Dataset Information

Neighborhood Racial Segregation Predict the Spatial Distribution of Supermarkets and Grocery Stores Better than Socioeconomic Factors in Cleveland, Ohio: a Bayesian Spatial Approach.

ABSTRACT:

Introduction

The food environment influences the availability and affordability of food options for consumers in a given neighborhood. However, disparities in access to healthy food options exist, affecting Black and low-income communities disproportionately. This study investigated whether racial segregation predicted the spatial distribution of supermarkets and grocery stores better than socioeconomic factors or vice versa in Cleveland, Ohio.

Method

The outcome measure was the count of supermarket and grocery stores in each census tract in Cleveland. They were combined with US census bureau data as covariates. We fitted four Bayesian spatial models. The first model was a baseline model with no covariates. The second model accounted for racial segregation alone. The third model looked at only socioeconomic factors, and the final model combined both racial and socioeconomic factors.

Results

Overall model performance was better in the model that considered only racial segregation as a predictor of supermarkets and grocery stores (DIC = 476.29). There was 13% decrease in the number of stores for a census tract with a higher majority of Black people compared to areas with a lower number of Black people. Model 3 that considered only socioeconomic factors was less predictive of the retail outlets (DIC = 484.80).

Conclusions

These findings lead to the conclusion that structural racism evidenced in policies like residential segregation has a significant influence on the spatial distribution of food retail in the city of Cleveland.

SUBMITTER: Yankey O

PROVIDER: S-EPMC11236921 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Publications

Neighborhood Racial Segregation Predict the Spatial Distribution of Supermarkets and Grocery Stores Better than Socioeconomic Factors in Cleveland, Ohio: a Bayesian Spatial Approach.

Yankey Ortis O Lee Jay J Gardenhire Rachel R Borawski Elaine E

Journal of racial and ethnic health disparities 20230627 4

<h4>Introduction</h4>The food environment influences the availability and affordability of food options for consumers in a given neighborhood. However, disparities in access to healthy food options exist, affecting Black and low-income communities disproportionately. This study investigated whether racial segregation predicted the spatial distribution of supermarkets and grocery stores better than socioeconomic factors or vice versa in Cleveland, Ohio.<h4>Method</h4>The outcome measure was the c ...[more]

PMID: 37368191

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Project description:Social determinants of health, including neighborhood factors, play a key role in the health of diverse older adults. However, few longitudinal studies have examined the role of neighborhood racial/ethnic segregation on cognitive decline in diverse samples. We examined older non-Hispanic White (NHW), Black, and Latino participants evaluated at an Alzheimer's Disease Research Center. Neighborhood racial/ethnic segregation was measured using the Getis-Ord Gi* statistic, a spatial measure of clustering that was created for Latino and Black clustering separately. Cognitive outcomes included episodic memory, semantic memory, and executive function. We used mixed effects multivariable regression models to evaluate associations between segregation and cognitive function and decline. We had 452 individuals: 46% NHW, 26% Black, and 21% Latino in 309 census tracts with an average of 5.2 years of follow-up data (range 0.6-15.0). In analyses that adjusted for a variety of covariates (including neighborhood SES), individuals in neighborhoods with a higher clustering of Latino residents (higher Gi* statistic) had slower declines over time on semantic memory and those in neighborhoods with a higher clustering of Black residents had slower declines over time on episodic memory. In race/ethnicity-stratified adjusted analyses: for Black participants, the association between clustering and cognition was present for episodic memory and executive function, showing lower baseline scores in highly clustered Black and Latino neighborhoods, respectively. There was no association with cognitive change. Among Latino participants, highly clustered Latino neighborhoods were associated with lower baseline scores in semantic memory, but slower declines in episodic memory; Latinos living in neighborhoods with a greater clustering of Black residents also had slower declines in episodic memory. Among NHWs, residing in neighborhoods with a higher clustering of Latino residents was associated with slower declines over time on semantic memory. Segregated neighborhoods may be differentially associated with cognitive outcomes depending on individual race/ethnicity.

Project description:BackgroundPurchases at small/non-traditional food stores tend to have poor nutritional quality, and have been associated with poor health outcomes, including increased obesity risk The purpose of this study was to examine whether customers who shop at small/non-traditional food stores with more health promoting features make healthier purchases.MethodsIn a cross-sectional design, data collectors assessed store features in a sample of 99 small and non-traditional food stores not participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Minneapolis/St. Paul, MN in 2014. Customer intercept interviews (n = 594) collected purchase data from a bag check and demographics from a survey. Store measures included fruit/vegetable and whole grain availability, an overall Healthy Food Supply Score (HFSS), healthy food advertisements and in-store placement, and shelf space of key items. Customer nutritional measures were analyzed using Nutrient Databases System for Research (NDSR), and included the purchase of ≥1 serving of fruits/vegetables; ≥1 serving of whole grains; and overall Healthy Eating Index-2010 (HEI-2010) score for foods/beverages purchased. Associations between store and customer measures were estimated in multilevel linear and logistic regression models, controlling for customer characteristics and store type.ResultsFew customers purchased fruits and vegetables (8%) or whole grains (8%). In fully adjusted models, purchase HEI-2010 scores were associated with fruit/vegetable shelf space (p = 0.002) and the ratio of shelf space devoted to healthy vs. less healthy items (p = 0.0002). Offering ≥14 varieties of fruit/vegetables was associated with produce purchases (OR 3.9, 95% CI 1.2-12.3), as was having produce visible from the store entrance (OR 2.3 95% CI 1.0 to 5.8), but whole grain availability measures were not associated with whole grain purchases.ConclusionsStrategies addressing both customer demand and the availability of healthy food may be necessary to improve customer purchases.Trial registrationClinialTrials.gov: NCT02774330 . Registered May 4, 2016 (retrospectively registered).

Dataset Information

Neighborhood Racial Segregation Predict the Spatial Distribution of Supermarkets and Grocery Stores Better than Socioeconomic Factors in Cleveland, Ohio: a Bayesian Spatial Approach.

Introduction

Method

Results

Conclusions

Publications

Neighborhood Racial Segregation Predict the Spatial Distribution of Supermarkets and Grocery Stores Better than Socioeconomic Factors in Cleveland, Ohio: a Bayesian Spatial Approach.

Similar Datasets

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