essay on street food and youth

Street foods are ready-to-eat foods and beverages prepared and/or sold by vendors or hawkers especially in the streets and other similar places.

They represent a significant part of urban food consumption for millions of low-and-middle-income consumers, in urban areas on a daily basis. Street foods may be the least expensive and most accessible means of obtaining a nutritionally balanced meal outside the home for many low income people, provided that the consumer is informed and able to choose the proper combination of foods.

In developing countries, street food preparation and selling provides a regular source of income for millions of men and women with limited education or skills.

Today, local authorities, international organisations and consumer associations are increasingly aware of the socioeconomic importance of street foods but also of their associated risks. The major concern is related to food safety, but other concerns are also reported, such as sanitation problems (waste accumulation in the streets and the congestion of waste water drains), traffic congestion in the city also for pedestrians (occupation of sidewalks by street vendors and traffic accidents), illegal occupation of public or private space, and social problems (child labour, unfair competition to formal trade, etc.).

The risk of serious food poisoning outbreaks linked to street foods remains a threat in many parts of the world. A lack of knowledge among street food vendors about the causes of food-borne disease is a major risk factor.

Although many consumers attach importance to hygiene in selecting a street food vendor, consumers are often unaware of the health hazards associated with street vended foods.

Mental health effects of poverty, hunger, and homelessness on children and teens

Rising inflation and an uncertain economy are deeply affecting the lives of millions of Americans, particularly those living in low-income communities. It may seem impossible for a family of four to survive on just over $27,000 per year or a single person on just over $15,000, but that’s what millions of people do everyday in the United States. Approximately 37.9 million Americans, or just under 12%, now live in poverty, according to the U.S. Census Bureau .

Additional data from the Bureau show that children are more likely to experience poverty than people over the age of 18. Approximately one in six kids, 16% of all children, live in families with incomes below the official poverty line.

Those who are poor face challenges beyond a lack of resources. They also experience mental and physical issues at a much higher rate than those living above the poverty line. Read on for a summary of the myriad effects of poverty, homelessness, and hunger on children and youth. And for more information on APA’s work on issues surrounding socioeconomic status, please see the Office of Socioeconomic Status .

Who is most affected?

Poverty rates are disproportionately higher among most non-White populations. Compared to 8.2% of White Americans living in poverty, 26.8% of American Indian and Alaska Natives, 19.5% of Blacks, 17% of Hispanics and 8.1% of Asians are currently living in poverty.

Similarly, Black, Hispanic, and Indigenous children are overrepresented among children living below the poverty line. More specifically, 35.5% of Black people living in poverty in the U.S. are below the age of 18. In addition, 40.7% of Hispanic people living below the poverty line in the U.S. are younger than age 18, and 29.1% of American Indian and Native American children lived in poverty in 2018. In contrast, approximately 21% of White people living in poverty in the U.S. are less than 18 years old.

Furthermore, families with a female head of household are more than twice as likely to live in poverty compared to families with a male head of household. Twenty-three percent of female-headed households live in poverty compared to 11.4% of male-headed households, according to the U.S. Census Bureau .

What are the effects of poverty on children and teens?

The impact of poverty on young children is significant and long lasting. Poverty is associated with substandard housing, hunger, homelessness, inadequate childcare, unsafe neighborhoods, and under-resourced schools. In addition, low-income children are at greater risk than higher-income children for a range of cognitive, emotional, and health-related problems, including detrimental effects on executive functioning, below average academic achievement, poor social emotional functioning, developmental delays, behavioral problems, asthma, inadequate nutrition, low birth weight, and higher rates of pneumonia.

Psychological research also shows that living in poverty is associated with differences in structural and functional brain development in children and adolescents in areas related to cognitive processes that are critical for learning, communication, and academic achievement, including social emotional processing, memory, language, and executive functioning.

Children and families living in poverty often attend under-resourced, overcrowded schools that lack educational opportunities, books, supplies, and appropriate technology due to local funding policies. In addition, families living below the poverty line often live in school districts without adequate equal learning experiences for both gifted and special needs students with learning differences and where high school dropout rates are high .

What are the effects of hunger on children and teens?

One in eight U.S. households with children, approximately 12.5%, could not buy enough food for their families in 2021 , considerably higher than the rate for households without children (9.4%). Black (19.8%) and Latinx (16.25%) households are disproportionately impacted by food insecurity, with food insecurity rates in 2021 triple and double the rate of White households (7%), respectively.

Research has found that hunger and undernutrition can have a host of negative effects on child development. For example, maternal undernutrition during pregnancy increases the risk of negative birth outcomes, including premature birth, low birth weight, smaller head size, and lower brain weight. In addition, children experiencing hunger are at least twice as likely to report being in fair or poor health and at least 1.4 times more likely to have asthma, compared to food-secure children.

The first three years of a child’s life are a period of rapid brain development. Too little energy, protein and nutrients during this sensitive period can lead to lasting deficits in cognitive, social and emotional development . School-age children who experience severe hunger are at increased risk for poor mental health and lower academic performance , and often lag behind their peers in social and emotional skills .

What are the effects of homelessness on children and teens?

Approximately 1.2 million public school students experienced homelessness during the 2019-2020 school year, according to the National Center for Homeless Education (PDF, 1.4MB) . The report also found that students of color experienced homelessness at higher proportions than expected based on the overall number of students. Hispanic and Latino students accounted for 28% of the overall student body but 38% of students experiencing homelessness, while Black students accounted for 15% of the overall student body but 27% of students experiencing homelessness. While White students accounted for 46% of all students enrolled in public schools, they represented 26% of students experiencing homelessness.

Homelessness can have a tremendous impact on children, from their education, physical and mental health, sense of safety, and overall development. Children experiencing homelessness frequently need to worry about where they will live, their pets, their belongings, and other family members. In addition, homeless children are less likely to have adequate access to medical and dental care, and may be affected by a variety of health challenges due to inadequate nutrition and access to food, education interruptions, trauma, and disruption in family dynamics.

In terms of academic achievement, students experiencing homelessness are more than twice as likely to be chronically absent than non-homeless students , with greater rates among Black and Native American or Alaska Native students. They are also more likely to change schools multiple times and to be suspended—especially students of color.

Further, research shows that students reporting homelessness have higher rates of victimization, including increased odds of being sexually and physically victimized, and bullied. Student homelessness correlates with other problems, even when controlling for other risks. They experienced significantly greater odds of suicidality, substance abuse, alcohol abuse, risky sexual behavior, and poor grades in school.

What can you do to help children and families experiencing poverty, hunger, and homelessness?

There are many ways that you can help fight poverty in America. You can:

• Volunteer your time with charities and organizations that provide assistance to low-income and homeless children and families.
• Donate money, food, and clothing to homeless shelters and other charities in your community.
• Donate school supplies and books to underresourced schools in your area.
• Improve access to physical, mental, and behavioral health care for low-income Americans by eliminating barriers such as limitations in health care coverage.
• Create a “safety net” for children and families that provides real protection against the harmful effects of economic insecurity.
• Increase the minimum wage, affordable housing and job skills training for low-income and homeless Americans.
• Intervene in early childhood to support the health and educational development of low-income children.
• Provide support for low-income and food insecure children such as Head Start , the National School Lunch Program , and Temporary Assistance for Needy Families (TANF) .
• Increase resources for public education and access to higher education.
• Support research on poverty and its relationship to health, education, and well-being.
• Resolution on Poverty and SES
• Pathways for addressing deep poverty
• APA Deep Poverty Initiative

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The 10 most popular types of street food in Moscow (PHOTOS)

These snacks make walking around Moscow even more interesting!

One of the symbols of Russian cuisine - bliny (pancakes) - are presented in Moscow in all their variety. You can try from classic savory bliny with caviar and sour cream, with minced meat, mushrooms or sweet ones with honey, cottage cheese, jam or apples, to the most exotic ones with sturgeon, game or lingonberries.

Where to try: ‘Teremok’, 'Grabli', 'Mari Vanna', 'Azbuka Vkusa'

2. Sandwiches

The most familiar Russian sandwiches are a piece of wheat or rye bread with sausage, salted fish or butter and cheese. Not so long ago, they were found only in canteens and buffets of theaters, but now, they appear in modern interpretations in menus of local cafes and restaurants. The basis for sandwiches can be almost anything: artisan bread, brioche bun, croissant or bagel. Eggs, fresh vegetables, pickles or sprouts, creamy, sweet and sour or berry sauces are added to traditional ingredients. Sandwiches in several layers are now also sweet - with fresh berries, fruit or jam.

Where to try: 'Shmak', 'Eggsellent', 'Prime', 'Vkusvill'

3. Pies, pastries & buns

'Kurniki' with meat and mushroom stuffing, meat ‘kulebyaka’, pies with cheese, cottage cheese, jam or apple jelly - you can buy them all at the city's street stalls. As well as all sorts of buns and ‘vatrushkas’ (pastry with cottage cheese). Tatar (‘echpochmaki’, ‘zur-belish’) and Asian pastries (‘samsa’) are also to many people's taste.

Where to try: 'Skalka', 'Bakhetle'

4. Ponchiki

Hot ‘ponchiki’ aka donuts with sugar icing in a paper bag are a childhood taste for many Muscovites. They are sold in kiosks in city parks, where families with children rush to on weekends. There are also now donut shops on crowded streets. One of the oldest establishments - ‘Ostankinskiye Ponchiki’ - is located in Ostankino and has been operating since 1953.

Where to eat: 'Ostankinskie Ponchiki', 'Te samye ponchiki' (VDNKh)

5. Chebureks

Crispy ‘chebureks’ with meat or cheese is a traditional dish of Crimean Tatars, which has long ago gained nationwide popularity. In the Soviet times, there were long waiting lines for ‘chebureks’. It's not a surprise, considering their thin appetizing dough, juicy stuffing and democratic price!

Where to try: 'CheburechnayaUSSR', ' Cheburechnaya Druzhba', 'Cheburechnaya N1'

6. Shawarma

Fried meat in lavash bread with vegetables is good as a nutritious snack and as a full lunch or dinner on the go. From fast food, which used to be sold in stalls at train stations and by the subway, the ‘shawarma’ has turned into a fashionable dish, which is often now included in many restaurant menus. You can try it in the classic version - with lamb or chicken, with onions, tomatoes, cucumbers, lettuce or cabbage and, in less familiar - with pomegranate seeds, with mozzarella, hummus, with mackerel or without meat at all, for example, with falafel.

Mexican cuisine has recently become especially popular in the city, so the usual ‘shawarma’ has been joined by more spicy variants: for example, burritos with salsa sauce. Fans of smaller forms choose tacos, which, aside from the classic fillings, are even prepared with porcini mushrooms and radish for the Moscow public.

Where to try: ‘Shawarma H@chu’, ‘Dark Side’, ‘Sangre Fresca’, ‘Tacobar’

Nobody can be surprised by the classic beef burger, which is why Moscow burger joints try to lure customers with less familiar variants: burgers on black buns with cherries, bacon and cheese, burgers with cod fillet filling or even vegetable meat.

Where to try: ‘Burger Heroes’, ‘BB&Burgers’, ‘Farsh’

A bun with sesame seeds, sausage with pickles, caramelized onions and mustard - it doesn't sound like the most diet-friendly dish, but it sure works up an appetite. Sold at street stalls and cafes, where chefs are happy to experiment with the size of the dish and ingredients, adding exotic ingredients like rabbit or crab sausages, fries and different sauces.

Where to try: ‘Stardogs’, 'Tehnikum'

9. Hot corn

Hot corn has been a healthy and nutritious snack for children and adults since Soviet times. It is mostly sold in park areas, on beaches and in stalls across the city. If you want variety, you can try corn in cafes: for example, Japanese-style corn with sea salt and black pepper (‘tomorokoshi’) or Mexican-style corn with chipotle aioli sauce and parmesan.

Where to try: city stalls, ‘[KU:] ramen izakaya bar’,   ‘ Sangre Fresca’

10. Ice Cream

Of course, you can eat ice cream in winter, but you'll enjoy it the most in summer. Ice cream stands are located all over the city and there are usually at least 30 kinds (‘eskimo’, ‘crème brûlée’, ‘fruit sherbets’, etc.). And don't miss the opportunity to go to the GUM department store on the Red Square for its legendary ice cream in a waffle cup.

Where to try: GUM, 'Vanilny Shpatel' ('Depo' food court)

READ MORE: 5 OLDEST restaurants in Moscow (PHOTOS)

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Frontiers for Young Minds

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The Impacts of Junk Food on Health

Energy-dense, nutrient-poor foods, otherwise known as junk foods, have never been more accessible and available. Young people are bombarded with unhealthy junk-food choices daily, and this can lead to life-long dietary habits that are difficult to undo. In this article, we explore the scientific evidence behind both the short-term and long-term impacts of junk food consumption on our health.

