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A Comparison of Protein and Fiber Content in 52 Chain Restaurant Menus
Author(s) -
Wang Yu,
Lau Rebecca,
Brown Diamond S.,
Cino Janette,
Jung Rebecca,
Mizuki Mayu,
Wang Mengli,
You Shengwen,
Nakamura Manabu T.
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.643.4
Subject(s) - calorie , fiber , overeating , computer science , block (permutation group theory) , food science , obesity , medicine , mathematics , biology , chemistry , geometry , organic chemistry
Background Over the past decade, obesity prevalence has remained high in the U.S. and is associated with multiple chronic diseases such as hypertension, type 2 diabetes, and cardiovascular diseases. American consumers today are eating out more frequently than before, thus making healthy food choices for maintaining weight challenging. Objectives 1) Develop an effective visualization of nutrition information of restaurant menus for consumer use, and 2) compare quality of menus among chain restaurants. Methods Nutrition data of menu items available online were obtained from 52 chain restaurants. Two important nutrients for preventing overeating, protein and fiber, in each menu item were analyzed. A previous study has shown that displaying graphical nutrition information in a cafeteria improved consumer purchasing behaviors compared to numerical based presentation. Based on the study, the protein % of total calorie and grams of fiber per 100 kcal of all menu items from each restaurant were plotted together with a box showing a target range (16–32% protein and 1.4–2.8 g fiber/kcal). To compare quality of menus among restaurants, we divided the graph into six blocks based on varying protein and fiber per calorie: block 1, both protein and fiber below target; block 2, either protein or fiber is on target but not both; block 3, both protein and fiber in the target range; block 4, fiber exceeds the target range but protein below target; block 5, protein exceeds target but fiber below target; and block 6, both protein and fiber beyond the target. Results Some restaurants had more than 200 menu items, making a plot of all the menu items in a graph difficult to use. Dividing a menu into sub‐categories in a logical manner would solve the problem. Another issue was that selecting a right combination is difficult without the assistance of interactive software although foods outside of the target can be used to create an on‐target meal. We found that the majority of menu items fell into blocks 1, 2 and 4, which are the high protein‐low fiber and low protein‐low fiber ranges. Relatively few items, less than 10 on average, fell into the target range or beyond. We found that fiber was the limiting nutrient in creating adequate combinations. Across all restaurants, relatively few menu items contained significant fiber content per calorie. For most of the restaurants, it is possible to make combinations with balanced protein and fiber content within the target range; however, these capabilities vary among restaurants. Conclusions With further modifications, an interactive visual aid can be created for customers to select healthy choices when eating out. Because most chain restaurants analyzed offer a small number of healthy items, choosing healthy options while eating out is possible. Support or Funding Information USDA NIFA ILLU‐698‐376