Calculation Of Energy Expenditure Research Articles

A stepwise science-industry collaboration to optimize the calculation of energy expenditure during walking and running with a consumer-based activity device

Physical activity (PA) and sedentary behavior (SB) have important implications for health benefits. A growing number of people use consumer available wearables such as activity trackers, which claim to objectively monitor PA and SB in free-living conditions. These devices could provide essential information to understand the influence of behavior on health. This understanding assumes that available consumer products correctly monitor PA in the everyday life. A general approach in science is to validate such activity devices in a controlled environment. The classical procedure to investigate criterion validity is to examine new devices based on the gold standard. To our knowledge, the resulting validation data are not often analyzed and shared with manufacturers to further develop and improve the activity device. The current study can be seen as a validation study to check the criterion validity of a consumer-level activity device. The novelty of this study was the application of a stepwise approach to optimize the calculations of a consumer available activity device (i.e., Activ8; www.activ8all.com/product/activ8-professional-activity-monitor/) for estimating energy expenditure (EE) in walking and running.Forty adults (27 males and 13 females) participated in three substudies. Each substudy consisted of several walking and running activities in which EE was simultaneously measured with indirect calorimetry (as reference value) and the Activ8 activity device. EE values at each walking and running speed were compared to identify the accuracy of the Activ8 device. After completion of the first and second substudies, the results were shared and discussed with the manufacturer of Activ8. Next, the calculations for EE were adapted to the indirect calorimetry values to improve accuracy. In the second and third substudies, the modifications were tested, and results were used to further optimize the calculation of EE.The results of this study show an improved correlation between EE measured by indirect calorimetry and the Activ8 activity device (R2 from 0.91 to 0.95); a decrease in differences between substudy A and substudy B considering EE measured (indirect calorimetry) and calculated (Activ8 calculation) was observed. The second modification in the calculation showed a further increase in correlation (R2 from 0.95 to 0.97) between the measured and calculated EE; however, the absolute difference between the two values increased. The results from a validation study are valuable to use for further adaptation of accelerometer device calculations. A stepwise science-industry collaboration can improve the calculation accuracy and may be a practical approach for validation studies in which human movement scientists and technology manufacturers work together to successfully improve the validity and accuracy of consumer-based activity devices.

MET-values of standardised activities in relation to body fat: studies in pregnant and non-pregnant women

BackgroundPhysical activity is associated with health in women. Published MET-values (MET: metabolic equivalent of task) may assess physical activity and energy expenditure but tend to be too low for subjects with a high total body fat (TBF) content and therefore inappropriate for many contemporary women. The MET-value for an activity is the energy expenditure of a subject performing this activity divided by his/her resting energy expenditure, often assumed to be 4.2 kJ/kg/h. Relationships between TBF and MET have been little studied although overweight and obesity is common in women. Available data indicate that MET-values decrease during pregnancy but more studies in pregnant contemporary women are needed.Subjects and methodsUsing indirect calorimetry we measured energy expenditure and assessed MET-values in women, 22 non-pregnant (BMI: 18–34) and 22 in gestational week 32 (non-pregnant BMI: 18–32) when resting, sitting, cycling (30 and 60 watts), walking (3.2 and 5.6 km/h) and running (8 km/h). Relationships between TBF and MET-values were investigated and used to predict modified MET-values. The potential of such values to improve calculations of total energy expenditure of women was investigated.ResultsThe resting energy expenditure was below 4.2 kJ/kg/h in both groups of women. Women in gestational week 32 had a higher resting energy metabolism (p < 0.001) and 7–15% lower MET-values (p < 0.05) than non-pregnant women. MET-values of all activities were correlated with TBF (p < 0.05) in non-pregnant women and modified MET-values improved estimates of total energy expenditure in such women. In pregnant women, correlations (p ≤ 0.03) between TBF and MET were found for running (8 km/h) and for walking at 5.6 km/h.ConclusionsOur results are relevant when attempts are made to modify the MET-system in contemporary pregnant and non-pregnant women. MET-values were decreased in gestational week 32, mainly due to an increased resting energy metabolism and studies describing how body composition affects the one MET-value (i.e. the resting energy metabolism in kJ/kg/h) during pregnancy are warranted. Studies of how pregnancy and TBF affect MET-values of high intensity activities are also needed. Corrections based on TBF may have a potential to improve the MET-system in non-pregnant women.

