For your next article assignment read the article below and write a short discussion paper on food deserts. In the top right hand corner of your paper include your name, course number and date (single spaced). However, within the body of your paper you must appropriately cite your work.

The content of your summary must be at least 2 typed pages (doubled space, Times New Roman 12 font, using APA writing style). As part of your conclusion describe any instances of food deserts that you may be familiar with (i.e. a neighborhood, a specific geographical area – examples include a city, rural town, region, etc.). Describe the determinants of health associated with the area you identified.

POLICY FORUM

Moving Beyond “Food Deserts”: Reorienting United States Policies to Reduce Disparities in Diet Quality Jason P. Block1,2, S. V. Subramanian2,3*

1 Obesity Prevention Program, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America, 2 Harvard Center for Population and Development Studies, Harvard T H Chain School of Public Health, Cambridge, Massachusetts, United States of America, 3 Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health Boston, Massachusetts, United States of America

* [email protected]

Summary Points

• Most Americans fail to meet recommendations for diet quality, with disparities evident by race/ethnicity, socioeconomic status, and use of nutrition assistance programs.

• The evidence supporting the elimination of food deserts as a strategy to reduce dispari- ties in diet quality is weak.

• More use of evidence-based policies to improve diet quality and reduce disparities in the United States is needed, specifically for school- and child care-based interventions, use- ful population educational strategies, changes to nutrition assistance programs, and tax- ation of unhealthy foods such as sugar-sweetened beverages.

Introduction Scientific interest in dietary patterns and the relationship between diet and disease has persisted for centuries [1]. During much of the 19th century, concerns regarding diet centered on the high prevalence of malnutrition, with a clear income gradient evident. Those living in abject poverty, often in urban centers that grew rapidly because of industrialization, were most affected. With increasing recognition of vitamin deficiencies and government-mandated vita- min fortification of foods such as bread, prevalence of “undernutrition” dramatically fell [1]. By the end of the 20th century, in industrialized countries, interest in the link between diet and disease was rekindled, except that the concern was “overnutrition,” reflected in equally dra- matic increases in the prevalence of overweight and obesity [1]. The Scientific Report of the 2015 US Dietary Guidelines Committee confirms that we still don’t eat a healthful diet [2]. Food insecurity remains a problem for low-income families, but the greatest challenge is poor dietary quality. In the US, nearly all people fail to consume recommended amounts of whole grains; 80% and 90% do not eat enough fruits and vegetables, respectively [2]. In contrast, 70% of the US population eats more saturated fat and refined grains than recommended, and 90% consumes too much added sugar [2].

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OPEN ACCESS

Citation: Block JP, Subramanian SV (2015) Moving Beyond “Food Deserts”: Reorienting United States Policies to Reduce Disparities in Diet Quality. PLoS Med 12(12): e1001914. doi:10.1371/journal. pmed.1001914

Published: December 8, 2015

Copyright: © 2015 Block, Subramanian. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: JB and SVS receive funding from R01HL109263 (PI: O’Malley, Subramanian), a study examining the relationship between the food environment and body weight, and JB receives funding from a mentored career development award K23HL111211 (PI: Block).

Competing Interests: The authors have declared that no competing interests exist.

Abbreviations: HFFI, Healthy Food Financing Initiative; SES, socioeconomic status; SNAP, Supplemental Nutrition Assistance Program; SSB, sugar-sweetened beverage; WIC, Special Supplemental Nutrition Program for Women, Infants, and Children.

Provenance: Commissioned; externally peer reviewedhttp://crossmark.crossref.org/dialog/?doi=10.1371/journal.pmed.1001914&domain=pdfhttp://creativecommons.org/licenses/by/4.0/

Poor diet quality is strongly patterned by socioeconomic status (SES). In a recent US study examining trends in dietary quality from 1999 to 2010, lower-income individuals consumed lower-quality foods, as measured by the Alternate Healthy Eating Index 2010 score, than higher-income individuals [3]. Notably, income disparities in dietary quality widened over this period, with some improvements for higher-income individuals alone. These disparities are also evident when comparing participants in nutrition assistance programs to nonparticipants. In a study of low-income individuals from 1999 to 2008, Supplemental Nutrition Assistance Program (SNAP, “food stamp”) participants had lower dietary quality and consumed fewer whole grains and more red meat, potatoes, and fruit juice than nonparticipants [4]. Among women, SNAP participants consumed more sugar-sweetened beverages than nonparticipants [4,5].

In this essay, we discuss the specific role of physical access to food and the extent to which eliminating food deserts can improve dietary quality and decrease economic and racial/ethnic disparities in dietary quality. While a variety of factors contribute to income disparities in die- tary quality, considerable attention has been focused on poor physical access to healthy foods leading to “food deserts.” The White House Task Force on Childhood Obesity explicitly con- sidered the existence of “food deserts” (see Box 1 for a formal definition) as a contributor to poor nutrition in the US and advocated their elimination by 2017 [6]. The World Health Orga- nization has advocated similar approaches [7]. Meanwhile, a small fraction (23.5 million, approximately 7% of the population) of Americans live in food deserts; even fewer live in food deserts without access to a privately owned car (2.3 million) [8]. Yet, there appears to be gov- ernmental enthusiasm for developing programs and regulations to eliminate food deserts. For instance, the US Departments of Agriculture, Health and Human Services and Treasury joined together to develop the Healthy Food Financing Initiative (HFFI) to “improve access to healthy, affordable foods” in food deserts [9], committing US$50 million in federal money for HFFI, with other substantial federal support through tax credits and community economic development grants to fund healthy food options in food deserts. Pennsylvania, Louisiana, and New York undertook large-scale programs to bring healthy food to low-income communities, with US$30 million in public funds in Pennsylvania alone, matched by nearly US$120 million in private funds [10]. These governmental programs provided funding to catalyze public–pri- vate partnerships leading to the construction of supermarkets and grocery stores in food

deserts.

