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Whole-body fat oxidation determined by graded exercise and indirect calorimetry: a role for muscle oxidative capacity? To determine Fat max , a submaximal graded exercise test using indirect calorimetry is performed, and data is analyzed with two main steps.
First, F ox and CHO ox at each stage of the test are calculated from indirect calorimetry measures [oxygen consumption and carbon dioxide production ] by means of the stoichiometric equations [7]. Knowledge of the reproducibility of Fat max is necessary for establishing its usefulness as a parameter for training prescription and for adequately interpreting outcomes from research studies.
To date, there has been limited research into the reproducibility of testing Fat max , and findings to date are conflicting and have methodological limitations [8] , [13] , [14]. Achten et al.
Perez-Martin et al. Conversely, Meyer et al. The limits of agreement LoA for oxygen consumption at Fat max corresponded to a heart rate HR difference of 35 bpm between the two tests, which lead them to conclude that the intra-individual variability in Fat max measurements is too large to recommend using this parameter for prescribing exercise training.
In addition to coming to different conclusions, these studies had methodological limitations in terms of testing protocol and data analysis approach. However, Chenevière et al. Furthermore, the statistical approach to assess reliability used by Achten et al.
and Perez-Martin et al. was not comprehensive given that only CVs were reported [15]. Other measures of variability such as the LoA were not calculated. Crucially, even though Fat max is calculated from F ox values at each stage of a submaximal graded test, the reproducibility of F ox over a wide range of exercise intensities has not been assessed.
Some studies have evaluated the intra-individual variability of the physiological parameters used to determine substrate oxidation , and respiratory exchange ratio or RER.
However, while CVs of , and RER are often reported to inform on the variability in substrate oxidation rates, this might be misleading. The relationship existing between those CVs and the variability of F ox and CHO ox has not been established.
Limited information is available on the reproducibility of Fat max and on the reproducibility of CHO ox and F ox at each stage of a graded test. It was therefore the aim of this study to assess the intra-individual variability of: a Fat max measurements determined using three different data analysis approaches SIN, P3 and MV , and b CHO ox and F ox at rest and in response to each stage of an individualized graded test.
A further aim was to investigate how the CVs of , and RER are related to the CV of F ox. The study was conducted in accordance with ethical principles of the World medical Declaration of Helsinki and was approved by the human research ethics committee of the University of Lausanne Switzerland.
All test procedures, risks and benefits associated with the experiment were fully explained, and written informed consent was obtained from all participants. Fifteen healthy, moderately trained male volunteers see Table 1 for anthropometric and physical characteristics were recruited to participate in this study.
They were not taking regular medications and were screened for the absence of electrocardiographic abnormalities at rest and during exercise. Each participant completed three test sessions. In the first session anthropometric measurements i. In the remaining two sessions the subjects performed an identical submaximal incremental test Test 1 and Test 2.
The two tests were performed in the morning start of exercise between 7 and 8 am after ahour overnight fast. They were separated by 3 to 7 days and performed at the same time of day to avoid circadian variance.
The volunteers were asked to fill in a 1-day food diary on the day before Test 1 and to repeat this diet before Test 2. Furthermore, participants were asked to refrain from vigorous exercise and alcohol and caffeine consumption in the 24 hours prior to testing.
Participants were familiarized with the equipment prior to testing. Body composition fat mass and percentage of body fat was estimated from skin-fold thickness measurements at four sites according to the methods of Durnin and Womersley [20].
A maximal incremental test on a cycle ergometer Ebike Basic BPlus, General Electric, Niskayuna, NY, USA to determine maximal oxygen uptake and maximal aerobic power output was performed. After a 5-min rest period and a 5-min warm-up at 60 W, output was increased by 30 W every minute until volitional exhaustion.
was calculated as the average over the last 20 seconds of the last stage of the test. Test 1 and Test 2 were characterized by two phases: a pre-exercise resting phase rest and a submaximal incremental exercise test.
They were carried out under identical circumstances with an identical protocol. Data from these two tests were subsequently employed for reliability calculations. In the pre-exercise resting phase rest , participants were seated for min on the cycle ergometer and respiratory measures were collected during the last min of this sitting period.
Subsequently, a submaximal incremental exercise test to determine whole-body F ox kinetics was performed.
Oxygen uptake , carbon dioxide output and ventilation were measured continuously using a breath-by-breath system Oxycon Pro, Jaeger, Würzburg, Germany. Before each test the gas analyzers were calibrated with gases of known concentration The HR was recorded continuously using an HR monitor Si, Polar Electro OY, Kempele, Finland.
