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Multicenter Study
. 2009 Jun;89(6):1723-8.
doi: 10.3945/ajcn.2008.27061. Epub 2009 Apr 15.

Estimating the changes in energy flux that characterize the rise in obesity prevalence

Boyd A Swinburn  1 , Gary Sacks, Sing Kai Lo, Klaas R Westerterp, Elaine C Rush, Michael Rosenbaum, Amy Luke, Dale A Schoeller, James P DeLany, Nancy F Butte, Eric Ravussin
Affiliations
Multicenter Study

Estimating the changes in energy flux that characterize the rise in obesity prevalence

Boyd A Swinburn et al. Am J Clin Nutr. 2009 Jun.

Abstract

Background: The daily energy imbalance gap associated with the current population weight gain in the obesity epidemic is relatively small. However, the substantially higher body weights of populations that have accumulated over several years are associated with a substantially higher total energy expenditure (TEE) and total energy intake (TEI), or energy flux (EnFlux = TEE = TEI).

Objective: The objective was to develop an equation relating EnFlux to body weight in adults for estimating the rise in EnFlux associated with the obesity epidemic.

Design: Multicenter, cross-sectional data for TEE from doubly labeled water studies in 1399 adults aged 5.9 +/- 18.8 y (mean +/- SD) were analyzed in linear regression models with natural log (ln) weight as the dependent variable and ln EnFlux as the independent variable, adjusted for height, age, and sex. These equations were compared with those for children and applied to population trends in weight gain.

Results: ln EnFlux was positively related to ln weight (beta = 0.71; 95% CI: 0.66, 0.76; R2 = 0.52), adjusted for height, age, and sex. This slope was significantly steeper than that previously described for children (beta = 0.45; 95% CI: 0.38, 0.51).

Conclusions: This relation suggests that substantial increases in TEI have driven the increases in body weight over the past 3 decades. Adults have a higher proportional weight gain than children for the same proportional increase in energy intake, mostly because of a higher fat content of the weight being gained. The obesity epidemic will not be reversed without large reductions in energy intake, increases in physical activity, or both.

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Figures

FIGURE 1
FIGURE 1
Schematic showing the energy balance characteristics of a population undergoing weight gain over a period of years. The energy imbalance gap is defined as the small average daily imbalance between total energy intake (TEI) and total energy expenditure (TEE), whereas the energy flux gap, which is the higher TEI and TEE (energy flux) associated with the higher weight, is relatively large.
FIGURE 2
FIGURE 2
The relation between body weight and energy flux in adults [energy flux = total energy expenditure (TEE) measured by the doubly labeled water technique], shown as the raw data with body weight as the independent variable (Pearson's correlation r = 0.65, P < 0.0001; n = 1399).
FIGURE 3
FIGURE 3
The relation between body weight and energy flux (EnFlux) in adults (EnFlux = total energy expenditure measured by the doubly labeled water technique), shown as natural log-transformed data with energy flux as the independent variable (Pearson's correlation r = 0.65, P < 0.0001; n = 1399). Ln, natural log.
FIGURE 4
FIGURE 4
The relation between energy flux and body weight (derived from Equation 4) is shown as the dotted line with a slope of 0.71. Compared with a population at point A, the settling points for other similar populations with a higher or lower energy intake (B and C, respectively) and lower or higher physical activity levels (D and E, respectively) are shown. A population with a combination of a higher energy intake and lower physical activity would fall into the top right shaded area, whereas a population with both a lower energy intake and a higher physical activity would fall into the lower left shaded area. TEE, total energy expenditure; TEI, total energy intake.
FIGURE 5
FIGURE 5
The relation between energy flux (EnFlux) and body weight in adults (n = 1399) and children (n = 963) with both variables expressed as natural logs (Ln) with the effects of height, age, and sex removed. The lines represent the regression lines (derived from linear regression models) for each group with 95% prediction bands (containing 95% of each population).
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