Manual of Clinical Nutrition Management II- 12 Copyright © 2013 Compass Group, Inc.
ESTIMATION OF ENERGY EXPENDITURES
Discussion
Since the early 1900s, various formulas have been employed to estimate energy expenditure. Since the
advent of the doubly labeled water (DLW) technique in the 1980s, scientists have begun to more accurately
determine total energy expenditure (TEE) in free-living persons (1). Unfortunately, due to its high cost and
the limited number of laboratories that perform the DLW technique, this application is not currently
accessible in the clinical setting. Most recently, the Academy of Nutrition and Dietetics (AND) explored
evidence that reported the accuracy and application of various methods used to measure energy expenditure,
particularly indirect calorimetry and predictive formulas for various population groups (2,3). These reports
provide evidence that can be used by dietetic professionals to make informed clinical decisions regarding
whether to measure or estimate resting metabolic rate (RMR), also known as resting energy expenditure
(REE) in patients (2). The predictive equations that have been evaluated include: the Harris-Benedict
equation (4), Mifflin–St. Jeor equation (MSJE) (5), Owen equations (6,7), and equations used by the World Health
Organization and the Dietary Reference Intakes (8). In 2012, the Swinamer equation, Ireton-Jones equations,
Penn State equations, MSJE, Brandi equation, and Faisey equation were evaluated for their application in
estimating energy expenditure in critically ill patients (3). The equations found to most reliable and validated
by the Academy Evidence Analysis Library are addressed in this publication (2,3).
The Dietary Reference Intakes for energy, which are based on studies using the DLW technique, are
considered the most accurate references for estimating TEE in free-living persons (2,9). These values can
serve as a resource for the assessment of patients who are not critically ill or do not have multiple disease
processes (2,8). (Refer to Section A: Estimated Energy Requirements (EER) for Male and Female Under 30
Years of Age.) The Mifflin–St. Jeor equation predicts RMR with the most consistency and the least percentage
of error in the ambulatory population (2). Multiple studies have reported variable accuracy with the Harris-
Benedict equation; this equation accurately predicts RMR only 45% to 81% of the time in healthy non-obese
subjects (2). The accuracy of all predictive equations decreases when applied to the obese population. In
studies of obese patients, the Harris-Benedict equation accurately predicted RMR only 33% to 64% of the
time, while the Mifflin–St. Jeor equation accurately predicted RMR 70% of the time (2). Because of the
variations reported with the use of the Harris-Benedict formula, evidence provides limited support for its use
in estimating the energy expenditure of ambulatory or hospitalized critically ill population groups, unless
otherwise specified in this section (2, 3, 9). Energy expenditure depends on factors including age, gender,
height, weight, and physical activity. In the hospital setting where patients generally have multiple
complications and the potential for rapid changes in medical status, predictive formulas that include not only
determinants of RMR, but also modifiers for illness severity, inflammatory state, and respiratory demands
may be needed (3,9,10). The clinician should realize that any method used to estimate energy expenditure
only provides an approximation (2). These equations should be used only as a guide or starting point, after
which the patient must be closely monitored and interventions must be devised based on individual needs
that promote the attainment of nutritional status.
Recommended Formulas to Calculate RMR in Critical Care Patients
Indirect calorimetry is the standard for determination of RMR in critically ill patients because RMR based on
measurement is more accurate than estimation using predictive equations (Grade I)* (3). If predictive equations
are needed in non-obese adult and older adult critically ill patients, the best prediction accuracy of equations
studied (listed in order of accuracy) include the Penn State equation (PSU 2003b version) (69% < 60 years
old, 77% > years old), Brandi (61% <60 years old, 61%> 60 years old), MSJE x 1.25 (54% < 60 years old, 54%
60 years old), and Faisey equation (65% <60 years old, 37% > 60 years old) (Grade II) (3,9,11). The Harris-
Benedict equation (with or without activity and stress factors), Ireton-Jones equations, and Fick equation
should not be used to determine RMR in critically ill patients, as these equations do not have adequate
prediction accuracy (Grade I) (3). If predictive equations are needed for critically ill individuals who are obese
and < 60 years the evidence recommends Penn State equation (PSU 2003b) worked best and predicted RMR
with 70% accuracy (Grade II) (3).. In obese critically ill patients > 60 years old, a modified Penn State equation
[PSU (2010)] predicted RMR with 74% accuracy (Grade II) (3). All other predictive equations tested had lower
accuracy rates (3). Refer to the Critical Illness Evidence-Based Nutrition Practice Guideline (2012) in the ADA
Evidence Analysis Library for detailed information (3).