Introduction

The world is currently facing an obesity epidemic, which puts people at risk for chronic diseases like heart disease and diabetes. Junk food can contribute to obesity and yet it is becoming a part of our everyday lives because of our fast-paced lifestyles. Life can be jam-packed when you are juggling school, sport, and hanging with friends and family! Junk food companies make food convenient, tasty, and affordable, so it has largely replaced preparing and eating healthy homemade meals. Junk foods include foods like burgers, fried chicken, and pizza from fast-food restaurants, as well as packaged foods like chips, biscuits, and ice-cream, sugar-sweetened beverages like soda, fatty meats like bacon, sugary cereals, and frozen ready meals like lasagne. These are typically highly processed foods , meaning several steps were involved in making the food, with a focus on making them tasty and thus easy to overeat. Unfortunately, junk foods provide lots of calories and energy, but little of the vital nutrients our bodies need to grow and be healthy, like proteins, vitamins, minerals, and fiber. Australian teenagers aged 14–18 years get more than 40% of their daily energy from these types of foods, which is concerning [ 1 ]. Junk foods are also known as discretionary foods , which means they are “not needed to meet nutrient requirements and do not belong to the five food groups” [ 2 ]. According to the dietary guidelines of Australian and many other countries, these five food groups are grains and cereals, vegetables and legumes, fruits, dairy and dairy alternatives, and meat and meat alternatives.

Young people are often the targets of sneaky advertising tactics by junk food companies, which show our heroes and icons promoting junk foods. In Australia, cricket, one of our favorite sports, is sponsored by a big fast-food brand. Elite athletes like cricket players are not fuelling their bodies with fried chicken, burgers, and fries! A study showed that adolescents aged 12–17 years view over 14.4 million food advertisements in a single year on popular websites, with cakes, cookies, and ice cream being the most frequently advertised products [ 3 ]. Another study examining YouTube videos popular amongst children reported that 38% of all ads involved a food or beverage and 56% of those food ads were for junk foods [ 4 ].

What Happens to Our Bodies Shortly After We Eat Junk Foods?

Food is made up of three major nutrients: carbohydrates, proteins, and fats. There are also vitamins and minerals in food that support good health, growth, and development. Getting the proper nutrition is very important during our teenage years. However, when we eat junk foods, we are consuming high amounts of carbohydrates, proteins, and fats, which are quickly absorbed by the body.

Let us take the example of eating a hamburger. A burger typically contains carbohydrates from the bun, proteins and fats from the beef patty, and fats from the cheese and sauce. On average, a burger from a fast-food chain contains 36–40% of your daily energy needs and this does not account for any chips or drinks consumed with it ( Figure 1 ). This is a large amount of food for the body to digest—not good if you are about to hit the cricket pitch!

• Figure 1 - The nutritional composition of a popular burger from a famous fast-food restaurant, detailing the average quantity per serving and per 100 g.
• The carbohydrates of a burger are mainly from the bun, while the protein comes from the beef patty. Large amounts of fat come from the cheese and sauce. Based on the Australian dietary guidelines, just one burger can be 36% of the recommended daily energy intake for teenage boys aged 12–15 years and 40% of the recommendations for teenage girls 12–15 years.

A few hours to a few days after eating rich, heavy foods such as a burger, unpleasant symptoms like tiredness, poor sleep, and even hunger can result ( Figure 2 ). Rather than providing an energy boost, junk foods can lead to a lack of energy. For a short time, sugar (a type of carbohydrate) makes people feel energized, happy, and upbeat as it is used by the body for energy. However, refined sugar , which is the type of sugar commonly found in junk foods, leads to a quick drop in blood sugar levels because it is digested quickly by the body. This can lead tiredness and cravings [ 5 ].

• Figure 2 - The short- and long-term impacts of junk food consumption.
• In the short-term, junk foods can make you feel tired, bloated, and unable to concentrate. Long-term, junk foods can lead to tooth decay and poor bowel habits. Junk foods can also lead to obesity and associated diseases such as heart disease. When junk foods are regularly consumed over long periods of time, the damages and complications to health are increasingly costly.

Fiber is a good carbohydrate commonly found in vegetables, fruits, barley, legumes, nuts, and seeds—foods from the five food groups. Fiber not only keeps the digestive system healthy, but also slows the stomach’s emptying process, keeping us feeling full for longer. Junk foods tend to lack fiber, so when we eat them, we notice decreasing energy and increasing hunger sooner.

Foods such as walnuts, berries, tuna, and green veggies can boost concentration levels. This is particularly important for young minds who are doing lots of schoolwork. These foods are what most elite athletes are eating! On the other hand, eating junk foods can lead to poor concentration. Eating junk foods can lead to swelling in the part of the brain that has a major role in memory. A study performed in humans showed that eating an unhealthy breakfast high in fat and sugar for 4 days in a row caused disruptions to the learning and memory parts of the brain [ 6 ].

Long-Term Impacts of Junk Foods

If we eat mostly junk foods over many weeks, months, or years, there can be several long-term impacts on health ( Figure 2 ). For example, high saturated fat intake is strongly linked with high levels of bad cholesterol in the blood, which can be a sign of heart disease. Respected research studies found that young people who eat only small amounts of saturated fat have lower total cholesterol levels [ 7 ].

Frequent consumption of junk foods can also increase the risk of diseases such as hypertension and stroke. Hypertension is also known as high blood pressure and a stroke is damage to the brain from reduced blood supply, which prevents the brain from receiving the oxygen and nutrients it needs to survive. Hypertension and stroke can occur because of the high amounts of cholesterol and salt in junk foods.

Furthermore, junk foods can trigger the “happy hormone,” dopamine , to be released in the brain, making us feel good when we eat these foods. This can lead us to wanting more junk food to get that same happy feeling again [ 8 ]. Other long-term effects of eating too much junk food include tooth decay and constipation. Soft drinks, for instance, can cause tooth decay due to high amounts of sugar and acid that can wear down the protective tooth enamel. Junk foods are typically low in fiber too, which has negative consequences for gut health in the long term. Fiber forms the bulk of our poop and without it, it can be hard to poop!

Tips for Being Healthy

One way to figure out whether a food is a junk food is to think about how processed it is. When we think of foods in their whole and original forms, like a fresh tomato, a grain of rice, or milk squeezed from a cow, we can then start to imagine how many steps are involved to transform that whole food into something that is ready-to-eat, tasty, convenient, and has a long shelf life.

For teenagers 13–14 years old, the recommended daily energy intake is 8,200–9,900 kJ/day or 1,960 kcal-2,370 kcal/day for boys and 7,400–8,200 kJ/day or 1,770–1,960 kcal for girls, according to the Australian dietary guidelines. Of course, the more physically active you are, the higher your energy needs. Remember that junk foods are okay to eat occasionally, but they should not make up more than 10% of your daily energy intake. In a day, this may be a simple treat such as a small muffin or a few squares of chocolate. On a weekly basis, this might mean no more than two fast-food meals per week. The remaining 90% of food eaten should be from the five food groups.

In conclusion, we know that junk foods are tasty, affordable, and convenient. This makes it hard to limit the amount of junk food we eat. However, if junk foods become a staple of our diets, there can be negative impacts on our health. We should aim for high-fiber foods such as whole grains, vegetables, and fruits; meals that have moderate amounts of sugar and salt; and calcium-rich and iron-rich foods. Healthy foods help to build strong bodies and brains. Limiting junk food intake can happen on an individual level, based on our food choices, or through government policies and health-promotion strategies. We need governments to stop junk food companies from advertising to young people, and we need their help to replace junk food restaurants with more healthy options. Researchers can focus on education and health promotion around healthy food options and can work with young people to develop solutions. If we all work together, we can help young people across the world to make food choices that will improve their short and long-term health.

Obesity : ↑ A disorder where too much body fat increases the risk of health problems.

Processed Food : ↑ A raw agricultural food that has undergone processes to be washed, ground, cleaned and/or cooked further.

Discretionary Food : ↑ Foods and drinks not necessary to provide the nutrients the body needs but that may add variety to a person’s diet (according to the Australian dietary guidelines).

Refined Sugar : ↑ Sugar that has been processed from raw sources such as sugar cane, sugar beets or corn.

Saturated Fat : ↑ A type of fat commonly eaten from animal sources such as beef, chicken and pork, which typically promotes the production of “bad” cholesterol in the body.

Dopamine : ↑ A hormone that is released when the brain is expecting a reward and is associated with activities that generate pleasure, such as eating or shopping.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

[1] ↑ Australian Bureau of Statistics. 2013. 4324.0.55.002 - Microdata: Australian Health Survey: Nutrition and Physical Activity, 2011-12 . Australian Bureau of Statistics. Available online at: http://bit.ly/2jkRRZO (accessed December 13, 2019).

[2] ↑ National Health and Medical Research Council. 2013. Australian Dietary Guidelines Summary . Canberra, ACT: National Health and Medical Research Council.

[3] ↑ Potvin Kent, M., and Pauzé, E. 2018. The frequency and healthfulness of food and beverages advertised on adolescents’ preferred web sites in Canada. J. Adolesc. Health. 63:102–7. doi: 10.1016/j.jadohealth.2018.01.007

[4] ↑ Tan, L., Ng, S. H., Omar, A., and Karupaiah, T. 2018. What’s on YouTube? A case study on food and beverage advertising in videos targeted at children on social media. Child Obes. 14:280–90. doi: 10.1089/chi.2018.0037

[5] ↑ Gómez-Pinilla, F. 2008. Brain foods: the effects of nutrients on brain function. Nat. Rev. Neurosci. 9, 568–78. doi: 10.1038/nrn2421

[6] ↑ Attuquayefio, T., Stevenson, R. J., Oaten, M. J., and Francis, H. M. 2017. A four-day western-style dietary intervention causes reductions in hippocampal-dependent learning and memory and interoceptive sensitivity. PLoS ONE . 12:e0172645. doi: 10.1371/journal.pone.0172645

[7] ↑ Te Morenga, L., and Montez, J. 2017. Health effects of saturated and trans-fatty acid intake in children and adolescents: systematic review and meta-analysis. PLoS ONE. 12:e0186672. doi: 10.1371/journal.pone.0186672

[8] ↑ Reichelt, A. C. 2016. Adolescent maturational transitions in the prefrontal cortex and dopamine signaling as a risk factor for the development of obesity and high fat/high sugar diet induced cognitive deficits. Front. Behav. Neurosci. 10. doi: 10.3389/fnbeh.2016.00189

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Introduction.

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Young people and healthy eating: a systematic review of research on barriers and facilitators

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J Shepherd, A Harden, R Rees, G Brunton, J Garcia, S Oliver, A Oakley, Young people and healthy eating: a systematic review of research on barriers and facilitators, Health Education Research , Volume 21, Issue 2, 2006, Pages 239–257, https://doi.org/10.1093/her/cyh060

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A systematic review was conducted to examine the barriers to, and facilitators of, healthy eating among young people (11–16 years). The review focused on the wider determinants of health, examining community- and society-level interventions. Seven outcome evaluations and eight studies of young people's views were included. The effectiveness of the interventions was mixed, with improvements in knowledge and increases in healthy eating but differences according to gender. Barriers to healthy eating included poor school meal provision and ease of access to, relative cheapness of and personal taste preferences for fast food. Facilitators included support from family, wider availability of healthy foods, desire to look after one's appearance and will-power. Friends and teachers were generally not a common source of information. Some of the barriers and facilitators identified by young people had been addressed by soundly evaluated effective interventions, but significant gaps were identified where no evaluated interventions appear to have been published (e.g. better labelling of food products), or where there were no methodologically sound evaluations. Rigorous evaluation is required particularly to assess the effectiveness of increasing the availability of affordable healthy food in the public and private spaces occupied by young people.

Healthy eating contributes to an overall sense of well-being, and is a cornerstone in the prevention of a number of conditions, including heart disease, diabetes, high blood pressure, stroke, cancer, dental caries and asthma. For children and young people, healthy eating is particularly important for healthy growth and cognitive development. Eating behaviours adopted during this period are likely to be maintained into adulthood, underscoring the importance of encouraging healthy eating as early as possible [ 1 ]. Guidelines recommend consumption of at least five portions of fruit and vegetables a day, reduced intakes of saturated fat and salt and increased consumption of complex carbohydrates [ 2, 3 ]. Yet average consumption of fruit and vegetables in the UK is only about three portions a day [ 4 ]. A survey of young people aged 11–16 years found that nearly one in five did not eat breakfast before going to school [ 5 ]. Recent figures also show alarming numbers of obese and overweight children and young people [ 6 ]. Discussion about how to tackle the ‘epidemic’ of obesity is currently high on the health policy agenda [ 7 ], and effective health promotion remains a key strategy [ 8–10 ].

