Skip to main content

Nutritional quality and consumer health perception of online delivery food in the context of China

Abstract

Background

Today, the popularization of mobile internet technology has enabled the public’s need for food convenience and diversity arising from modern fast-paced lifestyles to be met at a relatively low cost. The digital age of the restaurant industry has arrived. Online food delivery (OFD) is rapidly developing globally. However, the public’s awareness of the nutritional quality of food through OFD and their knowledge of dietary nutrition remain to be investigated.

Methods

In the context of China, this study attempts to evaluate the nutritional quality of best-selling OFD set meals (i.e., meal combos) based on the current official Chinese dietary guidelines 2022. It accomplishes this by collecting data on popular OFD restaurants among consumers in 115 Chinese universities from the restaurants’ delivery addresses. Moreover, 20,430 valid questionnaires were collected online from undergraduates, graduate students, and other young groups aged 18–30 throughout China for descriptive analysis to investigate consumers’ perceptions of the nutritional quality of food through OFD and its health impact.

Results

The results of the nutritional quality evaluation of the OFD set meals ranged widely from 15 to 85, with a mean of 36.57 out of a possible maximum score of 100; and 89.56% scored less than 50. The nutritional quality of OFD foods was thus generally low. The nutritional quality of foods was negatively correlated with their popularity among consumers.

Conclusions

Young OFD consumers generally paid low attention to dietary nutrition knowledge and seldom paid attention to nutritional quality when choosing OFD foods while the nutritional quality of OFD foods was generally low. Respondents subjectively reported that long-term consumption of OFD food caused weight gain, increased blood lipids, and gastrointestinal discomfort. They thought that the reason might be excessive oil, salt, and sugar in the food, while ignoring the balance between different types of food.

Peer Review reports

Background

The rapid development of the new “Internet Plus” economic form and the increase in broadband penetration has promoted the continuous expansion of electronic transactions across the world [1,2,3]. Online services are gaining popularity due to the convenience of electronic transactions, the wide range of suppliers, and the expansion of delivery services [4, 5]. As a new form of food consumption that is rapidly developing worldwide, online food delivery (OFD) provides consumers with online food ordering and delivery services, thereby changing traditional food production and retail practices. While solving the problem of time cost for individuals and families in food acquisition and preparation, OFD has also gradually changed consumer dietary consumption patterns. In particular, OFD has become more popular in the midst of the COVID-19 pandemic [6,7,8,9]. For example, although the size of the restaurant industry in China did not change significantly from 2019 to 2021, the size of OFD increased by 61.62% in the same time frame. In addition, the penetration rate of OFD increased from 3.87% in 2015 to 19.92% in 2021 [10]. In 2021, there were 544 million OFD users in China [3], and more than 40% of restaurants in China provide both online and in-person food services [11].

The global OFD market will reach USD 339.3 billion by 2022, and it is further estimated that the global OFD market will see its average annual growth rate remain at 8.28% from 2022 to 2026 [12]. The rise of OFD has greatly changed the food environment,Footnote 1 triggering changes in the practices of food production, transportation, and consumption worldwide. Consumers are increasingly buying food through online platforms, which has partially replaced traditional home cooking or dine-in patterns.Footnote 2

However, OFD may have negative effects. For example, by saving time spent on food shopping and home cooking, OFD may also reduce physical activity time, resulting in an increase in health problems associated with sedentary lifestyle [8, 13, 14]. Moreover, due to lack of information or labeling, it is difficult to guarantee the nutritional quality of OFD food [15,16,17], not to mention meeting the individualized nutritional needs [18, 19]. These may lead to a negative impact on public health. The increasing prevalence of chronic diseases in younger age groups due to dietary and nutritional health problems has become a widespread social problem in countries including China [20,21,22,23]. Therefore, it is of essential importance to investigate the nutritional value of OFD food and its impact on public health, especially on the risk of chronic diseases. However, only very few reports exist on this topic to date. It is of particular relevance to study this topic in China given the rapid development and huge market size of its OFD market.

According to Statista [12], the global OFD market will reach USD 339.3 billion by 2022, while China alone will account for USD 158.1 billion, equivalent to 46.60% of the global market. In other words, China has the largest OFD market, the greatest young consumer groups, and also the largest group of undergraduates and graduate students in the world. It is the uniqueness that other countries may not have. Moreover, due to the uncertainty of the COVID-19 pandemic, and more importantly, the convenience and relatively low prices of food ordered online, it is foreseeable that the online food delivery industry will develop faster in China in the future. In this sense, it is unique, forward-looking and representative to study the nutritional quality of OFD foods in China. In general, in addition to the special OFD foods for special groups, the OFD foods in western developed countries are also standardized produced and processed as in China. Objectively, the nutrition of OFD foods is difficult to effectively meet the health needs of the most consumer groups. Therefore, this study is representative to some extent, and the research conclusions have certain reference value for other countries. Nevertheless, the conclusions of this study are merited of greater reference value to China due to the differences in dietary structure and culture among countries in the world.

In the context of OFD’s rapid development and high penetration rate in China, this study aims to evaluate the nutritional quality of popular OFD foods. We analyze the best-selling OFD set meals of the 345 most popular OFD restaurants delivering to addresses near 115 different universities across China. Moreover, a survey was conducted among undergraduates, graduate students, and other young groups aged 18–30 to investigate consumers’ perception of the low nutritional quality of OFD food and analyze its health impact.

