Food choices in context

Food choices in context Maartje P. Poelman*, Ingrid H.M. Steenhuis† *Utrecht University, Utrecht, The Netherlands, †VU University Amsterdam, Amsterdam, The Netherlands

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Every day people have to make food choices. People have to decide what to eat, when to eat, and where to eat. People also have to decide where to buy their food. In the supermarket, at the farmers market, in a convenience store, or in one of the other many stores that sell food nowadays. Will people prepare their own meal, or will they go out to a restaurant, to a fast-food outlet, or get a take-away? When on the go, do people purchase snacks, meals, or drinks at the petrol or train station, or do they take snacks from home? Day in, and day out, people have to make these decisions and choose what to eat. Although these decisions may seem to be properly thought-out and rational, many food choices are habitual, automatic, and steered by social and physical environmental cues. Moreover, food choices are driven by bigger societal forces such as globalization, welfare, and urbanization. Therefore, peoples’ contexts cannot be ignored in research into food choices. This chapter discusses the context of food choices. First, a theoretical underpinning of the importance of context in food choice research is outlined. Thereafter, different contextual levels are discussed. We provide an overview of the macro context, local context, and the social context. Subsequently, we provide insight into several contextual settings in which food consumption or food purchases are taking place. These are the supermarket, workplace cafeteria/restaurant, home, and online/digital world. For each context, sample studies are provided to illustrate influences on food choices. The majority of these studies are in the field of public health nutrition, social psychology, and consumer marketing.

7.1

Why is the food choice context important?—A theoretical perspective

Food choices are complex. The reason why we eat what we eat is multifactorial, and changes from person to person. Not only do individual factors (such as neurobiological, physiological, psychological determinants) contribute to eating decisions, but also wider sociological, ecological, environmental, and cultural factors (e.g., culture and economics of food production) steer food choices. Yet, the conventional economic viewpoint is that humans are rational creatures who make deliberate decisions in their own best interest. However, over the past decades, evidence has revealed that people are often irrational and food choices are not always deliberated or in people’s best interest. Food choices are often the result of automatic and undeliberated processes. In peoples’ food choices, senses such as visual, olfactory, and auditory factors Context. https://doi.org/10.1016/B978-0-12-814495-4.00007-6 Copyright © 2019 Elsevier Inc. All rights reserved.

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also play a role, but often occur without full awareness, and food choices are, in large part, the result of undeliberated responses to contextual food cues, many of which lead to increased caloric consumption and poor dietary choices (Cohen & Babey, 2012). The fact that people do not always make food choices in their best interest is shown by the rise in obesity over the past few decades. Persistently consuming more calories from foods than are expended leads to a positive energy balance that in turn, results in weight gain. The energy intake side of the balance, which is the result of food choices, has been recognized as a dominant driver of the rise in obesity (Slater et al., 2009; Swinburn, Sacks, Lo, et al., 2009). In the short term, food intake can serve the best interest of good taste, satiation, and pleasure that food can bring. However, in the long term, overconsumption does not serve the best interest of individuals. Some individuals with obesity are stigmatized, bullied, experience chronic co-morbidity (e.g., type 2 diabetes, cardiovascular disease and depression), and their life expectancy drops considerably. It is argued that being overweight and obesity are the result of a normal response to an abnormal environment. In terms of economics, obesity (and overconsumption) can be seen as the result of market failure, as the market fails to deliver the best output for society, and puts a long-term burden on healthcare costs (Anand & Gray, 2009; Moodie, Swinburn, Richardson, & Somaini, 2006). Several theories underpin the influence of peoples’ contexts in behaviors such as food choices. These theories go beyond the more traditional health behavior conceptual models that explain individual factors of behaviors such as food choices. For example, according to the theory of planned behavior, peoples’ intention to engage in a certain behavior is central. Intentions are clear decisions to act in a certain way, and seen as an indication of how hard people are willing to try, and how much effort they want to put in to a certain behavior. The stronger the intention, the more likely it is that the behavior will be engaged in (Ajzen, 1991). Yet, intention cannot fully explain behavioral decisions. Moreover, people’s intentions to act in a certain way (e.g., I want to eat vegetables every day) do not always translate into the actual behavior (e.g., actual daily vegetable intake), also called the (Sheeran and Webb, 2016) which also shows that other—personal and environmental—factors steer behavior. Many theories and conceptual models with respect to the influence of contextual influences on food choices have been developed over the past few decades. For example, the social cognitive theory (Bandura) describes how individuals develop and maintain certain behavioral patterns, such as food consumption. According to this theory, a dynamic interaction between the person, the persons’ behavior, and the environment in which the behavior is performed steers people’s behavior, and these factors constantly influence each other (Bandura, 1989). Individual factors include cognitive, affective, and biological events. The factor behavior is rather broad, and includes, for example, people’s capacity to perform a behavior (e.g., skills to prepare a healthy meal), expectations of the behavior, and people’s self-efficacy. The environment includes social and physical influences. Social influences are behaviors of family members, peers, or role models. By observing the behaviors of others, people learn to behave in a certain way. The physical environment includes factors that steer

