1. Food environment interventions to promote healthy choices in a low-income, Latino community Anne Thorndike, MD, MPH General Medicine Division and Cardiovascular Prevention Center, Massachusetts General Hospital, Boston, MA Hispanic-American Institute, Healthy Foods Symposium March 9, 2015 1

2. Overview 2 1.Obesity, diabetes, and the food environment 2.Food environment interventions in Chelsea, MA 3.Summary/Next steps

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7. 7 Obesity Rates in Hispanic Youth and Adults 2011-2012 Ogden, et al. JAMA, 2014. % overweight or obese

8. Diabetes in Hispanic/Latinos 8 Rates of diabetes 7.1% non-Hispanic whites 12.6% non-Hispanic blacks 11.8% Hispanic/Latinos 7.6% Cuban Americans and Central/South Americans 13.3% Mexican Americans 13.8% Puerto Ricans Latinos are 1.5 times more likely to die from diabetes than non-Hispanic whites In 2014, one in five Latinos in America reported diabetes is the biggest health problem facing their families

9. A framework for thinking about the obesity problem 9 INDIVIDUALS ENVIRONMENTS VECTORS Non-modifiable factors: genes, age Modifiable factors: behaviors and attitudes Computers, cars, sedentary job; “toxic” food environment Physical, economic, sociocultural, policy Educational, behavioral, and medical intervention Food environment; technology Policy and social change Adapted from Swinburn et al, Obesity Reviews, 2002.

10. Targeting sugar-sweetened beverages and fruits and vegetables to prevent obesity 10 Sugar-sweetened beverages (SSBs) –major contributor to excessive calories in children’s diets; US children drink more than one SSB per day –reducing SSB consumption can help reduce obesity Fruits and vegetables (F/V) –increased F/V intake associated with lower rates of obesity and chronic disease Low-income individuals consume more SSBs and fewer F/V than those with higher incomes

11. Food Environment Interventions 11 1.Healthy Chelsea Corner Store Connection 2.Compare Market, Choose Well/Elige Bien!

12. Chelsea, Massachusetts 12 Two square miles; 35,000 residents 62% Latino; 44% Spanish as primary language Median income= $30,000; 25% of families live at or below poverty 2010: 50% school-aged children were overweight or obese 2011 survey: 46 of 49 stores that sold food had limited availability of healthy foods –25% no produce; 50% fewer than 4 varieties

13. Chelsea Corner Store Connection 13 Collaboration between MGH researchers, MGH Center for Community Health Improvement (CCHI), and six corner stores in Chelsea. Objective: Increase availability and visibility of produce in corner stores and test whether customers purchased more fruits and vegetables after the intervention. Enrolled 6 stores; 3 intervention and 3 control Outcomes: 1.WIC fruit and vegetable voucher redemption at stores 2.Store customer exit surveys

14. Chelsea Corner Store Connection 14 Key aspects All stores paid $500 every 3 months (total of $1500) to participate in the research Intervention: new produce baskets, shelving, refrigerator (one); signage; targeted education about produce storage, display, and shelf life Friendly negotiations with owners Evaluation of outcomes

15. 15 Intervention Store A: Before

16. 16 Intervention Store A: After

17. Intervention Store B: Before 17

18. Intervention Store B: After 18

19. Chelsea Corner Store Connection: preliminary survey results 19 Control store customers (N=280) Intervention store customers (N=294)P value Male43%47%NS Hispanic/Latino93%84%.001 Main reason for visiting store: Groceries Snack Beverage Lottery ticket/cigarettes Other 64% 13% 17% 7% 10% 36% 21% 20% 21% 18% <.001.02 NS <.001 Lives within 3 blocks of store88%79%.07 WIC participant29%24%NS SNAP participant38%36%NS

20. Chelsea Corner Store Connection: preliminary survey results 20 Pre- intervention Post- interventionChange P- value P-value interaction Purchased fresh fruit Control stores21%23%2%NS Intervention stores13% 0NS Purchased fresh vegetables Control stores26%15%-10%.03NS Intervention stores8%7%-1%NS Planned to buy F/V at corner store Control stores38%32%-6%NS Intervention stores20%21%1%NS

21. Collaboration between MGH and Harvard School of Public Health researchers, MGH CCHI, and Alberto Calvo, owner of Compare Objective: –To conduct a randomized controlled trial testing the effectiveness of in-store traffic-light labels, beverage education, and financial incentives to reduce the purchase of sugar-sweetened beverages by low- income, Latino families who were regular customers of Compare Supermarket. 21 Compare Supermarket: Choose Well/Elige Bien!

