Summary of All Predictive Equations (2019)
Prediction Methods Summary
Eleven equations were tested for validity in predicting resting metabolic rate (RMR) in adults with COPD. Two of these [Moore & Angelillo (MAE), Nordenson] were equations developed specifically for COPD patients, while the other equations were developed for healthy adults [Harris-Benedict (HBE), Mifflin St. Jeor (MSJE), Westerterp, de Oliveira, Owen and four variations of Food and Agriculture Organization of the United Nations/World Health Organization/United Nations University (FAO/WHO/UNU)], which were WHO (including ht), WHO (omitting ht), Nordic Nutrition Recommendation (NNRE) and the Schofield equation.
Three methods for predicting total energy expenditure (TEE) in adults with COPD were tested. In the first method, a pedometer was used to estimate physical activity and a multiplier was assigned based on the number of steps taken. The multiplier based on the number of steps taken was applied to six RMR equations [WHO (omitting ht), Schofield, HBE, MAE, NNRE, Nordenson)]. In the second and third method, motion and position sensors were used as the criterion to measure TEE. For TEE prediction, a simple ratio of 30kcal/kg body weight was then applied, as well as multiplying the WHO (omitting ht) equation by 1.7.
A summary of all prediction methods for RMR and TEE is below. For more information on the evidence for each of the predictive methods, see Individual Predictive Equations (2019) in Methods to Estimate Energy Requirements (2019) in the left navigation bar.
OVERALL: If measurements are not available, what are the best methods to predict energy needs in adults with COPD?
Conclusions for this question should be considered tentative.
For prediction of resting metabolic rate (RMR), the Westerterp equation yielded the highest accuracy rate, followed by the WHO (omitting ht) equation and HBE, which yielded slightly lower, but similar accuracy rates.
For prediction of total energy expenditure (TEE), 30 kcal/kg body weight in non-obese adults with COPD produced an estimate that was not different from measured values on average but whose variability was wide indicating that estimation errors might be common and large.
Synthesis of results for this question was challenging because large gaps exist in the available evidence (small numbers of studies with small sample sizes, inconsistency in the types of statistical treatments from study to study making data difficult to aggregate).
- Grade I means there is Good/Strong evidence supporting the statement;
- Grade II is Fair;
- Grade III is Limited/Weak;
- Grade IV is Expert Opinion Only;
- Grade V is Not Assignable.
Evidence Summary: If measurements are not available, what are the best methods to predict energy needs in adults with COPD?
- Quality Rating Summary
For a summary of the Quality Rating results, click here.
- Farooqi N, Slinde F, Carlsson M, Håglin L, Sandström T. Predicting energy requirement with pedometer-determined physical-activity level in women with chronic obstructive pulmonary disease. International Journal of Chronic Obstructive Pulmonary Disease 2015; 10:1129-37
- Nordenson A, Grönberg A, Hulthén L, Larsson S, Slinde F. A validated disease specific prediction equation for resting metabolic rate in underweight patients with COPD. International Journal of Chronic Obstructive Pulmonary Disease 2010; 5:271-6
- Ramos F, Rossato L, Ramires B, Pimentel G, Venâncio L, Orsatti F, de Oliveira E. Comparison of predictive equations of resting energy expenditure in older adults with chronic obstructive pulmonary disease. Revista Portuguesa de Pneumologia 2016; 23:40-42
- Slinde F, Svensson A, Gronberg AM, Nordenson N, Hulthen L, Larsson SC. Reproducibility of indirect calorimetry in underweight patients with chronic obstructive pulmonary disease. European e-Journal of Clinical Nutrition and Metabolism 2008; 3:40-45
- Slinde F, Gronberg A, Svantesson U, Hulthen L, Larsson S. Energy expenditure in chronic obstructive pulmonary disease-evaluation of simple measures. European Journal of Clinical Nutrition 2011; 65:1309-13
Search Plan and Results: COPD: Methods to Estimate Energy and Protein Requirements 2017