A Statistical Analysis of a Traffic-Light Food Rating System to Promote Healthy Nutrition and Body Weight

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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).

Conclusion:

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.

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