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behavior, such as the availability and prices of foods. Besides that, the actual environment, and people’s perception of the environment, also need to be taken into account. Also, the dual process theory reflects the importance of the context in which food choices are made, and provides an understanding of two different psychological processes steering people’s behavior and choices. On one hand, behavior and choices are made unconsciously or automatically, and may result in system 1, which includes behavioral responses to environmental factors of which individuals may even not be aware. These responses are intuitive, fast, unintentional, and emotional. On the other hand, behavior can be the result of system 2, including well-deliberated, controlled decisions that are rational, reasoned, and logical (Kahneman, 2011). A dual process view is used to gain an understanding of the circumstances in which food choices are made. According to the Environmental Research Framework for Weight Gain prevention (EnRG framework), food choices may be conscious decisions in response to the environment, or a result of undeliberated responses to contextual cues (Kremers et al., 2006). For example, a supermarket in which fruits and vegetables are nicely presented and advertised may positively steer individual attitudes and beliefs toward eating fruit and vegetables, and might improve people’s intention to buy these products (system 2). On the other hand, the sight and the nice smell of fruits and vegetables may prompt individuals to purchase these products (system 1) (Brug, Kremers, van Lenthe, Ball, & Crawford, 2008). Ecological models of behavior also highlight the influence of multiple environmental contexts (e.g., physical and policy circumstances) of behaviors, while taking individual, social, and psychological influences into account. Many ecological models have been developed over the past decades, all including this multi-level structure, and underpinning the interacting effect of factors across these levels on food choice behaviors (Sallis, Owen, & Fisher, 2015). Therefore, food contexts may have a different impact on different individuals. For example, a food truck in the neighborhood (local context) selling ice cream on a hot summer day may have a different impact on an individual with a strong intention to eat healthily versus an individual who does not, or on a single person versus a family with children walking by (Brug et al., 2008). Food policies or regulations may also have a different impact on different people. For example, the recently introduced soft-drink tax is having a different impact on people with a low socio-economic position, compared with those with a high socioeconomic position (Batis, Rivera, Popkin, & Taillie, 2016). To summarize this overview, several theories and scientific viewpoints underpin the importance and interaction between personal, intrapersonal, and environmental determinants, indicating that several circumstances influence food choices. One should be aware that there are several other theories and models that address the importance of contextual influences on food choices, but this paragraph underpins some of the theories that shaped the field of contextual food choices. Besides, in line with existing ecological models, we compose a food choice context framework (Fig. 7.1), indicating different contexts that will be outlined in this chapter that should be considered when conducting food choice research (Fig. 7.1).

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Fig. 7.1 Contexts of food choices.

7.2

Macro context

The macro food context is an intangible and invisible environment. It is not a welldefined place or setting where people come together, but is rather an anonymous context that steers the characteristics of micro-level food contexts (Swinburn, Egger, & Raza, 1999). For example, food production, safety, and price; and trade, agriculture policies, regulations, and agreements; which impact all aspects of the food supply chain (from production to sales), fall under the macro-context, and may steer national and local environments in which food choices take place. For centuries, people have attempted to overcome food scarcity and hunger, as they were dependent on the success of crops that were influenced by seasonal variations (Kapsiotis, 1975). The onset of the industrial revolution was crucial for stable food production, and led to an increase in the availability of dietary energy (Caballero, 2007). However, after World War II, evident changes in agricultural policies (e.g., subsidies), farming practices (e.g., factory farming), and technical innovations (e.g., irrigation) (Bleich, Cutler, Murray, & Adams, 2008; Tillotson, 2004; Wallinga, 2010) influenced the macro food context. These technical, political, and organizational developments in the past resulted in a farm system that was less labor-intensive and more efficient, that accelerated growth, and eventually resulted in the mass production of food (Swinburn, Sacks, Hall, et al., 2011). More societal developments, such as globalization, urbanization, and increases in economical welfare are also macro contextual factors that steer food choices. The so-called nutrition-transition shows a shift in dietary patterns due to several macro contextual changes over the past several decades (Popkin, 1993). For example, as a result of globalization, Western food companies spread to low-income and middle-income countries, as a result of which Western, often highly processed food, became available and more easily accessible. For example, the number of McDonald’s outlets increased from 5 in 1985, to 100 in 1992, to 214 in 1996, to 568 in 2001 in Brazil, reflecting an increase of 11.280% in a 16 year period (Gheza´n, Mateos, & Viteri, 2002). Also, in the Asia Pacific region, the number of these outlets increased, from 951 outlets in 1987 to 7135 in 2002, reflecting an increase of 650% in a 15 year period (Trail, 2017).

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In the United States, the number increased from 7000 outlets in 1985 to 13,099 outlets in 2001, reflecting an increase of approximately 87% (Gheza´n et al., 2002). Although the number of these fast food outlets is still higher in the USA, the relative growth has been higher in the lower-middle income countries. Also, other food sources, such as supermarkets (Reardon & Berdegu
e, 2002; Weatherspoon & Reardon, 2003), entered and expanded in developing countries. Such macro contextual influences have caused changes in food consumption patterns (Drewnowski & Popkin, 2009). For example, in China, animal-based foods tripled from 30 g to 103 g per day, and the energy intake from fat increased from 7.6% to 22.5% between 1949 and 1992 (Du, Wang, Zhang, Zhai, & Popkin, 2014). These changes are also reflected by the increasing number of residents who are overweight and obese in these countries (Popkin, Adair, & Ng, 2012). By way of an illustration, the number of children (2–18 years) considered obese has risen substantially in the past two decades. In 1991, 6.2% of Chinese children were overweight. In 2000, this had risen to 8.5%, and in 2011, the percentage was 15.4% (Gordon-Larsen, Wang, & Popkin, 2014). In the years ahead, ongoing challenges will define and reshape the macro context of food choices. For example, technological and digital developments, the growing world population, and sustainable development goals will drive the macro-contextual playing field of food choices. Macro contextual factors that become visible in the local contexts are, for example, those of pricing strategies (e.g., the price of food, as affected by subsidies and taxes) and regulations shaping product characteristics (e.g., information presented on food labels or the size of food packages). Pricing strategies affect food choices, and are used to improve food choices. A review including pooled analyses indicated that a price decrease of 10% on healthy foods increased the consumption of healthy foods by 12% (95%CI ¼ 10%–15%) and, more specifically, increased the consumption of fruits and vegetables by 14% (95%CI ¼ 11%–17%). A 10% price increase on unhealthy foods decreases the consumption of unhealthy products by 6% (95%CI ¼ 4%–8%). Each 10% price increase reduced sugar-sweetened beverage intake by 7% (95% CI ¼ 3%–10%) (Afshin, Pen˜alvo, Del Gobbo, et al., 2017). Worldwide, several countries have already implemented a sugar sweetened beverage tax. For example, Mexico implemented a tax on nonessential foods and sugar sweetened beverages in 2014. Observational data indicates a decline in purchases of these products after one year (5.1%), with larger effects among low SES households (10,2%) (Batis et al., 2016). Another example is that of food labeling regulations. In many high income countries, it a requirement to provide nutritional information on all packed food and beverage items, including a recommended serving size that reflects “the recommended amount to consume in one sitting.” However, different international regulations exist. In Australia and New Zealand, it is mandatory to display a recommended serving size, although standard serving sizes for food and beverages are not provided. In contrast, regulated serving sizes are available for the USA and Canada, including acceptable ranges in milliliters, within which beverage serving sizes must fall. What is more, package sizes differ substantially between countries. For example, the mean package size (bottle) of Dutch SSBs ((1313 (323) mL) is significantly smaller compared with the bottle sizes in New Zealand ¼1481 (595) mL,

