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Food labelling, food retail availability and food pricing – moving from research to action?

Published online by Cambridge University Press:  29 December 2014

Wilma E Waterlander
Affiliation:
Associate Editors Email: [email protected]; [email protected]
Shannon N Zenk
Affiliation:
Associate Editors Email: [email protected]; [email protected]
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Abstract

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In this Issue
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Copyright © The Authors 2015 

‘Making the healthy choice the easy choice’ is a commonly heard phrase and seemingly one of the most evident ways to stimulate healthier food choices. Indeed, when about a third of the total global population is overweight or obese( Reference Ng, Fleming and Robinson 1 ), it makes little sense to focus entirely on the individual rather than on strategies that can have a population impact. There is a growing call to implement structural interventions such as fiscal policies and front-of-pack labelling to create a more supportive food environment( Reference Gortmaker, Swinburn and Levy 2 Reference Roberto, Pomeranz and Fisher 4 ). This issue of Public Health Nutrition features some of the latest studies in this area, including new work on food labelling( Reference Cawley, Sweeney and Just 5 , Reference Liu, Bettman and Uhalde 6 ), policy-induced changes in retail food availability( Reference O’Malley, Luckett and Futrell Dunaway 7 ) and monetary fruit and vegetable incentives( Reference Andreyeva and Luedicke 8 ).

Structural nutrition interventions generally operate at the point of purchase in the retail setting( Reference Feng, Glass and Curriero 9 , Reference Holsten 10 ). Two of the most important food retail settings are supermarkets and fast-food restaurants. Supermarkets have long been the most important point of purchase for food items in developed countries and their share of retail sales is growing globally, including both developed and developing countries( Reference Regmi and Gehlhar 11 ). Likewise, fast food provides an increasing share of dietary energy and nutrient intakes, which is concerning since high fast-food intake is associated with increased obesity risk( Reference Fraser, Edwards and Cade 12 , Reference De Vogli, Kouvonen and Gimeno 13 ). Interventions within these retail settings have clear potential to improve the healthfulness of food purchases by making healthy food more available, apparent and affordable.

Food labelling

Food labelling, along with food pricing, is one of the most promising structural interventions in the retail setting( Reference Gortmaker, Swinburn and Levy 2 ). This issue of Public Health Nutrition features two new labelling studies: Cawley et al. investigated the effects of a supermarket nutrition rating system( Reference Cawley, Sweeney and Just 5 ) and Liu et al. examined the potential of menu labelling in fast-food restaurants to improve food choices( Reference Liu, Bettman and Uhalde 6 ).

Fast-food restaurants

In March 2010, the US President signed the health-care reform legislation into law. As part of this law, restaurants and food outlets with twenty or more locations are now required to list energy (calorie) content information for standard menu items on restaurant menus and menu boards( 14 ). The rationale behind this measure is that calorie labelling will help consumers more accurately estimate energy intakes from fast food( Reference Block, Condon and Kleinman 15 ). However, as Liu et al. point out in this issue( Reference Liu, Bettman and Uhalde 6 ), many menu items are likely to appear with energy ranges instead of specific energy values. This is because items are customizable; for example, total energy will differ for pizza depending on the selected toppings. These energy ranges might confuse consumers, leading them to misestimate the total energy value of their meal. Also, the authors hypothesize that consumers might confuse the energy range with healthiness, believing that the item with the lowest energy content is the healthiest instead of the item with the least ingredients( Reference Liu, Bettman and Uhalde 6 ).

In a series of four well-conducted randomized experiments, Liu et al. examine whether energy range information improves energy estimation accuracy (compared with no information) and whether people’s energy estimates can be improved by providing explicit information about the contents of items at the end points (identifying the items with the lowest and the highest energy content). In study 1, a total of 306 participants were asked to estimate the energy content of their selected entrée at a fast-food restaurant. They were randomly assigned to see either (i) no energy information or (ii) energy range information. Results revealed that energy estimation significantly improved in the second condition, but consumers continued to misestimate. Studies 2–4 expanded on these results by asking people to select hypothetical fast-food items in an online survey. In addition to the two conditions tested in study 1, these studies looked at whether pointing people to the energy information and/or adding specific end point content information (ingredients in lowest and highest energy option) would improve accuracy. Results showed that defining the specific end points generally did improve accuracy, but misestimating persisted in some cases. Also, even when participants were specifically asked to pay attention to the range end points, accuracy was not improved – suggesting that inaccuracy is not caused by lack of awareness( Reference Liu, Bettman and Uhalde 6 ).