Evidence for the effectiveness of interventions is therefore needed to support policy and practice. The aim of this paper is to report a systematic review of the literature on young people and healthy eating. The objectives were

(i) to undertake a ‘systematic mapping’ of research on the barriers to, and facilitators of, healthy eating among young people, especially those from socially excluded groups (e.g. low-income, ethnic minority—in accordance with government health policy);

(ii) to prioritize a subset of studies to systematically review ‘in-depth’;

(iii) to ‘synthesize’ what is known from these studies about the barriers to, and facilitators of, healthy eating with young people, and how these can be addressed and

(iv) to identify gaps in existing research evidence.

General approach

This study followed standard procedures for a systematic review [ 11, 12 ]. It also sought to develop a novel approach in three key areas.

First, it adopted a conceptual framework of ‘barriers’ to and ‘facilitators’ of health. Research findings about the barriers to, and facilitators of, healthy eating among young people can help in the development of potentially effective intervention strategies. Interventions can aim to modify or remove barriers and use or build upon existing facilitators. This framework has been successfully applied in other related systematic reviews in the area of healthy eating in children [ 13 ], physical activity with children [ 14 ] and young people [ 15 ] and mental health with young people [16; S. Oliver, A. Harden, R. Rees, J. Shepherd, G. Brunton and A. Oakley, manuscript in preparation].

Second, the review was carried out in two stages: a systematic search for, and mapping of, literature on healthy eating with young people, followed by an in-depth systematic review of the quality and findings of a subset of these studies. The rationale for a two-stage review to ensure the review was as relevant as possible to users. By mapping a broad area of evidence, the key characteristics of the extant literature can be identified and discussed with review users, with the aim of prioritizing the most relevant research areas for systematic in-depth analysis [ 17, 18 ].

Third, the review utilized a ‘mixed methods’ triangulatory approach. Data from effectiveness studies (‘outcome evaluations’, primarily quantitative data) were combined with data from studies which described young people's views of factors influencing their healthy eating in negative or positive ways (‘views’ studies, primarily qualitative). We also sought data on young people's perceptions of interventions when these had been collected alongside outcomes data in outcome evaluations. However, the main source of young people's views was surveys or interview-based studies that were conducted independently of intervention evaluation (‘non-intervention’ research). The purpose was to enable us to ascertain not just whether interventions are effective, but whether they address issues important to young people, using their views as a marker of appropriateness. Few systematic reviews have attempted to synthesize evidence from both intervention and non-intervention research: most have been restricted to outcome evaluations. This study therefore represents one of the few attempts that have been made to date to integrate different study designs into systematic reviews of effectiveness [ 19–22 ].

Literature searching

A highly sensitive search strategy was developed to locate potentially relevant studies. A wide range of terms for healthy eating (e.g. nutrition, food preferences, feeding behaviour, diets and health food) were combined with health promotion terms or general or specific terms for determinants of health or ill-health (e.g. health promotion, behaviour modification, at-risk-populations, sociocultural factors and poverty) and with terms for young people (e.g. adolescent, teenager, young adult and youth). A number of electronic bibliographic databases were searched, including Medline, EMBASE, The Cochrane Library, PsycINFO, ERIC, Social Science Citation Index, CINAHL, BiblioMap and HealthPromis. The searches covered the full range of publication years available in each database up to 2001 (when the review was completed).

Full reports of potentially relevant studies identified from the literature search were obtained and classified (e.g. in terms of specific topic area, context, characteristics of young people, research design and methodological attributes).

Inclusion screening

Inclusion criteria were developed and applied to each study. The first round of screening was to identify studies to populate the map. To be included, a study had to (i) focus on healthy eating; (ii) include young people aged 11–16 years; (iii) be about the promotion of healthy eating, and/or the barriers to, or facilitators of, healthy eating; (iv) be a relevant study type: (a) an outcome evaluation or (b) a non-intervention study (e.g. cohort or case control studies, or interview studies) conducted in the UK only (to maximize relevance to UK policy and practice) and (v) be published in the English language.

The results of the map, which are reported in greater detail elsewhere [ 23 ], were used to prioritize a subset of policy relevant studies for the in-depth systematic review.

A second round of inclusion screening was performed. As before, all studies had to have healthy eating as their main focus and include young people aged 11–16 years. In addition, outcome evaluations had toFor a non-intervention study to be included it had to

(i) use a comparison or control group; report pre- and post-intervention data and, if a non-randomized trial, equivalent on sociodemographic characteristics and pre-intervention outcome variables (demonstrating their ‘potential soundness’ in advance of further quality assessment);

(ii) report an intervention that aims to make a change at the community or society level and

(iii) measure behavioural and/or physical health status outcomes.

(i) examine young people's attitudes, opinions, beliefs, feelings, understanding or experiences about healthy eating (rather than solely examine health status, behaviour or factual knowledge);

(ii) access views about one or more of the following: young people's definitions of and/or ideas about healthy eating, factors influencing their own or other young people's healthy eating and whether and how young people think healthy eating can be promoted and

(iii) privilege young people's views—presenting views directly as data that are valuable and interesting in themselves, rather than only as a route to generating variables to be tested in a predictive or causal model.

Non-intervention studies published before 1990 were excluded in order to maximize the relevance of the review findings to current policy issues.

Data extraction and quality assessment

All studies meeting inclusion criteria underwent data extraction and quality assessment, using a standardized framework [ 24 ]. Data for each study were entered independently by two researchers into a specialized computer database [ 25 ] (the full and final data extraction and quality assessment judgement for each study in the in-depth systematic review can be viewed on the Internet by visiting http://eppi.ioe.ac.uk ).

Outcome evaluations were considered methodologically ‘sound’ if they reported:Only studies meeting these criteria were used to draw conclusions about effectiveness. The results of the studies which did not meet these quality criteria were judged unclear.

(i) a control or comparison group equivalent to the intervention group on sociodemographic characteristics and pre-intervention outcome variables.

(ii) pre-intervention data for all individuals or groups recruited into the evaluation;

(iii) post-intervention data for all individuals or groups recruited into the evaluation and

(iv) on all outcomes, as described in the aims of the intervention.

Non-intervention studies were assessed according to a total of seven criteria (common to sets of criteria proposed by four research groups for qualitative research [ 26–29 ]):

(i) an explicit account of theoretical framework and/or the inclusion of a literature review which outlined a rationale for the intervention;

(ii) clearly stated aims and objectives;

(iii) a clear description of context which includes detail on factors important for interpreting the results;

(iv) a clear description of the sample;

(v) a clear description of methodology, including systematic data collection methods;

(vi) analysis of the data by more than one researcher and

(vii) the inclusion of sufficient original data to mediate between data and interpretation.

Data synthesis

Three types of analyses were performed: (i) narrative synthesis of outcome evaluations, (ii) narrative synthesis of non-intervention studies and (iii) synthesis of intervention and non-intervention studies together.

For the last of these a matrix was constructed which laid out the barriers and facilitators identified by young people alongside descriptions of the interventions included in the in-depth systematic review of outcome evaluations. The matrix was stratified by four analytical themes to characterize the levels at which the barriers and facilitators appeared to be operating: the school, family and friends, the self and practical and material resources. This methodology is described further elsewhere [ 20, 22, 30 ].

From the matrix it is possible to see:

(i) where barriers have been modified and/or facilitators built upon by soundly evaluated interventions, and ‘promising’ interventions which need further, more rigorous, evaluation (matches) and

(ii) where barriers have not been modified and facilitators not built upon by any evaluated intervention, necessitating the development and rigorous evaluation of new interventions (gaps).

Figure 1 outlines the number of studies included at various stages of the review. Of the total of 7048 reports identified, 135 reports (describing 116 studies) met the first round of screening and were included in the descriptive map. The results of the map are reported in detail in a separate publication—see Shepherd et al. [ 23 ] (the report can be downloaded free of charge via http://eppi.ioe.ac.uk ). A subset of 22 outcome evaluations and 8 studies of young people's views met the criteria for the in-depth systematic review.

The review process.

Outcome evaluations

Of the 22 outcome evaluations, most were conducted in the United States ( n = 16) [ 31–45 ], two in Finland [ 46, 47 ], and one each in the UK [ 48 ], Norway [ 49 ], Denmark [ 50 ] and Australia [ 51 ]. In addition to the main focus on promoting healthy eating, they also addressed other related issues including cardiovascular disease in general, tobacco use, accidents, obesity, alcohol and illicit drug use. Most were based in primary or secondary school settings and were delivered by teachers. Interventions varied considerably in content. While many involved some form of information provision, over half ( n = 13) involved attempts to make structural changes to young people's physical environments; half ( n = 11) trained parents in or about nutrition, seven developed health-screening resources, five provided feedback to young people on biological measures and their behavioural risk status and three aimed to provide social support systems for young people or others in the community. Social learning theory was the most common theoretical framework used to develop these interventions. Only a minority of studies included young people who could be considered socially excluded ( n = 6), primarily young people from ethnic minorities (e.g. African Americans and Hispanics).

Following detailed data extraction and critical appraisal, only seven of the 22 outcome evaluations were judged to be methodologically sound. For the remainder of this section we only report the results of these seven. Four of the seven were from the United States, with one each from the UK, Norway and Finland. The studies varied in the comprehensiveness of their reporting of the characteristics of the young people (e.g. sociodemographic/economic status). Most were White, living in middle class urban areas. All attended secondary schools. Table I details the interventions in these sound studies. Generally, they were multicomponent interventions in which classroom activities were complemented with school-wide initiatives and activities in the home. All but one of the seven sound evaluations included and an integral evaluation of the intervention processes. Some studies report results according to demographic characteristics such as age and gender.

Soundly evaluated outcome evaluations: study characteristics (n = 7)

RCT = Randomized Controlled Trial; CT = controlled trial (no randomization); PE = process evaluation.

Separate evaluations of the same intervention in two populations in New York (the Bronx and Westchester County).

The UK-based intervention was an award scheme (the ‘Wessex Healthy Schools Award’) that sought to make health-promoting changes in school ethos, organizational functioning and curriculum [ 48 ]. Changes made in schools included the introduction of health education curricula, as well as the setting of targets in key health promotion areas (including healthy eating). Knowledge levels, which were high at baseline, changed little over the course of the intervention. Intervention schools performed better in terms of healthy food choices (on audit scores). The impact on measures of healthy eating such as choosing healthy snacks varied according to age and sex. The intervention only appeared possibly to be effective for young women in Year 11 (aged 15–16 years) on these measures (statistical significance not reported).

The ‘Know Your Body’ intervention, a cardiovascular risk reduction programme, was evaluated in two separate studies in two demographically different areas of New York (the Bronx and Westchester County) [ 45 ]. Lasting for 5 years it comprised teacher-led classroom education, parental involvement activities and risk factor examination in elementary and junior high schools. In the Bronx evaluation, statistically significant increases in knowledge were reported, but favourable changes in cholesterol levels and dietary fat were not significant. In the Westchester County evaluation, we judged the effects to be unclear due to shortcomings in methods reported.

A second US-based study, the 3-year ‘Gimme 5’ programme [ 40 ], focused on increasing consumption of fruits and vegetables through a school-wide media campaign, complemented by classroom activities, parental involvement and changes to nutritional content of school meals. The intervention was effective at increasing knowledge (particularly among young women). Effects were measured in terms of changes in knowledge scores between baseline and two follow-up periods. Differences between the intervention and comparison group were significant at both follow-ups. There was a significant increase in consumption of fruit and vegetables in the intervention group, although this was not sustained.

In the third US study, the ‘Slice of Life’ intervention, peer leaders taught 10 sessions covering the benefits of fitness, healthy diets and issues concerning weight control [ 41 ]. School functioning was also addressed by student recommendations to school administrators. For young women, there were statistically significant differences between intervention and comparison groups on healthy eating scores, salt consumption scores, making healthy food choices, knowledge of healthy food, reading food labels for salt and fat content and awareness of healthy eating. However, among young men differences were only significant for salt and knowledge scores. The process evaluation suggested that having peers deliver training was acceptable to students and the peer-trainers themselves.

A Norwegian study evaluated a similar intervention to the ‘Slice of Life’ programme, employing peer educators to lead classroom activities and small group discussions on nutrition [ 49 ]. Students also analysed the availability of healthy food in their social and home environment and used a computer program to analyse the nutritional status of foods. There were significant intervention effects for reported healthy eating behaviour (but not maintained by young men) and for knowledge (not young women).

The second ‘North Karelia Youth Study’ in Finland featured classroom educational activities, a community media campaign, health-screening activities, changes to school meals and a health education initiative in the parents' workplace [ 47 ]. It was judged to be effective for healthy eating behaviour, reducing systolic blood pressure and modifying fat content of school meals, but less so for reducing cholesterol levels and diastolic blood pressure.

The evidence from the well-designed evaluations of the effectiveness of healthy eating initiatives is therefore mixed. Interventions tend to be more effective among young women than young men.