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Australia ¼ 1542 (595) mL or Canada ¼ 1550 (434) mL) (Poelman, Eyles, Dunford, et al., 2016). Nevertheless, lacking national regulations also influence serving size availability. For example in the Netherlands, coffee, milkshakes, and ice cream are often for sale in different sizes, denoted with “small,” “medium,” or “large.” Yet, which amounts (e.g., milliliters) reflect these annotations are variable. For example, the sizes of milkshakes varied for different estimates; small was 210–490 mL; medium was 340–570 mL; and large was 440–660 mL (Poelman & Steenhuis, unpublished data).

7.3

Local context

With respect to the local context of food choices, we refer in this chapter to certain areas (e.g., neighborhood, city, or municipality) that include a range of facilities and settings in which food choices take place (Swinburn et al., 1999). There are several ways to conceptualize the local context in research with respect to food choices (Thornton, Pearce, & Kavanagh, 2011). Often used are the availability and the accessibility of food outlets (e.g., supermarkets, convenience stores, restaurants) in people’s living environment, or the so-called community nutrition environment (Glanz, Sallis, Saelens, & Frank, 2005). Availability refers to the presence and number of certain food outlets available in a pre-defined area. Public buildings (train stations), schools, recreation and sports facilities offering foods may also be included in the local contexts. Accessibility refers to the easiness of access to a particular food outlet, with more accessible destinations having lower travel costs in terms of distance, time, or monetary resources (Handy & Niemeier, 1997). Both the accessibility and availability of food outlets have been studied in heterogeneous ways; for example, studies define the food environment as the number of food outlets in a certain area (census tract, neighborhood, street network buffer around the home; distance to the nearest store, travel time to the store), or perceived availability or accessibility of certain products (e.g., fruits or vegetables) (Caspi, Sorensen, Subramanian, & Kawachi, 2012a). Later in this chapter we discuss the characteristics and impact on food choices of individual settings in more detail (also called the consumer nutrition environment) (Glanz et al., 2005), but here we focus on the overall local context in which all these settings are established. Several studies have been conducted on the local food context over the past few decades. On one hand, studies have been conducted to measure and define the local food context, and to detect changes over time. On the other hand, multiple studies have been conducted to examine associations between the local food context and food choices (e.g., food intake). Many studies with respect to defining the local food context have focused on so-called “food deserts,” defined as disadvantaged urban areas with poor availability and limited access to healthy foods (i.e., Osorio, Corradini, & Williams, 2013). In high-income countries, often the presence or absence of supermarkets in a certain area is taken into account to define food deserts as selling fresh and healthy foods such as fruits and vegetables. There is some evidence of the presence of food deserts in the United States, although evidence of food deserts is mixed for Canada (Larsen &

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Gilliland, 2008; Lu & Qiu, 2015; Smoyer-Tomic, Spence, & Amrhein, 2006), or is lacking in European countries (e.g., in the Netherlands) (Helbich, Schadenberg, Hagenauer, & Poelman, 2017). Nevertheless, most studies have been conducted in smaller areas (e.g., in cities), most often in high-income countries, and for many low- and mid-income countries, insight in the presence or absence of food deserts is lacking. Nevertheless, the concept “food desert” has been disputed over the past few years, as only a small number of residents shop for groceries within their own census area, and can use a car to access a supermarket that is not in walking distance. For example, a study showed that the vast majority of households (93%) living in food deserts have access to a car (Ploeg, Breneman, Farrigan, et al., 2009). Another point of critique is that food deserts may have been used as strategy to open more supermarkets. Yet, it is debatable whether simply enlarging food outlets that offer healthy food options, without restrictions on unhealthy options, has a beneficial impact on healthy food choices (Cohen, Sturm, Scott, Farley, & Bluthenthal, 2010; Cummins, Petticrew, Higgins, Findlay, & Sparks, 2005; Wrigley, Warm, & Margetts, 2003). By way of an illustration, a quasi-natural experiment that evaluated the impact of the opening of a large supermarket in a deprived Scottish community showed no population impact on daily fruit and vegetable consumption (Cummins et al., 2005). In response to food deserts, the term “food swamps” was introduced more recently to define local food contexts in which healthy fresh and whole foods are available, but where there is an overabundance of ultra-processed (unhealthier) foods sold in excessive numbers of food stores, such as fast food outlets, convenience stores, or petrol stations (Luan, Law, & Quick, 2015; Osorio et al., 2013). To illustrate, a Dutch study has been conducted recently, measuring the local food context within a 400 m walking distance of secondary schools in a large city in the Netherlands. The authors conclude that unhealthy food and drink products were predominantly for sale and promoted. Fruit was for sale in less than a quarter of the outlets around the schools (23.5%), and this was even less for vegetable snacks (12.2%); whereas sugar sweetened beverages (84.3%) were more often available than lite drinks (77.4%) or bottled water (76.0%) (Timmermans et al., 2018). Another recent study from the United States even indicates that the presence of food swamps is a stronger predictor of obesity rates than food deserts (Cooksey-Stowers, Schwartz, & Brownell, 2017). Theoretically, neighborhoods offering low access to healthy foods are expected to steer individual food choices disadvantageously with respect to health, and vice versa for neighborhoods offering high access to healthy food. Studying the influence of local food contexts on food choices is empirically complex, and evidence is inconsistent. A review study including 38 studies that explored the local food environment and diet found moderate evidence in support of the causal hypothesis that neighborhood food environments influence dietary health (Caspi, Sorensen, Subramanian, & Kawachi, 2012b). A large issue was that the overall reproducibility was lacking because of the absence of a standard measure of local food access, and assessment measures varied considerably across the included studies (Caspi et al., 2012b). Similar limitations were mentioned by a more recent review, including 51 studies on the community food environment-diet relationship. Moreover, only 32% of the associations between the food environment and obesity-related outcomes were in the expected