The Association of Muscular Strength and Treadmill-Based Walking Economy in Older Men and Women.

Ageing is linearly associated with increased body fat percentage (BF%) and decreased muscular strength, which may lead to lower force production and decreased physical function (PF) in older adults (age 60+ yrs.). The magnitude at which age-related decrements affect energy expenditure associated with walking economy (WE) is not well understood. A better understanding of the relationship between BF%, lower body muscular strength (LBMS), and PF, and the degree to which these variables are related to WE is important for the clinical exercise approach with older adults. PURPOSE: To determine the association of BF%, LBMS, and PF on WE in older adults when walking at three separate treadmill speeds. METHODS: Twenty-three older adults (12 men, 11 women; age 70 ± 6 yrs.) were recruited to participate. Session 1 included screening, protocol familiarization, and body composition assessment measure (BodPod®). During sessions 2 and 3, participants performed either a treadmill walking (TMW) protocol (three separate 6-minute TMW bouts at set speeds of 0.45, 0.89, and 1.34 m·sec-1) or a LBMS measure (1RM Leg Press) and PF test battery (SPPB). Session, walking speed, and strength/functional testing order was counter-balanced and WE was calculated as an index (kcal·min-1[BULLET OPERATOR]W-1). Steady state oxygen uptake was used to calculate energy expenditure for all TMW bouts. A linear mixed effects model was used to determine associations between BF%, LBMS, and PF on WE at the three TMW bouts. An a priori alpha of p ≤ 0.05 was set for statistical significance. RESULTS: Twenty-one older adults (11 men, 10 women; age 70 ± 6 yrs.) completed the study. There were no significant correlations for BF% (r1 = 0.19, p1 = 0.41), LBMS (r1 = -0.07, p1 = 0.78), and PF (r1 = 0.14, p1 = 0.55) on WE at the 0.45 m·sec-1 speed. Correlations were also not significant on WE at the 0.89 m·sec-1 speed [BF% (r2 = -0.22, p2 = 0.34), LBMS (r2 = 0.01, p2 = 0.96), and PF (r2 = 0.18, p2 = 0.44)] and the 1.34 m·sec-1 speed [BF% (r3 = 0.09, p3 = 0.71), LBMS (r3 = 0.14, p3 = 0.54), and PF (r3 = -0.26, p3 = 0.25)]. CONCLUSION: BF%, LBMS, and PF may not be associated with age-related decrements in WE with older adults during treadmill walking. Future research is needed to better determine the interactions of these variables on WE in older adults.

Why are women slimmer than men in developed countries?

Women have a lower BMI than men in developed countries, yet the opposite is true in developing countries. We call this the gender BMI puzzle and investigate its underlying cause. We begin by studying time trends in Japan, where, consistent with the cross-country puzzle, the BMI of adult women has steadily decreased since the 1950s, whereas the BMI of adult men has steadily increased. We study how changes in energy intake and energy expenditure account for the over-time gender BMI puzzle using the Japanese National Nutrition Survey from 1975 to 2010, which provides nurse-measured height and weight and nutritionist-assisted food records. Because long-term data on energy expenditure do not exist, we calculate energy expenditure using a steady-state body weight model. We then conduct cross-country regression analysis to corroborate what we learn from the Japanese data.We find that both energy intake and energy expenditure have significantly decreased for Japanese adult men and women and that a larger reduction in energy expenditure among men than women accounts for the increasing male-to-female BMI gap. Trends in BMI and energy expenditure vary greatly by occupation, suggesting that a relatively large decrease in physical activity in the workplace among men underlies the gender BMI puzzle.The cross-country analysis supports the generalizability of the findings beyond the Japanese data. Furthermore, the analysis suggests the increasing male-to-female BMI gap is driven not only by a reduction in the energy requirements of physically demanding work but also by weakening occupational gender segregation. No support is found for other explanations, such as increasing female labor force participation, greater female susceptibility to malnutrition in utero, and gender inequality in nutrition in early life.