The Food Environment and Diet: What’s the Evidence? Food deserts refer to low-income geographic areas that lack access to a supermarket or large grocery store. Eliminating food deserts could improve diet either by providing access to healthy foods for individuals seeking those foods but with prior poor access or by generating demand within communities that had limited exposure to healthy foods. In contrast, living

Box 1. What Is a Food Desert?

The US Department of Agriculture considers a census tract to be a food desert if it is low income (poverty rate greater than or equal to 20% or median family income at 80% or lower of the area median family income) and at least one-third of tract residents live more than 1 mile away (or 10 miles away in the case of rural areas) from a supermarket or large grocery store [11].

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near fast-food restaurants might lead to poor diet quality because of enhanced access to the foods sold there; restricting access to these locations might improve diet by making this food less available. It has been shown that while area poverty was not an independent predictor of access to fast food restaurants, predominantly black neighborhoods had closer access to fast food restaurants [12]. Meanwhile, evidence from longitudinal studies has raised substantial doubt about the connection between food access and health [13–16]. In these studies, no con- sistent relationship emerged between the food environment and body weight, for adults or chil- dren. Even studies commonly cited as providing evidence for an association between the food environment and body weight or unhealthy food consumption have found only small associa- tions that may not demonstrate a notable public health or clinical impact [17–19]. For example, in a study using birth certificates from over 3 million pregnant women, living within 0.5 miles of a chain fast-food restaurant was associated with 50 grams of extra gestational weight gain compared to women without this exposure [18].

Four quasi-experimental studies have found similar results. One study examined the effect of a new supermarket in a Philadelphia food desert [20]. After opening, just over half of the res- idents of the neighborhood with the new supermarket used the supermarket for shopping; about a quarter of the residents used it as their primary source for food shopping. When com- pared to residents of a control neighborhood that was also a food desert, the new supermarket was associated with a perception of improved food access among residents in that neighbor- hood, but it was not associated with any improvements in fruit/vegetable intake or changes in BMI. A study in New York City examined the availability and intake of healthy foods before and after a new supermarket was built in a food desert [21]. Only 13% of participants in the neighborhood with the new supermarket reported shopping there, and its opening was not associated with an improvement in the availability or intake of healthy foods compared to resi- dents of a control neighborhood. A study of a new supermarket in a Pittsburgh food desert found more positive results [22]. Residents of the neighborhood with a new supermarket had notable reductions in calories in added sugars after the opening of the supermarket, compared to the control neighborhood; there were no changes in BMI or whole grain, fruit, and vegetable intake. However, among the two-thirds of residents in the intervention community who shopped in the new store regularly, there were no improvements, beyond perceptions of healthy food access, compared to residents who rarely if ever used the new store. Investigating the flip side to food deserts, a quasi-experimental evaluation of the 2008 ban on new fast-food restaurants in South Los Angeles found no effect of the ban on fast-food consumption or obe- sity rates when compared to other areas in Los Angeles county [23].

Even if proximity to healthy food establishments were beneficial to health, can “healthy” food establishments be easily defined? While supermarkets typically devote more shelf space to fruits and vegetables than other food stores, unhealthy snack foods still dominate their shelves. One study in southern Louisiana and Los Angeles found that supermarkets had one-half to three-quarters more unhealthy snacks than fruit and vegetables in their stores; convenience stores and drug stores had 90% more of these unhealthy snacks than fruits and vegetables [24]. Supermarkets in low-income neighborhoods may offer even more unhealthy food [25]. Super- markets also focus their advertising on unhealthy foods and strategically position them near the front of stores, at the ends of aisles, or at cash registers [26,27]. This practice occurs even in the most highly acclaimed “healthy” supermarkets. In addition, supermarkets may offer less healthy canned and processed foods than some smaller food stores commonly considered to be “unhealthy,” such as convenience stores and “dollar” stores [28].

People may not shop within their own neighborhoods even when a supermarket is present [29–31]. In one study in France, only 30% of participants shopped for food at the supermarket closest to their home [31]. Even if low-income people have access to a supermarket, they may

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still buy unhealthy foods in greater proportion than people with higher income [32]. Factors beyond proximity, especially price, may be more important when choosing a food shopping location, and there is no evidence that simply increasing access to supermarkets enhances demand for healthier items.