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direction, 58% showed no association, and 10% were in the unexpected direction (Gamba, Schuchter, Rutt, & Seto, 2015). The most recent review, including 432 studies that were conducted between 2007 and 2015, emphasize that work is needed to understand construct validity as it relates to measures used to assess the food environment in studies determining the association with dietary behaviors. The authors conclude that it remains important to understand how the food environment influences individual and population-level health. Additionally, they stress that it is important to see the food environment as one construct in a larger, ecologically conceptual model, and that we need to enhance the level of interdisciplinary work between different disciplines working in the field (Lytle & Sokol, 2017). There are also several limitations in the literature to understanding the impact of the local food context, such as the majority of cross-sectional studies, and the wide variety of measures of food-outlet availability and accessibility (e.g., reliance on commercial business listings, ignoring changes in availability over time) (Gordon-Larsen, 2014). Longitudinal studies are needed to discern causality, as approximately 14% of the studies included had a longitudinal design (Lytle & Sokol, 2017). What is more, most studies conducted focused on achieving a better understanding of people’s interaction with a static local food context. From a this static viewpoint, the local food context is a predefined area, often related to people’s living environment; for example, the availability and accessibility of food outlets in residential neighborhood and census tracks, or “buffers” around the exact addresses of the individual (e.g., all outlets that can be accessed within 500 m). Yet, during the day, people not only undertake daily activities in close proximity to their home, but also travel to diverse places (e.g., work, shopping center) where they also face facilities and settings in which they make food choices. From this dynamic perspective, not the residential area, but the individual is the starting point in defining his or her personal local food context, or also people’s activity space (Crawford, Jilcott Pitts, McGuirt, Keyserling, & Ammerman, 2014). Although the latter may define exposure more specifically, one should be aware of selective daily mobility bias. This bias refers to the tendency of people to choose routes based on their personal needs and preferences, and may bias the association between the local food context and food choices (Chaix, M
eline, Duncan, et al., 2013). Therefore, insights about the decision-making process underlying people’s food choices in the local contexts are a necessity. Yet, most studies conducted so far lack this information (Gordon-Larsen, 2014). Although we currently lack a full understanding of the interplay between the local food context and food choices, including underlying mechanisms, local policy efforts have been introduced to improve the accessibility of healthier food outlets in the local food context. For example, the London (UK) mayor recently announced (2017) a plan to ban fast-food outlets from opening within a quarter mile radius of primary and secondary schools in London. In Amsterdam (the Netherlands), food companies are no longer allowed to advertise unhealthy products aimed at citizens younger than 18 in almost 60 metro stations. These examples show efforts to shape the local context to steer food choices in a positive direction with respect to health. The effectiveness of these efforts needs to be evaluated in the years ahead.

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Social context

Food and eating are entangled with our social lives, and often people eat together. The social context encompasses social relationships and cultural milieus within which defined groups of people function and interact. Individuals can often have multiple social environments simultaneously (e.g., family, colleagues, friends) that are dynamic and change over time (Barnett & Casper, 2001). People around us—our social context—may regulate, influence, or constrain our eating behavior. Several social influences on food intake are described in the literature, and also addressed more extensively in Chapter 2. Social facilitation of eating refers to the phenomenon of increased food consumption when people eat together instead of eating alone. In 1989, the first study into the particular influence of the number of other people and food intake was explored by means of an uncontrolled food diary study. Over a one-week period, participants filled out a food diary, including the social conditions of the meal. De Castro and de Castro found that individuals eating together ate significantly more (on average 44%) than individuals eating alone (de Castro & de Castro, 1989). Various experimental studies followed in subsequent years, showing comparable results: intake during group dinners is higher than intake during solo dinners (Berry, Beatty, & Klesges, 1985; Edelman, Engell, Bronstein, & Hirsch, 1986). In particular, social facilitation is present when participants eat together with others (rather than in the presence of a noneating audience) (Hetherington, Anderson, Norton, & Newson, 2006; Salvy & Pliner, 2010), and when eating together with friends (rather than strangers) (de Castro, 1994). In practice, social facilitation has been implemented and tested as a strategy in retirement homes to encourage residents to increase their meal intake. In a Dutch intervention study in a nursing home, the effect of family-style meals (e.g., eating together with other residents) versus individual preplating services on food intake was tested over a sixmonth period. The study showed that the intervention group (family-style meal) significantly increased their intake (992 kJ; 95%CI ¼ 504–1479) in comparison with the control group (preplated solo meal) (Nijs, de Graaf, Siebelink, et al., 2006). Several underlying explanations have been suggested for the social facilitation effect, although there is no definitive explanation. In a recent review, Herman (2015) outlines potential underlying mechanisms in detail, and proposes future directions for research to enhance our understanding of the social facilitation of eating (Herman, 2015). Via social modeling of food choices, people adapt their food choice to that of the food choice of their companion. In modeling, people use others’ food choices as a guide for their own behavior. A recent study reviewing 69 modeling studies over 40 years, including >5800 participants, indicated that the majority of the studies (92.8%) found significant modeling effects on food intake, irrespective of the social context, methodology, food consumed, or demographics of the studied group (Cruwys, Bevelander, & Hermans, 2015). For example, a study of social modeling effects on food purchase behavior in supermarkets examined whether food purchase