Young people's views

Table II describes the key characteristics of the eight studies of young people's views. The most consistently reported characteristics of the young people were age, gender and social class. Socioeconomic status was mixed, and in the two studies reporting ethnicity, the young people participating were predominantly White. Most studies collected data in mainstream schools and may therefore not be applicable to young people who infrequently or never attend school.

Characteristics of young people's views studies (n = 8)

All eight studies asked young people about their perceptions of, or attitudes towards, healthy eating, while none explicitly asked them what prevents them from eating healthily. Only two studies asked them what they think helps them to eat healthy foods, and only one asked for their ideas about what could or should be done to promote nutrition.

Young people tended to talk about food in terms of what they liked and disliked, rather than what was healthy/unhealthy. Healthy foods were predominantly associated with parents/adults and the home, while ‘fast food’ was associated with pleasure, friendship and social environments. Links were also made between food and appearance, with fast food perceived as having negative consequences on weight and facial appearance (and therefore a rationale for eating healthier foods). Attitudes towards healthy eating were generally positive, and the importance of a healthy diet was acknowledged. However, personal preferences for fast foods on grounds of taste tended to dominate food choice. Young people particularly valued the ability to choose what they eat.

Despite not being explicitly asked about barriers, young people discussed factors inhibiting their ability to eat healthily. These included poor availability of healthy meals at school, healthy foods sometimes being expensive and wide availability of, and personal preferences for, fast foods. Things that young people thought should be done to facilitate healthy eating included reducing the price of healthy snacks and better availability of healthy foods at school, at take-aways and in vending machines. Will-power and encouragement from the family were commonly mentioned support mechanisms for healthy eating, while teachers and peers were the least commonly cited sources of information on nutrition. Ideas for promoting healthy eating included the provision of information on nutritional content of school meals (mentioned by young women particularly) and better food labelling in general.

Table III shows the synthesis matrix which juxtaposes barriers and facilitators alongside results of outcome evaluations. There were some matches but also significant gaps between, on the one hand, what young people say are barriers to healthy eating, what helps them and what could or should be done and, on the other, soundly evaluated interventions that address these issues.

Synthesis matrix

Key to young people's views studies: Y1 , Dennison and Shepherd [ 56 ]; Y2 , Harris [ 57 ]; Y3 , McDougall [ 58 ]; Y4 , Miles and Eid [ 59 ]; Y5 , Roberts et al. [ 60 ]; Y6 , Ross [ 61 ]; Y7 , Watt and Sheiham [ 62 ]; Y8 , Watt and Sheiham [ 63 ]. Key to intervention studies: OE1 , Baranowski et al. [ 31 ]; OE2 , Bush et al. [ 32 ]; OE3 , Coates et al. [ 33 ]; OE4 , Ellison et al. [ 34 ]; OE5 , Flores [ 36 ]; OE6 , Fitzgibbon et al. [ 35 ]; OE7 , Hopper et al. [ 64 ]; OE8 , Holund [ 50 ]; OE9 , Kelder et al. [ 38 ]; OE10 , Klepp and Wilhelmsen [ 49 ]; OE11 , Moon et al. [ 48 ]; OE12 , Nader et al. [ 39 ]; OE13 , Nicklas et al. [ 40 ]; OE14 , Perry et al. [ 41 ]; OE15 , Petchers et al. [ 42 ]; OE16 , Schinke et al. [ 43 ]; OE17 , Wagner et al. [ 44 ]; OE18 , Vandongen et al. [ 51 ]; OE19 , Vartiainen et al. [ 46 ]; OE20 , Vartiainen et al. [ 47 ]; OE21 , Walter I [ 45 ]; OE22 , Walter II [ 45 ]. OE10, OE11, OE13, OE14, OE20, OE21 and OE22 denote a sound outcome evaluation. OE21 and OE22 are separate evaluations of the same intervention. Due to methodological limitations, we have judged the effects of OE22 to be unclear. Y1 and Y2 do not appear in the synthesis matrix as they did not explicitly report barriers or facilitators, and it was not possible for us to infer potential barriers or facilitators. However, these two studies did report what young people understood by healthy eating, their perceptions, and their views and opinions on the importance of eating a healthy diet. OE2, OE12, OE16 and OE17 do not appear in the synthesis matrix as they did not address any of the barriers or facilitators.

In terms of the school environment, most of the barriers identified by young people appear to have been addressed. At least two sound outcome evaluations demonstrated the effectiveness of increasing the availability of healthy foods in the school canteen [ 40, 47 ]. Furthermore, despite the low status of teachers and peers as sources of nutritional information, several soundly evaluated studies showed that they can be employed effectively to deliver nutrition interventions.

Young people associated parents and the home environment with healthy eating, and half of the sound outcome evaluations involved parents in the education of young people about nutrition. However, problems were sometimes experienced in securing parental attendance at intervention activities (e.g. seminar evenings). Why friends were not a common source of information about good nutrition is not clear. However, if peer pressure to eat unhealthy foods is a likely explanation, then it has been addressed by the peer-led interventions in three sound outcome evaluations (generally effectively) [ 41, 47, 49 ] and two outcome evaluations which did not meet the quality criteria (effectiveness unclear) [ 33, 50 ].

The fact that young people choose fast foods on grounds of taste has generally not been addressed by interventions, apart from one soundly evaluated effective intervention which included taste testings of fruit and vegetables [ 40 ]. Young people's concern over their appearance (which could be interpreted as both a barrier and a facilitator) has only been addressed in one of the sound outcome evaluations (which revealed an effective intervention) [ 41 ]. Will-power to eat healthy foods has only been examined in one outcome evaluation in the in-depth systematic review (judged to be sound and effective) (Walter I—Bronx evaluation) [ 45 ]. The need for information on nutrition was addressed by the majority of interventions in the in-depth systematic review. However, no studies were found which evaluated attempts to increase the nutritional content of school meals.

Barriers and facilitators relating to young people's practical and material resources were generally not addressed by interventions, soundly evaluated or otherwise. No studies were found which examined the effectiveness of interventions to lower the price of healthy foods. However, one soundly evaluated intervention was partially effective in increasing the availability of healthy snacks in community youth groups (Walter I—Bronx evaluation) [ 45 ]. At best, interventions have attempted to raise young people's awareness of environmental constraints on eating healthily, or encouraged them to lobby for increased availability of nutritious foods (in the case of the latter without reporting whether any changes have been effected as a result).

This review has systematically identified some of the barriers to, and facilitators of, healthy eating with young people, and illustrated to what extent they have been addressed by soundly evaluated effective interventions.

The evidence for effectiveness is mixed. Increases in knowledge of nutrition (measured in all but one study) were not consistent across studies, and changes in clinical risk factors (measured in two studies) varied, with one study detecting reductions in cholesterol and another detecting no change. Increases in reported healthy eating behaviour were observed, but mostly among young women revealing a distinct gender pattern in the findings. This was the case in four of the seven outcome evaluations (in which analysis was stratified by gender). The authors of one of the studies suggest that emphasis of the intervention on healthy weight management was more likely to appeal to young women. It was proposed that interventions directed at young men should stress the benefits of nutrition on strength, physical endurance and physical activity, particularly to appeal to those who exercise and play sports. Furthermore, age was a significant factor in determining effectiveness in one study [ 48 ]. Impact was greatest on young people in the 15- to 16-year age range (particularly for young women) in comparison with those aged 12–13 years, suggesting that dietary influences may vary with age. Tailoring the intervention to take account of age and gender is therefore crucial to ensure that interventions are as relevant and meaningful as possible.

Other systematic reviews of interventions to promote healthy eating (which included some of the studies with young people fitting the age range of this review) also show mixed results [ 52–55 ]. The findings of these reviews, while not being directly comparable in terms of conceptual framework, methods and age group, seem to offer some support for the findings of this review. The main message is that while there is some evidence to suggest effectiveness, the evidence base is limited. We have identified no comparable systematic reviews in this area.

Unlike other reviews, however, this study adopted a wider perspective through inclusion of studies of young people's views as well as effectiveness studies. A number of barriers to healthy eating were identified, including poor availability of healthy foods at school and in young people's social spaces, teachers and friends not always being a source of information/support for healthy eating, personal preferences for fast foods and healthy foods generally being expensive. Facilitating factors included information about nutritional content of foods/better labelling, parents and family members being supportive; healthy eating to improve or maintain one's personal appearance, will-power and better availability/lower pricing of healthy snacks.

Juxtaposing barriers and facilitators alongside effectiveness studies allowed us to examine the extent to which the needs of young people had been adequately addressed by evaluated interventions. To some extent they had. Most of the barriers and facilitators that related to the school and relationships with family and friends appear to have been taken into account by soundly evaluated interventions, although, as mentioned, their effectiveness varied. Many of the gaps tended to be in relation to young people as individuals (although our prioritization of interventions at the level of the community and society may have resulted in the exclusion of some of these interventions) and the wider determinants of health (‘practical and material resources’). Despite a wide search, we found few evaluations of strategies to improve nutritional labelling on foods particularly in schools or to increase the availability of affordable healthy foods particularly in settings where young people socialize. A number of initiatives are currently in place which may fill these gaps, but their effectiveness does not appear to have been reported yet. It is therefore crucial for any such schemes to be thoroughly evaluated and disseminated, at which point an updated systematic review would be timely.

This review is also constrained by the fact that its conclusions can only be supported by a relatively small proportion of the extant literature. Only seven of the 22 outcome evaluations identified were considered to be methodologically sound. As illustrated in Table III , a number of the remaining 15 interventions appear to modify barriers/build on facilitators but their results can only be judged unclear until more rigorous evaluation of these ‘promising’ interventions has been reported.

Finally, it is important to acknowledge that the majority of the outcome evaluations were conducted in the United States, and by virtue of the inclusion criteria, all the young people's views studies were UK based. The literature therefore might not be generalizable to other countries, where sociocultural values and socioeconomic circumstances may be quite different. Further evidence synthesis is needed on barriers to, and facilitators of, healthy eating and nutrition worldwide, particularly in developing countries.

The aim of this study was to survey what is known about the barriers to, and facilitators of, healthy eating among young people with a view to drawing out the implications for policy and practice. The review has mapped and quality screened the extant research in this area, and brought together the findings from evaluations of interventions aiming to promote healthy eating and studies which have elicited young people's views.

There has been much research activity in this area, yet it is disappointing that so few evaluation studies were methodologically strong enough to enable us to draw conclusions about effectiveness. There is some evidence to suggest that multicomponent school-based interventions can be effective, although effects tended to vary according to age and gender. Tailoring intervention messages accordingly is a promising approach which should therefore be evaluated. A key theme was the value young people place on choice and autonomy in relation to food. Increasing the provision and range of healthy, affordable snacks and meals in schools and social spaces will enable them to exercise their choice of healthier, tasty options.

We have identified that several barriers to, and facilitators of, healthy eating in young people have received little attention in evaluation research. Further work is needed to develop and evaluate interventions which modify or remove these barriers, and build on these facilitators. Further qualitative studies are also needed so that we can continue to listen to the views of young people. This is crucial if we are to develop and test meaningful, appropriate and effective health promotion strategies.

We would like to thank Chris Bonell and Dina Kiwan for undertaking data extraction. We would also like to acknowledge the invaluable help of Amanda Nicholas, James Thomas, Elaine Hogan, Sue Bowdler and Salma Master for support and helpful advice. The Department of Health, England, funds a specific programme of health promotion work at the EPPI-Centre. The views expressed in the report are those of the authors and not necessarily those of the Department of Health.

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When Students Patronize Fast-Food Restaurants near School: The Effects of Identification with the Student Community, Social Activity Spaces and Social Liability Interventions

Brennan davis.

1 Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA 93407, USA

Cornelia Pechmann

2 Paul Merage School of Business, University of California Irvine, Irvine, CA 92697, USA

Associated Data

The data presented in Studies 2–6 are available from either author upon request. Data from Study 1 were purchased from CHKS with a MOU that disallows data sharing because they must be purchased from CHKS.

US schools have fast-food restaurants nearby, encouraging student patronage, unhealthy consumption, and weight gain. Geographers have developed an activity space framework which suggests this nearby location effect will be moderated by whether people perceive the location as their activity space. Therefore, we study whether students perceive a fast-food restaurant near school as their activity space, and whether social marketing messages can change that perception. We conducted six studies: a secondary data analysis with 5986 students, a field experiment with 188 students, and four lab experiments with 188, 251, 178, and 379 students. We find that students who strongly identify with their student community patronize a fast-food restaurant near school (vs. farther away) because they view it as their activity space, while students who weakly identify do not. For example, in our field experiment, 44% vs. 7% of students who strongly identified with the student community patronized the near versus farther restaurant, while only 28% versus 19% of students who weakly identified patronized the near and farther restaurants comparably. We also find that to deter the strong identifiers, messages should convey that patronage is a social liability, e.g., portray student activism against fast food. We show that standard health messages do not change perceptions of restaurants as social activity spaces. Thus, to combat the problem of fast-food restaurants near schools causing unhealthy consumption, policy and educational interventions should focus on students who strongly identify with their student community and find ways to weaken their perceptions that fast-food restaurants near schools are their activity spaces.