With unhealthy dietary consumption so prevalent, initiatives that focus on a narrow, at-risk population such as those living in food deserts without cars (less than 1% of the US population) are likely to be less effective than alternate interventions that help families make better deci- sions regardless of where they live and which food establishments are near their homes. Rather than assuming that “if we build it, they will come” [33] and eat healthfully, why not focus solely on policies that have more face validity, especially those that directly target economic and racial/ethnic disparities in diet quality?

Toward Potential Solutions to Improve Diet among Low-Income Populations Research on effective population-level strategies to improve diet remains limited. More evi- dence is needed to determine which interventions are best for specific populations, including low-income and minority populations that bear a greater burden of diet-related diseases. Here we discuss several feasible strategies that have the potential to lower disparities in diet quality more than eliminating food deserts.

Improvements in Child Care and School Nutrition Programs Interventions in child care centers across both the US and Australia have demonstrated benefi- cial effects on diet, physical activity, screen time, and even body weight [34–37]. For example, one Australian community-based intervention (nearly 2,500 intervention participants and over 30,000 control participants) with a strong child care center component was associated with a reduction in prevalence of overweight and obesity in the intervention community of 2.5% and 3.4% for 2-year-old children and 3.5-year-old children, respectively, compared to a 0.7% reduc- tion for both age groups in control communities [36]. Children in the intervention communi- ties also reduced their consumption of packaged snacks and fruit juice, and the day care centers there reported less unhealthy foods available on-site after the intervention [35]. How- ever, studies on the effect of child care center interventions are mixed, with some studies, espe- cially in Hispanic and black children, showing no effect [38,39].

School nutrition programs also might have some effect on the diets of children [7]. Because low-income children get more food from these programs than other children, a beneficial effect of improved nutrition standards should help lower disparities in dietary quality [40]. The US Department of Agriculture recently updated school nutrition standards, requiring the provi- sion of healthier items in schools. These changes were required by the Healthy, Hunger-Free Kids Act of 2010. In four urban, low-income Massachusetts school districts, a recent study doc- umented a 23% increase in selection of fruit and a 16% increase in consumption of vegetables after implementation of the new regulations [41].

Population Educational Initiatives The provision of easily accessible information at the point of sale could help consumers better understand the health consequences of their purchases in restaurants and food stores. Calorie menu labeling in chain food establishments, which will be implemented across the US in 2016, is a start, though evidence of effectiveness is rather limited at this point [42,43]. Revisions of the Nutrition Facts label are forthcoming and will display calories and added sugar more prom- inently. Front-of-package labeling for food products may be implemented in the near future

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Yet, a recent study in Seattle provides evidence that we should be cautious about the potential for labeling to worsen disparities. In that study, adults reported using calorie information much more often to help guide their food purchases at restaurants following the introduction of a local calorie labeling law. However, disparities in use were present by income; those mak- ing more than US$75,000 per year were nearly twice as likely to report using calorie informa- tion compared to those making less than US$35,000 [44]. Thus, while further education is needed, greater attention should be focused on how to do so without worsening disparities.

Changes in Food Assistance Programs Incentivizing healthy food purchases, or disincentivizing unhealthy purchases, in food assis- tance programs could decrease disparities in diet quality. In 2009, the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) made changes to encourage pur- chases of healthier foods, including adding more fruits and vegetables to the food packages the program financed. This change led retailers to stock more healthy foods [45] and was associ- ated with a decline in juice purchases (24%) and whole milk (50%) and an increase in fresh fruits and vegetables (29% and 18%) and whole grains (3-fold increase in 100% whole grain bread, 5-fold increase in brown rice) [46–49]. SNAP, commonly referred to as the food stamp program, could do the same if the purchase of healthy foods were incentivized by increasing the value of vouchers for those families who buy more healthy foods. The Healthy Incentive Pilot, sponsored by the US Department of Agriculture, tested this concept in a study in western Massachusetts [50]. The study included all SNAP participants in one county, with 7,500 house- holds randomized to receive US$0.30 cash back for every US$1 spent on fruits and vegetables; the other 47,595 families in the county received traditional benefits. After one year, those receiving the incentive reported consuming one-fourth of a cup more per day of fruits and veg- etables and spent about US$1.19 more per month on fruits and vegetables than the control group. These higher expenditures were determined based on purchasing data from supermar- kets and superstores participating in the SNAP program. Self-reported expenditures for fruits and vegetables showed a larger effect with US$78.1 versus US$72.02 spent, respectively, for intervention versus control families. Organizations such as WholesomeWave, which operates in 31 states and the District of Columbia and caters to approximately 40,000 families, have taken this concept further, providing dollar-for-dollar matches when customers use their SNAP benefits to purchase fruit and vegetables at farmer’s markets [51]. Reviews of studies examining the effect of lower prices (or subsidies) for fruit and vegetables have found a gener- ally positive effect on consumption, with some evidence of lower weight after the introduction of subsidies [52,53].

The benefit of healthy food subsidies is generally modest and may be amplified in the SNAP population if SNAP vouchers could not be used for unhealthy foods such as sugar-sweetened beverages. Simulation studies have found that banning the use of SNAP dollars for sugar- sweetened beverages could be cost effective (savings of nearly US$3,000 per quality-adjusted life year saved) and could modestly reduce rates of diabetes, cardiovascular disease, and obesity with an expected 15% decline in calories from sugar-sweetened beverages [54,55]. These simu- lations also found that fruit and vegetable subsidies in SNAP could lead to reductions in cardio- vascular death, but not obesity, and may lead to greater consumption of fruits and vegetables, similar to what was found in the Healthy Incentive Pilot.

