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The caloric calculator: average caloric impact of childhood obesity interventions
Y Claire Wang1, Amber Hsiao, C Tracy Orleans
1Department of Health Policy & Management, Mailman School of Public Health, Columbia University, New York, NY 10032, USA. Ycw2102@columbia.edu
Background:
The childhood obesity epidemic reflects the daily accumulation of an "energy gap"-excess calories consumed over calories expended. Population-level interventions to reverse the epidemic can be assessed by the degree to which they increase energy expenditure and/or reduce caloric intake. However, no common metric exists for such comparative assessment.
Purpose:
To develop a common metric, the Average Caloric Impact (ACI), for estimating and comparing population-level effect sizes of a range of childhood obesity interventions.
Methods:
An iterative, collaborative process was used to review literature from 1996 to 2012 and select illustrative interventions showing effects on youth diet and/or activity levels, energy balance, and weight. The ACIs of physical activity interventions were estimated based on program reach, frequency, duration, and intensity and mean body weight of the targeted age and gender group from the 2009-2010 National Health and Nutrition Examination Survey. ACIs of dietary interventions were based on reach and changes in foods and/or beverages consumed.
Results:
Fifteen interventions informed by 29 studies were included, ranging from individual behavioral to population-level policies. A web tool, the Caloric Calculator, was developed to allow researchers and policymakers to estimate the ACIs of interventions on target populations with reference to energy gap reductions required to reach the nation's Healthy People childhood obesity goals.
Conclusions:
The Caloric Calculator and ACIs provide researchers and policymakers with a common metric for estimating the potential effect sizes of various interventions for reducing childhood obesity, providing a platform for evidence-based dialogues on new program or policy approaches as data emerge.
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