Obesity is among the biggest health challenges facing the world [1
], in particular for adolescents and young adults [2
]. The major risk factors driving the global burden of obesity are diet-related [3
]. Dietary risk factors for obesity and chronic diseases include diets high in discretionary foods (i.e., energy-dense, nutrient-poor foods high in saturated fat, added sugars and sodium) [4
]. Food retail environments influence dietary behaviors and obesity prevalence [5
]. Evidence for the causal relationship between food environments and obesity is limited [6
]. However, recent research has demonstrated associations between restaurant and takeaway food consumption with increased discretionary food intake [8
]. Takeaway foods are one of the fastest-growing categories in online retail sales index, experiencing a 99% annual growth in Australia [9
]. Young people (15-to-34-years-old) in Australia are spending on average AUD$
100/week eating at restaurants or ordering takeaway foods [10
]. Internet and smartphones in the modern food environment have emerged as tools to enable immediate access to many food outlets to order food directly to a residential home or workplace [11
Online food delivery services (OFD’s) are defined as websites or smartphone applications that allow customers to order menu items from food outlets for pick-up or delivery by freelance couriers [12
]. To access these services, customers create a personal account with credit or debit card details for automatic payment and their delivery address. If a customer selects delivery, they can generally track the progress of their order on the website or app. In 2020, the global revenue from OFD’s is projected to be US$
2,082 million [12
], with Uber Eats (UberEATS®
, Uber Technologies Inc) accounting for 30% of the market [12
]. Globally, young people (18–34-years) are the main users (48.4%) of OFD’s [13
]. In Australia and New Zealand, over 25% of young people (15–34 years) are reported users [14
]. A recent Australian study found that OFD’s are commonly used by working young adults who have higher disposable incomes [15
]. The recent increase in the popularity of OFD’s is challenging traditional food retail environments by changing the geographical reach and availability of restaurant and takeaway foods [16
]. The current COVID-19 (coronavirus disease of 2019, a disease caused by the SARS-CoV2 virus [17
]) pandemic and government restrictions related to social distancing may have further accelerated the demand for online food delivery. Subsequently, some restaurants and food outlets have increased their geographical delivery distance to reach more people [18
The rapidly escalating demands for the convenience of OFD’s have driven research in the consumer service-related fields [19
], yet there has been a paucity of research evaluating the public health implications of online food delivery services [24
]. A recent cross-sectional study examined the prevalence and frequency of using OFD’s in five countries in 2018. This study found that 15% of respondents had used online food delivery in the past seven days. Moreover, it showed that 35% of all meals purchased away-from-home were through OFD’s (40% among Australian responders). Respondents who were male and younger, among other sociodemographic characteristics, had greater odds of using OFD’s [25
]. Another cross-sectional study in three countries demonstrated a large variety of food types consumers can purchase using OFD’s [16
]. Most food types were considered unhealthy, and there was not a higher proportion of healthy food types available for consumers living in lower socioeconomic neighborhoods [16
]. The food types analyzed were based on keywords provided on the food delivery outlet, and the study did not independently assess the nutritional quality of food outlets or menu items. Both of these studies have provided crucial insights into the prevalence and frequency of OFD’s, and both reveal the vast number of food outlets now readily accessible at our fingertips. Important gaps remain about the nutritional quality of food outlets and the food they provide, in order to evaluate the public health implications of online food delivery services.
The primary aim of this present study was to evaluate the healthiness and geographical reach of popular food outlets and the nutritional quality menu items on a market-leading OFD platform, in areas with high concentrations of young consumers (15–34-years) across two high-income cities, Sydney, Australia and Auckland, New Zealand. A secondary aim was to examine the differences between food outlet characteristics and the socioeconomic disadvantage level within each city.
This study is the first to evaluate the characteristics and healthiness of the most popular food outlets in addition to the nutritional quality of their most popular menu items on a market-leading online food delivery platform. Overall, we found that almost three-quarters of the most popular food outlets were classified as unhealthy using the FES, with half of the food outlets in Auckland and a third of food outlets in Sydney being classified as takeaway food franchise stores such as McDonald’s® and Burger King®. We also found that almost 9 out of 10 of the most popular menu items in both cities were discretionary foods. In Sydney, 1 in 6 of the most popular items were SSBs, and in Auckland, almost 1 in 3 were meal deals which included hot chips or SSBs. Although this study did not directly measure consumption, our investigation of the most popular food outlets, as well as the most popular menu items of these outlets, suggest that a large proportion of users of OFD’s are using it to access and purchase ‘junk’ foods.
