The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making
from happening) may be a much less dramatic or salient outcome than treatment (removing a problem), whose effects are not only obvious but also potentially more rewarding—personally and politically. Thus, although the case for prevention is compelling, making the decision to give it priority and determining which strategies will lead to more “nonevents” are highly challenging.
The widely held conviction that such decisions should be “evidence-based” only increases the challenge. How does one best determine which aspects of the environment to change, what changes to make, and how to effect these changes? Which interventions can potentially be effective on a large scale and sustainable over time? Where are the synergies among interventions? Could there be undesirable effects not readily apparent at the outset? Ideally, there would be a firm and comprehensive evidence base to inform the myriad decision makers whose actions—intentionally or unintentionally—influence the social and environmental determinants of unwanted weight gain and obesity. In reality, the approaches to evidence that apply to decision making about the treatment of obesity or other clinical problems are inadequate and sometimes inappropriate for application to decisions about public health initiatives such as obesity prevention. This situation poses a dilemma, one that is clearly compounded by the urgency of deciding which interventions can best address the problem. Evidence is needed to support such decisions for many reasons:
to justify interventions generally, particularly when there is competition for resources or opposition;
to inform priority setting and justify actions targeting high-risk populations, differentiate actions that are likely to be effective from those that are not, and quantify likely impacts;
to estimate costs and cost-effectiveness and anticipate unintended consequences, including harms to individuals or businesses; and
to help understand implementation factors, that is, what to do and how to do it.
The purpose of this report is to present a framework that will make it possible to meet these evidence needs.
Figure 1-5, which illustrates the levels and sectors of influence on obesity in populations, is helpful for understanding why decisions about obesity prevention are so complex (IOM, 2007). The figure shows the variety of levels at which interventions may be aimed and demonstrates how, taken together, a set of actions across levels might interrelate. Actions within many of these levels are focal points for discussion on how to combat the obesity epidemic within the United States and globally. Pathways or logic models can be drawn to link these levels to weight-related behaviors of population groups and individuals, such as food purchases; intakes of sugar-sweetened beverages, fruits and vegetables, whole grains, and total calories; television watching and other screen time; automobile use; breastfeeding; and routine and recreational physical activity. Relevant initiatives might focus on international trade