The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach

Abstract

Background: Individual variability in response to multiple modalities of obesity treatment is well documented, yet our understanding of why some individuals respond while others do not is limited. The etiology of this variability is multifactorial; however, at present, we lack a comprehensive evidence base to identify which factors or combination of factors influence treatment response.

Objectives: This paper provides an overview and rationale of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, which aims to advance the understanding of individual variability in response to adult obesity treatment. This project provides an integrated model for how factors in the behavioral, biological, environmental, and psychosocial domains may influence obesity treatment responses and identify a core set of measures to be used consistently across adult weight-loss trials. This paper provides the foundation for four companion papers that describe the core measures in detail.

Significance: The accumulation of data on factors across the four ADOPT domains can inform the design and delivery of effective, tailored obesity treatments. ADOPT provides a framework for how obesity researchers can collectively generate this evidence base and is a first step in an ongoing process that can be refined as the science advances.

Figure 1. Individual Variability in the Response to Obesity Treatments

The variable outcomes in weight loss are shown for (A) diet/lifestyle interventions with or without pharmacotherapy (44); (B) supervised exercise in women and men (45, 46); and (C) bariatric procedures, Roux-en-Y Gastric Bypass (left panel) (47) and its comparison with sleeve gastrectomy (SG) (48).

Figure 2. ADOPT Working Model: From Treatment to Outcomes

Obesity treatments target specific biological, environmental, and psychosocial constructs. The targeted factors in these domains mediate the effect of the treatment by changing eating and physical activity behaviors or by directly altering metabolic requirements. The changes in behavior and metabolism affect energy balance by reducing energy intake and/or increasing energy expenditure. Compensatory adaptive responses to behavior change and to weight loss feedback in a manner that moderates the target domains and how well they mediate the treatment. Several other factors (age, sex, sociodemographics, etc.) are also likely to moderate the effect of treatment on weight loss or weight loss maintenance. Individual variability is inherent at every stage of the conceptual model connecting the treatment to the outcome.