Resting Metabolic Rate - Runner/Weight Loss

My BodyMedia FIT tells me my baseline is at 2200/day @ sedentary level. Found these equations..The random numbers are citations, so just ignore those.

Most of you who have formally (or informally) studied the fundamentals are already familiar with the 3 main components of total energy expenditure (TEE):

1. Resting energy expenditure (REE) is a term used interchangeably with basal metabolic rate (BMR), and resting metabolic rate (RMR). Although each of these are technically not the same thing, it’s impractical to factor in their differences when calculating needs. Those interested in reading about these differences can go to page 112 here.1 REE is about 60-75% of the TEE.2,3 As a matter of trivia, the FAO/WHO/UNU has published a figure as low as 45% of total expenditure.4

2. Thermiceffectofactivity(TEA)includesvoluntaryaswell as involuntary physical activity. A sub-component of TEA includes non-exercise activity thermogenesis (NEAT). TEA is approximately 15-30% of TEE.2

3. Thermiceffectoffood(TEF)accountsforroughly10-15% of the TEE. This range stems from a rough average of the variable thermic effects of each macronutrient. The TEFs of each macronutrient are approximated as follows:5 Protein (25-30%), carbohydrate (6-8%), and fat (2-3%).

Textbook approaches to predicting resting/basal expenditure

Traditional academic approaches to determining TEE involve calculating the sum of the 3 major components (REE/BMR, TEA, TEF). Perhaps the most commonly used formula for predicting REE/BMR is the Harris-Benedict equation. Keep in mind that there are other ‘texbook’ formulas, and Harris- Benedict is far from the definitive end-all. A systematic review by Frankenfield et al compared four of the most commonly used prediction equations and found the Mifflin-St Jeor equation to be
the most accurate and reliable.6 Another notable method is the Katch-McArdle equation,7 which is perhaps more methodologically sound, since it’s based on lean body mass (LBM)..

On a cautionary note, estimating LBM in itself can be problematic. This is in large part because people tend to have inaccurate perceptions of body composition. In my observations, it’s not uncommon for people to assume they have almost half the bodyfat that they actually do. Most recreationally fit guys assume their bodyfat percent is in the high single-digits, when they actually are closer to the low-to-mid double-digits. Women of the same profile often think they’re in the high teens, when in reality they’re closer to the low-to-mid-20’s. A review by Fleck discussing the body composition of elite Olympic athletes puts things into perspective, especially since it’s a safe bet to assume that most recreationally fit individuals as a group are not as lean as world-class competitive athletes. Here’s a summary of Fleck’s findings:8

␣ All groups of athletes were below the average values for % fat of college age men and women of 15% and 25%, respectively.
␣Athletes involved in a sport where their body weight is supported have higher % fat values. For example, canoers, kayakers, and swimmers had bodyfat levels at approximately 13% (men) and 22% (women).
␣ Athletes involved in sports where a weight class has to be met to compete (ie, boxing and wrestling) had lower % fat values. Men’s bodyfat ranged 6.9-7.9%.
␣ Sprinters in the 100, 200, and 400 meter events had even lower % fat values, approximately 6.5% (men) and 13.7 (women). Male marathoners averaged 6.4%.

Recent research by Vucetic et al found similar bodyfat levels in national-level male track & field athletes, ranging 5.5-6.3%.9
Although the Mifflin-St Jeor and Katch-McArdle equations are the most worthwhile of the bunch for predicting REE/BMR, I’ll go ahead and outline the Big Four for general reference purposes. I’ll also take the liberty to provide my own formula for estimating REE/BMR. The other formulas have a tendency to shoot too high when it comes to real-world applications. Important note: height is in centimeters, weight is in kilograms, and age is in years.

Harris-Benedict:
Men: 66 + (13.75 x weight) + (5 x height) - (6.76 x age) Women: 655 + (9.56 x weight) + (1.85 x height) - (4.68 x age)

Owen:
Men: 879 + (10.2 x weight) Women: 795 + (7.2 x weight)

Mifflin-St Jeor:
Men: (10 x weight) + (6.25 x height) - (5 x age) + 5 Women: (10 x weight) + (6.25 x height) - (5 x age) - 161

Katch-McArdle:
Both men & women: 370 + (21.6 x LBM)

Both men & women: 25.3 x LBM For pounds, it’s 11.5 x LBM.

Factoring in physical activity energy expenditure
The next step toward figuring total energy expenditure is multiplying the previously estimated resting expenditure with an activity factor, ranging from sedentary to extremely active. Bear in mind that these activity factors account for lifestyle physical activity in general, not just formal exercise sessions. Note that these activity factors typically shoot high enough to negate the need to add the 10-15% to account for the thermic effect of food. This means that once you’ve multiplied your estimated resting metabolic needs with your active metabolic needs, you’re done with the calculation.
␣ Sedentary (little or no exercise, desk job) TEE = BMR x 1.2
␣ Lightly Active (light exercise/sports 1-3 days/week) TEE = BMR x 1.3-1.4
␣ Moderately Active (moderate exercise/sports 3-5 days/week)
TEE = BMR x 1.5-1.6
␣ Very Active = (hard exercise/sports 6-7 days/week) TEE = BMR x 1.7-1.8
␣ Extremely Active (very hard daily exercise/sports & physical job or twice-a-day training)
TEE = BMR x 1.9-2.0

Toward building a better mousetrap

I find plenty of gratification in striving to improve current models. Some might consider this an attempt to build a better mousetrap, while others may see this as a more futile attempt to reinvent the wheel. Those of you who have my book Girth Control know that I like to play with formulas and try to strike the best compromise between simplicity and accuracy. I tend to favor simpler models instead of the multi-step textbook models.

Most existing formulas are designed to estimate current maintenance needs. So, in order to adjust for weight loss or weight gain, an arbitrary surplus or deficit must be assigned, and it’s usually about 500 kcals up or down. I recently developed a formula that accounts for training volume, intensity, and target bodyweight (TBW), which is a surrogate measure for LBM plus a small buffer. This circumvents the problem of having to attempt to measure or estimate your body composition. Rather, you simply have to have an idea of the total bodyweight you realistically are aiming at. Since this formula is geared toward figuring maintenance need of a targeted/goal set of circumstances, it eliminates the need to add or subtract calories arbitrarily for goals other than maintenance. Without further ado, my formula follows (important note: target bodyweight for this formula is in pounds):
Target BW x (8‐10 or 9‐11 + avg. total weekly training hours)

Notice that there are 2 separate ranges of multipliers. The lower range (8-10) is more suitable for women since they have a
higher percentage of bodyfat than men, and thus a lower proportion of lean mass. Using the higher range (9-11) on women would have a tendency to overestimate needs. Each range has a certain margin to account for differences in intensity. Low, medium, and high-intensity work can be factored in by using the low, middle, or high end of each range, depending on where your training sessions average during the week. Both formal cardio and weight training sessions must be included when totaling up average weekly training hours. Vigorous recreational physical activity (ie, sports games & practices) should also be tallied in.
Note that applying this formula to folks with zero hours of training per week can lead to underestimations if the lower end of each range is used as a multiplier. In the rare case of anyone with zero hours of training or vigorous physical activity per week, I’d suggest simply using the top end of each range (10 for women, 11 for men) as a multiplier.

Reference:© February 1st, 2011 by Alan Aragon, Research Review