These results suggest that energy labelling with ranges on fast-food menus might not have the anticipated impact on improved energy estimation, which is also supported by other study findings( Reference Elbel 16 ). If misinterpretation remains, it is unlikely that energy labelling will have a significant impact on the energy content of fast-food purchases or consumption. Indeed, a systematic review (2011) including outcomes from natural and laboratory experiments comparing calorie labelling v. no labelling on calorie ordering and consumption concluded that its impact was modest at best( Reference Swartz, Braxton and Viera 17 ). Likewise, a recent meta-analysis of experimental studies concluded that labelling menus with calorie information alone had no effects on calories selected or consumed( Reference Sinclair, Cooper and Mansfield 18 ). On the other hand, a review of quasi-experimental studies showed that the addition of contextual or interpretive information did affect calorie consumption( Reference Sinclair, Cooper and Mansfield 18 ), suggesting that the effects of the labels can be enhanced when designed in the right way.

Supermarkets

This brings us to nutrition labelling in supermarkets, the focus of a study by Cawley et al. in this issue( Reference Cawley, Sweeney and Just 5 ). In this setting, labels generally appear either on the front of the pack or on the shelf and provide ‘at a glance’ information that is easy for consumers to understand and act upon. There is now substantial evidence indicating that interpretative labels (using graphics, symbols or colours) are better understood than quantitative or informative (text) nutrition labels( Reference Hersey, Wohlgenant and Arsenault 19 ). However, evidence of the effects on actual purchases, sales or consumption is more inconclusive( Reference Hersey, Wohlgenant and Arsenault 19 ). This evidence is important as understanding a nutrition label does not necessarily mean people will positively change their purchases. In fact, effects could even be negative because people might link health with a bad taste( Reference Horgen and Brownell 20 ).

Cawley et al.’s study used objective sales data to measure the impact of the introduction of a nutrition labelling system, Guiding Stars, in 168 supermarkets in the USA( Reference Cawley, Sweeney and Just 5 ). Beginning in September 2006, Guiding Stars – which assigns scores of zero, one, two or three stars to food items, with three stars indicating the most nutritious – was added on shelf labels. Cawley et al. analysed aggregated weekly sales data from January 2005 to December 2007 and looked at overall weekly food sales, sales of less nutritious foods and sales of nutritious foods before and after the introduction of the labelling. While sales of nutritious foods did not change significantly, weekly sales of less nutritious foods decreased significantly by 8.3 %, meaning that the overall nutritional quality of purchases improved. These effects are promising. However, since this study used aggregate sales data and did not have a control group, some important issues remain unclear. First, we do not know how the labels impacted individual consumers or the extent to which population trends or other factors could account for the observed effects. Besides, any effects on purchases outside the participating supermarkets or long-term impacts are uncertain. These are all potential targets of future studies. Still, the fact that this study used objective sales data and was able to monitor the effects of a real-life labelling scheme are significant strengths. There are only a few other studies that have examined impacts of labels on supermarket sales or purchases, and evidence is mixed. Two studies looking at the impact of ‘traffic light’ nutrition systems did not find significant impacts on unit sales of healthier v. unhealthier products( Reference Sacks, Rayner and Swinburn 21 , Reference Sacks, Tikellis and Millar 22 ), while two other studies testing the effects of the Guiding Stars programme did find effects on healthier ready-to-eat cereals demand( Reference Rahkovsky, Lin and Lin 23 ) and purchases( Reference Sutherland, Kaley and Fischer 24 ).