Literature review

In the last few decades, rapid economic development and the need for convenience have led to a rapid global rise of food away from home (FAFH),Footnote 3 including dining out, takeaways, OFD, and other ways of preparing or consuming food outside of home [24]. This has raised concerns regarding the relationship between FAFH quality and public health. Lachat et al. (2012) [25] and Wallard-Cole et al. (2021) [24] concluded that FAFH led to increased intakes of energy, total fat, saturated fat, and sodium, as well as decreased micronutrient intake among consumers, and argued that the nutritional quality of FAFH generally did not meet the daily nutritional needs of consumers.

OFD is one of the most important ways through which FAFH has developed rapidly worldwide. Both the size of OFD users and the scope of influence OFD has on the food landscape have attracted the attention of scholars. Young people are the main users of OFD globally [26]. In the US, Canada, and France, consumers aged 18–34 make up more than one-third of all OFD consumers [12]. In Australia and New Zealand, more than 25% of OFD consumers are young people aged 15–34 [27]. Examining a Malaysian context, Eu and Sameeha (2021) [28] reported that OFD consumers were mainly college students aged 19–29. In China, more than 50% of OFD consumers are young people aged 18–30 [29]. Moreover, a survey on OFD conducted in China showed that 90.48% of the students had used OFD services and 92% of the restaurants around the university had joined online platforms designed to facilitate OFD [30].

Meanwhile, the impact of OFD on health has attracted great interest from scholars. The overall conclusion is that food through OFD cannot meet individuals’ nutritional needs. For example, Horta et al. (2021) [31] investigated online platforms where OFD is hosted and found that most restaurants provided a large number of pre-made foods and beverages without sufficient customization to fit individual needs. Partridge et al. (2020) [5] and Brar and Minaker (2021) [18] also found that most OFD foods popular with consumers were from takeout franchises with standardized production, which did not include much nutritional customization. Likewise, Stephens et al. (2020) [14] suggested that standardized online ordering of fast food similar to pizza was popular among OFD consumers in the US. Horta et al. (2022) [19] found that traditional meals and pasta set mealsFootnote 4 were the food items most frequently pushed to consumers by Brazilian OFD platforms.

In order to further verify the performance that the nutrition of OFD foods is difficult to effectively meet people’s health needs, scholars have conducted a series of studies on this. For example, the “Ghost kitchensFootnote 5” style production and processing mode [32], resulting in the increasing and serious public health problems [4]. Zang et al. (2018) [33] found that the low nutritional quality of FAFH was manifested in increased intake of energy, fat, and carbohydrates by consumers. Goffe (2020) [15] pointed out that the convenient meals available via OFD ordering platforms popular with the global public were generally characterized by high energy and low nutritional quality. Based on data from three countries, Poelman et al. (2020) [16] suggested that the majority of foods through OFD were unhealthy, and that consumers living in communities with lower socioeconomic levels only had access to a smaller proportion of healthy food types. Partridge et al. (2020) [5] used data from two international cities to evaluate the characteristics and nutritional quality of foods on OFD platforms, concluding that the most popular foods on the platforms were unhealthy. Brar and Minaker (2021) [18] also reported that foods available on OFD platforms in Canada were of low nutritional quality and did not meet the requirements of healthy dietary guidelines. After assessing the nutritional quality and marketing attributes of food on Australian OFD platforms, Wang et al. (2021) [17] speculated that OFD platforms promote unhealthy food, and strongly suggested scholars to further conduct specific research on the nutrition of OFD foods. Similarly, Keeble et al. (2020) [34] emphasized the necessity to investigate how OFD affects dietary patterns and public health in their research.

Moreover, some studies have investigated specific health problems caused by changes in the food environment as a result of OFD. For example, FAFH, which is closely supported by OFD, has been shown to be generally high in calories, added sugar, saturated fat, salt, and low in nutritional value [26, 35,36,37,38]. These food characteristics have been proven as key risk factors for chronic diseases such as obesity, high cholesterol, diabetes, and hypertension [20,21,22,23]. Nago et al. (2014) [39] and Wellard-Cole et al. (2018) [40] also reported a positive correlation between the degree of weight gain and the frequency of FAFH consumption. McCrory et al. (2019) [41] believed that the rising obesity rate is inextricably linked to the popularity of FAFH. Moreover, Janssen et al. (2018) [42] and Dana et al. (2021) [43] suggested that the low-nutrient food through OFD is a key factor leading to overweight and obesity. Stephens et al. (2020) [14] and Horta et al. (2022) [19] pointed out that long-term reliance on OFD may lead to chronic diseases such as obesity, hypertension, and diabetes.

Numerous studies have discussed the public health issues caused by food through OFD. However, Stephens et al. (2020) [14], Partridge et al. (2020) [5], and Keeble et al. (2020) [34] pointed out that despite the rapid increase in public dependence on OFD, few objectives and generally accepted research exist demonstrating the health impact of food through OFD from either individual or public health perspectives. Research on the nutritional quality of meals that focuses on consumers in the context of Chinese OFD platforms is even more scarce despite the fact that China has the largest OFD market in the world.

This paper attempts to fill the gaps in the above literature. Considering that the main users of OFD in China are young people [29], the best-selling OFD set meals from 345 most popular OFD restaurants delivering to consumers on or near 115 different university campuses in China were used as our sample. Different from previous studies, the efforts and contributions of this paper are as follows: Based on the background of rapid development, large scale, large number of users and high penetration rate of OFD in China, we evaluate the nutritional quality of OFD foods based on the dietary guidelines published by the Chinese Nutrition Society, which is believed to be the first study in this field. Moreover, an online survey was conducted among undergraduates, graduate students, and other young groups aged 18–30 to investigate consumers’ perception of the nutritional quality of OFD food and summarize its health impact, which is first to use China as a case.

