Determinants of sedentary 24-h energy expenditure: equations for energy prescription and adjustment in a respiratory chamber

Yan Y Lam, Leanne M Redman, Steven R Smith, George A Bray, Frank L Greenway, Darcy Johannsen, Eric Ravussin, Yan Y Lam, Leanne M Redman, Steven R Smith, George A Bray, Frank L Greenway, Darcy Johannsen, Eric Ravussin

Abstract

Background: Achieving energy balance is critical for the interpretation of results obtained in respiratory chambers. However, 24-h energy expenditure (24EE) predictions based on estimated resting metabolic rate and physical activity level are often inaccurate and imprecise.

Objective: We aimed to develop and validate equations to better achieve energy balance in a respiratory chamber by adding or subtracting food items.

Design: By using a randomized data set with measures of 24EE (n = 241) performed at the Pennington Biomedical Research Center, we developed equations to predict 24EE from anthropometric, demographic, and body composition variables before and at 3 and 7 h into the chamber measurement. The equations were tested on an independent data set (n = 240) and compared with published predictive equations.

Results: By using anthropometric and demographic variables, the equation was as follows: 24EE (kcal/d) = 11.6 [weight (kg)] + 8.03 [height (cm)] - 3.45 [age (y)] + 217 (male) - 52 (African American) - 235. The mean prediction error was -9 ± 155 kcal/d (2046 ± 305 compared with 2055 ± 343 kcal/d for measured 24EE; P = 0.36). The prediction achieved a precision of ±10% of measured 24EE in 83% of the participants. Energy prescription was then refined by equations with the use of energy expenditure values after 3 h, 7 h, or both into the chamber study. These later equations improved the precision (±10% of measured 24EE) to 92% (P = 0.003) and 96% (P < 0.0001) of the participants at 3 and 7 h, respectively. Body composition did not improve 24EE predictions.

Conclusions: We showed the use of a set of equations to prescribe and adjust energy intake to achieve energy balance in respiratory chambers over 24 h. These equations may be used in most respiratory chambers and modified to accommodate exercise or specific feeding protocols.

Trial registration: ClinicalTrials.gov NCT00099151 NCT00493701 NCT00565149 NCT00829140 NCT00936130 NCT00943215 NCT00945633 NCT01275235 NCT01672632 NCT01775163 NCT01898949.

Figures

FIGURE 1.
FIGURE 1.
Relations between energy intake prescriptions, total food intake, and 24EE during the chamber stay (n = 481). The dotted line indicates the line of identity. ○, energy intake prescription; Δ, total energy intake; 24EE, 24-h energy expenditure.
FIGURE 2.
FIGURE 2.
Agreement between 24EE measured in a respiratory chamber and that predicted by the body composition (A, C; n = 239) and anthropometric (B, D; n = 240) models. A, B: Pearson correlation; the solid and dotted lines indicate the predictive model with 95% CIs and the line of identity, respectively. C, D: Bland-Altman plot; the solid line indicates the regression model, and the dotted lines indicate the mean difference and 95% limits of agreement. A Pearson correlation was used to assess the relation between the variables. ○, subjects who were at the 0–25th percentile of time spent moving in the respiratory chamber; Δ, subjects who were at the 25–75th percentile of time spent moving in the respiratory chamber; x, subjects who were at 75–100th percentile of time spent moving in the respiratory chamber; 24EE, 24-h energy expenditure.
FIGURE 3.
FIGURE 3.
Correlation between 24EE measured in a respiratory chamber and that predicted by the Müller (A; n = 239) (22) and Mifflin (B; n = 240) (24) equations. Solid lines: predictive model with 95% CIs; dotted line: lines of identity. A Pearson correlation was used to assess the relation between the variables. 24EE, 24-h energy expenditure.
FIGURE 4.
FIGURE 4.
Relations between 24EE measured in a respiratory chamber and that predicted at 3 (A, C) and 7 (B, D) h into the chamber stay (n = 238). A, B: Pearson correlation; the solid and dotted lines indicate the predictive model with 95% CIs and the line of identity, respectively. C, D: Bland-Altman plot; the solid line indicates the regression model, and dotted lines indicate the mean difference and 95% limits of agreement. A Pearson correlation was used to assess the relation between the variables. ○, subjects who were at the 0–25th percentile of time spent moving in the respiratory chamber; Δ, subjects who were at the 25–75th percentile of time spent moving in the respiratory chamber; x, subjects who were at the 75–100th percentile of time spent moving in the respiratory chamber; 24EE, 24-h energy expenditure.

Source: PubMed

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