Hospitalized (Non-ICU) Adults (2010-2012)


Boullata J, Williams J, Cottrell F, Hudson L, Compher C. Accurate determination of energy needs in hospitalized patients. J Am Diet Assoc. 2007; 107: 393-401.

PubMed ID: 17324656
Study Design:
Diagnostic, Validity or Reliability Study
C - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:

To evaluate the accuracy of seven predictive equations, including the Harris-Benedict and the Mifflin equations, against measured resting energy expenditure (REE) in hospitalized patients, including patients with obesity and critical illness.  

Inclusion Criteria:

All patients for whom a nutrition assessment was ordered at the Hospital of the University of Pennsylvania that year underwent indirect calorimetry and were included in this study.


Exclusion Criteria:
  • No diagnoses were excluded
  • Patients with incomplete data sets were excluded.
Description of Study Protocol:


A retrospective evaluation of the nutrition support service REE database from 1991.


Comparative study (sensitivity and specificity of predictive equations for energy expenditure).


Available data was applied to REE predictive equations, and results were compared to REE measurements.

Statistical Analysis

  • Descriptive statistics included mean ± standard deviation REE values, and percent accuracy by patient subgroups
  • Pearson's correlation was used to compare measured REE to each predictive equation
  • Univariate and multivariate logistic regression was used to determine the odds of specific variables predicting accuracy of the given equation
  • The variables for logistic regression included age tertile (young and older tertile compared to middle-age tertile), race (African American compared to white), sex (women compared to men), BMI category (all other categories compared to desirable weight category) or ventilator status (ventilator compared to canopy measurement)
  • Data are presented as OR, with P values, and 95% CI. P<0.05 were considered statistically significant. Statistical analyses were performed using SPSS.


Data Collection Summary:

Timing of Measurements 

  • Energy expenditure measurements were obtained by a single respiratory therapist using a strict protocol
  • REE was measured after a 30-minute rest, a minimum two-hour fast (unless enteral or parental feedings were infusing continuously), with no movement by the patient in a thermoneutral environment
  • Patient height in the database was a measured value or documented in the medical record
  • BMI was calculated
  • The last recorded temperature on a patient's vital signs record just before the REE measurement was documented  
  • Whether or not gas measure was collected by a canopy or through attachment to a mechanical ventilator circuit.   

Dependent Variable

Difference between the measured EE (indirect calorimetry) and the predicted EE (per equation).

Independent Variable

Predictive equations:

  • General
    • Harris-Benedict
      • Men: 66.5 + (13.8)(weight) + (5)(height) - (6.8)(age)
      • Women: 655 + (9.6)(weight) + (1.8)(height) - (4.7)(age)
    • Mifflin-St. Jeor
      • Men: 5 + (10)(weight) + (6.25)(height) - (5)(age)
      • Women: -161 + (10)(weight) + (6.25)(height) - (5)(age)
    • Ireton-Jones 1992: 1,925 + (5)(weight) - (10)(age) + (281)(one if ventilated; zero if not) + 292(one if trauma; zero if none) + 851(one if burned; zero if not)
    • American College of Chest Physicians: (25kcal)(weight)
  • Obesity
    • Ireton-Jones for obese individuals
      • 1,444 + (606)(sex = one for male or zero for female) + (9)(weight) - (12)(age) + (400)(one if ventilated; zero if not)
    • Harris-Benedict using adjusted body weight
      • (Hamwi x 1.3)
        • Men: 48.2 + (2.7)(inches of height over 5 ft)
        • Women: 45.5 + (2.3)(inches of height over 5 ft)
      • James x 1.3
        • Men: (1.1013)(weight) - (0.01281)(BMI)(weight)
        • Women: (1.07)(weight) - (0.0148)(BMI)(weight)
  • Ventilated Patients
    • Swinamer
      • -4,349 + (948)(BSA) - (6.4)(age) + (108)(temperature) + (24.2)(breaths per minute) + (81.7)(Liters tidal volume)
    • Penn State
      • -6,433 + (Harris Benedict)(0.85) + (minute ventilation Liters per minute)(33) + (maximum temperature)(175).
Description of Actual Data Sample:
  • Initial N: 397  
  • Attrition (final N): 395
  • Age: Range 16 to 92 years
  • Ethnicity: 61% white, 36% African American, 3% Hispanic or Asian descent
  • Anthropometrics: The BMI values (13 to 53) covered all National Heart, Lung, and Blood Institute classifications, but the mean value fell in the desirable weight range (BMI of 24±5.6)
  • Location: Hospital of the University of Pennsylvania in Philadelphia.
Summary of Results:

In a subset of 117 mechanically ventilated patients, Swinamer predicted accuracy in 45% while Penn State predicted accuracy in 43%; however, the Penn State equation prediction had considerably lower maximal under-predictions (25%) and over-predictions (56%) than did Swinamer (33% and 116%, respectively). Harris-Benedict with factor of 1.1 was accurate in 55% of mechanically ventilated patients.

Obese Mechanically Ventilated Patients

Adjusted OR (95% CI; P-Value)











x 1.1










1.08 (0.26 to 4.40; P=0.916) 1.24 (0.35 to 4.35; P=0.736) 1.01 (0.28 to 3.73; P=0.986) 0.48 (0.09 to -2.45; P=0.37) 0.38 (0.09 to 1.66; P=0.19) 1.79 (0.67 to 4.75; P=0.243) 0.24 (0.08 to 0.75; P=0.014)


For all hospitalized patients:

  • All predictive equations were highly correlated with the measured REE, but no equation predicted more than 68% of the variance
  • Prediction for the entire group was 61% with Harris-Benedict 1.1 having the maximum under-prediction of 34%. The maximal over-prediction ranged from 63% to 109% of measured REE, and was least with the Harris-Benedict 1.1 equation.
  • For the subgroup of obese patients, Harris-Benedict using actual body weight predicted accurately more often (62%) than did Harris-Benedict using an adjusted weight (44% with Hamwi, 46% with James) or Ireton-Jones at 32%
  • For patients with obesity, the Harris-Benedict using actual weight had similar under-estimation (26%) and over-estimation (29%) errors. 


Author Conclusion:

No equation accurately predicted REE in most hospitalized patients. Without reliable predictive equation, only indirect calorimetry will provide accurate assessment of energy needs. Although indirect calorimetry is considered the standard for assessing REE in hospitalized patients, several predictive equations are commonly used in practice. Their accuracy in hospitalized patients has been questioned. This study evaluated several of these equations, and found that even the most accurate equation (Harris-Benedict 1.1) was inaccurate in 39% of patients and had an unacceptably high error rate. Indirect calorimetry may still be necessary in difficult cases to manage hospitalized patients.

Funding Source:
University/Hospital: University of Pennsylvania
Reviewer Comments:
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) Yes
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? N/A
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? Yes
5. Was blinding used to prevent introduction of bias? Yes
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) Yes
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? No
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? Yes
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? N/A
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? N/A
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? Yes
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? N/A
10. Is bias due to study's funding or sponsorship unlikely? N/A
  10.1. Were sources of funding and investigators' affiliations described? N/A
  10.2. Was the study free from apparent conflict of interest? N/A