Summary
Population energy needs can be estimated using the Basal Metabolic Rate (BMR) which constitutes 50-75% of the total energy expenditure. Prediction equations have been used to estimate the BMR that can be measured using either direct or indirect calorimetric. Most of these equations are based on gender, age, height and weight. These study shows that the three equations used in this paper have got no significant difference in estimation of BMR.
Introduction
Energy expenditure in humans helps determine the amount of energy the body requires relative to the source of energy intake and its effects (Levine, 2005). Energy expenditure as a whole is comprised of Basal Metabolic Rate (BMR) (minimum energy required when an organism is at rest), energy above BMR that is needed to process food (Diet induced thermogenesis), and physical activity thermogenesis which is the energy used during physical activities. Knowledge in daily total energy expenditure helps estimate the nutritional requirement of the body, although some researchers give justification that measurement of energy requirement does not necessarily reflect the energy requirement in the body (Bhanrgava and Reeds, 1995). This energy expenditure can be measured by a direct or indirect calorimetry (Levine, 2005). Indirect calorimetry is where heat produced by an organism is calculated from carbon dioxide production or energy consumption. Direct calorimetry is where the heat produced is measured as it is gets discharged from the organism’s body. Indirect calorimetry techniques are commonly used because they are easy and relatively cheaper compared to direct calorimetry (Levine, 2005). Examples of indirect caloriemtry include use of Douglas bag, open and closed circuit systems.
Methods
Refer to module booklet.
Results
Schofield Equation: gender, age and bodyweight specific – UK population
Men aged 18-29 yrs BMR (MJ/d) = 0.063W + 2.896
0.063 x 63.6 kg = 4.0068 + 2.896 = 6.9 MJ/d = 4.8kj/min
To convert this to kJ per minute (1 MJ = 1000 kJ and 1 day = 1440 minutes)
Harris-Benedict Equation: USA population – height, age, gender and bodyweight specific
BMR men = 66 + (13.7 x W) + (5 x H) – (6.8 x A)
W = weight (kg) H = height (cm) A = age (years)
66 + (13.7 x 63.6 kg) + (5 x 167 cm) – (6.8 x 28 yrs) = 1580 Kcal/d = 6.61MJ/d
To convert your value to MJ/day (multiply by 0.004184)
Metabolic Body Size Equation
W = weight (kg)
BMR = 290 x W0.75
290 x 63.60.75 = 6531.167691 ÷ 1000 = 6.53 MJ/d
Douglas bag calculations
MVR = volume / time x 0.9 = M
Weir = 20.5/100 x (20.93 – %O2) = W
Resting Metabolic rate (RMR) = M x W = Kj/min
First attempt = 17.3%O2 and 108.7litres of expired air
MVR = 108.7/10 x 0.9 = 9.783 l/min
Weir = 20.5/100 x (20.93 – 17.3) = 0.744
RMR = 9.783 x 0.744 = 7.28 Kj/min
Second attempt = 17%O2 and 59litres of expired air
MVR = 59/10 x 0.9 = 5.31 l/min
Weir = 20.5/100 x (20.93 – 17) = 0.806
RMR = 5.31 l/min x 0.806 = 4.28 Kj/min
Average RMR= (7.28Kj/min+4.28Kj/min)/2= 5.78Kj/min
Discussion
BMR is said to be around 50-75% of the total energy expenditure. Measurement of BMR is done after fasting for at least 8-12 hours under neutral temperature and when the organism is under total rest. Failure to meet all these conditions causes the BMR to become inaccurate. This is referred to as Resting Metabolic rate (Wong et al., 1996).
Basal Metabolic Rate (BMR) which constitutes 50-75% of the total energy expenditure is very suitable in estimation of energy need. Estimation equations which measures BMR that can be measured using either direct or indirect calorimetric achieves relative accuracy level. Most of these equations are based on gender, age, height and weight. These study shows that the three equations used in this paper have got no significant difference in estimation of BMR.