As with investigations of changes to the WIC [5,46–49], supermarkets are a natural partner for gathering evidence regarding dietary interventions and policies, especially for participants in food assistance programs. Most people, including low-income individuals and families, use supermarkets as a major source of food shopping [29,30]. Many of the larger supermarket

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chains offer loyalty cards that have been leveraged in prior investigations of policy changes. In the era of “Big Data,” in which large-scale data sources are being used for population health, clinical epidemiology, genetics, and surveillance initiatives [7,56], supermarkets could be encouraged to make their “Big Data” available for use in a responsible and helpful fashion, such as for policy evaluation and targeted interventions. Clinical institutions also might partner with supermarkets to better engage their patients in health education at the point when they are making dietary choices [57].

Taxing Unhealthy Food Taxing unhealthy foods such as sugar-sweetened beverages (SSBs) may have important benefits for dietary quality [52,53]. Based on simulation models using supermarket scanner data in the US, these taxes would likely decrease obesity rates of lower-income populations more because of higher consumption in this population. These models predict that overall overweight and obesity rates would decline modestly from taxes, with reductions in daily calorie intake of 24 to 34 calories [58–60]. These taxes would be economically regressive, costing low-income individ- uals more, but this additional cost may be offset by the greater health benefit on this popula- tion. Data on the outcomes of these policies are not always consistent. In a United Kingdom modeling study, SSB taxes demonstrated regressivity but no greater decline in overweight and obesity rates among low-income individuals [61]. While acknowledging the potential eco- nomic challenges, the World Health Organization has endorsed the use of fiscal policies to improve dietary quality [62]. Advertising restrictions on unhealthy foods, especially for kids, may work in concert with fiscal policies.

Conclusion Addressing disparities in dietary quality may have important payoffs for the health of the pop- ulation: we should promote policies and programs to support these changes while studying their effectiveness. These strategies do not preclude the elimination of food deserts but rather build a necessary infrastructure to promote healthy food consumption, in any neighborhood. Many reasons, such as economic and social justice, exist to support such initiatives and to rem- edy the lack of healthy food availability in low-income communities. We just should not expect the reduction of food deserts to have much impact on the prevailing health crisis of our time. We need to focus our efforts on initiatives more likely to improve dietary quality and decrease disparities.

Author Contributions Wrote the first draft of the manuscript: JB. Contributed to the writing of the manuscript: JB SVS. Agree with the manuscript’s results and conclusions: JB SVS. All authors have read, and confirm that they meet, ICMJE criteria for authorship.

References 1. Semba RD. Nutrition and development: a historical perspective. In: Semba RD, BloemMW, editors.

Nutrition and health in developing countries. 2nd edition ed. Totawa, NJ: Humana Press; 2008. p. 1– 33.

2. Scientific Report of the 2015 US Dietary Guidelines Advisory Committee: Scientific Report to the Secre- tary of the Department of Health and Human Services and the Secretary of Agriculture February 2015 [cited 2015 April 10]. http://www.health.gov/dietaryguidelines/2015-scientific-report/PDFs/Scientific- Report-of-the-2015-Dietary-Guidelines-Advisory-Committee.pdf.

PLOSMedicine | DOI:10.1371/journal.pmed.1001914 December 8, 2015 6 / 9http://www.health.gov/dietaryguidelines/2015-scientific-report/PDFs/Scientific-Report-of-the-2015-Dietary-Guidelines-Advisory-Committee.pdfhttp://www.health.gov/dietaryguidelines/2015-scientific-report/PDFs/Scientific-Report-of-the-2015-Dietary-Guidelines-Advisory-Committee.pdf

3. Wang DD, Leung CW, Li Y, Ding EL, Chiuve SE, Hu FB, et al. Trends in dietary quality among adults in the United States, 1999 through 2010. JAMA Intern Med. 2014; 174(10):1587–95. doi: 10.1001/ jamainternmed.2014.3422 PMID: 25179639

4. Leung CW, Ding EL, Catalano PJ, Villamor E, Rimm EB, Willett WC. Dietary intake and dietary quality of low-income adults in the Supplemental Nutrition Assistance Program. Am J Clin Nutr. 2012; 96 (5):977–88. doi: 10.3945/ajcn.112.040014 PMID: 23034960

5. Andreyeva T, Luedicke J, Henderson KE, Tripp AS. Grocery store beverage choices by participants in federal food assistance and nutrition programs. Am J Prev Med. 2012; 43(4):411–8. PMID: 22992359

6. White House Task Force on Childhood Obesity. Solving the problem of childhood obesity within a gen- eration. Washington, D.C.: Executive Office of the President of the United States, May 2010.

7. Beck AH. Open access to large scale datasets is needed to translate knowledge of cancer heterogene- ity into better patient outcomes. PLoSMed. 2015; 12(2):e1001794. doi: 10.1371/journal.pmed. 1001794 PMID: 25710538

8. Ver Ploeg M, Breneman V, Farrigan T, Hamrick K, Hopkins D, Kaufman P, et al. Access to affordable and nutritious food—measuring and understanding food deserts and their consequences: report to con- gress. Washington, DC: Economic Research Service, United States Department of Agriculture, June 2009. Report No.

