Concordance between 13 C:12 C ratio technique respect to indirect calorimetry to estimate carbohydrate and Fat oxidation rates by means stoichiometric equations during exercise. A reliability and agreement study

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.

The efficacy of a home-use metabolic device (Lumen) in response to a short-term low and high carbohydrate diet in healthy volunteers

BACKGROUND

Based on stoichiometric assumptions, and real-time assessment of expired carbon dioxide (%CO₂) and flow rate, the Lumen device provides potential for consumers/athletes to monitor metabolic responses to dietary programs outside of laboratory conditions. However, there is a paucity of research exploring device efficacy. This study aimed to evaluate Lumen device response to: i) a high-carbohydrate meal under laboratory conditions, and ii) a short-term low- or high-carbohydrate diet in healthy volunteers.

METHODS

Following institutional ethical approval, 12 healthy volunteers (age: 36 ± 4 yrs; body mass: 72.1 ± 3.6 kg; height: 1.71 ± 0.02 m) performed Lumen breath and Douglas bag expired air measures under fasted laboratory conditions and at 30 and 60 min after a high-carbohydrate (2 g·kg^-1) meal, along with capilliarized blood glucose assessment. Data were analyzed using a one-way ANOVA, with ordinary least squares regression used to assess the model between Lumen expired carbon dioxide percentage (L%CO₂) and respiratory exchange ratio (RER). In a separate phase, 27 recreationally active adults (age: 42 ± 2 yrs; body mass: 71.9 ± 1.9 kg; height: 1.72 ± 0.02 m) completed a 7-day low- (~20% of energy intake [EI]; LOW) or high-carbohydrate diet (~60% of EI; HIGH) in a randomized, cross-over design under free-living conditions. L%CO₂ and derived Lumen Index (L_I) were recorded daily across morning (fasted and post-breakfast) and evening (pre/post meal, pre-bed) periods. Repeated measures ANOVA were employed for main analyses, with Bonferroni post-hoc assessment applied (P ≤ 0.05).

RESULTS

Following the carbohydrate test-meal, L%CO₂ increased from 4.49 ± 0.05% to 4.80 ± 0.06% by 30 min, remaining elevated at 4.76 ± 0.06% by 60 min post-feeding (P < 0.001, η_p² = 0.74). Similarly, RER increased by 18.1% from 0.77 ± 0.03 to 0.91 ± 0.02 by 30 min post-meal (P = 0.002). When considering peak data, regression analysis demonstrated a significant model effect between RER and L%CO₂ (F = 5.62, P = 0.03, R² = 0.20). Following main dietary interventions, no significant interactions (diet × day) were found. However, main diet effects were evident across all time-points assessed, highlighting significant differences for both L%CO₂ and L_I between LOW and HIGH conditions (P < 0.003). For L%CO₂, this was particularly noted under fasted (4.35 ± 0.07 vs. 4.46 ± 0.06%, P = 0.001), pre-evening meal (4.35 ± 0.07 vs. 4.50 ± 0.06%, P < 0.001), and pre-bed time-points (4.51 ± 0.08 vs. 4.61 ± 0.06%, P = 0.005).

CONCLUSION

Our findings demonstrated that a portable, home-use metabolic device (Lumen) detected significantly increased expired %CO₂ in response to a high-carbohydrate meal, and may be useful in tracking mean weekly changes to acute dietary carbohydrate modifications. Additional research is warranted to further determine the practical and clinical efficacy of the Lumen device in applied compared to laboratory settings.

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.

Short-Term Ingestion of Medium-Chain Triglycerides Could Enhance Postprandial Consumption of Ingested Fat in Individuals with a Body Mass Index from 25 to Less than 30: A Randomized, Placebo-Controlled, Double-Blind Crossover Study

The elimination of obesity is essential to maintaining good health. Medium-chain triglycerides (MCTs) inhibit fat accumulation. However, studies examining energy expenditure and fat oxidation with continuous ingestion of MCTs show little association with the elimination of obesity. In this study, we conducted a randomized, double-blind crossover clinical trial to investigate the effects of continuous ingestion of MCTs on postprandial energy expenditure and ingested long-chain triglycerides (LCTs) oxidation. A daily 2 g of MCTs were ingested for two weeks by sedentary participants with a body mass index (BMI) from 25 (kg/m²) to less than 30. Ingestion of a meal containing MCTs and isotopic carbon-13-labeled (13C) LCTs increased energy expenditure and consumption of diet-derived LCTs, as determined by postprandial 13C carbon dioxide excretion, compared to canola oil as the placebo control. These results indicate that continuous ingestion of MCTs could enhance postprandial degradation of diet-derived fat and energy expenditure in sedentary, overweight individuals.

A systematic comparison of commonly used stoichiometric equations to estimate fat oxidation during exercise in athletes

BACKGROUND

Over the last half-century, different stoichiometric equations for calculating the energy cost of exercise based upon the combustion of mixtures of carbohydrates, fats, and proteins have been proposed and modified. With the means of indirect calorimetry, while measuring oxygen uptake, carbon dioxide production, and urinary urea nitrogen excretion, the contribution of specific substrates to overall energy production can be estimated. However, even with their long history of application, no previous studies have evaluated whether the use of different stoichiometric equations provides similar or distinct maximal fat oxidation rate (MFO) responses and information regarding MFO location (FAT<inf>max</inf>) in male athletes.

METHODS

Twenty healthy male athletes performed graded exercise testing (GXT) cycle ergometry using breath by breath gas analysis to assess fat oxidation and maximal oxygen uptake. Analysis of variance followed by within-equation effects, within-equation factors, and post hoc pairwise comparisons were used to examine within-equation differences.

RESULTS

Compared stoichiometric equations demonstrated significant differences in the mean and maximal fat oxidation rates, varying up to nearly 7%. FAT<inf>max</inf> differences, however, were not noticed.

CONCLUSIONS

Our findings suggest that for within-study designs, the equation used appears to be less important, but when inter-study comparisons are planned, caution is in order due to the presence of inter-equation differences.