Food labelling – conclusion

Summing up the evidence on labelling, it appears this strategy might have some impact on purchases, but no miracles should be expected. As outlined in earlier work, the best potential for labelling might lie in reformulation, as labels could form an incentive for producers to develop healthier products( Reference Vyth, Steenhuis and Roodenburg 25 ). It can be argued that clear labelling is the least we can do to support consumers in making healthier choices, but other measures are clearly needed to have a real impact.

Food availability

One way to enhance the effects of nutrition labelling is by increasing the availability and accessibility of healthy food. Principally, if healthy options are not available, of poor quality or expensive, they are not very likely to be purchased, in particular among poorer households who have limited access to resources including cars to travel to food establishments.

As the subject of the study by O’Malley et al. in this issue of Public Health Nutrition ( Reference O’Malley, Luckett and Futrell Dunaway 7 ), food packages for the US Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)Footnote * underwent substantial revisions in 2009 to align them with US dietary guidelines. The changes included the addition of low-fat dairy, whole grains and cash vouchers for fruits and vegetables. While the primary goal was to improve dietary quality of the target population, the policy change also required retail stores authorized to accept WIC to meet minimum stocking requirements for the new items. In their study, O’Malley et al. report interesting findings showing that the availability of foods meeting WIC requirements improved significantly pre- to post-policy in small and medium-sized stores. These stores are important points of purchase in many lower-income and racial/ethnic minority neighbourhoods due to the lack of supermarkets. This finding supports other prior published studies showing small improvements in healthier food availability (and pricing) following the WIC food package revision( Reference Andreyeva, Luedicke and Middleton 26 Reference Zenk, Powell and Odoms-Young 29 ).

O’Malley et al. examined the impact of the WIC food package revision using a new audit instrument, the WIC Availability Index (WIC-AI), and argue that their instrument is not only useful to monitor WIC adoption but also to measure the healthfulness of retail food environments in general. Advantages of the WIC-AI tool are that it is easy to use and provides a way to summarize complex food store environment data( Reference O’Malley, Luckett and Futrell Dunaway 7 ). However, as also acknowledged by the authors, there are some shortcomings to consider. For example, as recognized previously by members of the research team and others, there is evidence that not only the availability of healthy items is of importance, but also the availability of unhealthy items( Reference Rose, Hutchinson and Bodor 30 , Reference Zenk, Powell and Rimkus 31 ). In fact, when measuring the retail food environment, multiple aspects of the consumer food environment – beyond availability – should be considered, including prices, marketing and food quality (i.e. freshness, expiration dates)( Reference Glanz, Sallis and Saelens 32 Reference Zenk, Schulz and Izumi 34 ). A large number of food store and even restaurant audit instruments are now available, each with strengths and limitations. As research on the consumer retail food environment continues, investigators need to grapple with achieving the right balance between the creation of innovative tools that improve our ability to capture relevant aspects of the food environment or best suit their study aims v. the use of standardized instruments that allow for easier comparisons across places and over time. When making these decisions, researchers may find a recently proposed step-wise framework to monitor local food environments within and across countries useful( Reference Ni Mhurchu, Vandevijvere and Waterlander 35 ).

Food pricing

This brings us to the final promising strategy, food pricing. Food pricing interventions can broadly be divided into taxes on unhealthy foods or subsidies on healthy foods. This issue of Public Health Nutrition features a new well-designed food pricing study on the latter. Andreyeva and Luedicke examined the effects of cash-value vouchers ($US 10 for women and $US 6 for children per month) for fruits and vegetables through the WIC programme on fruit and vegetable purchases, using a one-group pre–post design( Reference Andreyeva and Luedicke 8 ). Results showed that the vouchers were effective in increasing monthly fruit and vegetable purchases, with a 17·5 % increase in fresh vegetable and 28·6 % increase in fresh fruit purchases following the introduction of the vouchers. There were some substitution effects (e.g. people now using the vouchers instead of other funds to pay for fruits and vegetables) but these were small and the authors conclude that the efforts to encourage consumption of fruits and vegetables by people receiving federal food assistance are paying off( Reference Andreyeva and Luedicke 8 ).