Physiological variables in energy expenditure estimation by actigraphy: a systematic review protocol

Background: Energy expenditure measurement based on movement quantity is showed as a relevant alternative in clinical and research contexts. The best recommended and validated methods are expensive and inconvenient to field measurement, limiting the use to the laboratory. Lately, several devices have been developed to identify and classify activities by body movements, showing acceptable outcomes. These devices and techniques have been used to estimate energy expenditure in many physical activities situations. However, for this, is necessary include physiological variables. Methods: We propose a systematic review to identify evidence of influence and relevancy of physiological variables in energy expenditure measurement by actigraphy. We will search for Academic Search Complete, Scopus, Web of Science, Science Direct, Pubmed, and Informaworld by Francis &amp; Taylor databases. Discussion: The outcomes will be synthesized to identify variables used in energy expenditure calculation methods and analyze the error between measured and calculated values considering the influence of physiological variables on this.

The essence of neuronal activity from the consistency of two different neuron models

Based on the H–H equation, this study has proposed the calculation and analysis of energy expenditure for a single neuron which is activated at sup-threshold and subthreshold, as well as the criterion of the energy expenditure of neurons activated sup-threshold and subthreshold, which was the maximum power of a sodium ion pump. Results of the study showed that not only the electrophysiological activities of neurons were strictly restricted by the energy levels in the brain, but also the activities of neurons also had dual nature, meaning that subthreshold neurons were mainly with energy expenditure, while sup-threshold neurons were with both energy absorption and energy expenditure. These new findings were compared with the novel neuro-biophysical models that we have published last year, uncovering that the two models were essentially equivalent.

Short-Term Overfeeding with Dairy Cream Does Not Modify Gut Permeability, the Fecal Microbiota, or Glucose Metabolism in Young Healthy Men

BackgroundHigh-fat diets (HFDs) have been linked to low-grade inflammation and insulin resistance. ObjectiveThe main purpose of the present study was to assess whether acute overfeeding with an HFD affects insulin sensitivity, gut barrier function, and fecal microbiota in humans. MethodsIn a prospective intervention study, 24 healthy men [mean ± SD: age 23.0 ± 2.8 y, body mass index (in kg/m2) 23.0 ± 2.1] received an HFD (48% of energy from fat) with an additional 1000 kcal/d (as whipping cream) above their calculated energy expenditure for 7 d. Insulin sensitivity (hyperinsulinemic euglycemic clamp), gut permeability (sugar and polyethylene glycol absorption tests, plasma zonulin), and gut microbiota profiles (high-throughput 16S rRNA gene sequencing) were assessed before and after overfeeding, and 14 d after intervention. Additionally, inflammation markers such as high-sensitivity C-reactive protein, lipopolysaccharide-binding protein, leptin, high-molecular-weight adiponectin, calprotectin, regulated on activation normal, T cell expressed and secreted (RANTES), and monocyte chemoattractant protein-1 were measured in plasma by ELISA. Finally, lipid parameters were analyzed in serum by a laboratory service. ResultsAlthough participants gained 0.9 ± 0.6 kg (P < 0.001) body weight, overnutrition was not associated with a significant change in insulin sensitivity (M value and glucose disposal). Overfeeding for 7 d resulted in elevated serum total (10.2%), LDL (14.6%) and HDL (14.8%) cholesterol concentrations (P < 0.01). In contrast, fasting plasma triglyceride significantly declined (29.3%) during overfeeding (P < 0.001). In addition, there were no significant changes in inflammatory markers. Urine excretion of 4 sugars and polyethylene glycol, used as a proxy for gut permeability, and plasma concentration of zonulin, a marker of paracellular gut permeability, were unchanged. Moreover, overfeeding was not associated with consistent changes in gut microbiota profiles, but marked alterations were observed in a subgroup of 6 individuals. ConclusionsOur findings suggest that short-term overfeeding with an HFD does not significantly impair insulin sensitivity and gut permeability in normal-weight healthy men, and that changes in dominant communities of fecal bacteria occur only in certain individuals. The study was registered in the German Clinical Trial Register as DRKS00006211.

Energy and Protein in Critically Ill Patients with AKI: A Prospective, Multicenter Observational Study Using Indirect Calorimetry and Protein Catabolic Rate.

