Estimating spatial accessibility to facilities on the regional scale: An extended commuting-based interaction potential model

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Abstract

Background: There is growing interest in the study of the relationships between individual health-related behaviours (e.g. food intake and physical activity) and measurements of spatial accessibility to the associated facilities (e.g. food outlets and sport facilities). The aim of this study is to propose measurements of spatial accessibility to facilities on the regional scale, using aggregated data. We first used a potential accessibility model that partly makes it possible to overcome the limitations of the most frequently used indices such as the count of opportunities within a given neighbourhood. We then propose an extended model in order to take into account both home and work-based accessibility for a commuting population.Results: Potential accessibility estimation provides a very different picture of the accessibility levels experienced by the population than the more classical "number of opportunities per census tract" index. The extended model for commuters increases the overall accessibility levels but this increase differs according to the urbanisation level. Strongest increases are observed in some rural municipalities with initial low accessibility levels. Distance to major urban poles seems to play an essential role.Conclusions: Accessibility is a multi-dimensional concept that should integrate some aspects of travel behaviour. Our work supports the evidence that the choice of appropriate accessibility indices including both residential and non-residential environmental features is necessary. Such models have potential implications for providing relevant information to policy-makers in the field of public health. © 2011 Salze et al; licensee BioMed Central Ltd.

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Salze, P., Banos, A., Oppert, J. M., Charreire, H., Casey, R., Simon, C., … Weber, C. (2011). Estimating spatial accessibility to facilities on the regional scale: An extended commuting-based interaction potential model. International Journal of Health Geographics, 10. https://doi.org/10.1186/1476-072X-10-2

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