Autism spectrum disorder and co-occurring symptoms often require lifelong services. However, access to autism spectrum disorder services is hindered by a lack of available autism spectrum disorder providers. We utilized geographic information systems methods to map autism spectrum disorder provider locations in Michigan. We hypothesized that (1) fewer providers would be located in less versus more populated areas; (2) neighborhoods with low versus high socioeconomic status would have fewer autism spectrum disorder providers; and (3) an interaction would be found between population and socioeconomic status such that neighborhoods with low socioeconomic status and high population would have few available autism spectrum disorder providers. We compiled a list of autism spectrum disorder providers in Michigan, geocoded the location of providers, and used network analysis to assess autism spectrum disorder service availability in relation to population distribution, socioeconomic disadvantage, urbanicity, and immobility. Hypotheses were supported. Individuals in rural neighborhoods had fewer available autism spectrum disorder providers than individuals in suburban and urban neighborhoods. In addition, neighborhoods with greater socioeconomic status disadvantage had fewer autism spectrum disorder providers available. Finally, statistically significant spatial disparities were found; wealthier suburbs had good provider availability while few providers were available in poorer, urban neighborhoods. Knowing autism spectrum disorder providers’ availability, and neighborhoods that are service deserts, presents the opportunity to utilize evidence-based dissemination and implementation strategies that promote increased autism spectrum disorder providers for underserved individuals. Lay abstract Autism spectrum disorder and co-occurring symptoms often require lifelong services. However, access to autism spectrum disorder services is hindered by a lack of available autism spectrum disorder providers. We utilized geographic information systems methods to map autism spectrum disorder provider locations in Michigan. We hypothesized that (1) fewer providers would be located in less versus more populated areas; (2) neighborhoods with low versus high socioeconomic status would have fewer autism spectrum disorder providers; and (3) an interaction would be found between population and socioeconomic status such that neighborhoods with low socioeconomic status and high population would have few available autism spectrum disorder providers. We compiled a list of autism spectrum disorder providers in Michigan, geocoded the location of providers, and used network analysis to assess autism spectrum disorder service availability in relation to population distribution, socioeconomic disadvantage, urbanicity, and immobility. Individuals in rural neighborhoods had fewer available autism spectrum disorder providers than individuals in suburban and urban neighborhoods. In addition, neighborhoods with greater socioeconomic status disadvantage had fewer autism spectrum disorder providers available. Finally, wealthier suburbs had good provider availability while few providers were available in poorer, urban neighborhoods. Knowing autism spectrum disorder providers’ availability, and neighborhoods that are particularly poorly serviced, presents the opportunity to utilize evidence-based dissemination and implementation strategies that promote increased autism spectrum disorder providers for underserved individuals.

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.

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