# 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**.

**Non-obese Adults**

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.

**Obese Adults**

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

**Summary**

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.

**References**

A new predictive equation for resting energy expenditure in healthy individuals