9. US Department of Health and Human Services. Administration for Children & Families. Community Economic Development Projects (HHS-2012-ACF-OCS-EE-0274). [cited 2012 May 30]. http://www. acf.hhs.gov/grants/open/foa/view/HHS-2012-ACF-OCS-EE-0274.

10. Karpyn A, Manon M, Treuhaft S, Giang T, Harries C, McCoubrey K. Policy solutions to the ‘grocery gap’. Health Aff. 2010; 29(3):473–80.

11. United States Department of Agriculture. Food deserts. [cited 2012 May 29]. http://apps.ams.usda.gov/ fooddeserts/foodDeserts.aspx.

12. James P, Arcaya MC, Parker DM, Tucker-Seeley RD, Subramanian SV. Do minority and poor neigh- borhoods have higher access to fast-food restaurants in the United States? Health Place. 2014; 29:10– 7. doi: 10.1016/j.healthplace.2014.04.011 PMID: 24945103

13. Block JP, Christakis NA, O’Malley AJ, Subramanian SV. Proximity to Food Establishments and Body Mass Index in the Framingham Heart Study Offspring Cohort over 30 Years. Am J Epidemiol. 2011; 174(10):1108–14. doi: 10.1093/aje/kwr244 PMID: 21965186

14. Lee H. The role of local food availability in explaining obesity risk among young school-aged children. Soc Sci Med. 2012; 74:1193–203. doi: 10.1016/j.socscimed.2011.12.036 PMID: 22381683

15. Eid J, Overman HG, Puga D, Turner MA. Fat city: questioning the relationship between urbal sprawl and obesity. J Urban Econ. 2008; 63(2):385–404.

16. Caspi CE, Sorensen G, Subramanian SV, Kawachi I. The local food environment and diet: a systematic review. Health Place. 2012; 18(5):1172–87. doi: 10.1016/j.healthplace.2012.05.006 PMID: 22717379

17. Boone-Heinonen J, Gordon-Larsen P, Kiefe CI, Shikany JM, Lewis CE, Popkin BM. Fast food restau- rants and food stores: longitudinal associations with diet in young and middle-aged adults: The Cardia Study. Arch Intern Med. 2011; 171(13):1162–70. doi: 10.1001/archinternmed.2011.283 PMID: 21747011

18. Currie J, Della Vigna S, Moretti E, Pathania V. The effect of fast food restaurants on obesity and weight gain. American Economic Journal: Economic Policy. 2010; 2(3):32–63.

19. Gibson DM. The neighborhood food environment and adult weight status: estimates from longitudinal data. Am J Public Health. 101(1):71–8. doi: 10.2105/AJPH.2009.187567 PMID: 21088263

20. Cummins S, Flint E, Matthews SA. New neighborhood grocery store increased awareness of food access but did not alter dietary habits or obesity. Health Aff (Millwood). 2014; 33(2):283–91.

21. Elbel B, Moran A, Dixon LB, Kiszko K, Cantor J, Abrams C, et al. Assessment of a government-subsi- dized supermarket in a high-need area on household food availability and children’s dietary intakes. Public Health Nutr. 2015:1–10

22. Dubowitz T, Ghosh-Dastidar M, Cohen DA, Beckman R, Steiner ED, Hunter GP, et al. Diet And Percep- tions ChangeWith Supermarket Introduction In A Food Desert, But Not Because Of Supermarket Use. Health Aff (Millwood). 2015; 34(11):1858–68.

23. Sturm R, Hattori A. Diet and obesity in Los Angeles County 2007–2012: Is there a measurable effect of the 2008 “Fast-Food Ban”? Soc Sci Med. 2015; 133:205–11. doi: 10.1016/j.socscimed.2015.03.004 PMID: 25779774

24. Farley TA, Rice J, Bodor JN, Cohen DA, Bluthenthal RN, Rose D. Measuring the food environment: shelf space of fruits, vegetables, and snack foods in stores. J Urban Health. 2009; 86(5):672–82. doi: 10.1007/s11524-009-9390-3 PMID: 19603271

