06 Combining straight-line and map-based distances to quantify neighborhood-level food access and its impact on health

Oregon Convention Center 

Healthy foods are essential for a healthy life, but not everyone has the same access to healthy foods, leading to disproportionate rates of diseases in low-access communities. Current methods to quantify food access rely on distance measures that are either computationally simple (the shortest straight-line route) or accurate (the shortest map-based route), but not both. We combine these food access measures through a multiple imputation for measurement error framework, leveraging information from less accurate straight-line distances to compute informative placeholders (i.e., impute) more accurate food access for any neighborhoods without map-based distances. Thus, computationally expensive map-based distances are only needed for a subset of neighborhoods. Using simulations and data for Forsyth County, North Carolina, we quantify and compare the associations between the prevalence of various health outcomes and neighborhood-level food access. Through imputation, predicting the full landscape of food access for all neighborhoods in an area is also possible without requiring map-based measurements for all neighborhoods.