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Metabolism Matters - Part 1


The following article is the first in a three-part series on metabolism. I will cover the basics of energy balance and metabolism, explain indirect calorimetry and the importance of measuring resting metabolic rate. Future articles will address factors affecting metabolism and dispel myths regarding metabolism.

Let’s explore the concept of energy balance and metabolism. Energy balance occurs when the number of calories consumed through food equals the number of calories burned. In simpler words, energy balance is when “calories in” equal “calories out.” The sum of calories burned in a day or “calories out,” is commonly called metabolism.

Metabolism is the biochemical process of combining nutrients with oxygen to release the energy our body needs to function. Metabolism is typically measured in kilocalories or, more commonly, calories. Total metabolic rate represents the calories needed to maintain body functions, daily activity (occupational and lifestyle) and the energy cost of exercise. In a state of energy balance, an individual will maintain her weight. When calories consumed outnumber calories burned, an individual is said to be in positive energy balance, resulting in weight gain.

Achieving energy balance or tipping the scale to achieve a weight goal requires an individual to know how many calories she burns and how many calories she consumes. Through careful dietary monitoring, food intake can be accurately measured and therefore, calorie intake can be determined. Energy expenditure (metabolism) is more challenging to assess. It requires knowledge of resting metabolic rate (RMR), which represents the number of calories the body requires to maintain vital functions. In addition, calories expended through purposeful exercise (running three miles on a treadmill), occupational activity (activity involved in your job) and lifestyle activity (cooking or cleaning) must be determined.

Resting metabolic rate is a significant portion of total metabolic rate representing calories the body burns to maintain vital body functions (heart rate, brain function and breathing). In simple terms, RMR is the number of calories a person would burn if she were awake but at rest all day. RMR represents 60 to 75 percent of a person’s total metabolism. This number comes closer to 75 percent if she is inactive or leads a sedentary lifestyle. Since RMR accounts for up to 75 percent of the total calories a person needs each day, it’s a critical piece of information to appropriately establish daily calorie needs, whether she is trying to lose, maintain or gain weight.

Traditionally, health and fitness professionals who have not had access to measurement technology have relied on estimates of RMR. The Harris-Benedict equation uses gender, height, weight and age to predict a person’s RMR. The equation is based on a sample of healthy and lean men and women measured in 1919 – not an ideal representation of the population today. Other equations use the same factors to estimate RMR. The errors in estimation for common equations are outlined in the table below:

ACCURACY: RESTING METABOLIC RATE MEASUREMENTS VERSUS ESTIMATIONS

[Note: Accuracy is defined as a predictive estimation within +/- 10% of measured RMR]

Equation Non-Obese (20-82 y)
(BMI 18.5-29.9 kg/m2)
Obese (20-82 y)
(BMI > 30 kg/m2)
Older Adults (60-82 y)
(Non-Obese and Obese)
Mifflin-
St. Jeor, et al.
82% of estimates are accurate; errors evenly distributed between under- and overestimation

Error Range:
Underestimations by 18% to overestimations by 15%
70% of estimates are accurate; errors tend to be underestimates

Error Range:
Underestimations by 20% to overestimations by 12%
Accuracy within 10% not available

Error Range:
Underestimations by 18% to overestimations by 5% in men; and, underestimations by 31% to overestimations by 7% in women
Harris-Benedict
(Actual body weight use)
59-81% of estimates are accurate; errors tend to be overestimates

Error Range:
Underestimation by 23% to overestimation by 38%
38-64% of estimates are accurate; errors tend to be overestimates

Error Range:
Underestimations by 35% to overestimations by 57% of measured
Accuracy within 10% not available.

Error Range:
Underestimations by 19% to overestimation errors by 9% in men; and, underestimations by 27% to overestimation by 12% in women
Harris-Benedict (Adjusted body weight (ABW)* Not Applicable 26% of estimates are accurate; errors tend to be underestimates

Error Range:
Underestimation by 42% to overestimation by 25%
Individual prediction accuracy using adjusted body weight is not reported for older adults in any of the evaluated studies
Owen, et al. 73% of estimates are accurate; errors tend to be underestimates

Error Range:
Underestimation by 24% to overestimation by 28%
51% of estimates are accurate; errors tend to be underestimates

Error Range:
Underestimation by 24% to overestimation by 20%
Accuracy within 10% not available

Error Range:
There is no individual error range for men. In Caucasian women, range of underestimation by 27% to overestimation by 12%
World Health Organization/
FAO/UNU
Individual prediction accuracy is not reported for non-obese adults in any of the evaluated studies. Individual prediction accuracy is not reported for obese adults in any of the evaluated studies. Accuracy within 10% not available

Error Range:
Underestimation by 17% to overestimation by 7% in men; and, underestimation by 8% to overestimation by 12% in women

*ABW=[(adjusted body wt - ideal wt) X 0.25] + ideal weight

NOTES: Data abstracted from studies reported men and women combined or as individual results. Not all equations were evaluated due to project resources. The date range for publications evaluating predictive error in healthy adults (normal and overweight) was from January 1, 1980 to April 30, 2003 and for weight management (obesity) January 1, 1980 to May 31, 2003. Studies not cited in the table were evaluated in the evidence analysis process, yet their data did not lend themselves to the individual error analysis format.

