![]() The accuracy rate of all predictive equations decreased compared to non-obese adults and individual errors increased. The maximum error of underestimation was 18% and the maximum error of overestimation was 15% of measured BMR. In 82% of the cases, the equation predicted 10% of the BMR measured by indirect calorimetry, with errors evenly distributed between underestimation and overestimation. The Mifflin-St, Jeor equation performed best among the four BMR predictive equations. The Mifflin-St Jeor equation, together with the Harris-Benedict, Owen, and WHO/FAO/UNU - the four most widely used equations - were studied in order to understand the validity of these equations for predicting BMR in non-obese and obese people of various ethnic and age groups. This equation is currently the most accurate for calculating BMR in individuals with normal BMI (i.e., with the index between 19 and 25), when it is not necessary to know the percentage of body fat. BMR (women) = 10 X weight (in kg) + 6.25 X height (in cm) - 5 X age (in years) - 161.BMR (men) = 10 X weight (in kg) + 6.25 X height (in cm) - 5 x age (in years) + 5.Then, a multiple regression analysis was performed to find the link between BMR and weight, height, and age for both men and women. The racial composition of the sample was not specified, and the representativeness of the elderly was limited.īMR was measured by indirect calorimetry. The paper that validated this equation, in 1990, estimated it using a group of women and men between the ages of 19 and 78, and whose BMI ranged from normal to obese. This is a predictive equation for resting energy expenditure in healthy individuals. In this article you will learn more about this equation and how to apply it in your nutrition appointment. BMR can be measured or estimated by equations, but estimation is by far the most common method. The assessment of energy requirements is an essential component in the creation of a meal plan.
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