Exploring sales data during a healthy corner store intervention in Toronto: the Food Retail Environments Shaping Health (FRESH) project

Introduction Population health interventions in the retail food environment, such as corner store interventions, aim to influence the kind of cues consumers receive so that they are more often directed toward healthier options. Research that addresses financial aspects of retail interventions, particularly using outcome measures such as store sales that are central to retail decision making, is limited. This study explored store sales over time and across product categories during a healthy corner store intervention in a lowincome neighbourhood in Toronto, Ontario. Methods Sales data (from August 2014 to April 2015) were aggregated by product category and by day. We used Microsoft Excel pivot tables to summarize and visually present sales data. We conducted t-tests to examine differences in product category sales by “peak” versus “nonpeak” sales days. Results Overall store sales peaked on the days at the end of each month, aligned with the issuing of social assistance payments. Revenue spikes on peak sales days were driven predominantly by transit pass sales. On peak sales days, mean sales of nonnutritious snacks and cigarettes were marginally higher than on other days of the month. Finally, creative strategies to increase sales of fresh vegetables and fruits seemed to substantially increase revenue from these product categories. Conclusion Store sales data is an important store-level metric of food environment intervention success. Furthermore, data-driven decision making by retailers can be important for tailoring interventions. Future interventions and research should consider partnerships and additional success metrics for retail food environment interventions in diverse Canadian contexts.

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Local Retail Food Environment and Consumption of Fruit and Vegetable among Adults in Hong Kong

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15102247 ◽

2018 ◽

Vol 15 (10) ◽

pp. 2247 ◽

Cited By ~ 3

Author(s):

Ting Zhang ◽

Bo Huang

Keyword(s):

Hong Kong ◽

Food Environment ◽

Fast Food ◽

Vegetable Consumption ◽

Grocery Stores ◽

Fruit Consumption ◽

Retail Food Environment ◽

Convenience Stores ◽

Fast Food Restaurants ◽

Retail Food

Outside of western countries, the study of the local food environment and evidence for its association with dietary behavior is limited. The aim of this paper was to examine the association between the local retail food environment and consumption of fruit and vegetables (FV) among adults in Hong Kong. Local retail food environment was measured by density of different types of retail food outlets (grocery stores, convenience stores, and fast food restaurants) within a 1000 m Euclidean buffer around individual’s homes using a geographic information system (GIS). The Retail Food Environment Index (RFEI) was calculated based on the relative density of fast-food restaurants and convenience stores to grocery stores. Logistic regressions were performed to examine associations using cross-sectional data of 1977 adults (18 years or older). Overall, people living in an area with the highest RFEI (Q4, >5.76) had significantly greater odds of infrequent FV consumption (<7 days/week) after covariates adjustment (infrequent fruit consumption: OR = 1.36, 95% CI 1.04–1.78; infrequent vegetable consumption: OR = 1.72, 95% CI 1.11–2.68) in comparison to the lowest RFEI (Q1, <2.25). Highest density of fast food restaurants (Q4, >53) was also significantly associated with greater odds of infrequent fruit consumption (<7 days/week) (unadjusted model: OR = 1.34, 95% CI 1.04–1.73), relative to lowest density of fast food restaurants (Q1, <13). No significant association of density of grocery stores or convenience stores was observed with infrequent FV consumption regardless of the covariates included in the model. Our results suggest that the ratio of fast-food restaurants and convenience stores to grocery stores near people’s home is an important environmental factor in meeting fruit and vegetable consumption guidelines. “Food swamps” (areas with an abundance of unhealthy foods) rather than “food deserts” (areas where there is limited access to healthy foods) seems to be more of a problem in Hong Kong’s urban areas. We advanced international literature by providing evidence in a non-western setting.

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Differences in the Neighborhood Retail Food Environment and Obesity Among US Children and Adolescents by SNAP Participation

Obesity ◽

10.1002/oby.22184 ◽

2018 ◽

Vol 26 (6) ◽

pp. 1063-1071 ◽

Cited By ~ 10

Author(s):

Mary T. Gorski Findling ◽

Julia A. Wolfson ◽

Eric B. Rimm ◽

Sara N. Bleich

Keyword(s):

Children And Adolescents ◽

Food Environment ◽

Retail Food Environment ◽

Us Children ◽

Retail Food

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The Influence of WIC Changes on the Retail Food Environment in New Orleans

The FASEB Journal ◽

10.1096/fasebj.25.1_supplement.98.5 ◽

2011 ◽

Vol 25 (S1) ◽

Author(s):

Diego Rose ◽

Lauren Futrell Dunaway ◽

Adriana Dornelles ◽

Keelia O'Malley ◽

J. Nicholas Bodor ◽

...

Keyword(s):

New Orleans ◽

Food Environment ◽

Retail Food Environment ◽

Retail Food

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Healthy Food Retail during the COVID-19 Pandemic: Challenges and Future Directions

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17207397 ◽

2020 ◽

Vol 17 (20) ◽

pp. 7397 ◽

Cited By ~ 2

Author(s):

Lucia A. Leone ◽

Sheila Fleischhacker ◽

Betsy Anderson-Steeves ◽

Kaitlyn Harper ◽

Megan Winkler ◽

...