PLOSMedicine | DOI:10.1371/journal.pmed.1001914 December 8, 2015 7 / 9http://dx.doi.org/10.1001/jamainternmed.2014.3422http://dx.doi.org/10.1001/jamainternmed.2014.3422http://www.ncbi.nlm.nih.gov/pubmed/25179639http://dx.doi.org/10.3945/ajcn.112.040014http://www.ncbi.nlm.nih.gov/pubmed/23034960http://www.ncbi.nlm.nih.gov/pubmed/22992359http://dx.doi.org/10.1371/journal.pmed.1001794http://dx.doi.org/10.1371/journal.pmed.1001794http://www.ncbi.nlm.nih.gov/pubmed/25710538http://www.acf.hhs.gov/grants/open/foa/view/HHS-2012-ACF-OCS-EE-0274http://www.acf.hhs.gov/grants/open/foa/view/HHS-2012-ACF-OCS-EE-0274http://apps.ams.usda.gov/fooddeserts/foodDeserts.aspxhttp://apps.ams.usda.gov/fooddeserts/foodDeserts.aspxhttp://dx.doi.org/10.1016/j.healthplace.2014.04.011http://www.ncbi.nlm.nih.gov/pubmed/24945103http://dx.doi.org/10.1093/aje/kwr244http://www.ncbi.nlm.nih.gov/pubmed/21965186http://dx.doi.org/10.1016/j.socscimed.2011.12.036http://www.ncbi.nlm.nih.gov/pubmed/22381683http://dx.doi.org/10.1016/j.healthplace.2012.05.006http://www.ncbi.nlm.nih.gov/pubmed/22717379http://dx.doi.org/10.1001/archinternmed.2011.283http://www.ncbi.nlm.nih.gov/pubmed/21747011http://dx.doi.org/10.2105/AJPH.2009.187567http://www.ncbi.nlm.nih.gov/pubmed/21088263http://dx.doi.org/10.1016/j.socscimed.2015.03.004http://www.ncbi.nlm.nih.gov/pubmed/25779774http://dx.doi.org/10.1007/s11524-009-9390-3http://www.ncbi.nlm.nih.gov/pubmed/19603271

25. Cameron AJ, Thornton LE, McNaughton SA, Crawford D. Variation in supermarket exposure to energy- dense snack foods by socio-economic position. Public Health Nutr.1–8.

26. Mehta K, Phillips C, Ward P, Coveney J, Handsley E, Carter P. Marketing foods to children through product packaging: prolific, unhealthy and misleading. Public Health Nutr.1–8.

27. Thornton LE, Cameron AJ, McNaughton SA, Worsley A, Crawford DA. The availability of snack food displays that may trigger impulse purchases in Melbourne supermarkets. BMC Public Health. 12 (1):194.

28. Bustillos B, Sharkey JR, Anding J, McIntosh A. Availability of more healthful food alternatives in tradi- tional, convenience, and nontraditional types of food stores in two rural Texas counties. J Am Diet Assoc. 2009; 109(5):883–9. doi: 10.1016/j.jada.2009.02.011 PMID: 19394475

29. Drewnowski A, Aggarwal A, Hurvitz PM, Monsivais P, Moudon AV. Obesity and supermarket access: proximity or price? Am J Public Health. 2012; 102(8):e74–80. doi: 10.2105/AJPH.2012.300660 PMID: 22698052

30. Dubowitz T, Zenk SN, Ghosh-Dastidar B, Cohen DA, Beckman R, Hunter G, et al. Healthy food access for urban food desert residents: examination of the food environment, food purchasing practices, diet and BMI. Public Health Nutr. 2015; 18(12):2220–30. doi: 10.1017/S1368980014002742 PMID: 25475559

31. Chaix B, Bean K, Daniel M, Zenk SN, Kestens Y, Charreire H, et al. Associations of supermarket char- acteristics with weight status and body fat: a multilevel analysis of individuals within supermarkets (RECORD study). PLoS ONE. 7(4):e32908. doi: 10.1371/journal.pone.0032908 PMID: 22496738

32. Vinkeles Melchers NV, Gomez M, Colagiuri R. Do socio-economic factors influence supermarket con- tent and shoppers’ purchases? Health Promot J Austr. 2009; 20(3):241–6. PMID: 19951246

33. Field of Dreams (1989) 1989 [cited 2015 September 15]. http://www.imdb.com/title/tt0097351/.

34. Benjamin Neelon SE, Taveras EM, Ostbye T, Gillman MW. Preventing obesity in infants and toddlers in child care: results from a pilot randomized controlled trial. Matern Child Health J. 2014; 18(5):1246–57. doi: 10.1007/s10995-013-1359-x PMID: 24065371

35. de Silva-Sanigorski A, Elea D, Bell C, Kremer P, Carpenter L, Nichols M, et al. Obesity prevention in the family day care setting: impact of the Romp & Chomp intervention on opportunities for children’s physi- cal activity and healthy eating. Child Care Health Dev. 2011; 37(3):385–93. doi: 10.1111/j.1365-2214. 2010.01205.x PMID: 21276039

36. de Silva-Sanigorski AM, Bell AC, Kremer P, Nichols M, Crellin M, Smith M, et al. Reducing obesity in early childhood: results from Romp & Chomp, an Australian community-wide intervention program. Am J Clin Nutr. 2010; 91(4):831–40. doi: 10.3945/ajcn.2009.28826 PMID: 20147472

37. Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, KauferChristoffel K, Dyer A. Two-year follow-up results for Hip-Hop to Health Jr.: a randomized controlled trial for overweight prevention in preschool minority children. J Pediatr. 2005; 146(5):618–25. PMID: 15870664

38. Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, KauferChristoffel K, Dyer A. Hip-Hop to Health Jr. for Latino preschool children. Obesity (Silver Spring). 2006; 14(9):1616–25.

39. Fitzgibbon ML, Stolley MR, Schiffer LA, Braunschweig CL, Gomez SL, Van Horn L, et al. Hip-Hop to Health Jr. Obesity Prevention Effectiveness Trial: postintervention results. Obesity (Silver Spring). 2006; 19(5):994–1003.

