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      A Geospatial Analysis of Access to Ethnic Food Retailers in Two Michigan Cities: Investigating the Importance of Outlet Type within Active Travel Neighborhoods

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          Abstract

          To date, the research that examines food accessibility has tended to ignore ethnic food outlets. This void leaves us with a limited understanding of how such food stores may, or may not, impact food security. The study discussed herein addressed this by conducting a geospatial assessment of ethnic food outlet accessibility in two U.S. cities: Flint and Grand Rapids, Michigan. We used Geographic Information Systems (GIS) tools to create a revealed accessibility index for each food outlet, and used the index to determine access within active travel service areas. We utilized an ordinary least squares regression (OLS), and two local models: spatial autoregression (SAR) and geographically weighted regression (GWR) to enhance our understanding of global and localized relationships between outlet accessibility and type (while controlling for known covariates). The results show that the local models outperformed ( R 2 max = 0.938) the OLS model. The study found that there was reduced access to ethnic restaurants in all service areas of Grand Rapids. However, in Flint, we observed this association in the bicycling areas only. Also notable were the influences that demographic characteristics had on access in each city. Ultimately, the findings tell us that nuanced planning and policy approaches are needed in order to promote greater access to ethnic food outlets and reduce overall food insecurity.

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          Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity

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            Physical activity and food environments: solutions to the obesity epidemic.

            Environmental, policy, and societal changes are important contributors to the rapid rise in obesity over the past few decades, and there has been substantial progress toward identifying environmental and policy factors related to eating and physical activity that can point toward solutions. This article is a status report on research on physical activity and food environments, and it suggests how these findings can be used to improve diet and physical activity and to control or reduce obesity. This article summarizes and synthesizes recent reviews and provides examples of representative studies. It also describes ongoing innovative interventions and policy change efforts that were identified through conference presentations, media coverage, and websites. Numerous cross-sectional studies have consistently demonstrated that some attributes of built and food environments are associated with physical activity, healthful eating, and obesity. Residents of walkable neighborhoods who have good access to recreation facilities are more likely to be physically active and less likely to be overweight or obese. Residents of communities with ready access to healthy foods also tend to have more healthful diets. Disparities in environments and policies that disadvantage low-income communities and racial minorities have been documented as well. Evidence from multilevel studies, prospective research, and quasi-experimental evaluations of environmental changes are just beginning to emerge. Environment, policy, and multilevel strategies for improving diet, physical activity, and obesity control are recommended based on a rapidly growing body of research and the collective wisdom of leading expert organizations. A public health imperative to identify and implement solutions to the obesity epidemic warrants the use of the most promising strategies while continuing to build the evidence base.
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              SPATIAL ANALYSIS OF LANDSCAPES: CONCEPTS AND STATISTICS

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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                25 December 2019
                January 2020
                : 17
                : 1
                : 166
                Affiliations
                [1 ]Department of Geography, Planning and Environment, University of Michigan-Flint, Flint, MI 48502, USA; dick.wetzel@ 123456gmail.com
                [2 ]The Michigan Institute for Data Science (MIDAS), Ann Arbor, MI 48108, USA
                [3 ]The Centre for Urban Design and Mental Health, London SW9 7QF, UK
                [4 ]School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48108, USA; dorceta@ 123456umich.edu (D.T.); sjbrines@ 123456umich.edu (S.B.)
                Author notes
                [* ]Correspondence: grybar@ 123456umich.edu ; Tel.: +1-810-762-3355
                Article
                ijerph-17-00166
                10.3390/ijerph17010166
                6982187
                31881710
                86c8278f-7031-4ccb-a94b-8e6f4931ba73
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 11 October 2019
                : 21 December 2019
                Categories
                Article

                Public health
                food access,ethnic food,service area analysis,gis,urban design,gwr,local regression,space syntax,demographic characteristics

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