Nutritional Characteristics of Foods With Addictive Potential: A Machine-Learning Approach.

Objectives. To identify nutritional characteristics associated with the perceived addictive potential of commonly consumed foods in the US food supply, the majority of which are ultraprocessed foods (UPFs). Methods. In a demographically diverse sample of US adults (n = 1664; 55.2% female), participa...

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Publicado en:	American Journal of Public Health Vol. 116; no. 7; pp. 950 - 960
Autores principales:	Gearhardt, Ashley N., Hutelin, Zach, Nartey, Emmanuel, Ahrens, Monica L., Baugh, Mary Elizabeth, Fazzino, Tera L., LaFata, Erica M., Sonneville, Kendrin R., DiFeliceantonio, Alexandra G.
Formato:	Artículo
Publicado:	American Public Health Association Jul2026
Materias:	United States Compulsive behavior Food consumption Food habits Food supply Nutrition Social classes Educational attainment Random forest algorithms Research funding Carbohydrates Visual analog scale Nutritional requirements Descriptive statistics Carbohydrate content of food Machine learning Glycemic index Data analysis software Algorithms
Acceso en línea:	Ver este registro en EBSCOhost