Developing the DIGIFOOD Dashboard to Monitor the Digitalization of Local Food Environments: Interdisciplinary Approach.

BACKGROUND

Online food delivery services (OFDS) enable individuals to conveniently access foods from any deliverable location. The increased accessibility to foods may have implications on the consumption of healthful or unhealthful foods. Concerningly, previous research suggests that OFDS offer an abundance of energy-dense and nutrient-poor foods, which are heavily promoted through deals or discounts.

OBJECTIVE

In this paper, we describe the development of the DIGIFOOD dashboard to monitor the digitalization of local food environments in New South Wales, Australia, resulting from the proliferation of OFDS.

METHODS

Together with a team of data scientists, we designed a purpose-built dashboard using Microsoft Power BI. The development process involved three main stages: (1) data acquisition of food outlets via web scraping, (2) data cleaning and processing, and (3) visualization of food outlets on the dashboard. We also describe the categorization process of food outlets to characterize the healthfulness of local, online, and hybrid food environments. These categories included takeaway franchises, independent takeaways, independent restaurants and cafes, supermarkets or groceries, bakeries, alcohol retailers, convenience stores, and sandwich or salad shops.

RESULTS

To date, the DIGIFOOD dashboard has mapped 36,967 unique local food outlets (locally accessible and scraped from Google Maps) and 16,158 unique online food outlets (accessible online and scraped from Uber Eats) across New South Wales, Australia. In 2023, the market-leading OFDS operated in 1061 unique suburbs or localities in New South Wales. The Sydney-Parramatta region, a major urban area in New South Wales accounting for 28 postcodes, recorded the highest number of online food outlets (n=4221). In contrast, the Far West and Orana region, a rural area in New South Wales with only 2 postcodes, recorded the lowest number of food outlets accessible online (n=7). Urban areas appeared to have the greatest increase in total food outlets accessible via online food delivery. In both local and online food environments, it was evident that independent restaurants and cafes comprised the largest proportion of food outlets at 47.2% (17,437/36,967) and 51.8% (8369/16,158), respectively. However, compared to local food environments, the online food environment has relatively more takeaway franchises (2734/16,158, 16.9% compared to 3273/36,967, 8.9%) and independent takeaway outlets (2416/16,158, 14.9% compared to 4026/36,967, 10.9%).

CONCLUSIONS

The DIGIFOOD dashboard leverages the current rich data landscape to display and contrast the availability and healthfulness of food outlets that are locally accessible versus accessible online. The DIGIFOOD dashboard can be a useful monitoring tool for the evolving digital food environment at a regional scale and has the potential to be scaled up at a national level. Future iterations of the dashboard, including data from additional prominent OFDS, can be used by policy makers to identify high-priority areas with limited access to healthful foods both online and locally.