Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study

Typical diets include an assortment of unprocessed, processed, and ultra-processed foods, along with culinary ingredients. Linear programming (LP) can be used to generate nutritionally adequate food patterns that meet pre-defined nutrient guidelines. The present LP models were set to satisfy 22 nutr...

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Autores principales:	Skyler Hallinan, Chelsea Rose, James Buszkiewicz, Adam Drewnowski
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	food patterns diet quality ultra-processed foods linear programming SOS III Nutrition. Foods and food supply TX341-641
Acceso en línea:	https://doaj.org/article/d58a6f63f0854a74989fcd0389804736
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spelling	oai:doaj.org-article:d58a6f63f0854a74989fcd03898047362021-11-25T18:34:33ZSome Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study10.3390/nu131138382072-6643https://doaj.org/article/d58a6f63f0854a74989fcd03898047362021-10-01T00:00:00Zhttps://www.mdpi.com/2072-6643/13/11/3838https://doaj.org/toc/2072-6643Typical diets include an assortment of unprocessed, processed, and ultra-processed foods, along with culinary ingredients. Linear programming (LP) can be used to generate nutritionally adequate food patterns that meet pre-defined nutrient guidelines. The present LP models were set to satisfy 22 nutrient standards, while minimizing deviation from the mean observed diet of the Seattle Obesity Study (SOS III) sample. Component foods from the Fred Hutch food frequency questionnaire comprised the market basket. LP models generated optimized 2000 kcal food patterns by selecting from all foods, unprocessed foods only, ultra-processed foods only, or some other combination. Optimized patterns created using all foods contained less fat, sugar, and salt, and more vegetables compared to the SOS III mean. Ultra-processed foods were the main sources of added sugar, saturated fat and sodium. Ultra-processed foods also contributed most vitamin E, thiamin, niacin, folate, and calcium, and were the main sources of plant protein. LP models failed to create optimal diets using unprocessed foods only and ultra-processed foods only: no mathematical solution was obtained. Relaxing the vitamin D criterion led to optimized diets based on unprocessed or ultra-processed foods only. However, food patterns created using unprocessed foods were significantly more expensive compared to those created using foods in the ultra-processed category. This work demonstrates that foods from all NOVA categories can contribute to a nutritionally adequate diet.Skyler HallinanChelsea RoseJames BuszkiewiczAdam DrewnowskiMDPI AGarticlefood patternsdiet qualityultra-processed foodslinear programmingSOS IIINutrition. Foods and food supplyTX341-641ENNutrients, Vol 13, Iss 3838, p 3838 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	food patterns diet quality ultra-processed foods linear programming SOS III Nutrition. Foods and food supply TX341-641
spellingShingle	food patterns diet quality ultra-processed foods linear programming SOS III Nutrition. Foods and food supply TX341-641 Skyler Hallinan Chelsea Rose James Buszkiewicz Adam Drewnowski Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
description	Typical diets include an assortment of unprocessed, processed, and ultra-processed foods, along with culinary ingredients. Linear programming (LP) can be used to generate nutritionally adequate food patterns that meet pre-defined nutrient guidelines. The present LP models were set to satisfy 22 nutrient standards, while minimizing deviation from the mean observed diet of the Seattle Obesity Study (SOS III) sample. Component foods from the Fred Hutch food frequency questionnaire comprised the market basket. LP models generated optimized 2000 kcal food patterns by selecting from all foods, unprocessed foods only, ultra-processed foods only, or some other combination. Optimized patterns created using all foods contained less fat, sugar, and salt, and more vegetables compared to the SOS III mean. Ultra-processed foods were the main sources of added sugar, saturated fat and sodium. Ultra-processed foods also contributed most vitamin E, thiamin, niacin, folate, and calcium, and were the main sources of plant protein. LP models failed to create optimal diets using unprocessed foods only and ultra-processed foods only: no mathematical solution was obtained. Relaxing the vitamin D criterion led to optimized diets based on unprocessed or ultra-processed foods only. However, food patterns created using unprocessed foods were significantly more expensive compared to those created using foods in the ultra-processed category. This work demonstrates that foods from all NOVA categories can contribute to a nutritionally adequate diet.
format	article
author	Skyler Hallinan Chelsea Rose James Buszkiewicz Adam Drewnowski
author_facet	Skyler Hallinan Chelsea Rose James Buszkiewicz Adam Drewnowski
author_sort	Skyler Hallinan
title	Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
title_short	Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
title_full	Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
title_fullStr	Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
title_full_unstemmed	Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study
title_sort	some ultra-processed foods are needed for nutrient adequate diets: linear programming analyses of the seattle obesity study
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d58a6f63f0854a74989fcd0389804736
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Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study

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