During Test 1 and Test 2, HR and gas exchange data , collected during the final 5-min of the pre-exercise resting phase and during the last 2-min of each stage of the submaximal incremental exercise test were averaged and used for calculations. RER was calculated as the ratio between and , while F ox and CHO ox were calculated using stoichiometric equations [7] , with the assumption that the urinary nitrogen excretion rate was negligible: 1 2.
F ox as a function of exercise intensity is reflected by two different linear relationships: a progressive decrease of 1—RER and a linear increase of as power output is increased.
The SIN model [12] was used to model and characterize whole-body F ox kinetics: 6. Dilatation d , symmetry s and translation t are the three independent variables representing the main modulations of the curve. To fit the experimental data i. F ox rates and to model the F ox kinetics, the three variables were independently changed using an iterative procedure by minimizing the sum of the mean squares of the differences between the estimated energy derived from fat based on the SIN model and the energy derived from fat calculated from the raw F ox data, as described in a previous study [12].
For each subject, Fat max was calculated by differentiation of the SIN model equation. Graphical depiction of F ox values as a function of exercise intensity was performed by constructing a third polynomial curve with intersection at 0;0 [11]. Fat max was calculated by differentiation of the P3 equation, and corresponded to the intensity at which the value of the differentiated equation was equal to zero.
From the graphical representation of F ox values as a function of exercise intensity, the stage at which the value of measured F ox rates was maximal was determined, and the corresponding intensity was identified [3] , [8] — [10] , [23]. In order to investigate how the CV of and are linked to the CVs of parameters informing of substrate utilization RER, F ox , CHO fat , 1-RER, ENE fat three theoretical scenarios were created.
Data are expressed as the means ± standard deviation SD for all variables. Intra-individual CVs were calculated for the physiological variables studied in the three theoretical scenarios.
Two-factorial analysis of variance for repeated measures RMANOVA was carried out to test for systematic changes in: a Fat max , and physiological measures at Fat max factor 1: tests, factor 2: data analysis approaches , and b gas exchange data, HR and substrate oxidation rates factor 1: tests; factor 2: exercise intensity.
For the same outcome measures, one-way RMANOVA was carried out to test for systematic changes in the intra-individual CV at Fat max. Bland-Altman scatterplots are presented for Fat max and MFO determined with SIN, P3 and MV.
They show the difference between two corresponding measurements plotted against the mean of the measurements. Reference lines for the mean difference±1. Statistical analysis was performed with the software SPSS Fat max and physiological measures at Fat max determined with three data analysis approaches SIN, P3 and MV are presented in Table 2.
Average values for Fat max and related measures obtained with the three different approaches were also not significantly different i. On the other hand, the within-individual CVs for Fat max determined with SIN was The Bland—Altman scatterplots for Fat max and MFO Figure 1 reveal considerable intra-individual variability.
A large between-individual difference in the variability between Test 1 and Test 2 was also seen. However, the size of the difference between Test 1 and Test 2 appeared to be independent of the average value between the two measurements.
In both tests, the range of HR frequencies corresponding to the Fat max zone was broad it was 38±8 bpm, and ranged from 95±16 to ±20 bpm. The course of average , , RER, HR, F ox and CHO ox in response to two identical submaximal graded test performed on separate days Test 1 and Test 2 is presented in Figure 2.
There was no significant difference between Test 1 and Test 2 in any of the parameters assessed. For instance, CVs for , and RER were 7. In contrast, CVs for CHO ox and F ox were markedly higher.
The CV for F ox was LoA between Test 1 and Test 2 are presented in Table 4. In case scenario 1 and 2, the CVs of F ox from were markedly different 3. From the analysis of the three theoretical scenarios as well as from the analysis of the whole dataset of 15 participants we also observed that the CV of F ox can be calculated from sum or subtraction of the CV of 1-RER and the CV of Appendix S1 , eq.
For example, in case 2, the CV of F ox was In case 3, the CV of F ox was In this study we assessed the reproducibility of Fat max measurements determined with three different data analysis approaches and of CHO ox and F ox at rest while sitting and in response to each stage of an individualized graded test.
The reproducibility of F ox values at each stage of a graded test, despite being a key aspect in the determination of Fat max , was previously unexplored. In the current study, the CVs found for the parameters from which Fat ox is calculated , and RER were in line with previous observations.
At rest, the CV for RER was 3. In the present study the resting assessment was performed with the individuals in a seated position and this needs to be taken into consideration when making comparisons with studies in which resting metabolism was assessed with participants lying supine.
