Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures: behavioral domain

Authors: LYTLE, LESLIE - University Of North Carolina; NICASTRO, HOLLY - National Institutes Of Health (NIH); ROBERTS, SUSAN - Jean Mayer Human Nutrition Research Center On Aging At Tufts University; EVANS, MARY - National Institutes Of Health (NIH); JAKICIC, JOHN - University Of Pittsburgh; LAPOSKY, AARON - National Institutes Of Health (NIH); LORIA, CATHERINE - National Institutes Of Health (NIH)

Submitted to: Obesity
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/12/2018
Publication Date: 3/23/2018
Citation: Lytle, L.A., Nicastro, H.L., Roberts, S., Evans, M.R., Jakicic, J.M., Laposky, A.D., Loria, C.M. 2018. Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures: behavioral domain. Obesity. 26(2):S16-S23. https://doi.org/10.1002/oby.22157.
DOI: https://doi.org/10.1002/oby.22157

Interpretive Summary: There has been little agreement on optimal methods for use in studies of obesity, which has hampered research progress. This paper describes the deliberations of an expert NIH-convened panel to recommend on behavioral and nutritional research measures for use in studies of obesity and energy regulation. Identified methods for specific outcomes are reported, including methods for assessing physical activity, dietary intake, and other related parameters including sleep. Use of these recommended methods will facilitate high quality research and will also support common methodology use across studies that will facilitate merged data for future analyses.

Technical Abstract: Background: The ability to identify and measure behaviors that are related to weight loss and prevention of weight regain is crucial to understanding variability in response to obesity treatment and the development of tailored treatments. Objectives: The overarching goal of the ADOPT Core Measures project is to provide obesity researchers with guidance on a set of constructs and measures that are related to weight control and that span and integrate obesity-related behavioral, biological, environmental and psychosocial domains. This article describes how the behavioral domain subgroup identified the initial list of high priority constructs and measures to be included, and describes practical considerations for assessing the four behavioral areas: eating, activity, sleep and self-monitoring of weight. We also discuss challenges and considerations for advancing the science related to weight loss and maintenance behaviors. Significance: Assessing a set of core behavioral measures in combination with those from other ADOPT domains is critical to improve our understanding of individual variability in response to adult obesity treatment. The selection of behavioral measures is based on the current science although there continues to be much work needed in this field.