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behavior of teenage girls would adapt to the same-sex confederate peer that purchased either low-caloric, mid-caloric, or high-caloric food products. Results suggested that teenage girls who shopped with a peer who chose high-caloric food products purchased higher caloric food products compared with the girls who shopped with a teenage peer buying low-caloric foods (Bevelander, Ansch€u, & Engels, 2011). First, people “model” because they search for information of the appropriate or “correct” behavior. Second, individuals model because they want to affiliate with others and be liked (Cruwys et al., 2015). Social norms are “implicit codes of conduct” or “perceived standards” that exist in a social group and provide a guide to appropriate action (Higgs, 2015). There are two types of social norms. Descriptive norms refer to individuals’ perceptions about how others around them behave (e.g., make food choices), so “what do others do?”. Injunctive norms refer to the perceived approval of food choice behavior and represent perceived moral rules of the peer group, so “what do other people accept?” (Cialdini, Reno, & Kallgren, 1990; Reno, Cialdini, & Kallgren, 1993). Previous studies have outlined the relation between social norms and food choices (Robinson, Thomas, Aveyard, & Higgs, 2014; Stok, de Vet, de Ridder, & de Wit, 2016). For example, in a lab and real-life study, information about how others behaved was controlled by using empty chocolate wrappers, indicating that others ate chocolates on a previous occasion. In the real-life study, customers of bakery lunchrooms participated. A transparent bowl with individually wrapped chocolates was placed on the food counter. In the experiment, a bowl with empty wrappers was placed beside the bowl of chocolates. In the control condition, this bowl was empty. Outcome measures were the number of chocolates consumed. The results indicated that the number of consumed chocolates was higher when it was indicated that previous customers had taken a chocolate (RR 2.10, 95%CI ¼ 1.08–4.09). The follow-up study in a laboratory setting resulted in similar outcomes (Odds ¼ 3.07, 95%CI ¼ 1.09–8.60) (Prinsen, De Ridder, & De Vet, 2013). These prior examples of social influences on food choices illustrate that individuals are not always fully aware of social influence. Yet, social influences do not always occur unnoticed, and social influences are also embedded in family or group structures and dynamics. This is nicely illustrated by a qualitative study examining the role wives played in shaping the eating behaviors of middle-aged and older urban AfricanAmerican men. The men indicated that women played a dominant role in household food provision and decision-making, and agreed that their wives influenced what they ate at home more than their own preferences. Quoting from this study: “When we first got married at 21 and 20, my wife decided that we weren’t going to eat like our parents. She made that decision for me. I didn’t think about it.... She made the decision that we’re not going to do this, and I didn’t argue with her.” Or “All my life I’ve been influenced by either my mother or my wife as far as food choices. I really didn’t have any choice other than what she put in front of me at the table” (Allen, Griffith, & Gaines, 2013). Although the interviewed men perceived themselves to have little control over what they ate at home, they appreciated the care and concern of their wives. This example illustrates that people experience and recognize social control others have over their food choices.

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Setting context

Whereas macro and local food contexts shape the overall scene in which populationlevel food choices take place, people interact with the food environment in specific settings. In this paragraph, we discuss five settings that are important for food choices, and objectives for food choice-related research: home, supermarket, workplace cafeteria/restaurants, and the digital/online setting. For each setting, we predominantly focus on the physical or policy factors that influence food choices. Yet, one should be conscious of other contextual factors (e.g., social influences) that also shape food choices being made.

7.5.1 Home The home food environment is fundamental in the development of food preferences and consumption habits, steering food choices. In fact, the home food environment is the place where the retail food environment interacts with actual food intake. The home food environment can be conceptualized as coinciding interactive domains made up of different environments, namely the socio-cultural, political, economic, and the built environments (at both micro and macro levels) that each contributes in a unique way to the determinants of the home food context (Rosenkranz & Dzewaltowski, 2008). Home contextual factors that shape food consumption include the availability of products, the salience of foods, and the size of dinnerware (Robinson, Nolan, Tudur-Smith, et al., 2014). Previous studies have illustrated the interdependence of home food availability and food intake (Campbell et al., 2007; Ding, Sallis, Norman, et al., 2012). Moreover, storing foods in visible places increased individuals’ consumption rates, consumption frequencies, and the amount of food consumed, especially for high-convenience foods and large packages (Chandon & Wansink, 2002). The salience of snack foods evokes individuals’ desire to eat, prompts their desire to consume larger amounts, and increases the actual amount they consume (Fedoroff, Polivy, & Herman, 1997; Ferriday & Brunstrom, 2008). For both high-and low-convenience foods, large amounts of stockpiled foods also induce increased usage and the intake of larger amounts (Raynor & Wing, 2007). Another factor in the home food environment that may influence food intake is dinnerware size. It has been implied that consuming from larger dishware affects the amount people consume, because people serve themselves a larger portion (Sobal & Wansink, 2007). Using mathematical modeling to estimate the influence of dinnerware size on energy intake, a study indicated that small increases in dishware (plates and bowls) could lead to a substantial increase in energy intake (Pratt, Croager, & Rosenberg, 2012). A systematic review and meta-analysis from 2014 that included eight heterogeneous studies concluded that the majority found no significant difference if people consumed food from small or large dishware (Robinson, Nolan, et al., 2014). However, contrary to this finding, a meta-analysis from 2015, which included 13 independent comparisons from 10 studies, found a small to moderate effect of