Methods

Data collection and nutritional quality assessment of OFD food

Selection of OFD platforms

One objective of this study is to evaluate the nutritional quality of foods available on Chinese OFD platforms. Food on the “Meituan” platform was used to evaluate the nutritional quality of OFD food. Founded in 2010, Meituan is one of the two OFD titans in China. According to the 2020–2021 Research Report on Food Delivery Industry Development in China [10] and Meituan Annual Financial Statements (2017–2021) [44] and as shown in Table 1, Meituan’s share of China’s OFD market increased from 62.42% in 2017 to 75.17% in 2021, with an average annual increase of 3.17%.

Table 1 OFD market size in China, and Meituan’s market share (100 million yuan, %)

Selection of OFD ordering locations and foods

Based on the findings from previous studies on main OFD consumer groups, young people aged 18–30, mainly students, are chosen as respondents for the study. A total of 115 Chinese universities, including Peking University, Tsinghua University, University of Science and Technology of China, and Fudan University, were selected as our data collection basis. The top three restaurants with the highest OFD monthly sales (each received over 10,000 orders) to each university were selected resulting in a total of 345 restaurants. The best-selling set meal from each selected restaurant was used as a sample for nutritional quality evaluation.

To ensure data integrity and consistency, and considering the usual meal time among Chinese consumers, all data were collected from the 345 restaurants including only lunch time (11:30–13:00) and dinner time (17:30–18:30) from May 01 to June 30, 2022. These best-selling set meals of the selected restaurants were sorted for types and weight and assessed for nutritional quality.

Nutritional quality evaluation method

Every country or region has different dietary nutrition standards. For example, a total of 20 countries or regions have published nutrient recommendations for milk and dairy products, and the recommended values in Asian countries are generally lower than those in Europe, America, and Oceania [45]. Unlike studies in other countries that evaluated the nutritional quality of OFD food [18, 46], the evaluation in this study is based on the Dietary Guidelines for Chinese Residents (2022) (referred to as the Guidelines hereafter). The Guidelines were developed by the Chinese Nutrition Society after drawing on the dietary guidelines in other countries and translating the existing evidence on dietary nutrition into food-based dietary guidelines based on the reality of China. The goal is to help individuals maintain health and reduce the incidence of nutrition-related diseases. They are more in line with the characteristics and changing trends of Chinese citizens’ dietary structure and the reality of food production and supply in China. Using the Chinese Guidelines can avoid the bias caused by using the nutritional quality standards of other countries.

According to the Guidelines, the 12 food items that Chinese people need on a daily basis and their daily recommended intake are shown in Table 2. Following the scoring methods used by Reedy et al. (2018) [47] and Bar and Minaker (2021) [18] for the US Healthy Eating Index-2015 (HEI-2015), a maximum total score of 100 was established for a perfect balance of the 12 food items and their recommended daily intake (Table 2). Food combinations were scored accordingly. A higher total score indicates a healthier food combination. Healthier food combinations mean better balanced meals containing items from various categories. The higher the content of a desirable food item in the set meal, the higher the component score. However, the opposite is true for some other items such as sodium and cooking oil; in other words, the lower the content of these items, the higher the overall score.

Table 2 Dietary nutrition evaluation criteria

The maximum scores for the 12 food items listed in Table 2 are not all the same. For example, the maximum score for poultry and meat (as a combined category) as well as aquatic products is 5, respectively, which are different from the maximum possible score of 10 for most other food items. There are two reasons for this. First, the Guidelines state that poultry, meat, and aquatic products are all animal products, and hence their nutritional components are complementary. Second, the maximum scores for total meats and seafood (as a combined category) and aquatic products set by HEI-2015 are also 5 for each category.

In addition, to evaluate nutritional quality, the following principles were used:

  • If a food item is present in the menu without content description, based on the principle of conservative estimation, it is assumed that the criterion is met and a corresponding score is assigned (for example, if “a serving of vegetables” was stated in the menu, a score of 10 would be assigned to “vegetables”);

  • If there is no set meal in the menu, the top three best-selling food items in the menu is selected and combined for nutritional quality evaluation;

  • If the text description in the menu does not match the picture, the text description prevails;

  • The contents of sodium and edible oil in the food are determined using Boohee.Footnote 6 Specifically, the content of edible oil can be estimated by calculating the sum of saturated, trans, monounsaturated, and polyunsaturated fats. If the content of sodium or edible oil cannot be determined in the software, the median score for that item, i.e., 5, is assigned.

Online survey

Questionnaire design

On the basis of previous qualitative research [9, 28, 46, 48], an online questionnaire was designed to evaluate current OFD consumption status, consumers’ perception of OFD food nutritional quality, and how OFD affects consumers’ health. The questionnaire contains two parts. The first part covers respondent demographics, such as gender, age, education, marital status, personal and family income, occupation, and the amount of OFD expenditure. The second part focuses on how respondents make OFD food choices, their nutritional and dietary needs, their perception of the nutritional quality of OFD food, and their perception of health after OFD food consumption. The detailed questionnaire contents are presented in the online supplementary material (see Additional file 1).