Because metabolism differs, even among individuals of similar height, weight and age, estimating can lead to errors and inaccurate calorie budgets. As a result of these estimates, individuals can be both over- or under-eating and be unsuccessful in reaching their personal goals. As technology advances, professionals must reassess their practices. The most accurate assessment of caloric needs is the measurement of oxygen consumption and determination of individual metabolism.

Resting metabolic rate is assessed using either direct or indirect calorimetry. Direct calorimetry requires the precise measure of heat output using a large, expensive and technically complex whole body calorimeter (thermally sealed chamber). Indirect calorimetry determines metabolic rate from the oxygen consumption of an individual and is based on the following three premises:

  1. The body uses oxygen for the sole purpose of oxidizing foodstuffs.
  2. The body does not store oxygen; therefore, oxygen consumed is equal to the rate of oxygen used to burn calories.
  3. A mathematical relationship exists between oxygen consumption and calories burned.

To convert energy consumption into energy expenditure (calories), most indirect calorimeters use the Weir equation (1949). The Weir equation is the universal standard for converting gas exchange measurements into metabolic rate.

There are several types of indirect calorimeters available. The “gold standard” is the Douglas bag method. Expired ventilation is collected into the bag and analyzed for concentrations of carbon dioxide, oxygen and nitrogen. Metabolic carts use the same principles with computer technology. The recent introduction of a portable, handheld device makes it simple and cost effective to measure RMR. Like other indirect calorimeters, it measures oxygen consumption to determine resting metabolic rate. With a simple breath test of 10 minutes or less, an individual can now have his/her unique metabolism measured for determination of a personalized calorie budget.

Once you have a measured your client’s resting metabolic rate, what do you do with it? Remember, you are trying to establish a personal calorie budget based on her goals. To do so, you need to know both sides of the equation, calories in and calories out. Calories out consist of the measured RMR, the energy cost of purposeful exercise and other daily activities (lifestyle and occupational). There are software applications available to calculate a calorie budget once you measure RMR. For the purpose of providing a simplified example, let’s use the personalized program sheet at the end of this article in order to calculate a daily calorie budget.

Let’s say your client’s measured RMR is 1500 calories. Using the personalized program sheet, you determine that her lifestyle and occupational activities combined with RMR amount to 1800 calories a day. If this person wants to lose 10 pounds of body weight at a rate of one pound per week, we now have good numbers to work with. One pound of body fat is equivalent to approximately 3500 calories. In order to lose one pound per week, we need to create a 3500 calorie deficit per week, which is equivalent to 500 calories per day. Your client can choose to eat 1300 calories a day with no exercise or keep her intake at 1800 calories a day and increase exercise to burn an additional 500 calories a day. More realistically, the client could use a combination of reducing caloric intake and increasing exercise to achieve her goal.

As you can see, this is no longer a guessing game. Knowing the “calories out” part of the equation allows you to calculate exactly how many calories your client should consume in her diet and how many calories she should burn through exercise. Accurately measuring metabolism is the foundation for any successful weight management program.

Please, try this PERSONALIZED PROGRAM WORKSHEET.

References:

  1. American Dietetic Association. Nutrition Accuracy of Determining Energy Expenditure in Healthy and Ill Individuals, A Systematic Review. Paper presented at the Food and Nutrition Conference and Expo, October 27, 2003: Let the Evidence Speak: Indirect Calorimetry and Weight Management Guides.
  2. Arciero PJ, Goran MI, Gardner AM, Ades PA, Tyzbir RS, Poehlman ET. A practical equation to predict resting metabolic rate in older females. J Am Geriatr Soc. 1993;41(4):389-395.
  3. Arciero PJ, Goran MI, Gardner AM, Ades PA, Tyzbir RS, Poehlman ET. A practical equation to predict resting metabolic rate in older men. Metabolism. 1993;42:950-957.
  4. Danforth E: Dietary induced thermogenesis: Control of energy expenditure. Life Sci 28:1821-1827, 1981.
  5. Feurer, ID, Crosby, LO, Mullen, JF. Measured and predicted resting energy expenditure in clinically stable patients. Clinical Nutrition. 1984; 3:27-34.
  6. Feurer ID, Crosby LO, Buzby GP, Rosato EF, Mullen JL. Resting energy expenditure in morbid obesity. Ann Surg. 1983;197(1):17-21.
  7. Frankenfield DC, Rowe WA, Smith JS, et al. Validation of several established equations for resting metabolic rate in obese and non-obese people. J Am Diet Assoc. 2003;103:1152-1159.
  8. Mault JR:”Nutrition” in Comprehensive Respiratory Care. N MacIntyre, D Dantsker, E Bakow (Editors). W.B. Saunders, Philadelphia, Pennsylvania, p. 589-601, 1995.
  9. Owen, OE, Holup, JL, Dalession, DA, et al. A reappraisal of the caloric requirements of men. Am J Clin Nutr, 1987; 46: 875-885.
  10. Owen, OE, Kavle E, Owen, RS, et al. A reappraisal of caloric requirements in healthy women. Am J Clin Nutr, 1986; 44:1-19.