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portion or tableware size on selection of food among adults. They also found a very large effect of exposure to differently shaped tableware on the selection of nonalcoholic beverages in adults and children (Hollands, Shemilt, Marteau, et al., 2014). In a study in the Netherlands among 278 households, it was found that the majority (70%) had a large amount of ultra-processed snack foods in stock (8 packages). In 33% of the households, processed snack foods were visible in the kitchen, and in 15% of the households, processed snack foods were visible in the living room. Of the dinnerware items, 14% (plates), 57% (glasses), 78% (dessert bowls), 67% (soup bowls), and 58% (mugs) were larger than the reference of the Netherlands Nutrition Centre (Poelman, De Vet, Velema, Seidell, & Steenhuis, 2015).

7.5.2 Supermarkets Supermarkets are a major source for food purchases, and subsequently, food intake (Stern, Ng, & Popkin, 2016). Many contextual factors within the supermarket influence grocery shopping, as many purchase decisions are made in-store (Cohen & Babey, 2012). Factors that play a role in these decisions are variety, place, promotion, and price. These in-store influences go mostly unnoticed by shoppers, as they target unconscious decisions (e.g., via system 1 according to the dual process theory). Generally, in-store contextual influences often lead to unhealthier dietary choices, and an increased caloric consumption (Cohen & Babey, 2012). The number of products available in supermarkets has increased immensely in the past few decades, to >40,000 nowadays (Cohen & Babey, 2012). The sales of processed and ultra-processed foods have particularly increased. For example, expressed as a percentage of total purchased calories, the sales of processed foods have increased over the past few decades. In Canada, the increase was from 24.4% in 1938 to 54.9% in 2001. In Brazil, it was from 18.7% in 1987 to 26.1% in 2003 (Monteiro, Moubarac, Cannon, Ng, & Popkin, 2013). A study in New Zealand supermarkets showed that >80% of products available could be classified as “ultraprocessed” (Luiten, Steenhuis, Eyles, Ni Mhurchu, & Waterlander, 2016). The increased availability may be overwhelming for shoppers, and may lead to “choice stress.” Iyengar & Lepper demonstrated that shoppers were more inclined to buy jam if they could choose between 6 flavors, compared with choosing among 24 flavors (Iyengar & Lepper, 2000). On the other hand, studies have shown that a wider variety of products leads to an increase in sales (Sela, Berger, & Liu, 2009). In terms of placement, the routing in supermarkets is designed to expose consumers to as many products as possible. High exposure locations are ends of aisles, shelves at eye level, free-standing product displays, and products displayed at checkouts. The number of facings of a product on the shelf has an influence (Chandon, Hutchinson, Bradlow, & Young, 2009). The in-store promotion of products can be done in different ways; for example, via product sampling, which is known to be an effective method to increase product sales. Research has demonstrated that, when offered, 70% of the shoppers consumed a free sample, of whom 40% bought the sampled food (Heilman, Lakishyk, & Radas, 2011).

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Advertisements on shopping carts, or by in-store audio are other examples of product promotion. Price discounts and promotions in supermarkets (such as “buy 1 get 1 free”) are often used to steer consumer behavior (Cohen & Babey, 2012). This is no surprise, because price is—next to other determinants of food choice, such as sensory appeal or convenience—a major determinant of food choice, and applies even more for consumers with a low socio-economic background (Steenhuis, Waterlander, & de Mul, 2011). Larger volumes offer consumers more “value for money,” that is, a relatively lower price per unit of the product (Vermeer, Alting, Steenhuis, & Seidell, 2010). Moreover, portion size is an important product feature that impacts purchase or intake. A development that has taken place over the past few decades with respect to product characteristics is the enlargement of portion and package sizes, and the introduction of multi-packages (Steenhuis, Leeuwis, & Vermeer, 2017; Steenhuis & Poelman, 2017). Larger portions and packages increase used volume (Hollands, Shemilt, Marteau, et al., 2015). Besides price and portion, the shape and color of the packaging, as well as the images used on the packaging, also play a role in attracting the attention of consumers, and that, in turn, determines purchases of the product, in addition to the perceived quality of the product (Cohen & Babey, 2012). The majority of price promotions in supermarket flyers are in the category of unhealthy food products (Ravensbergen, Waterlander, Kroeze, & Steenhuis, 2015). Health professionals have developed interventions to promote the purchase of healthier groceries in the supermarket by using price interventions. Waterlander et al. tested the effects of a 50% price discount on selected fruits and vegetables among Dutch consumers with a low socio-economic position (Waterlander, de Boer, Schuit, Seidell, & Steenhuis, 2013). The results of the randomized controlled trial indicated that the intervention resulted in substantially higher fruit and vegetable purchases during a 6 month period, and this effect was even stronger if combined with an educational program. A randomized controlled trial conducted in Australia showed that a 20% price reduction in fruits and vegetables was also effective, and led to a 35% increase in the purchases of fruit, and a 15% increase in the purchase of vegetables (Ball, McNaughton, Le, et al., 2015). Adam and Jensen conclude in their review that, of all interventions conducted in the supermarket setting to encourage people to eat more healthily, consumers respond most to economic incentives (Adam & Jensen, 2016). It is very challenging to study pricing interventions in real life. Therefore, virtual supermarkets have been developed (Waterlander, Jiang, Steenhuis, & Ni, 2015). These 3D software programs simulate a shopping experience, and make it feasible to study price interventions that are not yet feasible, or are difficult to implement and study in real life, such as food taxation. A randomized trial with a virtual supermarket showed, for example, the potential of a higher VAT-rate on sugar sweetened beverages (Waterlander, Ni Mhurchu, & Steenhuis, 2014). It is important to continue investing in IT developments in virtual technology and make sure it is up-to-date with the most recent computer systems (Poelman, Kroeze, Waterlander, de Boer, & Steenhuis, 2017).