A small pilot test was first conducted to check the quality, accuracy, and readability of the questionnaire. The formal large-scale survey was conducted by creating an online link on a website and sharing the link via a professional marketing firm, which includes venues such as social media. Respondents’ informed consent was obtained on the first page of the questionnaire before commencement of data collection.

Sample demographics

The respondents of this paper must be the consumers with the experience of buying and consuming OFD food. According to this, and the questionnaires submitted by the respondents without such requirements are rejected. Table 3 shows the sample demographics of the survey. A total of 20,430 valid online questionnaires were collected from undergraduates, graduate students, and other young consumers aged 18–30. The majority of the respondents (87.37%) lived in cities of various sizes, which is consistent with the fact that OFD is more popular in urban than in rural areas in China [28, 43, 49]. Students, company employees, and public institution employees accounted for 34.51%, 30.25%, and 12.92% of the sample, respectively. Moreover, more than 80% of the respondents had a bachelor’s degree or above. In addition, 81.75% of the respondents had a personal pre-tax annual income of less than 150,000 yuan.

Table 3 Demographics of respondents

Results

Results of nutritional quality evaluation of OFD foods

The 345 OFD set meals comprised 143 rice set meals (41.45%), 51 porridge and pastry set meals (14.78%), 49 crayfish and barbecue set meals (14.20%), 38 fast hot pots set meals (11.01%), 25 rice noodles and wheaten food set meals (7.25%), 13 fried chicken and skewers set meals (3.77%), 13 salad set meals (3.77%), and 13 pizzas and hamburgers set meals (3.77%).

The nutritional quality evaluation of three example OFD set meals is given in Table 4. Out of a maximum score of 100, the total score of the three OFD set meals ranged widely from 15 (crispy fried chicken set meal) to 85 (beef and chicken breast salad set meal), with a mean of 36.57 out of 100. In particular, as Fig. 1 displays, of all the set meals considered in this study, 65.05% scored below 40, and 89.56% scored below 50. It is thus clear that most OFD set meals have poor nutritional quality falling far below recommended values. They lacked fruit, milk and dairy products, aquatic products, whole grains and beans, soybeans and nuts, and eggs, and were high in sodium and cooking oils. The only food items with high scores were poultry and meat, and cereals.

Table 4 Nutritional quality of three example meals through OFD evaluated based on the Guidelines
Fig. 1
figure 1

Distribution of nutritional quality scores of OFD foods (% in total sample)

Figure 2 shows the nutritional quality scores of different meals ranked according to frequency of purchase. In particular, “salads”, which ranked seventh in terms of frequency of purchase, scored the highest in nutritional quality. “Rice meals” and “porridge and pastry” ranked first and second in terms of purchase frequency, together accounting for more than 50% of the total sampled meals. However, both had a nutritional quality score of less than 40. This suggests that the OFD foods consumed by more than half of the consumers did not meet the Guidelines’ dietary nutritional recommendations.

Fig. 2
figure 2

Nutritional quality scores of OFD meal types ranked by purchase frequency

Online survey results

Consumer perception of nutritional quality

Based on the online survey results, the popularity of the 13 OFD meal types is illustrated in Fig. 3. Obviously, “rice meals” were the most popular, accounting for 57.56% of the sample. This is in line with the data collected from the OFD platform reported in this study. However, as Fig. 2 suggests, the mean nutritional quality score of this meal type was only 36.14, which was 33.30 points lower than the highest score, which was earned by “salads” (Fig. 2). Because “milk tea and desserts,” which ranked second in popularity, are generally not considered a daily meal type, data were not collected for this category from the OFD platform. Therefore, the nutritional quality of “milk tea and desserts” was not evaluated in this study. However, according to Li and Yang (2017) [50] and Zheng (2021) [51], milk tea is generally an unhealthy food. The nutritional quality scores of “pizzas and hamburgers,” “fried chicken and skewers,” and “crayfish and barbecue,” which respectively ranked third, fourth, and fifth, had nutritional scores of 32.78, 29.58, and 27.43, far from meeting the Guidelines’ dietary nutritional recommendations. In contrast, “salads,” the meal type with the highest mean nutritional quality score shown in Fig. 2, had a very low purchase frequency of 7.34%. It ranked 11th in the list of 13 options in Fig. 3, which is consistent with the data collected from the OFD platform.

Fig. 3
figure 3

Proportion of popular OFD meal types based on online survey data (%)

As shown in Fig. 4, when making OFD food choices, 52.91% of the respondents paid most attention to taste, followed by price and delivery speed, and lastly nutritional value. This shows that consumers had low concern for dietary nutrition and health. In addition, respondents’ level of attention to dietary nutrition knowledge is shown in Fig. 5. Only 12.97% of respondents paid attention to this knowledge often and 33.43% occasionally paid attention. The majority either rarely or paid no attention at all. This result may indirectly indicate that the general public in China has not been too concerned about dietary nutrition. Young people in China have a low interest in acquiring, understanding, and using dietary nutrition knowledge related to their health. In addition, another possible reason for this result may be that young consumers tend to think they are overall healthy and thus care little about acquiring or using this knowledge.

Fig. 4
figure 4

Concerns when ordering food online (%)

Fig. 5
figure 5

Level of attention to dietary nutrition knowledge (%)

Consumer health perceptions

The online questionnaire also included consumer self-evaluated physical health changes after long-term consumption of food through OFD. As shown in Fig. 6, 57.46% of the respondents believed that long-term consumption of food through OFD led to their weight gain. Nearly 50% reported increased blood lipids and gastrointestinal discomfort. Only 17.47% believed that long-term consumption of food through OFD had no effect on their physical health. Therefore, this study supports the notion that popular food ordered through OFD does not meet consumers’ daily nutritional needs. Long-term consumption of food through OFD may have a negative health impact, and should be included in the public discussion on how food through OFD may be related to chronic diseases, such as obesity, hyperlipidemia, hypertension, and type 2 diabetes.

