135 resultados para ENERGY-EXPENDITURE


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Several empirical studies have shown that variation in daily energy expenditure (DEE) and resting metabolic rate (RMR) is influenced by environmental and individual factors, but whether these shared influences are responsible for, or independent of, relationships between DEE and RMR remains unknown. The objectives of this study were to (i) simultaneously evaluate the effects of environmental and individual variables on DEE and RMR in free-ranging eastern chipmunks (Tamias striatus) and (ii) quantify the correlation between DEE and RMR before and after controlling for common sources of variation. We found that the influence of individual factors on DEE and RMR is most often shared, whereas the influence of environmental factors tends to be distinct. Both raw and mass-adjusted DEE and RMR were significantly correlated, but this correlation vanished after accounting for the shared effect of reproduction on both traits. However, within reproductive individuals, DEE and RMR remained positively correlated after accounting for all other significant covariates. The ratio of DEE to RMR was significantly higher during reproduction than at other times of the year and was negatively correlated with ambient temperature. DEE and RMR appear to be inherently correlated during reproduction, but this correlation does not persist during other, less energy-demanding periods of the annual cycle.

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The domestic dog has undergone extensive artificial selection resulting in an extreme diversity in body size, personality, life‐history, and metabolic traits among breeds. Here we tested whether proactive personalities (high levels of activity, boldness, and aggression) are related to a fast “pace of life” (high rates of growth, mortality, and energy expenditure). Data from the literature provide preliminary evidence that artificial selection on dogs (through domestication) generated variations in personality traits that are correlated with life histories and metabolism. We found that obedient (or docile, shy) breeds live longer than disobedient (or bold) ones and that aggressive breeds have higher energy needs than unaggressive ones. These correlations could result from either human preference for particular trait combinations or, more likely, correlated responses to artificial selection on personality. Our results suggest the existence of a general pace‐of‐life syndrome arising from the coevolution of personality, metabolic, and life‐history traits.

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Objectives
Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers.

Methods
Forty children aged 4–6 years (5.3±1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points.

Results
The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others.

Conclusion
Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s−1 and ≥420 counts⋅15 s−1 for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended.

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The relationship between mass loss rate and chemical power in flying birds is analysed with regard to water and heat balance. Two models are presented: the first model is applicable to situations where heat loads are moderate. i.e. when heat balance can be achieved by regulating non-evaporative heat loss, and evaporative water loss is minimised. The second model is applicable when heat loads are high, non-evaporative heat loss is maximised. and heat balance has to be achieved by regulating evaporative heat loss. The rates of mass loss of two Thrush Nightingales Luscinia luscinia and one Teal Anas crecca were measured at various flight speeds in a wind tunnel. Estimates of metabolic water production indicate that the Thrush Nightingales did not dehydrate during experimental flights. Probably, the Thrush Nightingales maintained heat balance without actively increasing evaporative cooling. The Teal, however, most likely had to resort to evaporative cooling, although it may not have dehydrated. Chemical power was estimated from our mass loss rate data using the minimum evaporation model for the Thrush Nightingales and the evaporative heat regulation model for the Teal. For both Thrush Nightingales and the Teal, the chemical power calculated from our mass loss rate data showed a greater change with speed (more 'U-shaped' curve) than the theoretically predicted chemical power curves based on aerodynamic theory. The minimum power speeds calculated from our data differed little from theoretical predictions but maximum range speeds were drastically different. Mass loss rate could potentially be used to estimate chemical power in flying birds under laboratory conditions where temperature and humidity are controlled. However, the assumptions made in the models and the model predictions need further testing.

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This paper introduces an ambulatory energy expenditure technique using a single inertial sensor, and compares the performance with an industry standard metabolic measurement system. Wearable energy expenditure estimation systems are key instruments in athlete evaluation. The cost and size of traditional oxygen intake measurement systems (VO2 systems) limits usage of such technology in everyday athlete training and evaluation events. This project describes a method of estimating energy expenditure during treadmill exercise, from limb angular velocity and metabolic measurements. The feasibility of using such a system was evaluated using experimental results.