1. Introduction

Research finds that retail nearness relates to retail patronage and product consumption [ 1 ] which we will refer to as the nearby location effect. Much of this work has studied the effects of near retail locations that sell unhealthy or risky products, such as fast food [ 2 , 3 , 4 ] or alcohol or tobacco [ 5 , 6 , 7 ]. In the US, 1 in 3 students are overweight and 1 in 5 are obese [ 8 ]. Strikingly, the majority of schools have a fast-food restaurant within a 1-mile radius [ 9 , 10 ], and 40% of students eat fast food daily [ 11 , 12 ]. Nearby location effects have frequently been found; students who have fast food near school (vs. not) have poorer diets [ 1 , 2 , 13 , 14 , 15 ] and are more likely to be overweight or obese [ 2 , 3 , 9 , 14 , 15 , 16 ]. Virtually all studies have been observational, not experiments, but the robust results are compelling. The problem with fast-food restaurants contributing to obesity is now a global one. US fast-food ad spending is increasing in non-US markets [ 17 ], and in China, fast-food sales and obesity rates are concurrently increasing [ 18 ].

In the US, high school students’ fast-food consumption is rising because there are more open campuses, meaning students can leave school for lunch, not just eat fast food before or after school [ 12 , 19 , 20 ]. Approximately 50% of California high schools have open campuses [ 21 ], and 67% in Oregon [ 12 ]. Moreover, research indicates that fast-food restaurants near schools have a disproportionate impact on minority and low-income students [ 3 , 14 , 15 ], because fast-food restaurants are more often situated by their schools [ 22 , 23 ], a situation that has worsened over time [ 23 ]. Low-income adults are also disproportionately affected by fast-food proximity [ 24 ].

The most common policy solution in the US has been to try to ban fast-food restaurants near schools [ 25 , 26 , 27 ] and otherwise restrict land use for fast-food restaurants [ 1 ]. Small affluent communities have had some success with locational bans, but urban, racially diverse communities where fast-food restaurants already abound have faced fierce business opposition dooming their efforts to limit fast food [ 25 , 26 ]. Very little research has tried to identify other solutions to the problem [ 28 ]. Moreover, research on fast-food proximity has lacked a unifying framework that, for instance, identifies relevant moderators and mediators.

In this research, we borrow a unifying framework from the geography literature which posts that the most fundamental predictor of any nearby location effect relates to whether people perceive it as their activity space [ 29 , 30 ]. According to the activity space literature, an unsupervised location near adolescents will emerge as their risky social activity space if their own peer group congregates there [ 31 , 32 , 33 , 34 ]. So, we asked the following question: When might a fast-food restaurant near school emerge as a social activity space for students, encouraging patronage?

We reasoned that a nearby fast-food restaurant could become a social activity space for students who strongly identify with their student community. Due to their activities in and around school and their identification with their schoolmates, it could become a popular destination for these students to meet up. When students are strongly identified, this means they feel that they share beliefs, interests, and values with other students at their school, and feel accepted and liked by them [ 35 , 36 , 37 , 38 , 39 ]. Strong identification is often ignited when students engage in school-sponsored extracurricular activities such as sports, clubs, or the arts [ 40 , 41 , 42 ]. US schools provide wide access to extracurricular activities, and thus building strong identification with the student community is not limited to white or wealthy students [ 38 , 39 , 43 ].

Many US schools use surveys to measure students’ level of identification with the student community because of its predictive value [ 38 , 39 , 43 ]. Strong identification has been found to relate to many positive behaviors and to protect against numerous negative behaviors, from the teenage years through college [ 36 , 42 , 44 ]. Students who strongly identify with their student community tend to be more committed to academic goals [ 39 , 40 , 42 ] and less likely to use cigarettes, marijuana, or cocaine [ 41 , 42 ], though more likely to drink alcohol [ 40 , 41 , 45 , 46 ].

We posit that when a fast-food restaurant is located near school (vs. farther away), it will be perceived by high identifiers as their social activity space, attracting them there and promoting unhealthy eating. We will measure students’ perception of the location as their social activity space by asking them whether they go there to see friends. Strong identifiers should agree; weak identifiers should not. If the nearby fast-food restaurant is a draw for the strongly identified students, it is unlikely to attract the weakly identified, because different peer groups tend to hang out in separate places [ 29 , 30 , 31 , 32 , 34 ]. To summarize, we test the following hypothesis.

Among students who strongly identify with their student community, the location of a fast-food restaurant near (vs. farther from) school will enhance patronage because of a stronger perception that it is their social activity space. Among the weakly identified students, a fast-food restaurant near (vs. farther from) school will not have these effects.

If students who are strongly identified with their student community think the fast-food restaurant near school is their social activity space, how might they be dissuaded? Studies have examined social marketing messages to deter students from unhealthy eating [ 47 , 48 ], alcohol use [ 49 , 50 ], and drug use [ 51 , 52 , 53 ]. Messages countering activity spaces have not been studied. However, the activity space framework posits that those spaces attract people by providing social benefits such as seeing friends [ 33 , 34 , 54 ]. Because the attraction is a social benefit, reducing its attraction will likely require reversing that perception to one of a social liability. Stating that the fast-food restaurant’s food is unhealthy is unlikely to be effective because it does not address students’ perception that it is a social activity space. An analogous situation occurs with smoking; adolescents start smoking for social acceptance [ 55 , 56 ]. To reduce its attraction, the opposite message must be conveyed: smoking is a social liability [ 53 , 57 ]. It is generally ineffective to convey to adolescents that smoking is a health liability [ 58 ].

It will be challenging to reverse adolescents’ perception that a previously acceptable hangout has become socially unacceptable among their peers. How can they be persuaded to see it differently? An emerging approach is to educate adolescents that marketers target them for unhealthy products and encourage student activism against being so targeted [ 59 , 60 , 61 ]. Sometimes students even engage in major activism, by which we mean they actively protest or boycott a product. A student-run product boycott is highly likely to make the product socially unacceptable to use among their peers. The US “truth” campaign against big tobacco did this effectively [ 61 , 62 ]. We tested activism messages and hypothesized the following.

Among students who strongly identify with their student community, the location of a fast-food restaurant near (vs. farther from) school, which normally attracts patronage, will no longer do so if a message conveys going there as a social liability. A health liability message will not have this effect. Among the weakly identified students, no such effects will be observed.

2. Study 1 Materials, Methods, and Results

2.1. overview.

In Study 1, we used Geographic Information System (GIS) data on fast-food restaurant locations combined with California’s Healthy Kids student survey to study whether a fast-food restaurant near school (vs. farther away) increased students’ fast-food restaurant patronage. We sought to determine whether a nearby location effect mainly occurred among students who strongly identified with their student community.

2.2. Participants

The participants were 5986 eleventh grade students who completed the long form of the California Healthy Kids Survey. They were the oldest respondents, most likely to have off-campus lunchtime privileges and make their own food decisions. Most participants were aged 16 (50%) or 17 (43%) and half were female (53%). They were ethnically diverse; 18% were Non-Hispanic White, 61% Hispanic, 29% Asian, 11% Black, 3% Hawaiian, and 8% Native American (2+ ethnicities could be chosen). Additionally, 59% were socioeconomically disadvantaged, eligible for free or reduced-price school meals due to low family incomes.

2.3. Measures

To determine if at least one fast-food restaurant was near schools, we merged two types of GIS data: (1) the locations of all California high schools from the state’s Department of Education, and (2) the locations of all California fast-food restaurants from the GIS firm ESRI’s Business Analyst product using NAICS code 722513 [ 63 , 64 ]. The restaurant-to-school distance was the traversable distance, considering roads [ 65 ]. Research shows fast-food restaurants tend to be clustered in a one-mile radius around schools in the US [ 9 , 10 ], so we coded whether there was 1+ restaurant within one mile of each school.

To measure students’ fast-food restaurant patronage and identification with the student community, we used the California Healthy Kids school survey administered to public school students by the state’s Department of Education. Schools were sampled to represent the school district populations. Students were required to complete the survey if selected unless a parent actively withheld consent. We used surveys from 2011–2012 and 2013–2014, obtained GIS data for the same years, and verified result consistency across years. We used the long-form survey that was administered in 27 randomly selected public high schools (N = 222 students per school in average), because it asked: “How many times did you eat fast food in the past 24 hours?” (0 = 0 times; 5 = 5 or more times). It also included a measure of identification with the student community: “I feel like I am part of this school.”, “I feel close to the people at this school.”, and “I am happy to be at this school.” (1 = strongly disagree, 5 = strongly agree, averaged, α = 0.83).

2.4. Analyses

We estimated a hierarchical ordinary least square regression model of fast-food restaurant patronage, relating it to a fast-food restaurant near school, identification with the student community, and their interaction [ 2 ]. We used a hierarchical model to account for student observations being non-independent [ 3 ]. This allowed us to test our main hypothesis (H1) at the individual level while controlling for some students being from the same county or the same school within the county. To assess the interaction between nearness and identification, we used floodlight analysis [ 66 ]. Though we used ordinary least squares because the dependent variable was a scale (e.g., 5 = 5 times or more), all models were re-estimated using Poisson regressions for count variables with similar results.

2.5. Results

In our sample of predominantly urban, ethnically diverse, and economically disadvantaged high school students, 94% (N = 5627) had a fast-food restaurant near school; 6% did not (N = 359). They reported consuming fast food 0.83 times (SD = 1.19) in the past 24 h, and their mean identification with the student community was 3.40 (SD = 0.94, 1–5 scale). Whether these students had a fast-food restaurant near their school, as opposed to all fast-food restaurants being relatively far from school, did not relate to their fast-food restaurant patronage as a main effect (b = 0.10, df = 5980, z = 0.85, p = 0.40). Students’ identification with their student community related negatively to their fast-food restaurant patronage as a main effect, indicating that strong identification generally had a protective effect (b = −0.16, df = 5980, z = 3.79, p < 0.001). Finally, as hypothesized (H1), there was an interaction between fast-food restaurant nearness to school and identification with the student community on restaurant patronage (b = 0.23, df = 5980, z = 2.81, p < 0.01). See Table 1 .

Study 1 Fast-food Restaurant Patronage due to Nearness and Identification.

Note: * Patronage question asked how many times fast food was consumed in the past 24 h.

In supplemental analyses, we looked at whether students’ ethnicity or income (free or reduced-price meal eligible) related to identification with their student community. Hispanic (r = 0.03, p = 0.06) and White (r = 0.08, p < 0.001) correlated positively with identification. Black (r = −0.06, p < 0.001), Asian (r = −0.03, p < 0.01), and low income (r = −0.03, p < 0.05) correlated negatively. Native American (r = 0.005, p = 0.72), Pacific Islander (r = −0.01, p = 0.61), and mixed (r = −0.007, p = 0.58) were uncorrelated. However, all correlations were weak. We included ethnicity and income as covariates in our model, but the results were unaffected (see Appendix A ).

We also conducted a floodlight analysis to understand the interaction effect we had observed [ 66 ]. Among students who strongly identified with their student community, fast-food restaurant patronage was higher if a restaurant was near school compared to farther away (right side of graph, solid line > dotted line). This nearby location effect was significant at an identification level of 4.25 or more on a 1–5 scale, p < 0.05 (shaded area on graph). Among students who weakly identified with their student community, fast-food restaurant patronage was higher if a restaurant was farther from school compared to nearby (left side of graph, dotted line > solid line). However, this effect only became significant at a very low identification level of 1.25 or less on a 1–5 scale, nearly at the scale endpoint. See Figure 1 , which illustrates why the negative main effect for identification was qualified by the two-way interaction. The stronger the identification, the less the fast-food patronage if it was far from school (steep negative slope for dotted line); this was much less so if the fast food was near school (slight negative slope for solid line).

Study 1 Fast-food Restaurant Patronage due to Nearness to School and Identification. Note: Johnson–Neyman turning point = 4.25, p < 0.05.

2.6. Discussion

In Study 1, we analyzed data from a large statewide survey of high school students. We found that, overall, strong identification with the student community reduced the risk of fast-food restaurant patronage, consistent with other protective effects of strong identification. However, while the strongly identified students tended to avoid unhealthy fast food, when a fast-food restaurant was located near (vs. farther from) school, their patronage increased, indicating it was a social activity space for them. Weakly identified students showed elevated patronage overall, but no more so when a restaurant was near (vs. farther from) school and tending toward the reverse. Identification with the student community was not highly related to ethnicity or income, and our results were confirmed even when these variables were controlled. However, these data were observational, so unobserved variables could have affected the results. Additionally, while students reported how many times they ate fast food, we could not verify where the food came from or whom they were with. Additionally, the data were skewed toward fast-food being near schools due to our sample.