Effectiveness of food pricing interventions

The first economic law of demand states that if prices of a certain product increase, the demand will decrease and vice versa( Reference McCarthy 36 ). Indeed, there is growing evidence supporting the findings by Andreyeva and Luedicke in this issue showing that people are responsive to price changes of food( Reference Andreyeva and Luedicke 8 , Reference An 37 , Reference Andreyeva, Long and Brownell 38 ). Also, in other fields it has long been known that price is one of the most effective ways to steer consumer behaviour( Reference Han, Gupta and Lechmann 39 , Reference Hawkes 40 ) and when thinking about implementing population-wide nutrition interventions, price should definitely be part of the strategy. Nevertheless, it is important to be mindful of some potential side-effects that could influence the ultimate effects of pricing interventions.

For pricing strategies to be effective, we not only want them to impact on purchases of the targeted product (fruit and vegetables, in this issue) but also on the overall healthiness of the purchases. An important limitation of the study by Andreyeva and Luedicke is that it did not examine this overall effect. A concern with healthy food subsidies is that people might purchase the subsidized foods on top of their regular purchases, thereby ending up with a higher total energy value. Or, even worse, people might use the money they saved through the subsidy to buy extra unhealthier items( Reference Waterlander, Steenhuis and de Boer 41 , Reference Epstein, Dearing and Roba 42 ). Other mechanisms to consider include ‘product substitution’, ‘forward buying’, ‘purchase acceleration’, ‘brand switching’, ‘product testing’ and ‘repeat purchasing’, which all are expected to have different effects on consumption patterns and might not necessarily improve the healthiness of the diet( Reference Hawkes 40 ). Also, there is the issue of cross-price elasticity which has important consequences for the effectiveness of both subsidies and taxes.

Cross-price elasticity is a term from micro-economics relating to the change in demand of one product (full-fat milk) in response to the change in price of another product (low-fat milk), either through complementing or substitution. When products are complements, they are often purchased together (for example, milk and breakfast cereal) and if the price of one product changes, the demand for both changes. If products are substitutes, it means that people swap one product (regular soft drink) for another (diet soft drink) due to a price change (soft drink tax). These price-elasticity effects can have important impacts on the overall effects of pricing interventions. For example, Mytton and colleagues found that fruit purchases tended to fall as a result of taxation on milk and cream( Reference Mytton, Gray and Rayner 43 ) and Nederkoorn and colleagues found that people tended to replace more expensive energy-dense products with cheaper alternatives as a result of a tax on energy-dense foods( Reference Nederkoorn, Havermans and Giesen 44 ).

There is a clear lack of high-quality studies that have looked into price elasticity effects of food price interventions in detail. Most evidence comes from natural experiments/observational studies and modelling studies which generally do not provide detailed insight into cross-price elasticity effects( Reference Eyles, Ni Mhurchu and Nghiem 45 ). Apart from a field experiment aiming to simulate a tax by manipulating discount levels on unhealthier items and some experiments in simulated supermarket environments( Reference Epstein, Jankowiak and Nederkoorn 46 , Reference Waterlander, Ni Mhurchu and Steenhuis 47 ), no randomized controlled supermarket trials testing the effects of food taxes exist in the literature. The main reason for the dearth of high-quality trials is that they are complex and costly to conduct. Opposition from the food industry against several proposed intervention strategies is another important reason for the lack of experimental studies( Reference Stanford 48 ). There are a few examples of high-quality supermarket randomized controlled trials on healthy food subsidies( Reference Ni Mhurchu, Blakely and Jiang 49 Reference Escaron, Meinen and Nitzke 51 ). While no randomized controlled trial, the paper by Andreyeva and Luedicke in this issue of Public Health Nutrition is an important addition to this evidence base and key strengths include that it was conducted in a real-life supermarket setting and used objective loyalty card purchasing data of a large sample of 2137 households. With other studies showing that the cash-value vouchers were also associated with small improvements in fruit and vegetable availability( Reference Havens, Martin and Yan 27 ) and pricing( Reference Zenk, Odoms-Young and Powell 28 , Reference Zenk, Powell and Odoms-Young 29 ) and improvements in dietary intakes( Reference Odoms-Young, Kong and Schiffer 52 ), vouchers for fruits and vegetables and possibly other healthier foods seem a promising strategy worth further investigation( Reference Waterlander, de Boer and Schuit 50 ), particularly since they can be directly targeted to the groups most in need of this intervention.