Fig. 6
figure 6

Perceived health changes after long-term consumption of OFD food (%)

In addition, the respondents who believed that consuming food through OFD had an impact on their health were further asked about the signs and reasons of such a health impact (Fig. 7). The most reported reason was excessive cooking oil (79.00%), followed by high salt content (63.44%), high sugar content (50.32%), and improper balances of different types of food (30.64%). Obviously, the problem of high oil, salt, and sugar intake, which can lead to chronic diseases such as obesity, hyperlipidemia, and hypertension [52, 53], is of concern to consumers. It indicates that consumers are well-educated in this respect. However, the fact that of food ordered through OFD has improper nutrition balances has not been given adequate attention by young consumers.

Fig. 7
figure 7

Reasons consumers believe that food through OFD does not meet health standards (%)

Robustness test

In order to ensure the robustness of the cross-sectional study method and the representativeness of samples, this paper also collected data of OFD food around other types of ordering places. Similarly, using the Dietary Guidelines for Chinese Residents (2022) as the standard to evaluate the nutritional quality of OFD food by cross-sectional research method. The most popular shopping malls in 20 citiesFootnote 7 in China were selected as the OFD ordering places. The data of set meals from the top three restaurants with monthly sales volume around each shopping mall were selected as samples, that is, the set meals with the largest sales volume in 60 restaurants were selected as samples to evaluate the nutritional quality. The results show that the average score of nutritional quality assessment of the 60 online meals was 37.65 out of 100, among which 63.85% of the meals scored less than 40 out of 100, 89.05% of the meals scored less than 50 out of 100. The types of meals were also relatively single. It is not difficult to find that still be concluded that the nutritional quality of OFD food is generally low after selecting different types of places for ordering OFD food.

Conclusions and policy implications

This study uses the best-selling set meals of the 345 most popular restaurants surrounding 115 universities in China as the basis to gauge the nutritional quality of food through OFD. The study uses data obtained from the super-leading OFD platform provider Meituan and creates the nutritional valuation based on China’s Dietary Guidelines for Chinese Residents (2022). A follow-up online survey was administered among undergraduates, graduate students, and other young groups aged 18–30. The survey investigated consumer choices of food through OFD, as well as their perception of the nutritional quality and health impact of food ordered through OFD. We find that foods acquired through OFD generally had low nutritional quality scores. This is consistent with the findings of Bar and Minaker (2021) [18] regarding the nutritional quality of foods though OFD in North America. Meal types popular with young consumers had low nutritional quality, far from meeting the recommendations of the Guidelines. Relatedly, meal types with high nutritional quality were not common choices for young consumers. Furthermore, the vast majority of young consumers only paid attention to the taste and price of food, but ignored the nutritional value when using OFD. They generally had low awareness and might even lack basic appreciation of dietary nutrition and health. Weight gain, increased blood lipids, and gastrointestinal discomfort were the most common physical health changes perceived by young consumers after long-term consumption of food through OFD.

Our results may provide insights into improving the nutritional quality of food through OFD. The implications can be on both the supply side and the demand side [54]. Like in most countries in the world, a restaurant or food service usually does not make all their food items available for online ordering. For food providers, reducing the amount of unhealthy food and increasing the amount of healthy food offered through the online platform might be an essential component to improve the nutritional quality of food through OFD. However, if such an action reduces profit, food providers may not be willing to commit. This will need the effort from the demand side. Consumer education campaign can promote consumer awareness and knowledge about their nutritional health and reduce the intake of unhealthy or imbalanced food. As far as China is concerned, based on the fact that dietary nutrition and health knowledge has not received widespread attention from young consumers, efforts should be dedicated to this particular group to promote the Dietary Guidelines for Chinese Residents (2022). Many individuals order food through OFD due to its convenience, thus, increasing the convenience of healthy food preparation for consumers might assist consumers making healthier choices. More drastic approaches that may encounter some level of pushbacks but can nevertheless be powerful include limiting the amount of unhealthy food by each customer per order.

Several areas of extension exit. First, an immediate venue is to apply our framework to the broader public to include consumers of all ages. Second, consumer heterogeneity such as age and gender may lead to large variation in their food ordering and nutritional health response to OFD. Further work to explore this heterogeneity and establish situational context of OFD is likely useful. Third, we used respondents’ self-reported health status to describe the impact of food through OFD. Additional investigation can consider tying food nutritional data with the amount and variety of ordered food through a consumer diary. Finally, one can apply the framework and test the general applicability of the conclusions in this study in a non-Chinese context.

Availability of data and materials

The datasets used during the current study are available from the corresponding author on reasonable request.

Notes

  1. Food environment is defined as a collection of environmental, opportunity, physical, economic, policy, and sociocultural factors that affect food choices and individual nutritional status [55].

  2. Penetration rate is the ratio of the target product or service to the product or service that the existing market may have, and is one of the methods to calculate the influence of a product or service. For example, Yeo and Kim (2019) [56] assessed the global smartphone penetration rate.

  3. FAFH is defined as food prepared outside the home, and includes food that is eaten out, ordered in (taken out), and/or delivered [57].