40. Potamites E, Gordon A. Children’s food security and intakes from school meals: final report. Princeton, NJ: Mathematica Policy Research, 2010 Contract No.: Contractor and Cooperator Report No. 61.

41. Cohen JF, Richardson S, Parker E, Catalano PJ, Rimm EB. Impact of the new U.S. Department of Agri- culture school meal standards on food selection, consumption, and waste. Am J Prev Med. 2014; 46 (4):388–94. doi: 10.1016/j.amepre.2013.11.013 PMID: 24650841

42. Long MW, Tobias DK, Cradock AL, Batchelder H, Gortmaker SL. Systematic review and meta-analysis of the impact of restaurant menu calorie labeling. Am J Public Health. 2015; 105(5):e11–24. doi: 10. 2105/AJPH.2015.302570 PMID: 25790388

43. Kiszko KM, Martinez OD, Abrams C, Elbel B. The influence of calorie labeling on food orders and con- sumption: a review of the literature. J Community Health. 2014; 39(6):1248–69. doi: 10.1007/s10900- 014-9876-0 PMID: 24760208

44. Chen R, Smyser M, Chan N, Ta M, Saelens BE, Krieger J. Changes in awareness and use of calorie information after mandatory menu labeling in restaurants in King County, Washington. Am J Public Health. 2015; 105(3):546–53. doi: 10.2105/AJPH.2014.302262 PMID: 25602868

45. Andreyeva T, Middleton AE, Long MW, Luedicke J, Schwartz MB. Food retailer practices, attitudes and beliefs about the supply of healthy foods. Public Health Nutr. 14(6):1024–31. doi: 10.1017/ S1368980011000061 PMID: 21324231

PLOSMedicine | DOI:10.1371/journal.pmed.1001914 December 8, 2015 8 / 9http://dx.doi.org/10.1016/j.jada.2009.02.011http://www.ncbi.nlm.nih.gov/pubmed/19394475http://dx.doi.org/10.2105/AJPH.2012.300660http://www.ncbi.nlm.nih.gov/pubmed/22698052http://dx.doi.org/10.1017/S1368980014002742http://www.ncbi.nlm.nih.gov/pubmed/25475559http://dx.doi.org/10.1371/journal.pone.0032908http://www.ncbi.nlm.nih.gov/pubmed/22496738http://www.ncbi.nlm.nih.gov/pubmed/19951246http://www.imdb.com/title/tt0097351/http://dx.doi.org/10.1007/s10995-013-1359-xhttp://www.ncbi.nlm.nih.gov/pubmed/24065371http://dx.doi.org/10.1111/j.1365-2214.2010.01205.xhttp://dx.doi.org/10.1111/j.1365-2214.2010.01205.xhttp://www.ncbi.nlm.nih.gov/pubmed/21276039http://dx.doi.org/10.3945/ajcn.2009.28826http://www.ncbi.nlm.nih.gov/pubmed/20147472http://www.ncbi.nlm.nih.gov/pubmed/15870664http://dx.doi.org/10.1016/j.amepre.2013.11.013http://www.ncbi.nlm.nih.gov/pubmed/24650841http://dx.doi.org/10.2105/AJPH.2015.302570http://dx.doi.org/10.2105/AJPH.2015.302570http://www.ncbi.nlm.nih.gov/pubmed/25790388http://dx.doi.org/10.1007/s10900-014-9876-0http://dx.doi.org/10.1007/s10900-014-9876-0http://www.ncbi.nlm.nih.gov/pubmed/24760208http://dx.doi.org/10.2105/AJPH.2014.302262http://www.ncbi.nlm.nih.gov/pubmed/25602868http://dx.doi.org/10.1017/S1368980011000061http://dx.doi.org/10.1017/S1368980011000061http://www.ncbi.nlm.nih.gov/pubmed/21324231

46. Andreyeva T, Luedicke J. Federal food package revisions: effects on purchases of whole-grain prod- ucts. Am J Prev Med. 2013; 45(4):422–9. doi: 10.1016/j.amepre.2013.05.009 PMID: 24050418

47. Andreyeva T, Luedicke J. Incentivizing fruit and vegetable purchases among participants in the Special Supplemental Nutrition Program for Women, Infants, and Children. Public Health Nutr. 2014:1–9.

48. Andreyeva T, Luedicke J, Henderson KE, Schwartz MB. The positive effects of the revised milk and cheese allowances in the special supplemental nutrition program for women, infants, and children. J Acad Nutr Diet. 2014; 114(4):622–30. doi: 10.1016/j.jand.2013.08.018 PMID: 24210878

49. Andreyeva T, Luedicke J, Tripp AS, Henderson KE. Effects of reduced juice allowances in food pack- ages for the women, infants, and children program. Pediatrics. 2013; 131(5):919–27. doi: 10.1542/ peds.2012-3471 PMID: 23629613

50. Bartlett S, Klerman J, Olsho L, Logan C, Blocklin M, Beauregard M, et al. Evaluation of the Healthy Incentives Pilot (HIP): final report. U.S. Department of Agriculture, Food and Nutrition Service, Septem- ber 2014.

