标题：Using Population Reach as a Proxy Metric for Intervention Impact to Prioritize Selection of Obesity Prevention Strategies in Los Angeles County, 2010–2012
摘要：Recent federal initiatives have used estimates of population reach as a proxy metric for intervention impact, in part to inform resource allocation and programmatic decisions about competing priorities in the community. However, in spite of its utility, population reach as a singular metric of intervention impact may be insufficient for guiding multifaceted program decisions. A more comprehensive, validated approach to measure or forecast dose may complement reach estimates to inform decision makers about optimal ways to use limited resources. Although federal initiatives in obesity prevention have typically recommended the use of evidence-based community strategies, 1 less is known about the level of impact that these strategies can contribute to improving health in the real world. The absence of this type of practice-based information often poses significant challenges to funding agencies and program planners that are tasked with prioritizing and selecting intervention strategies for a city or community. Given that this information is not readily available or regularly reported, recent federal initiatives have begun to request data on intervention impact, using estimates of population reach as a proxy metric for predicting the extent of intervention effectiveness. The Centers for Disease Control and Prevention, for example, recently provided guidance on how to measure and report reach for a range of obesity prevention interventions focused on improving systems and environments in cities and communities across the United States. 2 They broadly defined “reach” as the number of unique individuals affected by a program initiative and further refined this concept to include direct reach as the number of unique individuals exposed to the intervention in some way and indirect reach as the number of unique individuals indirectly exposed to the intervention in some way but who are not residents of a targeted community (e.g., visitors). 2 To provide more specificity, other agencies and organizations (e.g., the Center for Community Health and Evaluation) have sought to account for the effects of community health interventions by incorporating intervention dose as an additional parameter for consideration in their priority-setting process and program planning. 3 In this context, “dose” has been defined as the product of reach (percentage of people exposed to an intervention) and strength (the degree to which people reached by the intervention changed their health behaviors). 3 Although dose is a more robust measure of intervention impact, reach is generally easier to estimate and use, given the time constraints and limited availability of relevant data sources to local leaders who must make daily decisions about policy development, program implementation, and operations. It is important to note, however, that the Centers for Disease Control and Prevention and the Center for Community Health and Evaluation differ in their definitions of “reach.” Although the former’s definition distinguishes between direct and indirect number of unique individuals, the latter’s does not, making comparisons of this metric across studies, interventions, places, settings, and times difficult to achieve. Although the aforementioned metrics (reach and dose) can provide meaningful data to inform health and public health decisions, 4,5 few strategic planning efforts have incorporated their use in the prioritization process. 6 In this article, we describe the effort of the Los Angeles County Department of Public Health (DPH) to systematically incorporate population reach as a proxy metric of intervention impact, using it to guide prioritization of system and environmental change strategies for community implementation (when appropriate). The motivation for writing this article is to inform the efforts of other agencies similarly tasked with addressing the obesity epidemic in their communities but often constrained by limited resources and several competing priorities in their jurisdictions.