3. Study 2 Materials, Methods, and Results

3.1. overview.

For Study 2, we conducted a behavioral field experiment. Each student received a money-saving promotional coupon for the same fast-food restaurant (e.g., McDonalds) redeemable either at a location near school or, alternatively, farther away but still reachable. We then monitored actual coupon redemption at both locations. To manipulate identification, students completed an essay eliciting either strong or weak identification.

3.2. Design and Participants

The design was a 2 (restaurant nearness to school) × 2 (identification with the student community) between-subjects factorial with both factors manipulated. Participants were 153 older adolescents, university students, with a mean age of 20.5 years, 44% female, 75% White Non-Hispanic, 10% Hispanic, 9% Black, 12% Asian, and 3% other. Respondents could select more than one ethnicity. We recruited 188 but dropped 35 because they had dietary restrictions precluding fast food or did not complete the identification essay (N near, strong = 30; N near, weak = 43; N far, strong = 37; N far, weak = 43).

3.3. Manipulations

Students participated for partial course credit. First, we manipulated their identification with the student community using an essay task [ 35 ]: “Please write for a few minutes (about 1 paragraph). In what ways do you think you are similar to (different from) other students here at University X? Consider attributes, interests, beliefs, values, etc. Try to recall some specific experiences that made you feel a part of (different from) the University X student community.” University X was named as their university in this and all studies.

Next, fast-food restaurant nearness to school was manipulated by giving students one of two promotional coupons for the same fast-food restaurant, redeemable at one of its two locations, one near the school, the other farther away but still accessible because most students had cars, or their friends did. Each promotional coupon offered “$5 off any food item” and showed the location. The nearby (farther) location was described as “2 (20) minutes away” and was in fact about 0.5 (5) miles away, but we referred to drive time rather than miles because travel time more meaningfully conveys distances [ 67 ]. The coupon also showed the address and a small map and stated the $5 off promotion could only be used at that location on that day by 7 PM (see Appendix B ). We asked participants not to share or discuss their coupon with others.

3.4. Measures

Research assistants were stationed at the two restaurant locations and collected the promotional coupons at the end of the redemption period. A subtle mark on each coupon identified each participant’s identification condition. We collected the promotional coupons from the cash registers, but we could not obtain the sales receipts. Therefore, we could not determine what participants bought or whom they were with if anyone. While having each individual sales receipt would have been more informative, the restaurants did not allow this, as it would have been obtrusive and slowed down their processes, which depend on speed.

The next day, participants completed an online survey with a restaurant nearness manipulation check which displayed their promotional coupon and asked: “How spatially close or far does this restaurant seem to you?” (very far to very close, very distant to very near, and very large travel time to very small travel time, 1–7, α = 0.91) [ 68 ]. A product attitude covariate was measured: “I like [restaurant X, named]” with 1 = strongly disagree and 100 = strongly agree, to control for product disinterest [ 69 ]. Demographics were measured in all studies.

To check the identification essay manipulation, two raters blinded to condition read each essay and answered [ 35 ]: “To what extent does this individual … seem to identify with University X?” “… discuss themselves as a part of the University X community?” “…discuss themselves as similar to other University X students?” “… discuss themselves as a prototypical University X student?” “… seem to feel that being a part of University X is important to them?” (1 = not at all, 6 = a great deal). Inter-rater reliability was high (α = 0.84).

3.5. Analyses

Restaurant patronage data were analyzed using 2 (nearness) × 2 (identification) logistic regressions as the outcome was binary (1 = redeemed coupon, 0 = did not redeem) and interactions were assessed using planned pairwise comparisons. Manipulation check data were analyzed similarly but using ANOVAs. In this and all lab studies, we included the product attitude covariate in our models and report covariate adjusted values.

3.6. Manipulation Check Results

Students who received the promotional coupon for the fast-food restaurant location that was near versus farther from school reported its location as nearer (F(1, 148) = 71.49, p < 0.001; M = 5.42 vs. 3.49), with no main effect for identification ( p = 0.28), no interaction ( p = 0.53), and no effect for the product attitude covariate ( p = 0.35). The raters judged the essays designed to elicit strong as compared to weak identification as more strongly identifying with the student community (F(1, 148) = 108.64, p < 0.001; M = 5.40 vs. 2.66), with no main effect for restaurant nearness ( p = 0.43), no interaction ( p = 0.89), and no effect for the product attitude covariate ( p = 0.58).

3.7. Main Results

On fast-food restaurant patronage, while there was no main effect for identification (b = −0.12, z(148) = 0.53, p = 0.60), there was a main effect for restaurant nearness (b = 0.77, z(148) = 3.33, p = 0.001), but it was qualified by an interaction between restaurant nearness and identification (b = 0.50, z(148) = 2.18, p = 0.03), and the product attitude covariate also related to patronage (b = 0.04, z(148) = 2.85, p = 0.004). Students who strongly identified with the student community patronized the near versus farther restaurant more (44% vs. 7%; b = 1.27, z(148) = 3.46, p = 0.001), while students who weakly identified patronized the near and farther restaurants comparably (28% vs. 19%; b = 0.26, z(148) = 0.94, p = 0.35). See Figure 2 .

Study 2 Fast-food Restaurant Patronage due to Nearness and Identification. Note: * p < 0.001 comparing 44% with 7% for the strong identifiers.

3.8. Discussion

In Study 2, we gave students a promotional coupon for a fast-food restaurant that was redeemable at only one location, either near or farther from school, and we observed coupon redemption. We also manipulated their identification with the student community. We found direct behavioral evidence that, among those who felt strongly identified with the student community, a fast-food restaurant near versus farther from school was a significant draw. Students who felt weakly identified with the student community were equally likely to redeem the coupon irrespective of restaurant location.

4. Study 3 Materials, Methods, and Results

4.1. design and participants.

In Study 3, we investigated the underlying mediating process that may have caused students who were strongly identified with their student community to patronize a nearby fast-food restaurant. The posited mediator was the perception of it being a social activity space, i.e., where friends could be found. The design was a 2 (restaurant nearness to school) × 2 (identification with the student community) between-subjects factorial with nearness manipulated and identification measured. Participants were 188 older adolescents, university students, with a mean age of 19.5 years, 54.8% female, 63% White Non-Hispanic, 4% Hispanic, 16% Asian, 1% Black, and 16% other (2+ ethnicities could be selected). We recruited 198 but dropped 10 with dietary restrictions precluding fast food (N near = 94; N far = 94).

4.2. Manipulations and Measures

Students completed a study “about consumer response to retailers” for partial course credit. Restaurant nearness was manipulated as follows: “Imagine you are just leaving the University X campus. You receive a text from a new donut shop at least 2 (20) minutes away from campus offering you an attractive promotional discount for donuts today only. Picture this place and the people there in your mind.” Then, we asked their restaurant patronage intent: “Would you redeem this promotional coupon to eat at the restaurant?” (1 = definitely not, 7 = definitely yes). Next, we performed a nearness manipulation check: “How spatially close or far does this restaurant seem to you?” (very far to very close, very distant to very near, and very large travel time to very small travel time, 1–7, α = 0.99). Then, we measured the mediator, the perception the fast-food restaurant was a social activity space to see friends: “Please indicate which items were salient to you when you decided whether to go eat at the restaurant”: “See friends” “Going to a place for people like me” “Be with people with whom I identify” (1 = strongly disagree to 7 = strongly agree; α = 0.73).

After this, we measured identification with the student community (see Appendix C ). We showed increasingly overlapping circles labeled “You” and “University X” (Tropp and Wright 2001) and asked: “Please click on the picture below that best describes how much you happily feel a part of your University X student community” (0 = no overlap, 7 = complete overlap).” Finally, we measured the product attitude covariate: “I like donuts” (1 = strongly disagree to 5 = strongly agree). The data were analyzed using 2 (nearness) × 2 (identification) ANOVAs, with interactions assessed using spotlight analysis [ 66 ]. Moderated mediation models used Hayes model 8 [ 70 ] with 5000 replications.

4.3. Manipulation Check Results

Students in the near versus farther restaurant condition reported the restaurant was nearer (F(1, 183) = 273.26, p < 0.001; M = 5.58 vs. 3.05). There was no main effect for identification ( p = 0.56), no interaction ( p = 0.27), and no effect of the product attitude covariate ( p = 0.53).

4.4. Main Results

We observed the hypothesized interaction between restaurant nearness and identification on restaurant patronage intent (F(1, 183) = 4.87, p = 0.03) which qualified the main effect for restaurant nearness that favored the near versus farther restaurant (F(1, 183) = 18.94, p < 0.001; M = 4.17 vs. 2.95), with no main effect for identification (F(1, 183) = 0.18, p = 0.67). Students strongly identified with their student community (mean + 1 SD) were more likely to intend to patronize the near versus farther restaurant (M = 4.54 vs. 2.58; t(183) = 5.32, p < 0.001). Students weakly identified with their student community (mean—1 SD), were indifferent to the near versus farther restaurant (M = 3.80 vs. 3.32; t(183) = 0.97, p = 0.33). The product attitude covariate also related to patronage (F(1, 183) = 25.08, p < 0.001).

4.5. Results on Mediation

We observed a marginal interaction between restaurant nearness and identification on the posited mediator: students’ perception of the restaurant as their social activity space (F(1, 183) = 2.87, p = 0.09), with no main effect for nearness (F(1, 183) = 0.78, p = 0.38) but a main effect for identification (F(1, 183) = 5.17, p = 0.02). Students who strongly identified with their student community (mean + 1 SD) were more likely to perceive the near versus farther restaurant as their social activity space (M = 4.21 vs. 3.66; t(183) = 2.21, p = 0.03); while students who weakly identified (mean—1 SD) perceived the near and farther restaurants comparably (M = 3.83 vs. 4.04; t(183) = 0.64, p = 0.52). The product attitude covariate was unrelated to this perception (F(1, 183) = 1.53, p = 0.22).

In a direct test of mediation, among students who strongly identified with their student community (mean + 1 SD), the effect of the near versus farther restaurant on patronage intent was mediated by the perception the restaurant was their social activity space (indirect effect = 0.18, SE = 0.11, 95% CI = 0.01, 0.46). Among students who weakly identified with their student community (mean—1 SD), there was no such effect (indirect effect = −0.01, SE = 0.09, 95% CI = −0.22, 0.16). See Figure 3 .

Study 3 Fast-food Restaurant Patronage Mediated by Activity Space Perceptions. Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

4.6. Discussion

In Study 3, we manipulated fast-food restaurant nearness to school, and we measured students’ identification with their student community and the theorized mediator. We found direct evidence of mediation. Students who strongly identified with their student community said they decided to patronize the nearby (vs. farther away) fast-food restaurant to see friends, indicating they perceived it to be their social activity space. Students who weakly identified with their student community did not perceive it this way or patronize it.

5. Study 4 Materials, Methods, and Results

5.1. design and participants.

Study 4 tested a mild form of student activism: a disparaging social media post from a student at the high school, indicating it would be a social liability to be seen at a fast-food restaurant. The design was a 2 (restaurant nearness to school) × 2 (identification with the student community) × 2 (social liability vs. control message) between-subjects factorial, with all three factors manipulated. Participants were 251 older high school students from MTurk, screened to be in high school but over the age of 17 to exclude minors as mandated by our human subjects review board. Virtually all were aged 18, 35% were female, 67% White Non-Hispanic, 15% Asian, 11% Hispanic, 8% Black, and 3% other (permitting 2+ ethnicities). We recruited 273 but dropped 22 who did not complete the identification manipulation (N near_strong_control message = 31; N near_strong_social liability message = 41; N far_strong_control message = 28; N far_strong_social liability message = 31; N near_weak_control message = 34; N near_weak_social liability message = 20; N far_weak_control message = 30; N near_weak_social liability message = 36).

5.2. Manipulations and Measures

The social liability message, described as a social media post from a student at their high school, stated: “Students at this school would never be seen by friends at fast-food restaurants.” The control message was likewise described as a social media post from a student at their high school: “The school library is now open on weekends.” These social media posts were displayed on mobile phones (see Appendix D ). Then, we used our prior methods to manipulate identification via an essay task, manipulate fast-food restaurant nearness using a burger restaurant (2 vs. 20 drive-time minutes) and measure restaurant patronage intent (“Would you redeem this promotional coupon…”).

