Various studies have been done on the expenditure of energy in living organisms. However, these studies have not yet established how much food living organisms take in for maintenance of body weight. In determining energy requirements more accurately in humans, energy expenditure ought to be measured over episodes of days or at least over 24 hours.
There are various methods of estimating the daily energy expenditure in a free living organism. This article focuses on the various methods, their advantages as well as their limitations. Some of the methods used are as follows; Daily Labelled Water (DLW), Heart rate, direct calorimetric, indirect calorimetric, Sense wear armband method and use of equations.
Delegate your assignment to our experts and they will do the rest.
Daily Labelled Water (DLW) method
This method employs the use of isotopes of Hydrogen and Oxygen in tracing the movement of water and carbon dioxide in the body over a given period. This method is based on the observation that the oxygen in respiratory carbon dioxide is in isotopic exchange equilibrium with oxygen in body water ( Rowlands and Trost, 2012 ). In this reaction, the catalyst used is Carbonic anhydrase. The records got from the experiment make it possible to derive an approximate value of the oxygen spent by the individual organism throughout the extent of the experiment.
The rate of flow of the isotopes (Oxygen and Hydrogen) through the body plays a dynamic role in determining how long the experiment takes place. Some of the factors that contribute to the popularity of this method are the low operational costs as well as the simplicity. This method involves various assumptions. Some of them are as follows; the body water pool volume is constant throughout the entire experiment, water influx, water, and carbon dioxide efflux rates are constant in the entire experiment, water and carbon dioxide are the only forms through which the isotopes exit the body. The other assumption is that no water or carbon dioxide re-enters the body after leaving it during the experiment.
Heart rate method
This method of determining energy expenditure method hinges on the physiological connection that exists between the heart and the volume of water. Burnett and Grobe, (2014) established that there is a linear association between the volume of water and heart rate in human beings during exercise. The level of the physical fitness of the individual greatly influences this relationship ( Heymsfield et al., 2012 ). Mental tests, as well as psychological stress, have been shown to influence this method directly.
The results obtained during experiments on his method also reveal that different body organs have varied responses. For instance, the values obtained from the arm are not similar to those obtained from the leg ( Leonard, 2012) ). Furthermore, results gotten during periods of intense exercise are markedly different from those gotten during rest ( Gao and Freedson, 2012 ). In this method, it is important to analyze the effect of body temperature on the heart rate.
In this method, a calibration equation should be derived for each species that is under study. This is one of the limitations of this method. Furthermore, the recording system has to be placed on or into the organism of interest. This may require surgical implantation which may take quite a lot of time. There might also be risks associated with the surgical procedure. These may include reactions by the immune system of the animal as well as postoperative infections if no aseptic procedures are strictly followed. Once the study is completed, the implants will require removal from the individual. Cumulatively, all these procedures will require a lot of time, both in carrying them out as well as allowing for the healing process.
In monetary terms, the heart rate process is expensive. The data loggers to be implanted into the individual are also extremely costly. The reliability of the recording device plays an important role in dictating the success of this method. The chances of the device detaching from the animal and getting lost are high if the device is eternally placed. In aquatic animals, the waterproofing may fail to lead to damage of the device.
Indirect calorimetry method
This kind of procedure involves in vivo estimation of both the type and rate of substrate utilization and metabolism of energy. The method involves estimation of the amount of oxygen expended as well as that of carbon dioxide eliminated. Heat produced is estimated based on Hess’s law; oxygen is used up, carbon dioxide is produced while Nitrogen is expelled, all based on the quantity of heat produced. This method is subdivided into two; open and closed circuit methods.
The uniqueness of the information provided by this method together with its noninvasive nature makes it be one of the best methods for estimating energy expenditure in many living organisms. Moreover, this method provides room for combination with other methods of energy expenditure evaluation to bring a lot of information ( Manns and Haennel, 2012) . These include information on the assimilation of nutrients in the body and thermogenesis. It also paves ways for one to study the pathogenesis of any metabolic diseases that may be present.
Direct calorimetry method
This entails the use of calorimeter. The heat produced by an enclosed organism within a small chamber can be evaluated using this method ( Yoon et al., 2014) . Both direct and indirect calorimetry methods are important in determining heat emission and heat expenditure simultaneously. This method employs the use of real time calculations on energy expenditure. Alcohol combustion within the calorimeter chamber is important in assessing the performance of the calorimeter ( Powers, 2014) . One of the disadvantages of direct calorimetry is that confinement has adversarial effects on the expenditure of energy. Also, the materials of the confinement room are supposed to be sensitive to heat. This method also requires extended study episodes to obtain good results.
