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Examining the Effect of Neighbourhood Segregation and Socioeconomic Factors on the Food Environment: A Bayesian Hierarchical Spatial Analysis Using INLA

Yankey, Ortis
http://orcid.org/0000-0002-0808-884X
http://rave.ohiolink.edu/etdc/view?acc_num=kent1648810823813421

Abstract Details

2022, PHD, Kent State University, College of Arts and Sciences / Department of Geography.
The retail food environment has a significant impact on the availability and affordability of food options for consumers within a given neighborhood. However, approaches for accounting for the complicated spatial clustering of diverse food outlets in a study location are mostly frequentist models, and there is an absence of Bayesian models. Furthermore, the majority of food environment studies combine socioeconomic characteristics and neighborhood segregation into a single model to study the food environment. This approach, often confound the subtle relationship that any of these factors have on policy. This research investigates the food environment using a Bayesian hierarchical spatial model, a method that has seldomly been employed in food environment studies. This research examines both the community and consumer food environments. This study is made up of three manuscripts. The first manuscript (Chapter 4) examined the effects of neighborhood socioeconomic factors and racial segregation on the distribution of supermarkets and grocery stores in Cleveland. The purpose of this chapter was to determine which of the two complimentary factors provides a more robust explanation for the geographical distribution of the stores in Cleveland. Using the Deviance Information Criterion (DIC) as a basis for model robustness, the results of comparing four models show that racial segregation predicts the store distribution far better than socioeconomic characteristics. This finding demonstrated how structural issues such as neighborhood segregation may have played a part in Cleveland's limited availability of supermarkets and grocery stores. The second paper (Chapter 5) investigated in-store and neighborhood healthy food availability as well as their relationships with neighborhood racial segregation and socioeconomic characteristics. Eleven healthy food items were rated in order to obtain a composite score for healthy food availability. According to the study's findings, supermarkets and grocery shops provided more nutritious food items than corner and convenience stores. The research also discovered that an accumulative model that examined both socioeconomic factors and neighborhood segregation together had a lower DIC value compared to the other models. This indicate that both socioeconomic factors and neighborhood segregation are intertwined in defining healthy food availability at the neighborhood level. The last manuscript, chapter 6, examined the co-clustering of the consumer and the community food environment using a joint Bayesian shared effect model. Two models were examined in this study. The first model examined the joint co-clustering of three store types, namely supermarkets (grocery stores), corner stores, and fast-food restaurants. In the second model, the study examined the co-location of the stores, excluding fast-food and healthy food availability, to observe bivariate co-clustering. The results from the study showed an overall general pattern of higher co-clustering of the stores in the west and the central city, whereas areas in the east had low co-clustering of the stores. A similar spatial pattern was also found for the joint association between healthy food availability and grocery stores in model 2. These results indicate that the food environment is not mutually exclusively "healthy or unhealthy," as has been suggested in the food environment literature. But consumers are exposed to a wide range of healthy and unhealthy food choices.
Dr. Jay Lee (Committee Chair)
Dr. Elaine Borawski (Committee Member)
Dr. He Yin (Committee Member)
Dr Timothy Assal (Committee Member)
185 p.
Geographic Information Science; Geography
Food Environment, Community Food Environment, Consumer Food Environment, Spatial Bayesian Method, Segregation, Food Desert, Food Swamp, Cleveland, INLA,

Recommended Citations

Citations

  • Yankey, O. (2022). Examining the Effect of Neighbourhood Segregation and Socioeconomic Factors on the Food Environment: A Bayesian Hierarchical Spatial Analysis Using INLA [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1648810823813421

    APA Style (7th edition)

  • Yankey, Ortis. Examining the Effect of Neighbourhood Segregation and Socioeconomic Factors on the Food Environment: A Bayesian Hierarchical Spatial Analysis Using INLA. 2022. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1648810823813421.

    MLA Style (8th edition)

  • Yankey, Ortis. "Examining the Effect of Neighbourhood Segregation and Socioeconomic Factors on the Food Environment: A Bayesian Hierarchical Spatial Analysis Using INLA." Doctoral dissertation, Kent State University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=kent1648810823813421

    Chicago Manual of Style (17th edition)

kent1648810823813421
281
© 2022, some rights reserved.Creative Commons License Examining the Effect of Neighbourhood Segregation and Socioeconomic Factors on the Food Environment: A Bayesian Hierarchical Spatial Analysis Using INLA by Ortis Yankey is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Kent State University and OhioLINK.