Finally, the major challenge in future food pricing research is to unfold the effects on health outcomes. This includes not only estimating more precise price elasticities, but also the long-term effects of price changes. People may eventually become unaware of new prices, especially when prices of a whole product range are changed at a certain point in time( Reference Nijs, Dekimpe and Steenkamp 53 ). An important aspect to also consider is tax salience, referring to how the tax/subsidy is communicated. Here, it may be more important to tell people that products are taxed than to actually tax them( Reference Lacaniloa, Cash and Adamowisz 54 ). Also, we should not forget the importance of industry response to taxes and subsidies. Companies can make decisions about absorbing (parts of) the tax and the cost change might only be partially passed on to the consumer. Furthermore, the abolishment of the Danish fat tax (mainly for economic reasons) within one year of its introduction shows that feasibility aspects are crucial to consider( Reference Stafford 55 ).

In conclusion, there is still much to learn about the effects of food taxes and subsidies, however time is ripe for action too. It is encouraging that different countries, including Hungary, France and Mexico, have introduced fiscal food policies( Reference Mytton, Clarke and Rayner 56 ) and it would be very interesting to learn the effects of these policies to inform further policy making.

Conclusion

The papers discussed in this editorial show potential for several structural nutrition interventions including food labelling, retail food availability and pricing interventions. While some important evidence is still missing, most importantly regarding the long-term effects of these interventions and the effects on dietary and health outcomes, the rising prevalence of obesity and non-communicable diseases also calls for more immediate action and the time seems right to start implementing a range of promising measures.

It is evident that our food environment is highly commercialized and it has been argued that unhealthy diets are simply the consequence of peoples’ incapability of choosing right from plenty( Reference Tillotson 57 ) or that obesity is ‘a robust sign of commercial success’( Reference Swinburn 58 ). If we are serious about population health, we should do something to change this environment, which might include doing something about vested commercial and political interests. There is clear evidence showing that promotional campaigns or nutrition education are not enough to achieve healthier population diets( Reference Rekhy and McConchie 59 ). Indeed, as outlined in a recent viewpoint in JAMA, we need governments and health bodies to take action and lead by example( Reference Gostin, Reeve and Ashe 60 ). Incentives such as the Danish fat tax should be given the opportunity to prove effects before being overturned by giving priority to other (economic or political) interests. Also, we should be mindful that the introduction of less hefty interventions, such as calorie labelling, are not used as ‘window-dressing’ and confine the introduction of any further measures. Calorie labelling is arguably the least we can do and should be seen as a first step to create healthier food environments. A range of measures are clearly needed where it is crucial that health, as opposed to economic interests, achieves a central role in food policy decisions.

Footnotes

* WIC is the US Special Supplemental Nutrition Program for Women, Infants, and Children providing supplemental food and nutrition education to low-income women, infants and children under the age 5 years.