Sense wear armband method
This method involves the use of four sensors; two axis accelerometers, heat flux sensor, sensitive thermistors and a galvanic skin response sensor ( Saito, 2013) . This is a method that gives very useful results in sports. It gives accurate results on physical stress. However, this method does not measure the Resting Energy Expenditure.
BMR equations
They are of different types ( Speakman and Herman, 2012) . For examples, Equations that estimate Resting Energy Expenditure in health (example, Schofield equations, and Oxford equations) and Equations that estimate Resting Energy Expenditure in illness (example, Ireton Jones, Swinamer).
References
Bassett Jr, D. R., Rowlands, A. V., & Trost, S. G. (2012). Calibration and validation of wearable monitors. Medicine and science in sports and exercise , 44 (1 Suppl 1), S32.
Burnett, C. M., & Grobe, J. L. (2014). Dietary effects on resting metabolic rate in C57BL/6 mice are differentially detected by indirect (O 2/CO 2 respirometry) and direct calorimetry. Molecular metabolism , 3 (4), 460-464.
Heymsfield, S. B., Thomas, D., Bosy ‐ Westphal, A., Shen, W., Peterson, C. M., & Müller, M. J. (2012). Evolving concepts on adjusting human resting energy expenditure measurements for body size. Obesity reviews , 13 (11), 1001-1014.
Leonard, W. R. (2012). Laboratory and field methods for measuring human energy expenditure. American Journal of Human Biology , 24 (3), 372-384.
Liu, S., Gao, R., & Freedson, P. (2012). Computational methods for estimating energy expenditure in human physical activities. Medicine and science in sports and exercise , 44 (11), 2138.
Manns, P. J., & Haennel, R. G. (2012). Sensewear Armband and stroke: validity of energy expenditure and step count measurement during walking. Stroke research and treatment , 2012 .
Park, J., Kazuko, I. T., Kim, E., Kim, J., & Yoon, J. (2014). Estimating free-living human energy expenditure: Practical aspects of the doubly labeled water method and its applications. Nutrition research and practice , 8 (3), 241-248.
Powers, S. (2014). Exercise physiology: Theory and application to fitness and performance . McGraw-Hill Higher Education.
Saito, M. (2013). Brown adipose tissue as a regulator of energy expenditure and body fat in humans. Diabetes & metabolism journal , 37 (1), 22-29.
Tschöp, M. H., Speakman, J. R., Arch, J. R., Auwerx, J., Brüning, J. C., Chan, L., ... & Herman, M. A. (2012). A guide to analysis of mouse energy metabolism. Nature methods , 9 (1), 57-63.
Estimating Human Energy Expenditure. Retrieved from https://link.springer.com/article/10.2165/00007256-200333090-00004
The doubly-labeled water method for measuring energy expenditure. Technical recommendations for use in humans . Retrieved from https://inis.iaea.org/search/search.aspx?orig_q=RN:21093729
Measuring metabolic rate in the field: the pros and cons of the doubly labelled water and heart rate methods. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.0269-8463.2004.00821.x/full
The theoretical bases of indirect calorimetry: A review. Retrieved from http://www.sciencedirect.com/science/article/pii/0026049588901102
Direct Calorimetry by Means of the Gradient Principle. Retrieved from http://aip.scitation.org/doi/abs/10.1063/1.1741416
Description of a direct-indirect room-sized calorimeter. Retrieved from http://ajpendo.physiology.org/content/260/2/E306.short
KIN Metabolism Main Pts Review. Retrieved from https://quizlet.com/10270661/kin-metabolism-main-pts-review-flash-cards/
Accuracy of methods for measuring and predicting energy expenditure. Retrieved from http://www.peng.org.uk/pdfs/presentations/2010/predicting-energy-expenditure.pdf
Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation. Retrieved from http://ajcn.nutrition.org/content/54/6/963.short
Energy expenditure of nonexercise activity 1 , 2 , 3 , 4 . Retrieved from http://ajcn.nutrition.org/content/72/6/1451.short
