University of Southern California (USC) researchers used machine learning to analyze digital menus from restaurants across Los Angeles to identify food disparities in the city.
The ultimate goal is to improve access to nutritional food options in disadvantaged communities via rezoning.
The researchers used generic meal data from food database and nutrition data and analytics provider Edamam, and nutrition and ingredient content data from large chain restaurant menus provided by Nutritionix.
In an initial analysis involving about 1,000 "limited service" restaurants in the region, USC's Abigail Horn said, "What we see is that the unhealthiest outlets are almost uniformly distributed across the map," but "the healthiest outlets are clustered only in the more affluent neighborhoods."
From USC Viterbi School of Engineering
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