51. Gillings D, Makuc D, Siegel E. Analysis of interrupted time series mortality trends: an example to evalu- ate regionalized perinatal care. Am J Public Health. 1981; 71(1):38–46. PMID: 7258429

52. Powell LM, Chriqui JF, Khan T, Wada R, Chaloupka FJ. Assessing the potential effectiveness of food and beverage taxes and subsidies for improving public health: a systematic review of prices, demand and body weight outcomes. Obes Rev. 2013; 14(2):110–28. doi: 10.1111/obr.12002 PMID: 23174017

53. Thow AM, Jan S, Leeder S, Swinburn B. The effect of fiscal policy on diet, obesity and chronic disease: a systematic review. Bull World Health Organ. 2010; 88(8):109–614.

54. Basu S, Seligman H, Bhattacharya J. Nutritional policy changes in the supplemental nutrition assis- tance program: a microsimulation and cost-effectiveness analysis. Med Decis Making. 2013; 33 (7):937–48. doi: 10.1177/0272989X13493971 PMID: 23811757

55. Basu S, Seligman HK, Gardner C, Bhattacharya J. Ending SNAP subsidies for sugar-sweetened bever- ages could reduce obesity and type 2 diabetes. Health Aff (Millwood). 2014; 33(6):1032–9.

56. Hay SI, George DB, Moyes CL, Brownstein JS. Big data opportunities for global infectious disease sur- veillance. PLoS Med. 2013; 10(4):e1001413. doi: 10.1371/journal.pmed.1001413 PMID: 23565065

57. Lewis KH, Roblin DW, Leo M, Block JP. The personal shopper—a pilot randomized trial of grocery store-based dietary advice. Clin Obes. 2015; 5(3):154–61. doi: 10.1111/cob.12095 PMID: 25873139

58. Finkelstein EA, Zhen C, Bilger M, Nonnemaker J, Farooqui AM, Todd JE. Implications of a sugar-sweet- ened beverage (SSB) tax when substitutions to non-beverage items are considered. J Health Econ. 2013; 32(1):219–39. doi: 10.1016/j.jhealeco.2012.10.005 PMID: 23202266

59. Lin BH, Smith TA, Lee JY, Hall KD. Measuring weight outcomes for obesity intervention strategies: the case of a sugar-sweetened beverage tax. Econ Hum Biol. 2011; 9(4):329–41. doi: 10.1016/j.ehb.2011. 08.007 PMID: 21940223

60. Zhen C, Finkelstein EA, Nonnemaker J, Karns S, Todd JE. Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System. Am J Agric Econ. 2014; 96(1):1–25. PMID: 24839299

61. Briggs AD, Mytton OT, Kehlbacher A, Tiffin R, Rayner M, Scarborough P. Overall and income specific effect on prevalence of overweight and obesity of 20% sugar sweetened drink tax in UK: econometric and comparative risk assessment modelling study. BMJ. 2013; 347:f6189. doi: 10.1136/bmj.f6189 PMID: 24179043

62. World Health Organization Regional Office for Europe. Using price policies to promote healthier diets. Copenhagen, Denmark: WHO Regional Office for Europe. 2014 [cited 2015 May 5]. http://www.euro. who.int/__data/assets/pdf_file/0008/273662/Using-price-policies-to-promote-healthier-diets.pdf.

PLOSMedicine | DOI:10.1371/journal.pmed.1001914 December 8, 2015 9 / 9http://dx.doi.org/10.1016/j.amepre.2013.05.009http://www.ncbi.nlm.nih.gov/pubmed/24050418http://dx.doi.org/10.1016/j.jand.2013.08.018http://www.ncbi.nlm.nih.gov/pubmed/24210878http://dx.doi.org/10.1542/peds.2012-3471http://dx.doi.org/10.1542/peds.2012-3471http://www.ncbi.nlm.nih.gov/pubmed/23629613http://www.ncbi.nlm.nih.gov/pubmed/7258429http://dx.doi.org/10.1111/obr.12002http://www.ncbi.nlm.nih.gov/pubmed/23174017http://dx.doi.org/10.1177/0272989X13493971http://www.ncbi.nlm.nih.gov/pubmed/23811757http://dx.doi.org/10.1371/journal.pmed.1001413http://www.ncbi.nlm.nih.gov/pubmed/23565065http://dx.doi.org/10.1111/cob.12095http://www.ncbi.nlm.nih.gov/pubmed/25873139http://dx.doi.org/10.1016/j.jhealeco.2012.10.005http://www.ncbi.nlm.nih.gov/pubmed/23202266http://dx.doi.org/10.1016/j.ehb.2011.08.007http://dx.doi.org/10.1016/j.ehb.2011.08.007http://www.ncbi.nlm.nih.gov/pubmed/21940223http://www.ncbi.nlm.nih.gov/pubmed/24839299http://dx.doi.org/10.1136/bmj.f6189http://www.ncbi.nlm.nih.gov/pubmed/24179043http://www.euro.who.int/__data/assets/pdf_file/0008/273662/Using-price-policies-to-promote-healthier-diets.pdfhttp://www.euro.who.int/__data/assets/pdf_file/0008/273662/Using-price-policies-to-promote-healthier-diets.pdf