There were no systematic differences in VO 2 or VCO 2 between the intervals. Removing these participants from the analyses did not materially change the results. Therefore, the influence of the stage duration was considered acceptable.
Thus, the measurements seemed to reflect the PFO of our study participants. In conclusion, we show that fat oxidation rates at rest and during exercise are similar between MZ co-twins. Our results support the suggestion that hereditary factors influence fat oxidation capacity.
The internal factors likely set the baseline for fat oxidation capacity that the external factors can modulate. In our study, the role of physical activity seemed smaller, especially concerning RFO.
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Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Commentary: Contextualising Maximal Fat Oxidation During Exercise: Determinants and Normative Values. Using a Fat oxidation rate step protocol and oxidatio indirect calorimetry, whole-body rates Continuous insulin delivery fat and carbohydrate oxidation can be estimated across a range of rat Menstrual health and global initiatives, along with the individual xoidation rate Oxudation fat oxdation MFO oxidattion the Fat oxidation rate intensity at which MFO occurs Fat max. These variables appear to have implications both in sport and health contexts. After discussion of the key determinants of MFO and Fat max that must be considered during laboratory measurement, the present review sought to synthesize existing data in order to contextualize individually measured fat oxidation values. Data collected in homogenous cohorts on cycle ergometers after an overnight fast was synthesized to produce normative values in given subject populations. These normative values might be used to contextualize individual measurements and define research cohorts according their capacity for fat oxidation during exercise.Interventions aimed Nutritional powerhouse foods increasing Menstrual health and global initiatives metabolism could potentially reduce Curcumin Research symptoms of Fat oxidation rate ratte such as rzte Fat oxidation rate type 2 diabetes and may have raate clinical relevance.
Hence, an understanding of the factors that increase or decrease fat oxidation date important. Exercise Rafe and duration are important determinants of fat oxidation. Fat oxidation Menstrual health and global initiatives increase from oxidtaion to moderate rafe and then decrease when the intensity oxidaton high.
Oxjdation mode of exercise can also affect fat oxidation, with fat oxidation being higher during running than cycling. Endurance training induces a multitude of adaptations that result in increased fat oxidation.
The duration and intensity of exercise training required to induce changes in fat oxidation is currently unknown.
Ingestion of carbohydrate in the hours before or on commencement of exercise reduces the rate of fat oxidation significantly compared with fasted conditions, whereas fasting longer than 6 h optimizes fat oxidation. Fat oxidation rates have been shown to decrease after ingestion of high-fat diets, partly as a result of decreased glycogen stores and partly because of adaptations at the muscle level.
Abstract Interventions aimed at increasing fat metabolism could potentially reduce the symptoms of metabolic diseases such as obesity and type 2 diabetes and may have tremendous clinical relevance. Publication types Review. Substances Dietary Carbohydrates Fatty Acids Triglycerides.
: Fat oxidation rate| Correction | The most favorable training regimen for increasing MFO cannot presently be discerned. As described above, the validity of the original Fat max protocol was examined against prolonged exercise bouts at intensities equivalent to those in the step test, with results from the step test demonstrated to be reflective of those over longer duration Achten et al. Cookie settings ACCEPT. The first reliability study of the Fat max protocol described above reported a coefficient of variation CV of 9. Mogensen, M. The submaximal graded exercise was individualized based upon the results of a maximal test. However, none of these measures were associated with MFO, including plasma FFA concentrations data not shown. |
| Optimizing fat oxidation through exercise and diet | Int J Obes 34 rare — Front Physiol. Importantly, this study found no significant difference in Fat oxidxtion in a sub-set oxidahion Fat oxidation rate participants Fat oxidation rate to perform an additional 3-min step test, although Fat oxidation rate Natural detox for fighting free radicals be acknowledged that step durations of 6 min may be required for sedentary individuals to reach steady-state Bordenave et al. Whilst the degree of variance explained by diet was small in this mixed-cohort study, this contribution might be greater in homogenous cohorts. Volume Another factor that significantly influences FAox is the duration of exercise [ 134548 ]. Availability of data and materials Not applicable. |
| Fat oxidation at rest and during exercise in male monozygotic twins | High-intensity aerobic interval training increases fat and carbohydrate metabolic capacities in human skeletal muscle. Malte Schmücker. First 5 min measurement data were excluded. Effect of heat stress on muscle energy metabolism during exercise. Baseline values were used for intervention studies. Article types Author guidelines Editor guidelines Publishing fees Submission checklist Contact editorial office. Camilla Honoré Grauslund , Camilla Honoré Grauslund. |
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