The optimal nutritional support in Acute Kidney Injury (AKI) still remains an open issue. The present study was aimed at evaluating the validity of conventional predictive formulas for the calculation of both energy expenditure and protein needs in critically ill patients with AKI. A prospective, multicenter, observational study was conducted on adult patients hospitalized with AKI in three different intensive care units (ICU). Nutrient needs were estimated by different methods: the Guidelines of the European Society of Parenteral and Enteral Nutrition (ESPEN) for both calories and proteins, the Harris-Benedict equation, the Penn-State and Faisy-Fagon equations for energy. Actual energy and protein needs were repeatedly measured by indirect calorimetry (IC) and protein catabolic rate (PCR) until oral nutrition start, hospital discharge or renal function recovery. Forty-two patients with AKI were enrolled, with 130 IC and 123 PCR measurements obtained over 654 days of artificial nutrition. No predictive formula was precise enough, and Bland-Altman plots wide limits of agreement for all equations highlight the potential to under- or overfeed individual patients. Conventional predictive formulas may frequently lead to incorrect energy and protein need estimation. In critically ill patients with AKI an increased risk for under- or overfeeding is likely when nutrient needs are estimated instead of measured.

COMPARISON STUDY OF ENERGY EXPENDITURE CALCULATION BETWEEN CONVENTIONAL METHOD AND IRETON-JONES METHOD FOR CRITICALLY ILL PATIENT

Background: The critically ill patients are having nutrition problems in dealing with the critical condition. The problem of nutrition is demanding on the severity of illness. Therefore, the ICU nurses should understand how nutrition can support the patients’ recovery. &#x0D; Objective: This study’s aim was to compare the result of energy expenditure calculation of conventional method with Ireton-Jones method for critically ill patients in the intensive care unit.&#x0D; Methods: This was a comparative and cross-sectional study which recruited 40 samples. The samples were divided into two groups, conventional group method and Ireton-Jones group method, and they met the inclusion criteria. The sample of this study was determined by convenience sampling. To answer the hypothesis, the hypothesis test used Independent sample t-test.&#x0D; Results: The results revealed that there is no significance difference between energy expenditure calculation conventional method and Ireton-Jones method statically. In the other word, either used the conventional method or the Ireton Jones method, the result of energy expenditure calculation has statically significant difference.&#x0D; Conclusion: It can be concluded that the nurse can use both methods to calculate the energy expenditure for critically ill patients to meet their nutrition need. We suggest that for further investigation will recruit many samples and do control of other factors that might be influenced in the study.

Can calculation of energy expenditure based on CO2 measurements replace indirect calorimetry?

BackgroundMethods to calculate energy expenditure (EE) based on CO2 measurements (EEVCO2) have been proposed as a surrogate to indirect calorimetry. This study aimed at evaluating whether EEVCO2 could be considered as an alternative to EE measured by indirect calorimetry.MethodsIndirect calorimetry measurements conducted for clinical purposes on 278 mechanically ventilated ICU patients were retrospectively analyzed. EEVCO2 was calculated by a converted Weir’s equation using CO2 consumption (VCO2) measured by indirect calorimetry and assumed respiratory quotients (RQ): 0.85 (EEVCO2_0.85) and food quotient (FQ; EEVCO2_FQ). Mean calculated EEVCO2 and measured EE were compared by paired t test. Accuracy of EEVCO2 was evaluated according to the clinically relevant standard of 5% accuracy rate to the measured EE, and the more general standard of 10% accuracy rate. The effects of the timing of measurement (before or after the 7th ICU day) and energy provision rates (<90 or ≥90% of EE) on 5% accuracy rates were also analyzed (chi-square tests).ResultsMean biases for EEVCO2_0.85 and EEVCO2_FQ were -21 and -48 kcal/d (p = 0.04 and 0.00, respectively), and 10% accuracy rates were 77.7 and 77.3%, respectively. However, 5% accuracy rates were 46.0 and 46.4%, respectively. Accuracy rates were not affected by the timing of the measurement, or the energy provision rates at the time of measurements.ConclusionsCalculated EE based on CO2 measurement was not sufficiently accurate to consider the results as an alternative to measured EE by indirect calorimetry. Therefore, EE measured by indirect calorimetry remains as the gold standard to guide nutrition therapy.

Scoring protocol for calculation of total energy expenditure by physical activity questionnaires used in Japanese cohort studies

Scoring protocol for calculation of total energy expenditure by physical activity questionnaires used in Japanese cohort studies

Seasonal changes in background levels of deuterium and oxygen-18 prove water drinking by harp seals, which affects the use of the doubly labelled water method.