We used our prior nearness manipulation check (α = 0.95). We used an identification manipulation check with increasingly overlapping circles “You” and “High School X” [ 37 ] that asked: “Please click on the picture below that best describes how much you feel part of [or close to, or happily part of] your High School X student community” (0 = no overlap, 7 = complete overlap, α = 0.94). Our manipulation check of the social liability message measured seeing that post (1 = strongly disagree, 5 = strongly agree), e.g., “Students at my high school would not like to be seen by friends at fast-food restaurants” (3 items, α = 0.82). Finally, we measured the product attitude covariate (“I like fast food” 1 = strongly disagree, 5 = strongly agree; 4 missing responses). The data were analyzed using 2 (nearness) × 2 (identification) × 2 (message) ANOVAs and interactions were assessed using planned pairwise comparisons.

5.3. Manipulations Check Results

Students in the near versus farther condition reported the fast-food restaurant was nearer to them (F(1, 238) = 32.35, p < 0.001; M = 5.16 vs. 4.02). Those in the strong versus weak identification condition reported more identification (F(1, 238) = 46.93, p < 0.001; M = 4.00 vs. 2.74). Those seeing the social liability versus control message reported what it said; students would not like to be seen at fast-food restaurants (F(1, 238) = 12.92, p < 0.001; M = 3.12 vs. 2.97). There were no other effects.

5.4. Restaurant Patronage Intent

As hypothesized (H2), there was a three-way interaction on restaurant patronage intent (F(1, 238) = 6.89, p = 0.009). There were no other effects except a main effect for the product attitude covariate (F(1, 238) = 22.70, p < 0.001). With the control message, strongly identified students increased their intent to patronize a fast-food restaurant if near versus farther from school (t(238) = 10.51, p = 0.009; M = 5.48 vs. 4.10); weakly identified students did not (t(238) = 0.07, p = 0.79; M = 4.85 vs. 4.95). With the social liability message, strongly identified students no longer increased their intent to patronize if near versus farther (t(238) = 0.91, p = 0.34; M = 4.87 vs. 5.24), and weakly identified students remained indifferent to nearness (t(238) = 0.57, p = 0.45; M = 4.94 vs. 4.60). See Figure 4 .

Study 4 Fast-food Restaurant Patronage after a Social Liability Message. Note: * p < 0.01 comparing 5.48 vs. 4.10 for the strong identifiers seeing a control message.

5.5. Discussion

We tested a mild form of student activism; a student posted that going to a nearby fast-food restaurant was a social liability. Others saw a control post. The effects were, again, limited to the strongly identified students. If they saw the control post, they were attracted to a nearby (vs. farther) fast-food restaurant; if they saw the social liability post, they were not.

6. Study 5 Materials, Methods, and Results

6.1. design and participants.

We tested a stronger student activism message; students announced a boycott of nearby fast-food restaurants. Student activism of this type is increasingly prevalent; thus, the message was realistic [ 71 ]. The design was a 2 (restaurant nearness to school) × 2 (social liability vs. control message) between-subjects factorial with both factors manipulated. All participants were manipulated to feel strongly identified with their student community. We studied 178 older adolescents, university students, with a mean age of 19.7 years, 68% female, 60% White Non-Hispanic, 6% Hispanic, 1% Black, 20% Asian, and 14% other (2+ ethnicities allowable). We recruited 193 but dropped 15 because of dietary restrictions precluding fast food or the identification manipulation not being done (N near, control message = 51; N near, social liability message = 41; N far, control message = 40; N far, social liability message = 46).

6.2. Manipulations and Measures

The social liability message was a color poster of students stating: “The University X student community boycotts fast food near campus.” The visually identical control message stated: “The University X student community boycotts tobacco shops near campus.” (See Appendix E ). We used our prior strong identification essay and manipulated nearness as 2 vs. 20 drive-time minutes. We used prior measures of restaurant patronage intent, the nearness manipulation check (α = 0.98), identification with the student community (α = 0.86), and the product attitude covariate. The social liability manipulation check asked whether “the poster encouraged the University X student community to boycott fast-food restaurants” (1 = strongly disagree to 5 = strongly agree). Data were analyzed using 2 (nearness) × 2 (message) ANOVAs and interactions using planned pairwise comparisons.

6.3. Manipulations Check Results

Students in the near versus farther condition reported the restaurant was nearer (F(1, 173) = 65.34, p < 0.001; M = 5.62 vs. 3.39). Students who saw the social liability versus control message reported the content correctly (F(1, 173) = 341.84, p < 0.001; M = 4.30 vs. 1.33). Identification was strong as manipulated (M = 4.33 out of 5). There were no other effects.

6.4. Main Results

Restaurant nearness and message interactively affected restaurant patronage intent (F(1, 173) = 3.89, p < 0.05) which qualified main effects for near versus far (F(1, 173) = 17.20, p < 0.001, M = 4.16 vs. 3.11) and social liability versus control message (F(1, 173) = 11.81, p < 0.001, M = 3.18 vs. 4.10), with product attitude covariate having no effect (F(1, 173) = 2.08, p = 0.15). When the strongly identified students saw the control message, as before, they reported higher intent to patronize the near versus farther fast-food restaurant (t(173) = 19.03, p < 0.001; M = 4.75 vs. 3.32), but when they saw the social liability message, this effect was nullified (t(173) = 2.32, p = 0.130; M = 3.44 vs. 2.91; see Figure 5 ).

Study 5 Fast-food Restaurant Patronage after a Social Liability Message. Note: * p < 0.001 comparing 4.75 vs. 3.32 for the strong identifiers seeing a control message.

6.5. Discussion

In Study 5, we showed strongly identified students a forceful activism message: a boycott against nearby fast-food restaurants, implying that going there would be a social liability. The strong identifiers who saw the control message were attracted to the nearby (versus farther) fast-food restaurant; those who saw the social liability message no longer were.

7. Study 6 Materials, Methods, and Results

7.1. design and participants.

Study 6 tested a health liability message stressing that fast food was unhealthy. The design was a 2 (restaurant nearness to school) × 2 (identification with the student community) × 2 (health liability versus control message) between-subjects factorial, with all three factors manipulated. Participants were 379 older adolescents, university students, with a mean age of 20.3 years, 48% female, 64% White Non-Hispanic, 12% Hispanic, 21% Asian, 1% Black, and 3% other. We recruited 425 but dropped 46 who had dietary restrictions precluding fast food; all completed the identification manipulation (N near, strong, control message = 46; N near, strong, health liability message = 45; N far, strong, control message = 40; N far, strong, health liability message = 57; N near, weak, control message = 59; N near, weak, health liability message = 45; N far, weak, control message = 46; N far, weak, health liability message = 41).

7.2. Manipulations and Measures

The health liability message was visually similar to the liability message used in Study 5. This message showed a similar group of students who proclaimed: “Students at this school do not like unhealthy fast-food restaurants.” Thus, the main emphasis was unhealthy food. The control message was: “The school library is now open on weekends.” (See Appendix F ). We used our prior manipulations of identification and nearness.

Next, we asked: “Would you make a purchase at this fast-food restaurant?” (1 = extremely unlikely, 7 = extremely likely). We checked our nearness manipulation as before (α = 0.98), and our identification manipulation (“I identify with the University X student community.” 1 = strongly disagree, 7 = strongly agree). We checked our message manipulation: “This study showed me a poster discouraging University X students from going to fast-food restaurants” (1 = strongly disagree to 5 = strongly agree). We measured the product attitude covariate as before. Data were analyzed using 2 (nearness) × 2 (identification) × 2 (health liability versus control message) ANOVAs and interactions were assessed using planned pairwise comparisons.

7.3. Manipulations Check Results

Students in the near versus farther condition reported the restaurant was nearer (F(1, 370) = 323.83, p < 0.001; M = 5.34 vs. 3.21). Those in the strong versus weak identification condition reported stronger identification (F(1, 370) = 6.54, p = 0.01; M = 5.10 vs. 4.83). Those shown the health liability versus control message reported the content correctly (F(1, 370) = 353.23, p < 0.001; M = 3.59 vs. 1.50). There were no other effects.

7.4. Main Results

There was a three-way interaction for nearness, identification, and health liability message on restaurant patronage intent (F(1, 370) = 4.97, p = 0.03), a main effect for nearness (F(1, 370) = 49.48, p < 0.001), a main effect for the product attitude covariate (F(1, 370) = 40.55, p < 0.001), but no other effects. The control message results replicated what we saw earlier. Those strongly identified with the student community reported higher intent to patronize the fast-food restaurant when near versus farther from school (t(370) = 4.03, p < 0.001; M = 4.48 vs. 3.10); weakly identified students did not (t(370) = 1.67, p = 0.10; M = 4.04 vs. 3.53). The health liability message results were different. This message failed to lower the attraction of nearby fast food among strong identifiers, and it increased fast-food attraction among weak identifiers. After seeing the health liability message, the strong identifiers continued to report higher intent to patronize the near (vs. farther) fast-food restaurant (t(370) = 3.35, p < 0.001; M = 4.31 vs. 3.26). The weak identifiers did likewise, primarily because they became attracted to the near restaurant (t(370) = 4.85, p < 0.001; M = 4.62 vs. 2.96; see Figure 6 ).

Study 6 Fast-food Restaurant Patronage Intent after a Health Liability Message. Note: * p < 0.001 for all comparisons shown.

7.5. Discussion

Study 6 tested a health liability message, stressing that fast food was unhealthy. Showing it to strong identifiers had no effect; a fast-food restaurant near (vs. farther from) school continued to increase patronage intent. Showing it to weak identifiers was counterproductive; now even they were attracted to the nearby (vs. farther) restaurant. Conceivably, the weak identifiers experienced reactance when told the food was unhealthy, and so they decided to patronize the nearby restaurant.

8. Final Discussion

8.1. contributions.

Fast-food restaurants near schools are problematic, contributing to poor diet, weight gain and obesity. Our novel hypothesis, supported by detailed data analysis, is that teenagers who have a strong sense of identity with their student community, although their risk is usually low, face the greatest risk of a fast-food restaurant near school, because they think the restaurant is their social activity place. Advocating policy and educational interventions to change this view has important practical significance for solving the problem of unhealthy consumption caused by fast-food restaurants near schools.

Our findings suggest new policy approaches to addressing the problem of unhealthy fast-food restaurants near schools, that are not reliant on zoning restrictions that have been tried in the past [ 1 ]. Zoning restrictions have largely been unsuccessful in the US, especially at protecting disadvantaged students [ 25 , 26 ]. We advocate the use of school policies, social marketing messages, and educational efforts targeted at students that seek to change their perception of fast-food restaurants near school from socially beneficial spaces to social liability spaces.

Specifically, we recommend that teachers use their educational toolbox to encourage student activism, e.g., boycotts against local fast-food restaurants. Local activism is an increasingly popular strategy for promoting social change in the US and abroad, used by students [ 71 ], employees [ 72 , 73 ], even corporations [ 74 ]. For instance, social studies, nutrition, or language teachers might encourage students to think critically about whether and how they have been targeted by unhealthy fast-food restaurants. If students understand they have been targeted by fast-food marketers who have encouraged them to eat unhealthy food since they were small children unable to think critically, they may want to do something, perhaps start a boycott.

8.2. Links to Past Literature

Our research complements past work that discovered that student demographics moderate their vulnerability to fast-food restaurants near schools [ 3 , 14 , 15 ]. We study a different moderating variable, not a demographic variable, but rather strong identification with the student community [ 38 , 39 , 43 ]. Strong identification generally protects students from risk [ 36 , 42 , 44 ], but in the case of fast food it elevates their risk because they perceive a fast-food restaurant near school as a social activity space where they can derive social benefits, i.e., see friends. Policymakers should adopt educational and messaging strategies to change this perception, so that going to a fast-food restaurant is a social liability. They should not stress the health liability, i.e., unhealthy food, as we found this to be ineffective.

Our work supports the geographers’ activity space framework which indicates that the most fundamental moderator of any nearby location effect relates to whether people perceive that location as their activity space [ 29 , 30 , 31 , 32 ]. However, we add to the work in geography by showing that students’ identification with their school community affects their activity space perceptions.

We also contribute to past work in marketing on social influences that often adversely affect food consumption. Studies have found that people tend to match others’ portion sizes despite their hunger [ 75 ], match others’ menu selections despite their preferences [ 76 ] and use food to signal preferred identities independent of other considerations [ 77 ]. We demonstrate another adverse social influence on food consumption by showing that adolescents will go to a fast-food restaurant, despite its unhealthy food, to see friends.

8.3. Theoretical and Methodological Contributions

Our work makes a theoretical contribution by showing that an individual difference variable, student identification with their student community, moderates their perception of whether they will see peers at a nearby fast-food restaurant and want to go there. Past research tells us that adolescents’ perceptions of peers strongly influence their use of drugs and alcohol [ 55 , 78 , 79 ], elevating social concerns over health ones [ 58 , 80 , 81 ]. We add the insight that peers also matter with fast food. While this may seem to be a logical extension, the focus of past fast-food research has been on restaurant location not peer perceptions. Activity space geographers have challenged the narrow focus on location, noting that perceptions of locations as activity spaces also matter [ 31 , 32 , 33 , 34 ]. However, we are the first to identify an individual difference variable, adolescent identification with the student community, which affects activity space perceptions. Moreover, we demonstrate how to measure activity space perceptions as a mediating variable, and how to test for mediation.