  4. In China, except liquid food and drinks, meal combos are often presented in a single container. As such, a meal combo is more commonly known as set meals in China.

  5. Ghost kitchens, also known as cloud or dark kitchens, are restaurants that prepare meals solely for the delivery market, with no dine-in area or service staff [4].

  6. Boohee is a popular App in China providing consumers with information such as nutrient calculation, calorie calculation, and diet analysis.

  7. The top 20 cities in China were selected according to the 2022 City Business Charm Ranking released by CBN—New First-Tier Cities Research Institute (2022) [58]. Available at: https://view.inews.qq.com/wxn/20220608A049WY00?(2022–06-08).

Abbreviations

OFD:

Online Food Delivery

FAFH:

Food Away from Home

HEI-2015:

Healthy Eating Index-2015

CNNIC:

China Internet Network Information Center

References

  1. Gunden N, Morosan C, DeFranco A. Consumers’ intentions to use online food delivery systems in the USA. Int J Contemp Hosp Manag. 2020;32(3):1325–45.

    Article  Google Scholar 

  2. Cheng CC, Chang YY, Chen CT. Construction of a service quality scale for the online food delivery industry. Int J Hosp Manag. 2021;95: 102938.

    Article  Google Scholar 

  3. China Internet Network Information Center (CNNIC). (2022). Statistical Report on Internet Development in China. https://baijiahao.baidu.com/s?id=1725995360605237824&wfr=spider&for=pc. Accessed 28 Feb 2022.

  4. Li C, Mirosa M, Bremer P. Review of online food delivery platforms and their impacts on sustainability. Sustainability. 2020;12(14):5528.

    Article  Google Scholar 

  5. Partridge SR, Gibson AA, Roy R, Malloy JA, Raeside R, Jia SS, Singleton AC, Mandoh M, Todd AR, Wang T, Halim NK, Hyun K, Redfern J. Junk Food on Demand: A Cross-Sectional Analysis of the Nutritional Quality of Popular Online Food Delivery Outlets in Australia and New Zealand. Nutrients. 2020;12:3107.

    Article  PubMed Central  Google Scholar 

  6. Oncini F, Bozzini E, Forno F, Magnani N. Towards food platform? An analysis of online food provisioning services in Italy. Geoforum. 2020;114:172–80.

    Article  Google Scholar 

  7. Gao X, Shi X, Guo H, Liu Y. To buy or not buy food online: The impact of the COVID-19 epidemic on the adoption of ecommerce in China. PLoS ONE. 2020;14(8): e07900. https://doi.org/10.1371/journal.pone.0237900.

    Article  CAS  Google Scholar 

  8. Li X, Li J, Qing P, Hu W. Covid-19 and the change in lifestyle: bodyweight, time allocation, and food choices. Int J Environ Res Public Health. 2021;18(19):10552.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Lu M, Wang R, Li P. Comparative analysis of online fresh food shopping behavior during normal and COVID-19 crisis periods. British Food Journal. 2022;124(3):968–86.

    Article  Google Scholar 

  10. China Hotel Association, Ali New Service Research Center, Ele.me Training and Learning Center, & Keruyun. 2020–2021 Research Report on Food Delivery Industry Development in China. 2021. http://www.aliresearch.com/ch/information/informationdetails?articleCode=243631150608814080&type=%E6%96%B0%E9%97%BB.

  11. Huaan Securities. In-depth Report on Online Media Industry. 2021. https://download.csdn.net/download/sysocc/81425507.

  12. Statista. Online Food Delivery in the United States. 2022. https://www.statista.com/outlook/374/109/online-food-delivery/united-states.

  13. Dutra GF, Kaufmann CC, Pretto ADB, Albernaz EP. Sedentary lifestyle and poor eating habits in childhood: a cohort study. Ciencia & Saude Coletiva. 2016;21(4):1051–9. https://doi.org/10.1590/1413-81232015214.08032015.

    Article  Google Scholar 

  14. Stephens J, Miller H, Millitello L. Food delivery Apps and the negative health impacts for Americans. Front Nutr. 2020;7:14.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Goffe L, Uwamahoro NS, Dixon CJ, Blain AP, Danielsen J, Kirk D, Adamson AJ. Supporting a healthier takeaway meal choice: creating a universal health rating for online takeaway fast-food outlets. Int J Environ Res Public Health. 2020;17:9260. https://doi.org/10.3390/ijerph17249260.

    Article  PubMed Central  Google Scholar 

  16. Poelman MP, Thornton L, Zenk SN. A cross-sectional comparison of meal delivery options in three international cities. Eur J Clin Nutr. 2020;74(10):1465–73.

    Article  PubMed  Google Scholar 

  17. Wang C, Korai A, Jia SS, Allman-Farinelli M, Chan V, Roy R, Raeside R, Phongsavan P, Redfern J, Gibson AA, Partridge SR. Hunger for home delivery: cross-sectional analysis of the nutritional quality of complete menus on an online food delivery platform in Australia. Nutrients. 2021;13:905.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Brar K, Minaker LM. Geographic reach and nutritional quality of foods available from mobile online food delivery service applications: novel opportunities for retail food environment surveillance. BMC Public Health. 2021;21:458.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Horta PM, Matos JDP, Mendes LL. Food promoted on an online food delivery platform in a Brazilian metropolis during the coronavirus disease (COVID-19) pandemic: a longitudinal analysis. Public Health Nutr. 2022;25(5):1336–45.