References

1. Ng, M, Fleming, T, Robinson, M et al. (2014) Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 384, 766781.Google Scholar
2. Gortmaker, SL, Swinburn, BA, Levy, D et al. (2011) Changing the future of obesity: science, policy, and action. Lancet 378, 838847.Google Scholar
3. Swinburn, BA, Sacks, G, Hall, KD et al. (2011) The global obesity pandemic: shaped by global drivers and local environments. Lancet 378, 804814.Google Scholar
4. Roberto, CA, Pomeranz, JL & Fisher, JO (2014) The need for public policies to promote healthier food consumption: a comment on Wansink and Chandon (2014). J Consum Psychol 24, 438445.Google Scholar
5. Cawley, J, Sweeney, MJ, Just, DR et al. (2015) The impact of a supermarket nutrition rating system on purchases of nutritious and less nutritious foods. Public Health Nutr 18, 814.Google Scholar
6. Liu, JL, Bettman, JR, Uhalde, AR et al. (2015) How many calories are in my burrito? Improving consumers’ understanding of energy (calorie) range information. Public Health Nutr 18, 1524.Google Scholar
7. O’Malley, K, Luckett, BG, Futrell Dunaway, L et al. (2015) Use of a new availability index to evaluate the effect of policy changes to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) on the food environment in New Orleans. Public Health Nutr 18, 2532.Google Scholar
8. Andreyeva, T & Luedicke, J (2015) Incentivizing fruit and vegetable purchases among participants in the Special Supplemental Nutrition Program for Women, Infants and Children. Public Health Nutr 18, 3341.Google Scholar
9. Feng, J, Glass, TA, Curriero, FC et al. (2010) The built environment and obesity: a systematic review of the epidemiologic evidence. Health Place 16, 175190.CrossRefGoogle ScholarPubMed
10. Holsten, JE (2009) Obesity and the community food environment: a systematic review. Public Health Nutr 12, 397405.Google Scholar
11. Regmi, A & Gehlhar, M (2005) Processed food trade pressured by evolving global supply chains. Amber Waves 3, issue 1. http://www.ers.usda.gov/amber-waves/2005-february/processed-food-trade-pressured-by-evolving-global-supply-chains.aspx#.VEiqrSx0zhg (accessed 23 October 2014).Google Scholar
12. Fraser, LK, Edwards, KL, Cade, JE et al. (2011) Fast food, other food choices and body mass index in teenagers in the United Kingdom (ALSPAC): a structural equation modelling approach. Int J Obes (Lond) 35, 13251330.Google Scholar
13. De Vogli, R, Kouvonen, A & Gimeno, D (2014) The influence of market deregulation on fast food consumption and body mass index: a cross-national time series analysis. Bull World Health Organ 92, 99107.Google Scholar
14. US Food and Drug Administration (2013) Menu & vending machines labeling requirements. http://www.fda.gov/Food/IngredientsPackagingLabeling/LabelingNutrition/ucm217762.htm (accessed 23 October 2014).Google Scholar
15. Block, JP, Condon, SK, Kleinman, K et al. (2013) Consumers’ estimation of calorie content at fast food restaurants: cross sectional observational study. BMJ 346, f2907.Google Scholar
16. Elbel, B (2011) Consumer estimation of recommended and actual calories at fast food restaurants. Obesity (Silver Spring) 19, 19711978.Google Scholar
17. Swartz, JJ, Braxton, D & Viera, AJ (2011) Calorie menu labeling on quick-service restaurant menus: an updated systematic review of the literature. Int J Behav Nutr Phys Act 8, 135.Google Scholar
18. Sinclair, SE, Cooper, M & Mansfield, ED (2014) The influence of menu labeling on calories selected or consumed: a systematic review and meta-analysis. J Acad Nutr Diet 114, 13751388. e15.Google Scholar
19. Hersey, JC, Wohlgenant, KC, Arsenault, JE et al. (2013) Effects of front-of-package and shelf nutrition labeling systems on consumers. Nutr Rev 71, 114.Google Scholar
20. Horgen, KB & Brownell, KD (2002) Comparison of price change and health message interventions in promoting healthy food choices. Health Psychol 21, 505512.Google Scholar
