APHA- Washington, DC, November 1, 2011

1. Over exposure to food opportunities around schools: A sea of choices that lead to obesity? APHA- Washington, DC, November 1, 2011 Presented by: Alyssa Ghirardelli, MPH, RD Additional contributors: Valerie Quinn, MEd., Sharon Sugerman, MS, RD, Mee Vang, MPH, Bhavdeep Sachdev, MS, BE This material was produced by the California Department of Public Health, Network for a Healthy California, with funding from the USDA Supplemental Nutrition Assistance Program (formerly the Food Stamp Program). This material was produced by the California Department of Public Health, Network for a Healthy California, with funding from the USDA Supplemental Nutrition Assistance Program (formerly the Food Stamp Program). These institutions are equal opportunity providers and employers. In California, food stamps provide assistance to low-income households, and can help buy nutritious foods for better health. For food stamp information, call 877-847-3663. For important nutrition information visit www.cachampionsforchange.net. This material was produced by the California Department of Public Health, Network for a Healthy California, with funding from the USDA Supplemental Nutrition Assistance Program (formerly the Food Stamp Program). These institutions are equal opportunity providers and employers. In California, food stamps provide assistance to low-income households, and can help buy nutritious foods for better health. For food stamp information, call 877-847-3663. For important nutrition information visit www.cachampionsforchange.net. This material was produced by the California Department of Public Health, Network for a Healthy California, with funding from the USDA Supplemental Nutrition Assistance Program (formerly the Food Stamp Program). These institutions are equal opportunity providers and employers. In California, food stamps provide assistance to low-income households, and can help buy nutritious foods for better health. For food stamp information, call 877-847-3663. For important nutrition information visit www.cachampionsforchange.net.

2. Presenter Disclosures Alyssa Ghirardelli, MPH, RD (1) The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months: No relationships to disclose

3. Retail Food in Close Proximity to Schools : Evidence Growing • Babey, et al. Food environments near home and school related to consumption of soda and fast food. Policy Brief UCLA Cent Health Policy Res. 2011 • Davis, et al. Proximity of Fast Food Restaurants to schools and Adolescent Obesity.Am J Public Health, 2009. • Links fast-food within a ½ mile of schools to higher BMI and poor dietary behaviors • Simon, et al. Proximity of fast food restaurants to schools: Do neighborhood income and type of school matter? Preventive Med, 2008. • Sturm, Disparities in the food environment surrounding US middle and high schools J Royal Inst Public Health, 2007 • Austin, et al. Clustering of fast-food restaurants around schools a novel application of spatial statistics to the study of food environments. Am J Public Health, 2005.

4. California Teen Eating, Exercise, and Nutrition Survey (CalTEENS) Trends Overweight and Obesity California Teens Aged 12-17 28.6 26.7 24.3 23.4 21.8 21.3 (BMI ≥ 85th %ile 1998-2004 p<.001), (BMI ≥ 85th %ile 2002-2004 p<.01) (BMI ≥ 95th %ile 1998-2004 p<.001), (BMI ≥ 85th %ile 2004-2008 p<.001)

5. CX3: Communities of Excellencein Nutrition, Physical Activity and Obesity Prevention • Documents the physical environment and encourages local action to change conditions to support individual behaviors • Involves assessing communities in relation to a variety of obesity prevention benchmarks known as community indicators and assets • Uses data to activate consumers and partners to improve food availability in low-income neighborhoods and around schools • 3= nutrition, physical activity and obesity prevention

6. CX3:Use of On-line Network GIS Map Viewerhttp://www.cnngis.org

7. CX3 Data: Retail Database Layers Dun and Bradstreet Retail Dataset • Grocery Stores • Convenience Stores • Fast Food • Fast food chain/not chain • Pizza • Deli • Restaurants • Cafes, ice cream, donut shops, etc.

8. CX3 Data: Retail Database Layers Revised Restaurant layer • Important to factor types like fast-casual that are not part of fast food retail layers • Includes Chipotle, Panera Bread, etc. • Also, diners (Denny’s, IHOP) • Cleaned to remove establishments clearly not restaurants by name • Dentists, insurance providers, handymen, plumbers, roofers, jewelers, attorneys, etc. • Removed catering services and personal chefs

9. CX3 Data: Retail Database Layers Revised Restaurant layer • Created “youth” specific data layer • adding to GIS currently • Removed alcohol-related establishments • bars, night clubs, pubs, taverns, etc. • Added back in juice bars, taco bars, noodle bars, etc. • Removed chains with 20+ not meeting youth-oriented criteria developed • serves alcohol, menu items ≥ $10, sit-down/upscale appearance on web

10. CX3 Retail Opportunities Dataset • 8,923 Public schools from California Department of Education 2009 • 1,123 (12.5%) have no retail food w/in ½ mile • 7,800 (87.4%) have retail food w/in ½ mile

11. Retail food opportunities around schools ½ mile buffer High School

12. Mean of All Retail by School Type All food retail types combined, high schools have more

13. Small Differences in Mean for Type of Retail Food Opportunities by School Type

14. Retail Food Exposure Scale Range 0-677 locations w/in ½ mile of schools n= 8923

15. Neighborhood Income Disparities for Schools with Higher Numbers of Retail 185% Federal Poverty Level=WIC, SNAP-Ed Eligible 2005-2009 American Communities Survey (ACS)

16. Top 10 Worst High Schools • 7 out of 10 areas qualified as low-income or very low income using SNAP-Ed criteria • More than 50% population ≤ 185% Federal Poverty Level- 2005-2009 American Communities Survey • Two nearly met income criteria • (40-49% population in poverty) • Six schools have students with measures not in the healthy fitness zone for body composition higher than the state level • Three schools no FITNESSGRAM data

17. Top Worst High Schools

18. Top Worst High Schools

19. Top Worst High Schools

20. Implications • More evidence documenting presence of retail food opportunities around schools • Important for developing meaningful, targeted nutrition education, media literacy • Critical for understanding what kids are up against outside the school walls • Can inform partnerships and policies • Shows need for initiatives to reduce retail food opportunities around schools

21. Implications Need to reduce disparities between lower income communities, unfairly saturated with retail food opportunities Need to consider more than fast food or small stores in isolation of other retail food Study underscores the need for better quality data sources for mapping applications to consider retail food environments Is there potential to work with Environmental Health Specialists to standardize reporting measures that track retail food for inspections?

22. Next Steps for CX3 • Finalizing a school score that examines environment within ½ mile boundary of school and includes • Retail food stores • Fast food • Outdoor marketing (1000 ft) • Mobile vending (500 ft) • Walkability and safety • More work with retail and school databases • Examine relationships with body composition of youth (FITNESSGRAM), income and school level

23. Thank you! Alyssa Ghirardelli, MPH, RD Research Scientist Network for a Healthy California CA Dept. of Public Health Public Health Institute Alyssa.Ghirardelli@cdph.ca.gov 916-449-5342