22. Randomized, controlled trial 216 customers enrolled; half randomly assigned to get financial incentives Inclusion criteria: regular customer of Compare supermarket; speak English or Spanish “Loyalty card” identifies customer’s purchases at check-out; 5% off every purchase 22 Study Design and Data Collection Anne Thorndike

23. Collected baseline purchasing data for 2 months Labeled beverages with “traffic lights” Half of study participants received monthly letters with targeted beverage education and financial incentive ($25 Compare gift card) for not purchasing “red” beverages Collected sales data for 5 months after labels in place 23 Study Design and Data Collection

24. 24 In-store signage

25. 25 Traffic-light shelf labels

26. 26 Demographics of study participants Intervention group (N=77) Control group (N=71) Subjects who never used card (N=36) Age category 18-39 40 and over 66% 34% 66% 34% 74% 26% Female100%97%100% Hispanic/Latino99% 100% Children in household, mean (SD)2.0 (1.0)2.1 (1.1)2.1 (0.9) Use SNAP for groceries66%49%*54% Frequency of shopping at Compare Once a month Once a week Twice a week or more 1% 26% 73% 3% 34% 63% 9% 23% 63% Proportion groceries from Compare More than half or all About half 42% 58% 38% 62% 29% 71% * P=0.04 compared to intervention group

27. 27 Self-reported daily beverage consumption Intervention group (N=77) Control group (N=71) Water94%97% Hot coffee or tea77% Seltzer water5%7% Diet soda3%6% 100% fruit juice55%54% Juice drinks40%32% Soda29%23% Powder mixes29%17% Sports drinks14%21%

28. 28 Proportion of intervention subjects who purchased any red beverages decreased 9% more per month than control (N=148) % who purchased red beverages Baseline Intervention P=0.002 Traffic-light labels posted

29. 29 Trend over time in proportion of subjects who purchased any red beverages % who purchased red beverages Baseline Intervention P=0.002 Traffic-light labels posted

30. 30 Proportion of intervention subjects on SNAP who purchased any red beverages decreased 8% more per month than control (N=86) % who purchased red beverages Baseline Intervention P=0.07 Traffic-light labels posted

31. 31 Trend over time in proportion of subjects on SNAP who purchased “red” beverages % who purchased red beverages Baseline Intervention P=0.07 Traffic-light labels posted

32. Choose Well/Elige Bien! Conclusions 32 In-store traffic-light labels, beverage education, and financial incentives reduced SSB purchases among low-income Latino families. Strategies that combine point-of-purchase labeling, education, and incentives have potential to improve both motivation and skills for making healthier choices among low-income populations. Future research is needed to test scalability and long-term effectiveness.

33. Summary 33 Obesity is higher among Hispanic/Latino youth and adults and contributes to higher rates of chronic disease and death. The strong evidence base for reducing SSB’s and increasing F/V to reduce obesity provides an opportunity for targeted efforts that could have a large impact in low-income neighborhoods. Relatively small changes in neighborhood corner stores and grocery stores have potential for promoting healthier choices.

34. Next steps 34 Project to connect the MGH Chelsea pediatric practice with Compare Supermarket and to evaluate change in consumption and purchases of SSB’s and F/V. Hypothesize “linking” health care and food retail to provide consistent, evidence-based nutrition information reinforced in the community food environment will lead to healthier choices. New rules allow non-profit hospitals to use community benefits for “nutrition and other social determinants of health,” and could potentially fund these types of partnerships in the future.

35. Acknowledgements Collaborators MGH Center for Community Health Improvement –Melissa Dimond –Ron Fishman MGH Health Policy –Douglas Levy Harvard School of Public Health –Eric Rimm –Lorena Macias-Navarro –Becky Franckle Compare Supermarket –Alberto Calvo Funding Nutrition Obesity Research Center at Harvard Harvard Catalyst MGH Center for Community Health Improvement 35