21. Sacks, G, Rayner, M & Swinburn, B (2009) Impact of front-of-pack ‘traffic-light’ nutrition labelling on consumer food purchases in the UK. Health Promot Int 24, 344352.Google Scholar
22. Sacks, G, Tikellis, K, Millar, L et al. (2011) Impact of ‘traffic-light’ nutrition information on online food purchases in Australia. Aust N Z J Public Health 35, 122126.Google Scholar
23. Rahkovsky, I, Lin, BH, Lin, CTJ et al. (2013) Effects of the Guiding Stars Program on purchases of ready-to-eat cereals with different nutritional attributes. Food Policy 43, 100107.Google Scholar
24. Sutherland, LA, Kaley, LA & Fischer, L (2010) Guiding Stars: the effect of a nutrition navigation program on consumer purchases at the supermarket. Am J Clin Nutr 91, issue 4, 1090s1094s.Google Scholar
25. Vyth, EL, Steenhuis, IHM, Roodenburg, AJC et al. (2010) Front-of-pack nutrition label stimulates healthier product development: a quantitative analysis. Int J Behav Nutr Phys Act 7, 65.Google Scholar
26. Andreyeva, T, Luedicke, J, Middleton, AE et al. (2012) Positive influence of the revised Special Supplemental Nutrition Program for Women, Infants, and Children food packages on access to healthy foods. J Acad Nutr Diet 112, 850858.Google Scholar
27. Havens, EK, Martin, KS, Yan, J et al. (2012) Federal nutrition program changes and healthy food availability. Am J Prev Med 43, 419422.Google Scholar
28. Zenk, SN, Odoms-Young, A, Powell, LM et al. (2012) Fruit and vegetable availability and selection: federal food package revisions, 2009. Am J Prev Med 43, 423428.Google Scholar
29. Zenk, SN, Powell, LM, Odoms-Young, AM et al. (2014) Impact of the revised Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food package policy on fruit and vegetable prices. J Acad Nutr Diet 114, 288296.Google Scholar
30. Rose, D, Hutchinson, PL, Bodor, JN et al. (2009) Neighborhood food environments and body mass index: the importance of in-store contents. Am J Prev Med 37, 214219.CrossRefGoogle ScholarPubMed
31. Zenk, SN, Powell, LM, Rimkus, L et al. (2014) Relative and absolute availability of healthier food and beverage alternatives across communities in the United States. Am J Public Health 104, 21702178.Google Scholar
32. Glanz, K, Sallis, JF, Saelens, BE et al. (2005) Healthy nutrition environments: concepts and measures. Am J Health Promot 19, 330333, ii.Google Scholar
33. Swinburn, B, Sacks, G, Vandevijvere, S et al. (2013) INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support): overview and key principles. Obes Rev 14, Suppl. 1, 112.Google Scholar
34. Zenk, SN, Schulz, AJ, Izumi, B et al. (2012) Development, evolution, and implementation of the food environment audit for diverse neighborhoods. In Methods for Conducting Community-based Participatory Research for Health, pp. 277302 [B Israel, E Eng, A Schulz et al., editors]. San Francisco, CA: Jossey Bass.Google Scholar
35. Ni Mhurchu, C, Vandevijvere, S, Waterlander, W et al. (2013) Monitoring the availability of healthy and unhealthy foods and non-alcoholic beverages in community and consumer retail food environments globally. Obes Rev 14, Suppl. 1, 108119.Google Scholar
36. McCarthy, M (2004) The economics of obesity. Lancet 364, 21692170.Google Scholar
37. An, R (2013) Effectiveness of subsidies in promoting healthy food purchases and consumption: a review of field experiments. Public Health Nutr 16, 12151228.Google Scholar
38. Andreyeva, T, Long, MW & Brownell, KD (2010) The impact of food prices on consumption: a systematic review of research on the price elasticity of demand for food. Am J Public Health 100, 216222.Google Scholar
39. Han, S, Gupta, S & Lechmann, DR (2001) Consumer price sensitivity and price thresholds. J Retailing 77, 435456.Google Scholar
40. Hawkes, C (2009) Sales promotions and food consumption. Nutr Rev 67, 333342.Google Scholar