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© 2015, Springer-Verlag Berlin Heidelberg. According to the “pace-of-life syndrome” concept, slow-fast life-history strategies favored under different ecological conditions should lead to co-adaptations between metabolic rate and personality traits such as activity, exploration, and boldness. Although the relationships between resting metabolic rate (RMR) and personality traits have been recently tested several times, we still do not know whether personality is related to the daily energy expenditure (DEE) of free-living individuals in their natural habitat. The objectives of this study were to assess the links between RMR, DEE, and two personality traits (exploration in an open-field and docility during handling) in wild eastern chipmunks (Tamias striatus). Using a multivariate mixed model, we found that exploration and docility were significantly correlated at the among-individual level, confirming the presence of a behavioral syndrome within our population. We also found that exploration, but not docility, was negatively correlated with DEE. Hence, fast explorers show lower DEE levels than slow explorers, independently of RMR and docility. This result adds to an increasingly large (and complex) literature reporting the impacts of personality traits on the biology, ecology, and physiology of animals in their natural environment.

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The purpose of this study was to assess the validity of a GPS tracking system to estimate energy expenditure (EE) during exercise and field sport locomotor movements. Twenty-seven participants each completed one 90 minute exercise session on an outdoor synthetic futsal pitch. During the exercise session participants wore a 5 Hz GPS unit interpolated to 15 Hz (SPI HPU, GPSports Pty Ltd, Australia) and a portable gas analyser (Metamax® 3B, Cortex Pty Ltd, Germany) which acted as the criterion measure of EE. The exercise session was comprised of alternating five minute exercise bouts of randomised walking, jogging, running or a field sport circuit (x3) followed by 10 minutes of recovery. One-way ANOVA showed significant (p<0.01) and very large underestimations between GPS metabolic power derived EE and VO2 derived EE for all field sport circuits (% difference ≈ -44%). No differences in EE were observed for the jog (7.8%) and run (4.8%) while very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90 minute session was significantly lower (p<0.01) than the VO2 EE, resulting in a moderate underestimation overall (-19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however is able to provide a reasonably accurate estimation of EE during continuous jogging and running.

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OBJECTIVES: To quantify energy expenditure in older adults playing interactive video games while standing and seated, and secondarily to determine whether participants' balance status influenced the energy cost associated with active video game play. DESIGN: Cross-sectional study. SETTING: University research center. PARTICIPANTS: Community-dwelling adults (N=19) aged 70.7±6.4 years. INTERVENTION: Participants played 9 active video games, each for 5 minutes, in random order. Two games (boxing and bowling) were played in both seated and standing positions. MAIN OUTCOME MEASURES: Energy expenditure was assessed using indirect calorimetry while at rest and during game play. Energy expenditure was expressed in kilojoules per minute and metabolic equivalents (METs). Balance was assessed using the mini-BESTest, the Activities-specific Balance Confidence Scale, and the Timed Up and Go (TUG). RESULTS: Mean ± SD energy expenditure was significantly greater for all game conditions compared with rest (all P≤.01) and ranged from 1.46±.41 METs to 2.97±1.16 METs. There was no significant difference in energy expenditure, activity counts, or perceived exertion between equivalent games played while standing and seated. No significant correlations were observed between energy expenditure or activity counts and balance status. CONCLUSIONS: Active video games provide light-intensity exercise in community-dwelling older people, whether played while seated or standing. People who are unable to stand may derive equivalent benefits from active video games played while seated. Further research is required to determine whether sustained use of active video games alters physical activity levels in community settings for this population.

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The RT3 is a relatively new triaxial accelerometer that has replaced the TniTrac. The aim of this study was to validate the RT3 against doubly labeled water (DLW) in a free-living, mixed weight sample of adults. Total energy expenditure (TEE) was measured over a 15-day period using DLW Activity-related energy expenditure (AEE) was estimated by subtracting resting energy expenditure and thermic effect of feeding from TEE. The RT3 triaxial accelerometer was worn over 14 consecutive days. TEE and AEE were estimated using the RT3 proprietary equation. Thirty-six adults ages 18-56 years (56% women) with an average weight of 75.9 kg (SD = 14.8) completed all measurements. Compared to DLW the RT3 underestimated TEE by 539 kJ (4%) and AEE by 485 kJ (15%) on average. The RT3 provided a relatively accurate assessment of free-living activity-related energy expenditure at the group level and generally underestimated total and activity-related energy expenditure compared to DLW