The Accuracy of Equations Used To Predict the Resting Metabolic Rate (RMR) Requirements of Males: Aged 18 to 65 Years, in Trinidad and Tobago

Abstract

Objectives To determine the level of accuracy of recommended resting metabolic rate (RMR) prediction equations among healthy and acutely ill males: aged 18 to 65-years, in Trinidad and Tobago. Methods Following informed consent and enrolment, sixty-six male (acutely ill 33; healthy 33) volunteers had anthropometry and RMR (MedGem® indirect calorimeter, Micro life, USA) measured using recommended procedures. RMR from prediction equations were compared to RMR measured by indirect calorimetry with values between ±10% of measured RMR being considered accurate. The university's ethics committee approved the study. Results The top-four ranked recommended RMR prediction equations for acutely ill males, in decreasing order of accuracy were Müller (39.4%), Bernstein (39.4%), Korth (36.4%) and Mifflin St. Joer (36.4%). Among the healthy males, the top-five ranked recommended RMR prediction equations were Müller (54.5%), Huang (54.5%), Lürhmann (51.5%), Korth (48.5%) and Valencia (48.5). Population-derived RMR prediction equations had 54.5% and 63.6% accuracies among the acutely ill and healthy males respectively. These were significantly higher than the top-ranked recommended prediction equations for both groups. Notably, limiting the risk of malnutrition by at least 5%: through diet quality by way of accurate energy predictions could improve health-related quality of life. Increasing the predictability of energy needs within any population can also ensure the accuracy of RMR per weight (kilogram) needed daily and energy balance. On average, this male population utilized 17.5 kcal of energy per kilogram body weight. Conclusions All other recommended RMR prediction equations except Huang, Lürhmann, and Müller resulted in biases >50%. Substituting the commonly used prediction equations with our population-specific equation can increase the level of accuracy by at least 10%, thus limiting the risk of malnutrition by at least 5%, and improving health-related quality of life for this male population. Funding Sources nil.