8.4. Limitations

Limitations of our research include that we focused on fast-food restaurant patronage not consumption. We do not know what students might have eaten at the restaurants and, thus, it is conceivable some might have chosen the relatively healthier items. We did not study socializing at the restaurants, only whether students decided to go to see friends. Only one of our studies (study 3) measured the theorized mediating process, about the nearby restaurant being a social activity space or hangout for friends. We used high school students in Studies 1 and 4, but otherwise used college students. Our findings replicate with both groups, consistent with extensive research indicating that adolescence extends from the teenage years through to about age 24 [ 79 ]. The entire period of adolescence is characterized by highly salient social goals and affiliation needs, and a tension between necessary dependence on parents versus independence from them, e.g., with respect to cars, meals, and privileges [ 82 ]. However, as the younger adolescents are understudied, more research should be done on them.

We also recommend studies of other risky locations near schools, to ascertain if students who are strongly identified with their student community are especially vulnerable. What about nearby liquor, tobacco, nicotine vape or pot (cannabis) retailers; do they attract students who are strong identifiers? What about nearby fitness centers or fresh produce markets (farmers markets); do they attract strong identifiers but elicit positive behaviors? In addition, researchers should examine adults with workplaces nearby fast-food restaurants who vary in workplace identification, to see if the results replicate. Activity space researchers have replicated their findings among adolescents and adults, and replication work would be beneficial here too. Researchers should study other negative behaviors that might be evoked by strong identification with a student community, e.g., aggressive behavior at intercollegiate sports events. Among geography researchers, it would be useful to study other individual difference variables that may affect perceptions of locations as social activity spaces. “Location, location, location” is indeed important, but social perceptions of locations matter too and should be investigated further.

9. Conclusions

Fast-food restaurants near schools are problematic, contributing to poor diet, weight gain, and obesity. Adolescents who strongly identify with their student community, while generally at lower risk, face the greatest risk from fast-food restaurants near school because they perceive the restaurants as their social activity spaces. Education and policy should be directed at changing that perception. Students must perceive the restaurants differently, as well as adults.

Acknowledgments

The authors thank Russ White, the Numeric and Spatial Data Specialist at the Robert E. Kennedy Library at California Polytechnic State University, and his research team for their extraction of spatial information about fast food near schools using ESRI GIS (Geographic Information System) tools.

Appendix A. Study 1 Supplemental Analyses

Model with student ethnicity and income. We included ethnicity and low income (free or reduced-price meals) as covariates in the Study 1 hierarchical regression model and verified our results held even after controlling for these variables; see table below. Spotlight analyses with covariate-adjusted means showed the expected pattern: Among those reporting stronger identification with the student community (mean + 1 SD), a fast-food restaurant near (vs. farther from) school related to restaurant patronage (b = 0.36, df = 4472, z = 1.93, p < 0.05); while among those reporting weaker identification with the student community (mean—1 SD), nearness did not relate to patronage (b = −0.20, df = 4472, z = 1.14, p = 0.26). Sample sizes and df are lower in these analyses due to some missing data.

Study 1 School Survey Results on Fast-food Restaurant Patronage with Covariates.

Note: Native American was the comparison ethnicity, but the results replicate using other ethnic comparison groups. There were some missing values for ethnicity and low income.

Model with hierarchical Poisson regression. The dependent variable in this study was measured as “How many times did you eat fast food in the past 24 hours?” The response options were 0, 1, 2, 3, 4 or 5 or more times. Since this is technically a scale rather than count, and to be consistent with past work, we analyzed the data using hierarchical ordinary least squares regression. However, we see similar results with hierarchical Poisson regression. See the table below.

Study 1 School Survey Results on Fast-food Restaurant Patronage Using Poisson Hierarchical Regression Model.

Appendix B. Study 2 Methodological Details

Restaurant nearness to school was manipulated using the following promotional coupon.

Coupon used in Study 2 to Manipulate Restaurant Nearness to School.

Appendix C. Study 3 Methodological Details

Identification with the student community was measured as follows: “Please click on the picture below that best describes how much you feel happily a part of your University X student community” (0 = no overlap, 7 = complete overlap; see below). University X was identified by name and was the students’ university.

Diagram used to Measure Identification with Student Community.

Appendix D. Study 4 Methodological Details

The left post shows the social liability restaurant message, the right post shows the control message. Both posts were described as from a student at their high school. After showing one of these messages to students, we asked them “What does this Twitter message say?” to increase salience.

Images used in Study 4 to Manipulate Restaurant as Social Liability.

The promotional coupon used to manipulate restaurant nearness stated: “Imagine you are just leaving your high school, and you are moderately hungry. You receive a text from a new fast-food restaurant 2 (20) minutes away from where you are at your high school, offering you an attractive promotional discount today only for dine-in orders (meaning you must eat in their dining area) of any burger meal, fries and a regular coke.”

Appendix E. Study 5 Methodological Details

The top image shows the social liability restaurant message, the bottom image shows the control message. Both messages were introduced as “Consider the following poster at University X”. After showing students one of these messages, we asked them “What does this poster mean?” to increase salience. Note: Squares hide University X identification to protect confidentiality. Participants saw the poster without the squares, so University X (their university) was identified.

Images used in Study 5 to Manipulate Restaurant as Social Liability.

The above images were based on photos of actual student activism against fast-food restaurants like the one shown below [ 71 ].

Actual Student Activism Against Fast-food Restaurants.

Appendix F. Study 6 Methodological Details

The top image shows the health liability restaurant message, the bottom image shows the control message. Both messages were described as emails from the student council. After showing students one of these messages, we asked them, “What does this poster say?” to increase salience. Note: Squares hide University X identification to protect confidentiality. Participants saw the poster without the squares, so University X (their university) was identified.

Images used in Study 6 to Manipulate Restaurant as Health Liability.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, B.D. and C.P.; methodology, B.D. and C.P.; formal analysis, B.D. and C.P.; investigation, B.D.; resources, B.D. and C.P.; writing—original draft preparation, B.D. and C.P.; writing—review and editing, B.D. and C.P.; visualization, B.D. and C.P.; supervision, B.D. and C.P.; project administration, B.D. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

These studies were conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Boards of California Polytechnic State University (2020-009-OL and 2020-010-OL, 1/2020) and Baylor University (360816, 7/2012).

Informed Consent Statement

Informed consent was obtained from all subjects involved in each study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

The first McDonald’s in Moscow that drove the city mad, 1990

On January 31, 1990, the first Soviet McDonald’s opened in Moscow. The first McDonald’s ever in Soviet Union.

Nowadays it’s hard to believe that thousands of people would be willing to stand out in the cold for hours just to try a McDonald’s hamburger. But when the first McDonald’s arrived in Moscow in 1990, the whole city went mad.

The Moscow McDonald’s initiative was a joint venture between McDonald’s of Canada and the Moscow city council. A plan first envisioned when George Cohon, founder, and CEO of McDonald’s Canada, met Soviet Union officials at the ’76 Summer Olympics in Montreal. And almost a quarter of a century later, on January 31st, 1990 it became a reality.

The Russian capital’s inaugural McDonald’s set the record for most customers on its first day of opening by serving over 30,000 hungry punters. Budapest’s main branch of McDonald’s previously held the record, with 9,100 clients.

Thousands of Muscovites flocked to the new burger joint, forming lines several kilometers long in the center of Moscow on Pushkinskaya Square. The crowds of people were so huge that scores of policemen were sent to control the commotion, much like security at rowdy football matches.

It was the largest McDonald’s in the world at the time of its construction.

At the time of its construction, it was the largest McDonald’s restaurant in the world. A venue with 900 seats with a staff of about 600 workers that were carefully selected from 35,000 applicants.

As a result, the first workers were the crème de la crème of Soviet youth: students from prestigious universities who could speak foreign languages with brilliant customer service skills were hired.

This new workforce was a sharp contrast to the typical Soviet service sector, known for being dismissive, unsmiling, and cold. Soviet people were so accustomed to rude, boorish service that when they were faced with the polite manners and beaming faces they were completely shocked. In fact, the customers felt so uneasy while being served by someone who was smiling that the McDonald’s chiefs asked their employees to smile less.

For the ordinary Soviet citizen during perestroika, McDonald’s offered a glimpse of what life (and eating out) was like over the Iron Curtain. People from Soviet Union heard so much about western culture without being able to get near it, so Soviet citizens really went mad when the golden arches rocked up in Moscow.

And a venue with 900 seats needed a lot of employees, too.

However, McDonald’s was not cheap in those days. In a country where the average salary was about 150 rubles per month, a Big “Mak” was selling for 3.75 rubles. One Big Mac cost the equivalent of a monthly bus/metro pass.

The summer came, but the lines just kept growing. People from other cities were flocking the McDonald’s restaurant just for a single hamburger. “We stood under the melting sun for around eight hours,” photographer Mitya Kushelevich recalled. “That wasn’t so much of a problem as we were used to standing in lines for days just to get our monthly ration of sugar and tea.”

“Once inside we were blown away by the number of young cashiers behind the huge counter, smiling, moving like bees, serving one meal after another.

Nothing like our fat old ladies in white gowns sitting in front of empty shelves, pyramids of dusty canned food as window dressing.” “I still remember how insanely huge the milkshake looked and I didn’t know how to hold a Big Mac with my tiny hands.”

In 1991 and 1992, long lines could still be seen and people had to wait for hours to enter. The crowds outside the Moscow restaurant did eventually die down a little from Jan. 31,1990, when more McDonald’s were opened in Russia.

The unveiling of the next McDonald’s restaurants were also considered big historic moments. The opening ceremony of the second restaurant in 1993 was even attended by President Boris Yeltsin.

In a country where unemployment did not exist, 35,000 people applied for a job in the fast food restaurant.

Around 600 were hired.

The venture had been in talks with the Soviet officials since 1976.

And you could say that the appearance of this notorious symbol of capitalism was a sign that times were changing.

Reportedly, the restaurant expected to serve around 1,000 during its first day, but more than 5,000 Russians lined up in Pushkinskaya Square before it even opened.

One Big Mac cost the equivalent of a monthly bus/metro pass.

The summer came but the lines just kept growing. People from other cities were flocking the restaurant just for a single hamburger.

“We stood under the melting sun for around eight hours,” one visitor said.

“That wasn’t so much of a problem as we were used to standing in lines for days just to get our monthly ration of sugar and tea”.

“Once inside we were blown away by the number of young cashiers behind the huge counter, smiling, moving like bees, serving one meal after another”.

“Nothing like our fat old ladies in white gowns sitting in front of empty shelves, pyramids of dusty canned food as window dressing”.

“I still remember how insanely huge the milkshake looked and I didn’t know how to hold a Big Mac with my tiny hands”.

The Moscow McDonald’s initiative was a joint venture between McDonald’s of Canada and Moscow city council.

A plan first envisioned when George Cohon, founder and CEO of McDonald’s Canada, met Soviet officials at the ’76 Summer Olympics in Montreal.

“I’m particularly proud of the people story behind the first opening, both from Canada and Russia, learning from each other and working as one team”.

“This is a story about co-operation between nations”.

“And it is also a story about the Soviet who saw a sign outside reading ‘Rubles Only’ – and who said to me, ‘This is my restaurant’”.

The opening drew many important people.

The opening ceremony of the second restaurant in 1993 was even attended by President Boris Yeltsin.

Waiving the capitalism “flag”.

Huge crowd lined up outside the first McDonald’s in Moscow.

And people couldn’t get enough.

In total, over 30,000 customers passed through the doors on the opening day of the restaurant.

Setting a record for the number of customers served by a single McDonald’s in a day.

An old lady enjoyed her burger.

The Soviet Union dissolved on December 26, 1991.

(Photo credit: Sputnik).

Updated on: November 20, 2021

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The World Youth Festival as a Soviet Cultural Product during the Cold War

This article discusses Soviet cultural diplomacy from the perspective of cultural production. It analyses a Soviet-sponsored international event, the World Festival of Youth and Students, as a cultural product created within the socialist system. The first festival was held in Prague in 1947, and the tradition continued throughout the Cold War period until today. Earlier scholarship has examined the festival as a propaganda tool, a forum for cross-cultural encounters, and a battlefield of the cultural Cold War between the capitalist West and the socialist East. Much has been written about individual world youth festivals and national delegations, while the design, cultural background and fundamental ideas behind the event have been much less acknowledged. By employing the concept of mega-event and comparing the festival with iconic international events, such as World’s Fairs and the Olympic Games, it discusses the festival’s composition and evolution, its reception, and how the even...

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