Abstract
Addressing health disparities requires both community engagement and an understanding of the social determinants of health. Although elements of the built environment can influence behavior change in public health interventions, such determinants have not been explicitly teased out via participatory mapping. An opportunity exists to integrate community voice in the development of such metrics. To fill this gap and inform the deployment of public health interventions in the Flint (USA) Center for Health Equity Solutions (FCHES), we created a means of assessing spatially-varying community needs and assets in a geographic information system (GIS), what we refer to as a healthfulness index. We engaged community and academic partners in their expert opinions on features of Flint's built environment that may promote or inhibit healthy behaviors via a multiple-criteria decision analysis framework. Experts selected from and ranked 29 variables in 6 categories (including amenities, environment, greenspace, housing, infrastructure, and social issues) using the analytic hierarchy process. The resulting matrices of expert opinions were aggregated and appended as weights for each variable's corresponding map layer. When combined through map algebra, composite scores yield spatially-varying healthfulness indices which signal any neighborhood's relative health promoting qualities (along a 0-100 scale). Results varied substantially across Flint, with the middle belt scoring highest and older neighborhoods in the northeast and north center of the city scoring lowest. Scores were aggregated to 38 Flint neighborhoods; for each of two project-specific indices, these ranged from lows of 38.7 (Hilborn Park) and 41.8 (Columbia Heights) to highs of 52.9 (College Cultural) and 58.0 (University Ave Corridor). We hypothesize that-even when controlling for individual-level factors-we will measure better and more sustained behavior change among participants living in neighborhoods with high healthfulness scores. Future work will examine this hypothesis and determine the importance of such indices in other similar communities.