Various methods are being used to estimate the daily energy expenditure. Different equations among them; Schofield Equation, Harris Benedict equation and metabolic body size equation have been used to estimate the energy needed daily (Wong et al., 1996). The three equations consider the body size and how it correlates with the metabolic rate. This puts into consideration the energy of every individual depending on the activity that the individual is involved in. most of the BMR prediction equations generated by various scientists are based on the weight of the subject, height, and gender (Talbot, 1938). It is known that energy requirement of the body depends on the genetic constituent of an individual, health and nutritional status or the physical activity.
In our case, the three equations give almost the same BMR; 6.9Mj/d, 6.61Mj/d and 6.53Mj/d for Schofield equations, Harris Benedict equation and metabolic body size equation respectively. The difference ranges from 0.08Mj/d to 0.37Mj/day. This shows that the three researchers who came up with the equations had put into consideration major components that determine the BMR. That is, the prediction equations are based on weight and height for Schofield equations and Harris Benedict equation while that of Metabolic body size was based on weight (Benedict and Harris, 1999; Schofield, 1995).
In a research done by Wong et al (1996), it showed how different prediction equations were used to estimate the BMR for adolescent female children. According to this particular study, Schofield, Harris and Benedict equations which used both body weight and height, showed the most accurate BMR compared to the direct calorimetry mean BMR. The earlier measurements consisted of many errors and that prompted the Food and Agricultural organization (FAO), World Health Organisation (WHO) and Schofield to come up with better estimating equations that eliminated most of these errors (WHO, 1985)
The methods used in this study used data generated from indirect calorimetry and the prediction equations used shows accuracy. This is similar to a study that was done by Dietz at al (1991), which showed that the prediction equations by FAO and WHO generated BMR values that were consistent and there was no significant difference.
Possible sources of error and ways to improve the study
Douglas bag has been used in various laboratories to measure the energy expenditure through gaseous exchange. However, there are some errors that arise where gas diffuses through the bag (Shepherd, 1954). Carbon dioxide loss has been shown to occur through the rubber. The level of this loss depends on the time that the gas is held in the bag; the more the time the more the loss. This can be resolved by measuring the volume of gas as soon as it is collected to avoid this error (Bhargava and Reeds, 1995).
The other possible source of error is taking data from non-fasted subject or sleeping subject. In order to avoid such errors the basic requirements of the condition of subject during assessment should be met. There should be at least 8 hours fasting and the subject should not be asleep (Benedict and Harris, 1999). Accuracy can also be improved by making several attempts of the experiment and they doing their average. This helps to standardize the errors that may occur in individual attempts. Although indirect calorimetry helps estimate daily energy expenditure in living organisms, direct calorimetry gives a more accurate measure of the daily energy expenditure. However, the method is very expensive (Benedict and Harris, 1999).
References
Benedict, F. and Harris, J., 1999. A Biometric Study of Basal Metabolism in Man. Washington, DC: arnegie Institute of Washington.
Bhargava, A. and Reeds, P., 1995. Requirements for What? Is the Measurement of Energy Expenditure a Sufficient Estimate of Energy Needs? Issues and Opinions in Nutrition. Journal of Nutrition, 5(8), pp. 7-23.
Dietz, W., Bandini, L., Schoeller, D., 1991. Estimates of metabolic rate in obese and no obese adolescents. Pediatrics, 118, pp. 146-149.
Levine, A., 2005. Measurement of energy expenditure. Public Health Nutrition: 8(7A), pp.1123–1132.
Schofield, W., 1995. Predicting basal metabolic rate, new standards and review of previous work. New York: Human Nutrition and Clinical Nutrition 39C:5–41.
Talbot, F. 1938. Basal metabolism standards for children. American Journal of Diseases of Children 55:455–459.
Wong, W., Butte, N., Hergernroeder, A., Hill, R., Stuff, J. and Smith, E., 1996. Are basal metabolic rate prediction equations appropriate for female children and adolescents? Journal of Plant Physiology, 81 (6), 2407-2414.
World Health Organization, 1985. Estimates of energy and protein requirements of adults and children. Energy and Protein Requirements. (World Health Organization, Geneva), pp 71–112.