An important finding of this study is that the majority (~90%) of delivery distances were greater than 1 km, a distance which has been typically used to define a neighborhood food environment [41
]. This demonstrates that OFD’s are disrupting traditional food environments by increasing the reach and accessibility of food outlets. Moreover, using OFD’s may further promote sedentary lifestyle behaviors [24
]. The impacts OFD’s have on population dietary intake remains an outstanding and crucial question. It is not known whether the use of OFD’s is simply changing the mode
of purchasing food away from home, i.e., from face-to-face to online, or whether it is changing what
or how often
food is purchased away from home. Regardless, our findings combined with the growing demand for OFD’s demonstrate the need to incorporate ‘digital food environments’ into public health nutrition strategies and policies, which to date are still focused on the built environment [43
Unhealthy food outlets and discretionary menu items dominated the sample of food outlets and menu items in this study. This finding aligns with reports released from other OFD’s. For example, a 2019 report from the most frequently used app for OFD’s in the United States of America, ‘Door Dash’®
revealed American consumers’ top ordered foods were discretionary foods, including, cheeseburger and fries, pizza, nachos, cheesecake, baby back pork rib, chicken and waffle sliders [45
]. Moreover, in the United Kingdom, the leading app, Grubhub®
, reported that in 2018 over 70% of its customers utilized the app to order quick service or fast-casual foods [46
]. As such, it is becoming evident that these energy-dense nutrient-poor discretionary options are the most popular selections to be delivered. However, in contrast to our findings, a report released from Uber Eats Australia stated that ‘one in five Australians said that they tend to eat healthier when they order in compared to when they cook
.’ Applying the FES to food outlets suggested that those food outlets that were categorized as ‘healthy’ on Uber Eats were mostly ‘unhealthy.’ As such, health claims by food outlets on Uber Eats may be misleading consumers. Further independent research is needed to understand the impact of such services on exposure to unhealthy foods and dietary intake, given OFD’s have strong commercial interests with large fast-food franchises.
Emerging research from other countries have also provided insights into the impacts of online food delivery exposure to unhealthy foods, dietary intake and risk factors for chronic disease. For example, a survey in Xi Hu District, Hangzhou, China found that 42% of the total food outlets in the district provided food delivery services. Of all the food outlets, fast-food restaurants comprised 66% of these providers, potentially increasing the likelihood of exposure to unhealthy food choices [47
]. Moreover, a study of 1220 university students in Beijing, China found that a high frequency of online delivery food consumption was associated with a preference for discretionary foods (high fat and high sugar foods), physical inactivity and high body mass index [48
]. Consumption was not measured in the current study to draw comparisons. Despite this, geographical areas were selected with high concentrations of young people as they are the predominate users of online food delivery. With a majority of food on these platforms classified as discretionary, our data indicates that young people have increased accessibility to these unhealthy choices, thereby increasing their risk for excess weight gain and obesity [4
]. Although, whether there is a casual relationship between neighborhood accessibility to fast-food outlets and obesity remains a topic for debate [49
]. OFD’s are furthermore, disrupting the traditional neighborhood food environment and studies have yet to take this into consideration. As OFD’s continue to change accessibility to fast-food and potential consumer behaviors, further research must assess whether there is an association with risk factors for chronic diseases, like obesity amongst young consumers.
A strength of this study is the independent evaluation of the healthiness of food outlets on Uber Eats using the FES. On Uber Eats food outlets were classified as ‘healthy’. Poelman et al. evaluated meal delivery options in three international cities using the pre-defined keywords set by the food outlets [16
]. Limited evidence was found for socioeconomic differences of ‘healthy’ options within the three cities. However, this study did not independently assess the healthiness of food outlets. Our evaluation demonstrated most food outlets that were classified as ‘healthy’ on Uber Eats were unhealthy according to the FES. This unhealthy score was further supported by our classification of popular menu items as mostly discretionary from these food outlets. Despite this, we did not evaluate the nutritional quality of the full menu and we used a conservative approach to the classification of discretionary based on limited information. For instance, in the absence of nutrition information, a menu item was counted as core food. As such, popular dishes such as Pad Thai were counted as core food, but, are likely to be discretionary as they are commonly high in energy (856 kJ/100 g), and sodium (527 mg/100 g) [50
]. Therefore, it is likely that we have overestimated the proportion of core foods.
There are further limitations to this study that should be acknowledged. We searched and extracted publicly available data from Uber Eats, the market-leading company and most popular online food delivery platform for young people in Australia and New Zealand. However, there are other online food delivery platforms with large usage (e.g., in Australia, Menulog® and Deliveroo® and in New Zealand, Just Eat®). Thus, we may have excluded key food outlets as some may only be affiliated with one online food delivery platforms. Furthermore, the Sydney and Auckland data were not collected over the same period and this may affect comparison analysis. We extracted data in Sydney and Auckland during periods of no government restrictions due to the COVID-19 pandemic (excluding international travel and border restrictions). The Sydney data was collected between 9 February to 25 February 2020 before any stay at home, personal movement or gathering restrictions. The Auckland data was collected between 23 June until 31 July 2020. During this time, the New Zealand government was enforcing COVID-19 Alert Level 1, which enforced no restrictions on personal movement or on gatherings. Nonetheless, the COVID-19 pandemic has possibly influenced people’s dietary intake; however, data is not available. Additionally, the geographical delivery distance was calculated based on road distance by car which may have been a longer route than by bicycle. The definition of the most popular food outlets and most popular menu items were assumed to mean the most popular based on customer purchasing and ratings. Evaluating the most popular food outlets may not be representative of all food outlets on Uber Eats; however, this data potentially gives a better indication of what consumers purchase and consume through the online delivery service. The proprietary Uber Eats algorithms for most popular food outlets and menu items are not made publicly available.