The aim of this study was to monitor seasonal changes in stable isotopes of pool freshwater and harp seal (Phoca groenlandica) body water, and to study whether these potential seasonal changes might bias results obtained using the doubly labelled water (DLW) method when measuring energy expenditure in animals with access to freshwater. Seasonal changes in the background levels of deuterium and oxygen-18 in the body water of four captive harp seals and in the freshwater pool in which they were kept were measured over a time period of 1year. The seals were offered daily amounts of capelin and kept under a seasonal photoperiod of 69°N. Large seasonal variations of deuterium and oxygen-18 in the pool water were measured, and the isotope abundance in the body water showed similar seasonal changes to the pool water. This shows that the seals were continuously equilibrating with the surrounding water as a result of significant daily water drinking. Variations in background levels of deuterium and oxygen-18 in freshwater sources may be due to seasonal changes in physical processes such as precipitation and evaporation that cause fractionation of isotopes. Rapid and abrupt changes in the background levels of deuterium and oxygen-18 may complicate calculation of energy expenditure by use of the DLW method. It is therefore strongly recommended that analysis of seasonal changes in background levels of isotopes is performed before the DLW method is applied on (free-ranging) animals, and to use a control group in order to correct for changes in background levels.

Evaluation of a non-invasive multisensor accelerometer for calculating energy expenditure in ventilated intensive care patients compared to indirect calorimetry and predictive equations.

Continuous measurement of resting energy expenditure (REE) in critically ill patients remains challenging but is required to prevent malnutrition. SenseWear Pro 3 Armband (SWA) is a research grade accelerometer for assessment of REE with the advantage of easy handling. In a prospective study we compared SWA with indirect calorimetry (IC) and predictive equations in critically ill, ventilated patients. REE was measured by SWA, IC and calculated by predictive formulas. Potential confounding factors that influence REE were also recorded. Results of SenseWear Armband and indirect calorimetry were compared using the Bland-Altman method. 34 ICU patients were investigated. SWA underestimated resting energy expenditure compared to IC with a mean bias of ΔREE=-253.6±333.2kcal, equivalent to -11.7% (p=0.025). This underestimation was seen in both, medical (-14.9%) and surgical (-12.9%) patients and the bias was greater in patients with fever (-19.0%), tachycardia (-18.7%) or tachypnea (-26.2%). Differences were also noted when SWA was compared to predictive formulas. At present, SWA cannot be regarded as an alternative to indirect calorimetry. Individual measurements are often inaccurate and should be used with caution until improved algorithms, based on the results of this study, have been implemented.

Metabolic Demand and Internal Training Load in Technical-Tactical Training Sessions of Professional Futsal Players.

Wilke, CF, Ramos, GP, Pacheco, DAS, Santos, WHM, Diniz, MSL, Gonçalves, GGP, Marins, JCB, Wanner, SP, and Silami-Garcia, E. Metabolic demand and internal training load in technical-tactical training sessions of professional futsal players. J Strength Cond Res 30(8): 2330-2340, 2016-The aim of the study was to characterize aspects of technical-tactical training sessions of a professional futsal team. We addressed 4 specific aims: characterize the metabolic demands and intensity of these training sessions, compare the training intensity among players of different positions, compare the intensity of different futsal-specific activities (4 × 4, 6 × 4, and match simulation), and investigate the association between an objective (training impulse; TRIMP) and a subjective method (session rating of perceived exertion; sRPE) of measuring a player's internal training load. Twelve top-level futsal players performed an incremental exercise to determine their maximal oxygen consumption, maximal heart rate (HRmax), ventilatory threshold (VT), and respiratory compensation point (RCP). Each player's HR and RPE were measured and used to calculate energy expenditure, TRIMP, and sRPE during 37 training sessions over 8 weeks. The average intensity was 74 ± 4% of HRmax, which corresponded to 9.3 kcal·min. The players trained at intensities above the RCP, between the RCP and VT and below the VT for 20 ± 8%, 28 ± 6%, and 51 ± 10% of the session duration, respectively. Wingers, defenders, and pivots exercised at a similar average intensity but with different intensity distributions. No difference in intensity was found between the 3 typical activities. A strong correlation between the average daily TRIMP and sRPE was observed; however, this relationship was significant for only 4 of 12 players, indicating that sRPE is a useful tool for monitoring training loads but that it should be interpreted for each player individually rather than collectively.

