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Geographies of grocery shopping in major Canadian cities: Evidence from large-scale mobile app data
Environment and Planning B: Urban Analytics and City Science ; 2022.
Article in English | Web of Science | ID: covidwho-2070695
ABSTRACT
Socioeconomic and place-based factors contribute to grocery shopping patterns which may be important for diet and health. Big data provide the opportunity to explore behaviours at the population level. We used data collected from Flipp, a free all-in-one savings and deals content app, to identify visitation to grocery stores and estimate home-to-store distances, monthly frequencies and number of unique stores visited in eight Canadian cities during 2020. Grocery shopping outcomes and associations with income, population density and percentage of car commuters were explored using data aggregated at the Aggregate Dissemination Area level in which app users lived. Changes in patterns of grocery shopping following restrictions implemented in response to the COVID-19 pandemic were also investigated. The median of average home-to-store distances ranged from 4 to 5 km across all cities throughout 2020. Shorter distances for grocery shopping were shown consistently for shoppers living in lower income, densely populated and low car-commuting ADAs. A maximum of three unique supermarkets were visited on average each month. Decreases in the frequency and variability of grocery store visits were shown across all cities in April 2020 following the implementation of restrictions in response to COVID-19, and pre-pandemic levels of shopping were rarely achieved by the end of the year. Ultimately, these results provide much needed information regarding the characteristics of grocery shopping trips in a high-income country, as well as how food shopping was impacted by the onset of the COVID-19 pandemic. This information will be useful for a range of future studies seeking to characterise access to food retail.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Environment and Planning B: Urban Analytics and City Science Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Environment and Planning B: Urban Analytics and City Science Year: 2022 Document Type: Article