Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Sydney Informatics Hub, University of Sydney, Sydney, Australia.
JMIR Public Health Surveill. 2024 Aug 13;10:e59924. doi: 10.2196/59924.
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.
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.
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.
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%).
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.
在线食品配送服务（OFDS）使个人能够方便地从任何可配送地点获取食品。食品获取便利性的提高可能会对健康食品和不健康食品的消费产生影响。令人担忧的是，先前的研究表明，OFDS 提供了大量的高能量、低营养的食品，这些食品通过优惠或折扣大量推广。
本文描述了 DIGIFOOD 仪表板的开发，该仪表板用于监测澳大利亚新南威尔士州本地食品环境的数字化，这是由于 OFDS 的普及而导致的。
我们与一个数据科学家团队一起使用 Microsoft Power BI 设计了一个专用的仪表板。开发过程涉及三个主要阶段：（1）通过网络爬虫获取食品店数据，（2）数据清理和处理，以及（3）在仪表板上可视化食品店。我们还描述了食品店的分类过程，以描述本地、在线和混合食品环境的健康程度。这些类别包括外卖连锁店、独立外卖店、独立餐厅和咖啡馆、超市或杂货店、面包店、酒类零售商、便利店和三明治或沙拉店。
截至目前，DIGIFOOD 仪表板已经在澳大利亚新南威尔士州映射了 36967 个独特的本地食品店（本地可访问并从谷歌地图中抓取）和 16158 个独特的在线食品店（在线可访问并从 Uber Eats 中抓取）。2023 年，市场领先的 OFDS 在新南威尔士州的 1061 个独特郊区或地区运营。悉尼-帕拉马塔地区是新南威尔士州的一个主要城区，占 28 个邮政编码，记录了最多的在线食品店（n=4221）。相比之下，新南威尔士州的远西部和奥拉拉地区只有 2 个邮政编码，记录了在线可访问的食品店数量最少（n=7）。城市地区似乎在线食品配送可访问的食品店总数增长最大。在本地和在线食品环境中，独立餐厅和咖啡馆的比例最大，分别为 47.2%（17437/36967）和 51.8%（8369/16158）。然而，与本地食品环境相比，在线食品环境相对有更多的外卖连锁店（2734/16158，16.9%，而 3273/36967，8.9%）和独立外卖店（2416/16158，14.9%，而 4026/36967，10.9%）。
DIGIFOOD 仪表板利用当前丰富的数据环境来显示和对比本地可访问的食品店和在线可访问的食品店的可用性和健康程度。DIGIFOOD 仪表板可以作为区域尺度上不断发展的数字食品环境的有用监测工具，并有可能在国家层面上扩大规模。仪表板的未来版本，包括来自其他主要 OFDS 的数据，可以被政策制定者用来识别在线和本地健康食品获取机会有限的高优先级地区。
