Study â„–1: Metabolic Rate in Obese and Nonobese People
The research was conducted due to the assumption of the not applicable standard of outside-the-range resting metabolic rate (RMR) of obese people. The objective of the study was to evaluate several equations for predicting RMR against measured values in obese and nonobese people. For that purpose, RMR was measured with indirect calorimetry (Frankenfield et al., 2003). The calculation standards used were: Harris-Benedict, Owen, Mifflin, and Harris-Benedict equation using adjusted body weight in obese individuals; with various combinations of weight, height, and age. One hundred thirty non-hospitalized adults grouped by degree of obesity volunteered to participate in the research (Frankenfield et al., 2003). The study concluded with the Mifflin calculation standard, providing an accurate estimate of RMR in the largest percentage of nonobese and obese individuals.
Study â„–2: Resting Energy Prediction with Six Equations
The research was conducted due to the questionable accuracy of predictive equations for calculating resting energy expenditure (REE) in older people. The study aims to identify the most accurate predictive equation for REE (Karlsson et al., 2017). For that, indirect calorimetry was used as a reference value, considering body composition. Twenty-two octogenarian men participated in REE measurements, which were compared with six predictive equations: two based on fat-free mass (FFM) and four based on body weight, height, and age (Karlsson et al., 2017). The study resulted in indicating the Mifflin-St Jeor, based on FFM, equation to be the most accurate to estimate REE.
Study â„–3: REE in Underweight, Normal Weight, Overweight, and Obese Adults
The research was conducted due to the lack of consensus about which equation to use in hospitalized patients when indirect calorimetry is not available. The study focuses on examining the validity of REE predictive equations for underweight, normal weight, overweight, and obese adult patients by comparison with indirect calorimetry (Kruizenga et al., 2016). The included equations were based on weight, height, age, and gender. REE was measured with indirect calorimetry; a prediction between 90-110% of the measured REE was considered accurate. Five hundred thirteen patients participated in the study with the use of 15 predictive equations. As a result, REE predictive equations were accurate in about half the patients. The WHO equation is advised for BMI 30, HB equation – over BMI 30 (Kruizenga et al., 2016). The research concluded with the preference for measuring REE with indirect calorimetry.
Review
The common ideas of the three articles cover the validity and accuracy of several established equations for predicting REE (RMR) in patients of different weights and ages. The area of concern that might be seen with the study №1 and № 2’s findings is similar. Despite identifying the most accurate equation for predicting REE (RMR), the precision of all equations used in these studies is limited, rendering the use of indirect calorimetry preferable. The area of concern for study №3 is that the low level of accuracy of the research’s analysis could be explained by the selection bias that mostly included patients that were difficult to assess or treat. Overall, the findings of the studies are very useful in professional practice. They helped identify the best equations to use for predicting REE (RMR) in patients of different weight and age categories when indirect calorimetry is unavailable. A professional medical worker should be ready to assess a patient’s condition despite any unpredictable turn of events.
References
Frankenfield, D., Rowe, W., Smith, J. S., & Cooney, R. N. (2003). Validation of several established equations for resting metabolic rate in obese and nonobese people. Journal of the American Dietetic Association, 103(9), 1152-1159.
Karlsson, M., Olsson, E., Becker, W., Karlstrom, B., Cederholm, T., & Sjogren, P. (2017). Ability to predict resting energy expenditure with six equations compared to indirect calorimetry in octogenarian men. Experimental Gerontology, 92, 52-55.
Kruizenga, H., Hofsteenge, G., & Weijs, P. (2016). Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients. Nutrition &Metabolism, 13, 85-95.