Martin, Jolie MBeshears, JohnMilkman, Katherine LBazerman, Max HSutherland, Lisa A2023-05-232023-05-232009-06-012016-09-15https://repository.upenn.edu/handle/20.500.14332/42197Research during the last several decades indicates the failure of existing nutritional labels to substantially improve the healthfulness of consumers' food/beverage choices. The present study aims to fill this void by developing a nutrition metric that is more comprehensible to the average shopper. The healthfulness ratings of 205 sample foods/beverages by leading nutrition experts formed the basis for a linear regression that places weights on 12 nutritional components (ie, total fat, saturated fat, cholesterol, sodium, total carbohydrate, dietary fiber, sugars, protein, vitamin A, vitamin C, calcium, and iron) to predict the average healthfulness rating that experts would give to any food/beverage. Major benefits of the model include its basis in expert judgment, its straightforward application, the flexibility of transforming its output ratings to any linear scale, and its ease of interpretation. This metric serves the purpose of distilling expert knowledge into a form usable by consumers so that they are empowered to make more healthful decisions.© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Human and Clinical NutritionOther Food ScienceArticle