Keyword(s):

Food Environment ◽

Business Models ◽

Food System ◽

Interaction Model ◽

Geographic Location ◽

The United States ◽

Retail Food Environment ◽

Nutrition Assistance ◽

The Impact ◽

Retail Food

Disparities in dietary behaviors have been directly linked to the food environment, including access to retail food outlets. The Coronavirus Disease of 2019 (COVID-19) pandemic has led to major changes in the distribution, sale, purchase, preparation, and consumption of food in the United States (US). This paper reflects on those changes and provides recommendations for research to understand the impact of the pandemic on the retail food environment (RFE) and consumer behavior. Using the Retail Food Environment and Customer Interaction Model, we describe the impact of COVID-19 in four key areas: (1) community, state, tribal, and federal policy; (2) retail actors, business models, and sources; (3) customer experiences; and (4) dietary intake. We discuss how previously existing vulnerabilities and inequalities based on race, ethnicity, class, and geographic location were worsened by the pandemic. We recommend approaches for building a more just and equitable RFE, including understanding the impacts of changing shopping behaviors and adaptations to federal nutrition assistance as well as how small food business can be made more sustainable. By better understanding the RFE adaptations that have characterized the COVID-19 pandemic, we hope to gain greater insight into how our food system can become more resilient in the future.

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Diet Quality and Food Prices Modify Associations between Genetic Susceptibility to Obesity and Adiposity Outcomes

Nutrients ◽

10.3390/nu12113349 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3349

Author(s):

Hannah Yang Han ◽

Catherine Paquet ◽

Laurette Dubé ◽

Daiva E Nielsen

Keyword(s):

Waist Circumference ◽

Diet Quality ◽

Food Environment ◽

High Energy ◽

Healthy Eating Index ◽

Food Prices ◽

Polygenic Risk Score ◽

Polygenic Risk ◽

Retail Food Environment ◽

Retail Food

The role of the retail food environment in obesity risk is unclear, which may be due in part to the lack of consideration of individual differences in the responsivity to food cues. This cross-sectional investigation geo-temporally linked the CARTaGENE biobank (including genetic, dietary, lifestyle, and anthropometric data) with in-store retail food environment data to examine interactions between a polygenic risk score (PRS) for obesity and (1) diet quality (n = 6807) and (2) in-store retail food measures (n = 3718). The outcomes included adiposity-related measures and diet quality assessed using the 2010 Canadian-adapted Healthy Eating Index. A vegetable:soft drink ratio was constructed for each retail measure to assess the relative healthfulness of exposures. Generalized linear models adjusted for individual and neighborhood socio-demographic factors were used to evaluate main and interactive effects. Diet quality significantly modified the association between polygenic risk of obesity and body mass index, waist circumference, and body fat percent. A significant interaction was also observed between PRS and regular price of vegetables in relation to soft drinks on waist circumference. These results replicate previous reports of diet moderating polygenic risk of obesity and suggest that prices of low vs. high-energy density foods are an intervention target to address population obesity rates.

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The association between the retail food environment, economic deprivation, fast food intake and obesity: Findings from the Survey of the Health of Wisconsin

ISEE Conference Abstracts ◽

10.1289/isee.2013.p-3-15-22 ◽

2013 ◽

Vol 2013 (1) ◽

pp. 3787

Author(s):

Michael Laxy ◽

Kristen C. Malecki ◽

Marjory L. Givens ◽

F. Javier Nieto

Keyword(s):

Food Intake ◽

Food Environment ◽

Fast Food ◽

Economic Deprivation ◽

Retail Food Environment ◽

Retail Food

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DETERMINING THE AREA SIZES OF EACH PRODUCT CATEGORY IN A DEPARTMENT STORE USING MULTI-CRITERIA DECISION MAKING METHODOLOGIES

International Journal of the Analytic Hierarchy Process ◽

10.13033/ijahp.v12i1.602 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Gulcin Dinc Yalcin ◽

Zehra Kamisli Ozturk

Keyword(s):

Decision Making ◽

Product Category ◽

Department Store ◽

Analytic Network Process ◽

Pairwise Comparisons ◽

Multi Criteria Decision Making ◽

Department Stores ◽

Ahp Model ◽

Product Categories ◽

Wide Range

In a department store, customers have the opportunity to reach a wide range of consumer goods from different product categories within a single store area. Store layouts generally show the size and location of each department, any permanent structures, fixture locations, and customer traffic patterns. Determining the area sizes to be allocated to each product category and the layout of these areas in the department store is a strategic planning decision problem. The layout problem has been studied in the literature with different approaches where the sizes of the areas are known. The first purpose of this paper is to determine the area sizes of each product category. Customers decide to go to a department store for several reasons including the quality of products, services, location, etc. These reasons have been studied in the literature. However, “for which product categories do customers decide to go to a department store” is an open question. The second purpose of this paper is to find the frequency of product categories from the viewpoint of the customers. Therefore, our aim is to obtain the required results in a systematic way with multi-criteria decision making methodologies. For this purpose, we perform the Analytic Network Process (ANP) and the Analytic Hierarchy Process (AHP) from the viewpoints of department managers and customers, respectively. In the ANP model, several tangible and intangible criteria such as product costs, the demands of customers, sales history, overall inventory, floor space and relationship with suppliers are chosen, and the intersections between them are specified. Pairwise comparisons are made by department store managers. The ANP outcome is the weight of each product category, and these weights are considered the percentage of the area size within the store from the viewpoint of the department stores. In the AHP model, a simple model is constructed to define the customers’ preference for each product category. Pairwise comparisons between product categories are made by the customers. Therefore, the outcome of the AHP model is the weight of each product category, and this is the preference of each product category from the viewpoint of the customers. The outcomes show that these weights may be different. This is an expected situation since even if a product category is preferred by some as the driver to visit a department store, the footprint of that category in the actual store may be small. The outcome from customers provides feedback to department store managers on which product category should be diversified as well as the area sizes of those categories.

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