, respectively). Contrary to our expectations, the postcalorimetric correction procedure did not influence the day-to-day reproducibility of the energy metabolism response, possibly because the Omnical's accuracy was ~ 100%.

CONCLUSION

Our study demonstrates that the energy metabolism response to an OGTT is poorly reproducible (CVs > 20%) even using a very accurate metabolic cart. Furthermore, the postcalorimetric correction procedure did not influence the day-to-day reproducibility. Trial registration NCT04320433; March 25, 2020.

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.

Acute Effects of Whole-Body Electromyostimulation on Energy Expenditure at Resting and during Uphill Walking in Healthy Young Men

The effects of the different electrical frequencies of whole-body electrical stimulation (WB-EMS) on energy expenditure (EE) and the respiratory exchange ratio (RER) remain poorly understood. This study aimed to determine the effects of different WB-EMS electrical frequencies on EE and the RER during supine resting and uphill walking. A total of 10 healthy and recreationally active men (21.6 ± 3.3 years old) participated in the present study. Participants completed two testing sessions in a randomized order. In each session, a variety of impulse frequencies (1 hertz (Hz), 2 Hz, 4 Hz, 6 Hz, 8 Hz, and 10 Hz) were applied in a randomized order, allowing a 10 min passive recovery between them. Oxygen consumption and carbon dioxide production were measured to calculate EE and the RER. All frequencies increased EE at rest (all p ≤ 0.001), with 4 Hz being the frequency producing the highest increase (Δ = 8.89 ± 1.49 kcal/min), as did 6 Hz (Δ = 8.05 ± 1.52 kcal/min) and 8 Hz (Δ = 7.04 ± 2.16 kcal/min). An increment in the RER at rest was observed with 4 Hz, 6 Hz, 8 Hz and 10 Hz (all p ≤ 0.016), but not with 1 Hz and 2 Hz (p ≥ 0.923). During uphill walking, the frequency that elicited the highest increase in EE was 6 Hz (Δ = 4.87 ± 0.84 kcal/min) compared to the unstimulated condition. None of the impulse frequencies altered the RER during uphill walking. WB-EMS increases EE in healthy young men both during resting and uphill walking.

The cost of chewing: The energetics and evolutionary significance of mastication in humans

Any change in the energetic cost of mammalian mastication will affect the net energy gain from foods. Although the energetic efficiency of masticatory effort is fundamental in understanding the evolution of the human masticatory system, nothing is known currently about the associated metabolic costs of chewing different items. Here, using respirometry and electromyography of the masseter muscle, we demonstrate that chewing by human subjects represents a measurable energy sink. Chewing a tasteless odorless gum elevates metabolic rate by 10 to 15% above basal levels. Energy expenditure increases with gum stiffness and is paid for by greater muscle recruitment. For modern humans, it is likely that mastication represents a small part of the daily energy budget. However, for our ancestors, before the onset of cooking and sophisticated food processing methods, the costs must have been relatively high, adding a previously unexplored energetic dimension to the interpretation of hominin dentofacial fossils.