41. Waterlander, WE, Steenhuis, IH, de Boer, MR et al. (2012) Introducing taxes, subsidies or both: the effects of various food pricing strategies in a web-based supermarket randomized trial. Prev Med 54, 323330.Google Scholar
42. Epstein, LH, Dearing, KK, Roba, LG et al. (2010) The influence of taxes and subsidies on energy purchased in an experimental purchasing study. Psychol Sci 21, 406414.CrossRefGoogle Scholar
43. Mytton, O, Gray, A, Rayner, M et al. (2007) Could targeted food taxes improve health? J Epidemiol Community Health 61, 689694.Google Scholar
44. Nederkoorn, C, Havermans, RC, Giesen, JC et al. (2011) High tax on high energy dense foods and its effects on the purchase of calories in a supermarket: an experiment. Appetite 56, 760765.Google Scholar
45. Eyles, H, Ni Mhurchu, C, Nghiem, N et al. (2012) Food pricing strategies, population diets, and non-communicable disease: a systematic review of simulation studies. PLoS Med 9, e1001353.Google Scholar
46. Epstein, LH, Jankowiak, N, Nederkoorn, C et al. (2012) Experimental research on the relation between food price changes and food-purchasing patterns: a targeted review. Am J Clin Nutr 95, 789809.Google Scholar
47. Waterlander, WE, Ni Mhurchu, C & Steenhuis, IH (2014) Effects of a price increase on purchases of sugar sweetened beverages. Results from a randomized controlled trial. Appetite 78, 3239.Google Scholar
48. Stanford, DD (2012) Anti-obesity soda tax fails as lobbyists spend millions: retail. Bloomberg Business Week, 13 March 2012. http://www.bloomberg.com/news/2012-03-13/anti-obesity-soda-tax-fails-as-lobbyists-spend-millions-retail.html (accessed 23 October 2014).Google Scholar
49. Ni Mhurchu, C, Blakely, T, Jiang, Y et al. (2010) Effects of price discounts and tailored nutrition education on supermarket purchases: a randomized controlled trial. Am J Clin Nutr 91, 736747.Google Scholar
50. Waterlander, WE, de Boer, MR, Schuit, AJ et al. (2013) Price discounts significantly enhance fruit and vegetable purchases when combined with nutrition education: a randomized controlled supermarket trial. Am J Clin Nutr 97, 886895.Google Scholar
51. Escaron, AL, Meinen, AM, Nitzke, SA et al. (2013) Supermarket and grocery store-based interventions to promote healthful food choices and eating practices: a systematic review. Prev Chronic Dis 10, E50.Google Scholar
52. Odoms-Young, AM, Kong, A, Schiffer, LA et al. (2014) Evaluating the initial impact of the revised Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages on dietary intake and home food availability in African- American and Hispanic families. Public Health Nutr 17, 8393.Google Scholar
53. Nijs, RN, Dekimpe, MG, Steenkamp, J-BEM et al. (2001) The category-demand effects of price promotions. Mark Sci 20, 122.Google Scholar
54. Lacaniloa, RD, Cash, SB & Adamowisz, WL (2011) Heterogeneous consumer responses to snack food taxes and warning labels. J Consum Affairs 45, 108122.Google Scholar
55. Stafford, N (2012) Denmark cancels ‘fat tax’ and shelves ‘sugar tax’ because of threat of job losses. BMJ 345, e7889.Google Scholar
56. Mytton, OT, Clarke, D & Rayner, M (2012) Taxing unhealthy food and drinks to improve health. BMJ 344, e2931.Google Scholar
57. Tillotson, JE (2004) America’s obesity: conflicting public policies, industrial economic development, and unintended human consequences. Annu Rev Nutr 24, 617643.Google Scholar
58. Swinburn, BA (2008) Obesity prevention: the role of policies, laws and regulations. Aust N Z Health Policy 5, 12.Google Scholar
59. Rekhy, R & McConchie, R (2014) Promoting consumption of fruit and vegetables for better health. Have campaigns delivered on the goals? Appetite 79, 113123.Google Scholar
60. Gostin, LO, Reeve, BH & Ashe, M (2014) The historic role of boards of health in local innovation: New York City’s soda portion case. JAMA 312, 15111512.Google Scholar