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7.5.3 Cafeterias, restaurants, and all-you-can-eat Workplace cafeterias are considered a relevant setting to study and intervene in food choices. Employees visit workplace cafeterias on a regular, or even daily, basis during their career. A qualitative study among employees into motives and drivers for visiting the workplace cafeteria showed that employees wanted to have a break from their work, and valued the convenience of purchasing their meal at the cafeteria. It also transpired that healthiness played a less important role in selecting foods at the workplace cafeteria. This was opposite of the key drivers mentioned for food selection in general, in which health was considered important. Reasons for unhealthy choices at the workplace cafeteria were feeling tempted by the offerings, and people feeling they deserved it after hard or stressful work (Velema, Vyth, & Steenhuis, 2019). Several factors in the workplace cafeteria setting are considered important when determining food choices. Characteristics of the products offered, the placement in the cafeteria, the price of the product, and the way products are promoted are all relevant (Velema, Vyth, & Steenhuis, 2017). Relevant product characteristics are the availability, the portion size, and convenience (for example, peeled fruit snacks). With respect to placement, products that are placed at the beginning of the route, and highly visible products, are purchased more. Visibility relates to placement at eye level, the visible share of products, and placement near the checkout. In addition, price promotions also have an effect, as well as free offerings of, for example, water. Promotional tactics that enhance sales numbers of products and meals include using attractive names on the menu, and promotional displays (Velema et al., 2017). Whether food labeling in the workplace cafeteria influences food choice is still the subject of debate (Afshin, Penalvo, Del Gobbo, et al., 2015). We found no meaningful effects of labeling with a nutrition logo on sales of sandwiches, soups, snacks, fruit, and salads (Vyth et al., 2011). In recent years, nudging has also become a strategy of interest that can be applied in workplace cafeterias in order to promote healthy eating. A nudge is defined by Thaler and Sunstein as “any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives” (Thaler & Sunstein, 2008). Another term used is choice architecture. By altering the eating environment in workplace cafeterias, people can be encouraged to choose the healthy option. This is in line with the recommendation of the WHO that defines the workplace as a priority setting for health promotion (WHO, 2010). A healthy workforce is considered essential for future success. Nudging in the workplace cafeteria targets the aforementioned contextual factors of the workplace cafeteria. A study by Vermeer et al. (2011) showed that simply offering an option to choose a smaller size of a hot meal resulted in 10.2% of consumers replacing the large meal with the small meal (Vermeer, Steenhuis, Leeuwis, Heymans, & Seidell, 2011). However, possible compensation behavior (i.e., buying more products than usual due to having chosen the small meal) should also be taken into account. Van Kleef et al. (2012) demonstrated a positive effect of an increased availability of healthy snacks at the cash desk on sales in a hospital cafeteria (van Kleef, Otten, & van Trijp, 2012). Velema et al. (2018) applied a combination of several nudging strategies in the workplace cafeteria, together with some pricing

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strategies. A randomized controlled trial showed that some strategies were effective in promoting healthier choices, and that these effects remained over a 12-week period (Velema, Vyth, Hoekstra, & Steenhuis, 2018). Workplace cafeterias are not the only relevant location within the work setting. Vending machines and food and beverages offered at meetings and conferences are also important (Gardner, Whitsel, Thorndike, et al., 2014). Beyond the workplace cafeteria, other places where people go out are, for example, coffee shops, lunch rooms, and fast food and take-a-way outlets. The number of these food outlets increased hand in hand with visits to these settings. In the United States, 82% of adults eat out at least once per week (US Department of Agriculture ERS, 2010). In all-you-can-eat restaurants, people pay a fixed amount, and are responsible for the type and amount of food they serve themselves. Both the variety at these restaurants and the fixed-pricing strategy steer people’s food choices in these places ( Just & Wansink, 2008; Rolls et al., 1981). The considerable meal variety means people might experience more hedonic hunger, and are prompted to serve themselves with larger quantities (Rolls et al., 1981). Because most buffet-style restaurants have fixedprice offers, most visitors are motivated by the desire to get their money’s worth, and consume as much as possible. Consequently, the more people pay for their all-youcan-eat deal, the more they consume ( Just & Wansink, 2008). In restaurants, the impact of menu labeling on food choices is a frequently studied factor globally. In the United States, the US Congress passed Section 4205 of the Patient Protection and Affordable Care Act, “Nutrition labeling of standard menu items at chain restaurants,” which requires restaurants with 20 or more locations to provide nutritional information for standard items on menus (Public Law United States, 2010). The US Food and Drug Administration began enforcing the final rule in May 2018 (US Food and Drug Administration, 2018). To date, many global chain restaurants have implemented menu labeling, including fast-food restaurants, bakeries, coffee shops, ice cream shops, and movie theaters. Several mechanisms of the influence of menu labeling on food choices have been hypothetically suggested. First, menu labeling could motivate consumers to select healthier food options, and ultimately lower their overall energy intake. Second, it could teach visitors over time that the majority of restaurant meals have a high energy content, and subsequently steer consumers to visit restaurants less often; or third, to choose the restaurant that serves healthier meals more often. Fourth, it may stimulate consumers to compensate for their restaurant intake (e.g., by reducing the energy intake of other meals during the day), and finally, menu labels may motivate the restaurant industry to reformulate meals so that they contain less energy (VanEpps, Roberto, Park, Economos, & Bleich, 2016). Currently, a number of meta-analyses and review studies have been conducted to examine the effectiveness of menu labeling. The evidence to date is, however, mixed (Littlewood, Lourenc¸o, Iversen, & Hansen, 2016; Long, Tobias, Cradock, Batchelder, & Gortmaker, 2015; Sacco, Lillico, Chen, & Hobin, 2017; VanEpps et al., 2016). For example, a meta-analysis including 19 intervention studies found an overall small, but significant, reduction in calories (18.1 kcal, 95%CI ¼  33.56 to 2.70) ordered/purchased per meal associated with menu labeling. There was, however, considerable heterogeneity in settings across the 19 studies. Subsequent

