Prediction of energy expenditure in a whole body indirect calorimeter at both low and high levels of physical activity

OBJECTIVES: In studies that involve the use of a room calorimeter, 24h ener gy intake is often larger than 24h energy expenditure (24 h EE) because of a decrease in activity energy expenditure due to the confined space. This p ositive energy balance can have large consequences for the interpretation o f substrate balances. The objective of this study was to develop a method f or predicting an individual's 24 h EE in a room calorimeter at both low (1. 4xRMR) and high (1.8xRMR) levels of physical activity. METHODS: Two methods are presented that predict an individual's 24 h EE in a metabolic chamber. The first method was based on three components: (1) a 30min measurement of resting metabolic rate (RMR) using a ventilated hood s ystem; (2) measurement of exercise energy expenditure during 10 min of trea dmill walking; and (3) estimation of free-living energy expenditure using a tri-axial motion sensor. Using these measurements we calculated the amount of treadmill time needed for each individual in order to obtain a total 24 h EE at either a low (1.4xRMR) or a high (1.8xRMR) level of physical activ ity. We also developed a method to predict total 24 h EE during the chamber stay by using the energy expenditure values for the different levels of ac tivity as measured during the hours already spent in the chamber. This woul d provide us with a tool to adjust the exercise time and/or energy intake d uring the chamber stay. RESULTS: Method 1: there was no significant difference in expected and meas ured 24 h EE under either low (9.35 +/- 0.56 vs 9.51 +/- 0.47 MJ/day; measu red vs predicted) or high activity conditions (13.41 +/- 0.74 vs 13.97 +/- 0.78MJ/day; measured vs predicted). Method 2: the developed algorithm predi cted 24 h EE for 97.6 +/- 4.0% of the final value at 3 h into the test day, and for 98.6 +/- 3.7% at 7 h into the test day. CONCLUSION: Both methods provide accurate prediction of energy expenditure in a room calorimeter at both high and low levels of physical activity. It equally shows that it is possible to accurately predict total 24 h EE from energy expenditure values obtained at 3 and 7 h into the study.