AWM: Estimating Resting Metabolic Rate (RMR) (2014)
Spears KE, Kim H, Behall KM, Conway JM. Hand-held indirect calorimeter offers advantages compared with prediction equations, in a group of overweight women, to determine resting energy expenditures and estimated total energy expenditures during research screening. J Am Diet Assoc 2009; 109 (5): 836-845.PubMed ID: 19394470
To compare the four most common standardized prediction equations to a hand-held indirect calorimeter in estimating resting energy and total energy requirements in overweight women.
Subjects were included if they were female, overweight, over 25 years old and non-smokers.
Subjects were excluded if their BMI was less than 25kg/m2, were not weight stable, were pregnant or recently pregnant, or had a severe health problem based on their medical history.
Subjects were recruited through local newspaper advertisements, electronic messaging to local USDA employees and fliers mailed to volunteers in Beltsville Human Nutrition Research Center database.
Implied with measurements
Resting energy expenditure (REE) was measured by the MedGem hand-held indirect calorimeter and calculated by four prediction equations: Harris-Benedict (HB), Mifflin St. Jeor (MSJ), World Health Organization (WHO), and Dietary Reference Intakes (DRI).
- Repeated measures analysis of variance, paired t-test, and Bland-Altman plots were used to evaluate the relationships between hand-held indirect calorimeter and predictive equations
- Significance level was set at P<0.05
- Normal probability plots and histograms of residuals were used to evaluate normality of error distribution. Due to heteroscedasticity of differences, Bland and Altman recommend constructing 95% limits of agreement using the residual standard deviation from a fitted regression line of the difference on the average of the two methods. Cutoff for agreement between two methods was defined as a difference of no more than ±10%.
Timing of Measurements
Measurements were obtained only once, at the entry into the study. Subjects reported after an overnight fast (12 hours), weight was measured, and the MedGem calorimeter was used to measure oxygen consumption.
Resting energy expenditure was measured using the MedGem calorimeter, after subjects sat quietly for five minutes, and after the machine autocalibrated. Subjects were reminded to relax, rest and breath normally during measurement, a period which lasted about seven minutes.
REE was calculated with four different prediction equations:
- The Harris-Benedict equation was used with actual, not adjusted body weight
- Mifflin St. Jeor
- World Health Organization/Food and Agriculture Organization/United Nations
- Dietary Reference Intakes.
Physical activity was assessed by questionnaire (Godin Leisure Time Exercise Questionnaire) and used to estimate total energy expenditure. The REE multiplication factors used were 1.6, 1.5 and 1.4 for active, low-active, and sedentary, respectively.
- Initial N: 41 subjects were recruited into the study
- Attrition (final N): 39 subjects completed the study
- Age: Average age was 51.7±11.3 years (range in age from 26-72 years)
- 51.3% of participates were white
- 38.5% were African American
- 5.1% White-Hispanic
- 2.6% Asian
- 2.6% were missing data
- Other relevant demographics:
- 23.1% were considered sedentary
- 51.3% were considered moderately active
- 15.4% were very active
- 10.3% had missing data
- Average weight: 90.7kg±15.5kg (range 65.4-120.8kg)
- Average BMI: 33.4±4.9kg/m2 (range 25.7-44.5)
- Average percentage body fat: 44.1%±5.7% (range 22.8-53.4)
- Location: USDA, Agricultural Research Service, Beltsville Human Nutrition Research Center in Beltsville, MD.
Resting Energy Expenditure (REE)
- A significant difference existed between REE and TEE between hand-held indirect calorimeter (HHIC) values and all predictive equations as found by repeated measures of analysis of variance
- REE comparison: The mean difference between HHIC and predicted REE ranged from -22 to 70 kcals per day and were not statistically significant, however, a significant proportional bias was detected.
- The REE estimated by the Harris-Benedict equation had the lowest mean difference to REE measured by HHIC. But agreement between measured and predicted was poor with only 41-46% of predicted REE values being within ±10%.
|Means for REE and TEE measured by hand-held indirect calorimeter and calculated by predictive equations (kcals per day).|
a Four subjects did not complete activity questionnaires and were excluded from TEE analysis.
bSD=standard deviation; cSE=Standard Error=SD/square root of the sample size; dHHIC=hand held indirect calorimeter; eHB=Harris Benedict; fMSJ=Mifflin-St. Jeor; gWHO=World Health Organization; hDRI=Dietary Reference Intake.
|Pairwise comparison of the mean difference and percent agreement in REE by hand-held indirect calorimeter and predictive equations
(kcals per day, n=39)
|Data pair||Mean difference ± SEMa||P-valueb||Percent agreement|
aSEM=standard error of the mean; bPaired t-test.
Total Energy Expenditure (TEE)
- TEE Comparison: Means for TEE measured by HHIC were slightly, but not significantly less than TEE estimated from the WHO equation and higher than means estimated by HB, MSJ, and DRI equations
- Less than half of the subjects TEE measured by HHIC were within 250kcals of their estimated TEE values.
|Pairwise comparison of the mean difference and percent agreement, and percent within 250kcals of an individual's mean HHIC for TEE measured by HHIC and calculated by predictive equations (kcals per day, n=35)|
|Data Pair||Mean difference ± SEM||P-value||Percent agreement||Percent within 250kcals of HHIC|
Bland-Altman Evaluation of REE and TEE:
- Showed a linear association.
- Prediction equations tended to overestimate at lower REE and TEE values, and underestimate at higher REE and TEE values
- Due to heteroscedasticity, the assumptions for calculating Bland-Altman's 95% limits of agreement were not met and thus the residual standard deviation from the fitted regression line was used to calculate 95% limits of agreement
- A proportional bias was present for both REE and TEE when HHIC values were compared with other methods
- Approximately 20%-55% of the variation can be attributed to variation in mean
- No fixed bias was observed.
- These findings support other studies that suggestion it is difficult to estimate an individual's REE and TEE through prediction equations
- There was poor agreement between measured and predicted REE and TEE values, with only 37%-46% of individual's estimated values within 10% of her measured values.
Less than 50% of predictive equation values were within ±10% of hand-held indirect calorimeter values, indicating poor agreement.
A significant discrepancy between predicted and measured energy expenditure was observed. Further evaluation of hand-held indirect calorimeter research screening is needed.
- Questionable validity of the MedGem
- Relatively small sample size.
Quality Criteria Checklist: Primary Research
|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|
|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?||???|
|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?||???|
|3.||Were study groups comparable?||N/A|
|3.1.||Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT)||N/A|
|3.2.||Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline?||N/A|
|3.3.||Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.)||N/A|
|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?||N/A|
|4.5.||If diagnostic test, was decision to perform reference test not dependent on results of test under study?||N/A|
|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?||Yes|
|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?||N/A|
|6.4.||Was the amount of exposure and, if relevant, subject/patient compliance measured?||Yes|
|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?||???|
|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?||???|
|7.5.||Was the measurement of effect at an appropriate level of precision?||???|
|7.6.||Were other factors accounted for (measured) that could affect outcomes?||Yes|
|7.7.||Were the measurements conducted consistently across groups?||N/A|
|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)?||N/A|
|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?||Yes|
|10.||Is bias due to study's funding or sponsorship unlikely?||???|
|10.1.||Were sources of funding and investigators' affiliations described?||No|
|10.2.||Was the study free from apparent conflict of interest?||???|