    Article  Google Scholar 

  20. Kant AK, Graubard BI. A prospective study of frequency of eating restaurant prepared meals and subsequent 9-year risk of all-cause and cardiometabolic mortality in US adults. PLOS ONE. 2018;13(1):e0191584. https://doi.org/10.1371/journal.pone.0191584.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, Mullany EC, Abate KH, Abbafati C, Abebe Z, et al. Health effects of dietary risks in 195 countries, 1990–2017: A systematic analysis for the global burden of disease study 2017. Lancet. 2019;393:1958–72.

    Article  Google Scholar 

  22. Taher AK, Evans N, El Evans C. The cross-sectional relationships between consumption of takeaway food, eating meals outside the home and diet quality in British adolescents. Public Health Nutr. 2019;22:63–73.

    Article  PubMed  Google Scholar 

  23. Jia P, Luo M, Li Y, Zheng J-S, Xiao Q, Luo J. Fast-food restaurant, unhealthy eating, and childhood obesity: a systematic review and meta-analysis. Obes Rev. 2021;22:1–27.

    Google Scholar 

  24. Wellard-Cole L, Davies A, Allman-Farinelli M. Contribution of foods prepared away from home to intakes of energy and nutrients of public health concern in adults: A systematic review. Crit Rev Food Sci Nutr. 2021;10:1–12.

    Google Scholar 

  25. Lachat C, Nago E, Verstraeten R, Roberfroid D, Van Camp J, Kolsteren P. Eating out of home and its association with dietary intake: a systematic review of the evidence. Obes Rev. 2012;13(4):329–46. https://doi.org/10.1111/j.1467-789X.2011.00953.x.

    Article  PubMed  CAS  Google Scholar 

  26. Bates S, Reeve B, Trevena H. A narrative review of online food delivery in Australia: challenges and opportunities for public health nutrition policy. Public Health Nutr. 2020;1:1–11.

    Article  Google Scholar 

  27. Roy Morgan Research. Meal delivery services double usage in only 18 months. 2020. Available online: https://www.roymorgan.com/findings/8270-food-delivery-services-september-2019-202002030451.

  28. Eu EZR, Sameeha MJ. Consumers’ perceptions of healthy food availability in online food delivery applications (OFD Apps) and its association with food choices among public university students in Malaysia. Front Nutr. 2021;8: 674427. https://doi.org/10.3389/fnut.2021.674427.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Meituan Research Institute. China Food Delivery Industry Development Report 2019 and the first half of 2020. 2020.

    Google Scholar 

  30. Yin Y, Hu J. The analysis of the advantages and disadvantages of the online food delivery phenomenon in universities and the research on the countermeasures—based on the empirical study of Jiangpu campus of Nanjing university of technology and its surroundings. Pop Stand. 2019;16:46–8.

    Google Scholar 

  31. Horta PM, Matos JDP, Rocha LL, Mendes LL. Digital food environment of a Brazilian metropolis: food availability and marketing strategies used by delivery apps. Public Health Nutr. 2021;24(3):544–8.

    Article  PubMed  Google Scholar 

  32. Granheim SI, Løvhaug AL, Terragni L, et al. Mapping the digital food environment: a systematic scoping review. Obes Rev. 2022;23: e13356.

    Article  PubMed  Google Scholar 

  33. Zang J, Luo B, Wang Y, Zhu Z, Wang Z, He X, Wang W, Guo Y, Chen X, Wang C, et al. Eating out-of-home in adult residents in Shanghai and the nutritional differences among dining places. Nutrients. 2018;10(7):951. https://doi.org/10.3390/nu10070.

    Article  PubMed Central  Google Scholar 

  34. Imamura F, Micha R, Khatibzadeh S, Fahimi S, Shi P, Powles J, Mozaffarian D. Dietary quality among men and women in 187 countries in 1990 and 2010: A systematic assessment. Lancet Glob Health. 2015;3:132–42.

    Article  Google Scholar 

  35. Donin AS, Nightingale CM, Owen CG, et al. Takeaway meal consumption and risk markers for coronary heart disease, type 2 diabetes and obesity in children aged 9–10 years: a cross-sectional study. Arch Dis Child. 2018;103:431–6.

    Article  PubMed  Google Scholar 

  36. Robinson E, Jones A, Whitelock V, Mead BR, Haynes A. (Over)eating out at major UK restaurant chains: Observational study of energy content of main meals. BMJ. 2018;363:1–8.

    Google Scholar 

  37. Robinson E, Marty L, Jones A, White M, Smith R, Adams J. Will calorie labels for food and drink served outside the home improve public health? BMJ. 2021;372: n40. https://doi.org/10.1136/bmj.n40.

    Article  PubMed  Google Scholar 

  38. McCrory M, Harbaugh A, Appeadu S, Roberts S. Fast-food offerings in the united states in 1986, 1991, and 2016 show large increases in food variety, portion size, dietary energy, and selected micronutrients. J Acad Nutr Diet. 2019;119:923–33. https://doi.org/10.1016/j.jand.2018.12.004.

    Article  PubMed  Google Scholar 

  39. Nago ES, Lachat CK, Dossa RA, Kolsteren PW. Association of out-of-home eating with anthropometric changes: a systematic review of prospective studies. Crit Rev Food Sci Nutr. 2014;54(9):1103–16. https://doi.org/10.1080/10408398.2011.627095.