Mobile cardiorespiratory and metabolic laboratory: diagnosis of chronic obstructive pulmonary disease, cardiovascular and metabolic diseases

The aim of this study was to determine risk factors of chronic non-infectious diseases and early diagnosis of cardiovascular, respiratory and endocrine functional disorders in industrial workers using a mobile cardiorespiratory and metabolic laboratory. Methods. This was a prospective non-comparative observational study in a non-selected population. All participants underwent the following measurements: weight and height, wrist and thigh circumferences, pulse oxymetry, exhaled nitric oxide (NO) and exhaled carbon monooxide (CO), spirometry before and after bronchodilator inhalation, electrocardiogram, arterial stiffness and endothelial dysfunction, blood glucose and blood total cholesterol. Indirect calorimetry with energy expenditure calculation was used in several patients. Validated questionnaires were also used. Results. The study involved 194 industrial workers. High prevalence of risk factors, such as tobacco smoking (45% of active smokers, 31% of ex-smokers), obesity (BMI ≥ 30 kg x m –2 in 37%), hypercholesterolemia (34%), and endothelial dysfunction (57%), was found. Vascular biomechanics correlated with bronchial patency, systemic arterial pressure and exhaled CO concentration. Bronchial obstruction was found in 56% of subjects, of them, COPD was diagnosed in 13%. Conclusion. Mobile cardiorespiratory and metabolic laboratory allows medical care delivery directly to a working place, and effective detection of risk factors and chronic lung disease.

Simple equations for complex physiology: can we use VCO2 for calculating energy expenditure?

In a recent article, Stapel et al. [1] gave a practical and easy solution for the evaluation of energy expenditure in critically ill patients. Predictive equations are routinely used to determine energy needs and to guide the prescription of calories in critically ill patients [2]. However, their accuracy is very poor, resulting in both over- and underfeeding [3], and thus confounding the validity of many studies based on these equations. Indirect calorimetry remains the gold standard to determine calorie requirements, as well as to calculate energy expenditure (EE) from oxygen consumption (VO2), carbon dioxide production (VCO2) and nitrogen excretion (NM) measurements [4]. These devices are still seldom used since they may be expensive, require expertise and have several technical limitations [5]. Moreover, the most accurate device, the Deltatrac II (GE, Finland) is not widely available and other new devices have still to achieve its accuracy [6].

Dilution space ratio of 2H and 18O of doubly labeled water method in humans.

Variation of the dilution space ratio (Nd/No) between deuterium ((2)H) and oxygen-18 ((18)O) impacts the calculation of total energy expenditure (TEE) by doubly labeled water (DLW). Our aim was to examine the physiological and methodological sources of variation of Nd/No in humans. We analyzed data from 2,297 humans (0.25-89 yr old). This included the variables Nd/No, total body water, TEE, body mass index (BMI), and percent body fat (%fat). To differentiate between physiologic and methodologic sources of variation, the urine samples from 54 subjects were divided and blinded and analyzed separately, and repeated DLW dosing was performed in an additional 55 participants after 6 mo. Sex, BMI, and %fat did not significantly affect Nd/No, for which the interindividual SD was 0.017. The measurement error from the duplicate urine sample sets was 0.010, and intraindividual SD of Nd/No in repeats experiments was 0.013. An additional SD of 0.008 was contributed by calibration of the DLW dose water. The variation of measured Nd/No in humans was distributed within a small range and measurement error accounted for 68% of this variation. There was no evidence that Nd/No differed with respect to sex, BMI, and age between 1 and 80 yr, and thus use of a constant value is suggested to minimize the effect of stable isotope analysis error on calculation of TEE in the DLW studies in humans. Based on a review of 103 publications, the average dilution space ratio is 1.036 for individuals between 1 and 80 yr of age.

GEDAE-LaB: A Free Software to Calculate the Energy System Contributions during Exercise.

