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Estimating the changes in energy flux that characterize the rise in obesity prevalence^1,2,3

¹ From the Faculty of Health, Medicine, Nursing, and Behavioural Sciences, Deakin University, Melbourne, Australia (BAS, GS, and SKL); the Department of Human Biology, Maastricht University, Maastricht, Netherlands (KRW); the Body Composition and Metabolism Research Centre at Auckland University of Technology, Auckland, New Zealand (ECR); the Department of Pediatrics, Columbia University Medical Center, New York, NY (MR); the Stritch School of Medicine, Loyola University, Chicago, IL (AL); the Department of Nutritional Sciences, University of Wisconsin–Madison, Madison, WI (DAS); the Department of Medicine, University of Pittsburgh, Pittsburgh, PA (JPD); the Children's Nutrition Research Center, Baylor College of Medicine, Waco, TX (NFB); and the Pennington Biomedical Research Centre, Baton Rouge, LA (ER).

² Supported by the Australian National Health and Medial Research Council (no. 410507).

³ Address correspondence to BA Swinburn, WHO Collaborating Centre for Obesity Prevention, Deakin University, 221 Burwood Highway, Melbourne, Victoria 3125, Australia. E-mail: boyd.swinburn{at}deakin.edu.au.

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 (β = 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 (β = 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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