    Article  PubMed  Google Scholar 

  40. Wellard-Cole L, Jung J, Kay J, Rangan A, Chapman K, Watson WL, Hughes C, Mhurchu CN, Bauman A, Gemming L. Examining the frequency and contribution of foods eaten away from home in the diets of 18-to 30-year-old Australians using smartphone dietary assessment (MYMeals): protocol for a cross-sectional study. JMIR Research Protocols. 2018;7: e24.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Janssen HG, Davies IG, Richardson LD, et al. Determinants of takeaway and fast-food consumption: a narrative review. Nutr Res Rev. 2018;31:16–34.

    Article  PubMed  Google Scholar 

  42. Dana LM, Hart E, McAleese A, et al. Factors associated with ordering food via online meal ordering services. Public Health Nutr. 2021;24:5704–9.

    Article  PubMed  Google Scholar 

  43. Keeble M, Adams J, Sacks G, Vanderlee L, White CM, Hammond D, Burgoine T. Use of online food delivery services to order food prepared away-from-home and associated sociodemographic characteristics: a cross-sectional, multi-country analysis. Int J Environ Res Public Health. 2020;17:5190. https://doi.org/10.3390/ijerph17145190.

    Article  PubMed Central  Google Scholar 

  44. Meituan-WHK3690. Financial statements. 2017–2020. http://stockpage.10jqka.com.cn/HK3690/.

  45. Chinese Nutrition Society. Dietary Guidelines for Chinese Residents (2022). 2022 https://www.cnsoc.org/notice/442220200.html

  46. Schnelbacher C, Behr J, Leonhauser IU. Potential of online food shopping. An opportunity to relieve mothers everyday life food routines. Science and Research. 2015;62(11):178–87.

    Google Scholar 

  47. Reedy J, Leman JL, Krebs-Smith SM, et al. Evaluation of the healthy eating Index-2015. Journal of The Academy Of Nutrition And Dietetics. 2018;118(9):1622–33.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Wang X, Wang Z, Ren Y, Zhang Y. Study on the purchase intention of fresh agricultural product in O2O mode. J Anhui Agric Sci. 2017;45(34):228–30.

    Google Scholar 

  49. Lau TC, Ng DCY. Online food delivery services: making food delivery the new normal. J Mark Adv Pract. 2019;1:62–77.

    Google Scholar 

  50. Li JL, Yang JS. Preference transfer, income effect and hidden cost of social-addictive consumption. Econ Perspect. 2017;7:74–87.

    CAS  Google Scholar 

  51. Zheng G. The influence of milk tea addiction on adolescents and its countermeasures. Tea Commun. 2021;48(2):348–52 373.

    Google Scholar 

  52. Lim SS, Vos T, Flaxman AD, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380:2224–60.

    Article  PubMed  PubMed Central  Google Scholar 

  53. World Health Organisation. Global Action Plan for the Prevention and Control of Noncommunicable Diseases. 2013–2020. https://www.who.int/nmh/events/ncd_action_plan/en/. (Accessed November 2019).

  54. Zheng Y, Wang L, Zhao S, Hu W. Meet the meatless: Demand for new generation plant-based meat alternatives, Applied Economic Perspectives and Policy. 2022. Forthcoming.

    Google Scholar 

  55. Downs SM, Ahmed S, Fanzo J, et al. Food environment typology: advancing an expanded definition, framework, and methodological approach for improved characterization of wild, cultivated, and built food environments toward sustainable diets. Foods. 2020;9:532.

    Article  PubMed Central  Google Scholar 

  56. Yeo HJ, Kim S-H. Mobile commerce consumer value disparity by generation gap: gift-giving case. J Theor Appl Inf Technol. 2019;97(17):4636–46.

    Google Scholar 

  57. Mcguire S, Todd JE, Mancino L, Lin B-H. The impact of food away from home on adult diet qualityERR-90, U.S. department of agriculture. Econ Res Serv. 2011;2(5):442–3. https://doi.org/10.3945/an.111.000679 Advances Nutrition.

    Article  Google Scholar 

  58. CBN - New First-Tier Cities Research Institute. 2022 City Business Charm Ranking. 2022. https://view.inews.qq.com/wxn/20220608A049WY00? (Accessed 2022–06–08).

Download references

Acknowledgements

The authors are grateful to the referees for their valuable comments and their helps on how to improve the quality of our paper.

Funding

The first two authors acknowledge support by the National Social Science Fund of China: Research on social co-governance of food safety risks and cross-border cooperative governance mechanism (grant number 20&ZD117).

Author information

Authors and Affiliations

Authors

Contributions

Xiaoting Dai and Linhai Wu jointly conceptualized the research study, planned the data collection and analysis, and interpreted data. Xiaoting Dai conducted data collection and data analysis, and drafted the initial manuscript. Linhai Wu and Wuyang Hu provided oversight and contributed to writing the manuscript. All authors have read and approved this manuscript.

Corresponding author

Correspondence to Linhai Wu.

Ethics declarations

Ethics approval and consent to participate

Ethical Approval was received from the Ethics Committee of Jiangnan University. All methods and procedures in this study were confirmed to the ethics guidelines of the Declaration of Helsinki and followed the ethical standards of the relevant guidelines and regulations. Respondents’ informed consent was obtained on the first page of the questionnaire before commencement of data collection.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

 Questionnaire contents.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dai, X., Wu, L. & Hu, W. Nutritional quality and consumer health perception of online delivery food in the context of China. BMC Public Health 22, 2132 (2022). https://doi.org/10.1186/s12889-022-14593-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-022-14593-9

Keywords