title: A Statistical Analysis of a Traffic-Light Food Rating System to Promote Healthy Nutrition and Body Weight.
abstract: BACKGROUND
  Restaurant eating while optimizing nutrition and maintaining a healthy weight is challenging. Even when nutritional information is available, consumers often consider only calories. A quick and easy method to rate both caloric density and nutrition is an unmet need. A food rating system created to address that need is assessed in this study.
  
  
  METHODS
  The food rating system categorizes food items into 3 color-coded categories: most healthy (green), medium healthy (yellow), or least healthy (red) based on calorie density and general nutritional quality from national guidelines. Nutritional information was downloaded from 20 popular fast-food chains. Nutritional assessments and the 3 color coded categories were compared using the Wilcoxon and Median tests to demonstrate the significance of nutrition differences.
  
  
  RESULTS
  Green foods were significantly lower than yellow foods, which in turn were significantly lower than red foods, for calories and calories from fat, in addition to content of total fat, saturated fat and carbohydrates per 100 g serving weight (all P < .02). The green foods had significantly lower cholesterol than the yellow (P = .0006) and red (P < .0001) foods. Yellow foods had less sugar than red foods (P < .0001). Yellow foods were significantly higher in dietary fiber than red foods (P = .001).
  
  
  CONCLUSIONS
  The food rating color-coded system identifies food items with superior nutrition, and lower caloric density. The smartphone app, incorporating the system, has the potential to improve nutrition; reduce the risk of developing diabetes, hypertension, heart disease, and stroke; and improve public health.
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, LA, USA.
authors.forename: Sandra
authors.initials: S
authors.lastname: Larrivee
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, LA, USA FrankGreenway@pbrc.edu.
authors.forename: Frank L
authors.initials: FL
authors.lastname: Greenway
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, LA, USA.
authors.forename: William D
authors.initials: WD
authors.lastname: Johnson
mesh_terms: D001835:Body Weight; D002755:Choice Behavior; D054626:Consumer Health Information; D004435:Eating; D002149:Energy Intake; D057140:Fast Foods / Q000706:statistics & numerical data; D005247:Feeding Behavior; D005515:Food Labeling / Q000706:statistics & numerical data; D005518:Food Preferences; D015438:Health Behavior; D006801:Humans; D063731:Mobile Applications / Q000706:statistics & numerical data*; D015233:Models, Statistical; D009752:Nutritional Status; D009753:Nutritive Value; D064787:Portion Size; D012147:Restaurants / Q000706:statistics & numerical data*; D000068997:Smartphone / Q000706:statistics & numerical data*; D012985:Software Design; D014342:Truth Disclosure
keywords: consumer health; dietary guide; healthy eating; improving poor nutrition; nutritional assistance