PurposeThe aim of the current study is to describe the functionality of free software developed for energy system contributions and energy expenditure calculation during exercise, namely GEDAE-LaB.MethodsEleven participants performed the following tests: 1) a maximal cycling incremental test to measure the ventilatory threshold and maximal oxygen uptake (O2max); 2) a cycling workload constant test at moderate domain (90% ventilatory threshold); 3) a cycling workload constant test at severe domain (110% O2max). Oxygen uptake and plasma lactate were measured during the tests. The contributions of the aerobic (AMET), anaerobic lactic (LAMET), and anaerobic alactic (ALMET) systems were calculated based on the oxygen uptake during exercise, the oxygen energy equivalents provided by lactate accumulation, and the fast component of excess post-exercise oxygen consumption, respectively. In order to assess the intra-investigator variation, four different investigators performed the analyses independently using GEDAE-LaB. A direct comparison with commercial software was also provided.ResultsAll subjects completed 10 min of exercise at moderate domain, while the time to exhaustion at severe domain was 144 ± 65 s. The AMET, LAMET, and ALMET contributions during moderate domain were about 93, 2, and 5%, respectively. The AMET, LAMET, and ALMET contributions during severe domain were about 66, 21, and 13%, respectively. No statistical differences were found between the energy system contributions and energy expenditure obtained by GEDAE-LaB and commercial software for both moderate and severe domains (P > 0.05). The ICC revealed that these estimates were highly reliable among the four investigators for both moderate and severe domains (all ICC ≥ 0.94).ConclusionThese findings suggest that GEDAE-LaB is a free software easily comprehended by users minimally familiarized with adopted procedures for calculations of energetic profile using oxygen uptake and lactate accumulation during exercise. By providing availability of the software and its source code we hope to facilitate future related research.

Psyhical effort, energy expediture, and motivation in structured and unstructured active video games: a randomized controlled trial

PurposeThe goals of the study were: a) to compare the way that two types of active video games (AVG) influenced physical effort and motivation in young adults; b) to compare direct and indirect instruments and use an indirect instrument (heart rate analysis) as a practical tool to verify physical effort in AVGsMethodsMethods. Initially, 16 healthy but physically inactive young adult males with no AVGs experience took part in the randomized control trial. After the baseline assessments of blood pressure (BP), heart rate (HR), and aerobic capacity (AE), the participants were randomized into two groups: structured AVG (&lt;i&gt;n&lt;/i&gt; = 6) and unstructured AVG (&lt;i&gt;n&lt;/i&gt; = 7) (3 dropouts). They played 3 sessions a week, during 6 weeks. Direct and indirect metabolic measurements were made. To compare direct and indirect AE, Student t-test was used for related samples. Changes (group × time) in HR, perceived exertion (PE), calculated energy expenditure (EE), calculated metabolic equivalent (MET), and motivation (points) were assessed with the two-way analysis of varianceResultsThere were no differences between direct and indirect AE (36.0 ± 5.2 vs 33.9 ± 6.0 ml/kg/min: unstructured; 39.0 ± 5.9 vs 37.7 ± 5.9 ml/kg/min; &lt;i&gt;p&lt;/i&gt; &gt; 0.05). No differences were observed in maximal HR, PE, or motivation (&lt;i&gt;p&lt;/i&gt; &gt; 0.05). Statistically significant differences referred to average HR, MET, and EE over the sessions (&lt;i&gt;p&lt;/i&gt; &lt; 0.05). HR and EE values were higher in structured than in unstructured AVGsConclusionsHR and EE responses of structured AVGs turned out higher than those of unstructured AVGs, and the measurements proved efficient to analyse physical effort in AVGs in a long-term perspective

Análise do gasto energético na Distrofia muscular de Duchenne nos ambientes aquático e terrestre

Introduction. Duchenne muscular dystrophy (DMD) is a progres­sive genetic disease, characterized by progressive and irreversible de­generation of muscle fibers, requiring energy demand during func­tional activities. Given this characteristic, energy expenditure becomes a key factor in a rehabilitation program. So, it is essential energy ex­penditure clinical assessment in different environments. Objective. Analyze the energy expenditure of children with DMD during gait in aquatic and land environments. Method. The study included 8 boys with DMD (10.4±0.5 years), ambulating and collaborative for testing. They were not included in rehabilitation programs and had no associated diseases. It was applied 6-minute walk test (6MWT) in land and aquatic environment, and calculate energy expenditure in­dex by the formula: End FC - divided by the initial speed FC (meters/ second) and is expressed in beats/minute in the aquatic and terres­trial. Results. It was observed that DMD patients walked (p=0.012) a shorter distance in water in relation to the ground. DMD patients had (p=0.012) higher average of energy expenditure in aquatic envi­ronment (3.69±0.44) when compared to land (0.43±0.15). Conclu­sion. The patients walked a shorter distance and with higher energy expenditure in aquatic environment.