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analyses that only included studies conducted in restaurants under control conditions showed a nonsignificant effect of menu-labeling on calories purchased (7.6 kcal, 95%CI ¼  21.02 to 5.76) (Long et al., 2015). Evidence to date suggests little effect of menu labeling on traditional fast-food purchases, but it may be encouraging lowercalorie purchases for some people in some contexts (VanEpps et al., 2016). Highquality real life studies are needed in the future.

7.5.4 Digital and online context An important context that has arisen in the past decade, and which will grow even more in the upcoming years, is the digital and online context. The presence and use of televisions, computers, tablets, and smartphones has increased over the past few decades. On one hand, the digital context facilitates the marketing of foods and, in this way, steers food preferences and food choices. Online and digital channels facilitate digital marketing, and the possibility to purchase online groceries or order meals. Digital marketing includes promotional activities via websites, social networking channels (e.g., Facebook), e-mail, online games, smartphone applications, or mobile phone text messaging (Kelly, Vandevijvere, Freeman, & Jenkin, 2015). Digital marketing is available 24/7, is interactive, and ubiquitous (Spero & Stone, 2004). Adolescents and young adults have a strong online presence, and growing purchase power (Freeman, Kelly, Vandevijvere, & Baur, 2015). A recent review, including a metaanalysis, showed that children exposed to digital marketing of unhealthy products had a slightly, but significantly higher, risk of selecting the online promoted foods or beverages (relative risk ¼ 1.1, 95%CI ¼ 1.0–1.2). Moreover, they significantly increased their intake of these products during or shortly after exposure to the online advertisements (mean differences 30.4 kcal (95%-CI ¼ 2.9–57.9) (Sadeghirad, Duhaney, Motaghipisheh, Campbell, & Johnston, 2016). On the other hand, the upcoming market of online food shopping and meal ordering is creating an intangible virtual setting in which food choices can take place. Meal kit delivery services with recipes and preportioned ingredients (such as Blue Apron, Plated, or Hello Fresh) or farm-to-table boxes (FarmFreshToYou) have also been introduced. Online supermarkets and the restaurant and takeaway delivery sector are becoming more and more important for individual food choices. Although still quite small, these are on the rise around the world, with an annual growth rate of 14% over the past 5 years (Anesbury, Nenycz-Thiel, Dawes, & Kennedy, 2016; Halzack, 2015). In the United States, 31% of consumers were likely to purchase groceries online in 2017. Moreover, the total of US online grocery sales was about $14.2 billion in 2017, and is expected to increase to nearly $30 billion by 2021 (Statista, 2017). Prior research has identified differences in shopping behavior between the online and offline environments. Studies have indicated that brand names were more important in the online than in the offline grocery context, that online consumers have higher loyalty to brands than in-store purchasers, are less sensitive to price, and preferred buying larger pack sizes (Andrews & Currim, 2004; Chu, ArceUrriza, Cebollada-Calvo, & Chintagunta, 2010; Degeratu, Rangaswamy, & Wu, 2000).

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In addition to grocery shopping, the meal delivery sector is also increasing in importance. In the past, food delivery services were limited to some local take-away stores, or to pizza or Asian outlets, and were obtained via phone orders. There has been an increase in instant food delivery initiatives that extend consumers’ options to a larger range of products, including premium restaurants. Nowadays, the online ordering of take-aways and meals has become more and more popular in Europe and the United States. In 2010, approximately 1.39 billion phone delivery orders were placed in the US. By May 2015, that number had dropped to about 1.02 billion. In the same period, online orders more than doubled, from approximately 403 million to nearly 904 million. This was facilitated by online food ordering platforms (“digital marketplaces”) that provide online ordering opportunities to restaurants (e.g., takeaway. com). A more recent development is the instant delivery service platform that enables restaurants and take-outs to offer delivery without employing their own drivers, and includes various channels for food orders (e.g., UberEats, Deliveroo) (Dablanc et al., 2017). In the years ahead, research should assess how and what features of these online settings have an impact on food choices.

7.6

Closing paragraph and future directions

In this chapter on food choice in context, we provided an insight into factors in different food contextual layers that steer food choices, varying from macro contexts to everyday settings in which people make food choices. At each contextual level (Fig. 7.1), we provided an overview of contextual factors that affect people’s food choices. However, one should still be aware that the list of examples provided in this chapter is not definitive, and more factors within each contextual layer may impact food choices. In addition, all contexts are connected and interrelated, illustrating the extensiveness and complexity of contextual influences on individual food choices. It is a challenge for researchers to understand the sum and interactive effect of contextual factors of all these levels on eating behavior (Swinburn et al., 2011), or account for each contextual influence during the day, or over the life course. Currently, researchers in the field are challenged to understand the combined effect of several contexts on food choices. System thinking in the field of food choices reinforces the influences of both interrelated and interdependent factors in a system, consisting of multiple contexts and factors (Glass & McAtee, 2006; Mabry, Olster, Morgan, & Abrams, 2008). From this perspective, food choices are more than the sum of contextual affects, given that changes in one context affect other contexts, and the whole system as well.

Acknowledgments The contribution by the first author (M.P.) is supported by the Innovational Research Incentives Scheme (#451-16-029), financed by the Netherlands Organization for Scientific Research (NWO).

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