Mifflin-St. Jeor for nutrition professionals
The assessment of energy requirements is an essential component in the creation of a meal plan. BMR can be measured or estimated by equations, but estimation is by far the most common method. Are you familiar with the Mifflin-St. Jeor equation?
In this article you will learn more about this equation and how to apply it in your nutrition appointment.
What is the Mifflin-St. Jeor Equation?
This is a predictive equation for resting energy expenditure in healthy individuals.
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. The racial composition of the sample was not specified, and the representativeness of the elderly was limited.
BMR was measured by indirect calorimetry. Then, a multiple regression analysis was performed to find the link between BMR and weight, height, and age for both men and women. The simplified equations are as follows:
- BMR (men) = 10 X weight (in kg) + 6.25 X height (in cm) - 5 x age (in years) + 5;
- BMR (women) = 10 X weight (in kg) + 6.25 X height (in cm) - 5 X age (in years) - 161.
When should you use the Mifflin-St. Jeor equation?
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.
The Mifflin-St. Jeor equation in comparison to others
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.
The Mifflin-St, Jeor equation performed best among the four BMR predictive equations. 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 maximum error of underestimation was 18% and the maximum error of overestimation was 15% of measured BMR.
The accuracy rate of all predictive equations decreased compared to non-obese adults and individual errors increased. This trend was less prominent in the Mifflin-St Jeor equation than it was in any other equation studied. The Mifflin-St Jeor equation accurately predicted the BMR of 70% of obese individuals, compared with 82% in non-obese individuals. Underestimations occurred more frequently than overestimations. The maximum underestimation was 20% and the maximum overestimation was 15% of measured BMR.
How to determine a client's energy requirements in a nutrition consultation?
Step 1: Determine the BMR
Females: (10 x weight in kg) + (6,25 x height in cm) – (5,0 x age in years) – 161
Males: (10 x weight in kg) + (6,25 x height in cm) – (5,0 x age in years) + 5
Step 2: Multiply the BMR by the appropriate activity factor
Sedentary - BMR X 1,2 (little to no exercise, desk job)
Light Activity - BMR X 1.375 (exercise 1 to 3 days per week)
Moderate Activity - BMR X 1,55 (exercise 3 to 5 days per week)
Very Active - BMR X 1.725 (exercise 6 to 7 days per week)
Extra Active - BMR X 1,9 (exercise 2x per day)
It is important to keep in mind that these equations are only an estimate and therefore individual nutritional needs and goals should be taken into account.
You should evaluate, and re-evaluate if necessary, how the client is progressing and how they are feeling, and from there make adjustments to the meal plan.
Other equations to calculate the basal metabolic rate:
- Harris-Benedict Equation
- Katch McArdle Equation
- ten Haaf Equation
- Cunningham Equation
Of the four predictive equations for basal metabolic rate most commonly used in clinical practice (Harris-Benedict, Mifflin-St Jeor, Owen, and WHO/FAO/UNU), the Mifflin-St Jeor equation appears to be the most reliable. It predicts resting metabolic rate at 10% of that measured by indirect calorimetry in more non-obese and obese subjects, higher than any other equation, and also had the lowest error rate.
Comparison of Predictive Equations for Resting Metabolic Rate in Healthy Nonobese and Obese Adults: A Systematic Review
A new predictive equation for resting energy expenditure in healthy individuals