142nd APHA Annual Meeting and Exposition

Annual Meeting Recordings are now available for purchase

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Grellin: A new website ranking the top chain restaurant menus on healthiness

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Wednesday, November 19, 2014 : 11:30 AM - 11:50 AM

Lenard Lesser, MD MSHS , Palo Alto Medical Foundation Research Institute, Palo Alto, CA
Leslie Wu, PhD , Palo Alto Medical Foundation Research Institute, Palo Alto, CA
INTRODUCTION: Consumers and policy makers do not have an efficient and objective way to analyze the health of chain restaurant menus. APPROACH: The New York City Department of Health Menustat database compiles nutrient data (e.g. calories, saturated fat, sodium, protein, fiber) on the top chain restaurants in the USA. To determine the amount of fruit, vegetable, and nut (FVN) amounts in menu items, we utilized computer science techniques based on crowd sourcing. We ran the Menustat nutrient data and FVN amounts through the modified Oxford Nutrient Profiling Criteria, which assigns points to a food item based on its nutrient content as well as FVN content. Each menu item received a Nutrient Profile Index (NPI) Score, between 0 and 100 (poorest to highest nutritional quality). Foods with a score of 64 or higher, that contained less than or equal to 700 calories per entrée were considered healthy. Restaurants were then ranked according to the proportion of menu items that were determined healthy. RESULTS: Based on preliminary analyses using only nutrient content points, the median proportion of healthy items for 66 chains was 31.9 (range 0-78.9).  We will present the overall rankings for the top chain restaurants based on the full scoring method. DISCUSSION: By combining established nutritional analyses with innovative computer science methods, researchers can objectively analyze the healthiness of restaurant food offerings. These rankings can thus provide consumers more complete information on healthier dining options and allow policy makers to evaluate initiatives that intend to change menu offerings.

Learning Areas:

Public health or related public policy
Public health or related research

Learning Objectives:
Demonstrate how using computer science methods such as crowdsourcing, can allow nutrition researchers to quickly analyze the nutritional quality of restaurant menus. Compare the relative healthiness of popular chain restaurants based on menu offerings.

Keyword(s): Nutrition, Obesity

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a researcher in the area of food marketing and the food environment.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.