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A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals

BACKGROUND: Nutrient profiling methods can be applied to individual foods or to composite meals. This article introduces a new method to assess the nutrient density of breakfast meals. OBJECTIVE: This study aimed to develop a new breakfast quality score (BQS), based on the nutrient standards previou...

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Autores principales: Poinsot, Romane, Maillot, Matthieu, Masset, Gabriel, Drewnowski, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569224/
https://www.ncbi.nlm.nih.gov/pubmed/37841394
http://dx.doi.org/10.3389/fnut.2023.1213065
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author Poinsot, Romane
Maillot, Matthieu
Masset, Gabriel
Drewnowski, Adam
author_facet Poinsot, Romane
Maillot, Matthieu
Masset, Gabriel
Drewnowski, Adam
author_sort Poinsot, Romane
collection PubMed
description BACKGROUND: Nutrient profiling methods can be applied to individual foods or to composite meals. This article introduces a new method to assess the nutrient density of breakfast meals. OBJECTIVE: This study aimed to develop a new breakfast quality score (BQS), based on the nutrient standards previously published by the International Breakfast Research Initiative (IBRI) consortium. METHODS: BQS was composed of three sub-scores derived from the weighted arithmetic mean of corresponding nutrient adequacy: an eLIMf sub-score (energy, saturated fat, free sugars, and sodium), a PF (protein and fiber) sub-score, and a VMn(1 − 14) micronutrient sub-score, where n varied from 0 to 14. The effects of assigning different weights to the eLIMf, PF, and VMn were explored in four alternative models. The micronutrients were calcium, iron, potassium, magnesium, zinc, vitamin A, thiamin, riboflavin, niacin, vitamin B5, vitamin B6, vitamin B12, vitamin C, and vitamin D. Micronutrient permutations were used to develop alternate VMn(1 − 14) sub-scores. The breakfast database used in this study came from all breakfasts declared as consumed by adults (>18 years old) in the French dietary survey INCA3. All models were tested with respect to the Nutrient Rich Food Index (NRF9.3). BQS sensitivity was tested using three prototype French breakfasts, for which improvements were made. RESULTS: The correlations of the models with NRF9.3 improved when the VMn(>3) sub-score (n > 3) was included alongside the PF and eLIMf sub-scores. The model with (PF+VMn) and eLIMf each accounting for 50% of the total score showed the highest correlations with NRF9.3 and was the preferred final score (i.e., BQS). BQS was sensitive to the changing quality of three prototype breakfasts defined as tartine, sandwich, and cereal. CONCLUSION: The proposed BQS was shown to valuably rank the nutritional density of breakfast meals against a set of nutrient recommendations. It includes nutrients to limit along with protein, fiber, and a variable number of micronutrients to encourage. The flexible VMn sub-score allows for the evaluation of breakfast quality even when nutrient composition data are limited.
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spelling pubmed-105692242023-10-13 A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals Poinsot, Romane Maillot, Matthieu Masset, Gabriel Drewnowski, Adam Front Nutr Nutrition BACKGROUND: Nutrient profiling methods can be applied to individual foods or to composite meals. This article introduces a new method to assess the nutrient density of breakfast meals. OBJECTIVE: This study aimed to develop a new breakfast quality score (BQS), based on the nutrient standards previously published by the International Breakfast Research Initiative (IBRI) consortium. METHODS: BQS was composed of three sub-scores derived from the weighted arithmetic mean of corresponding nutrient adequacy: an eLIMf sub-score (energy, saturated fat, free sugars, and sodium), a PF (protein and fiber) sub-score, and a VMn(1 − 14) micronutrient sub-score, where n varied from 0 to 14. The effects of assigning different weights to the eLIMf, PF, and VMn were explored in four alternative models. The micronutrients were calcium, iron, potassium, magnesium, zinc, vitamin A, thiamin, riboflavin, niacin, vitamin B5, vitamin B6, vitamin B12, vitamin C, and vitamin D. Micronutrient permutations were used to develop alternate VMn(1 − 14) sub-scores. The breakfast database used in this study came from all breakfasts declared as consumed by adults (>18 years old) in the French dietary survey INCA3. All models were tested with respect to the Nutrient Rich Food Index (NRF9.3). BQS sensitivity was tested using three prototype French breakfasts, for which improvements were made. RESULTS: The correlations of the models with NRF9.3 improved when the VMn(>3) sub-score (n > 3) was included alongside the PF and eLIMf sub-scores. The model with (PF+VMn) and eLIMf each accounting for 50% of the total score showed the highest correlations with NRF9.3 and was the preferred final score (i.e., BQS). BQS was sensitive to the changing quality of three prototype breakfasts defined as tartine, sandwich, and cereal. CONCLUSION: The proposed BQS was shown to valuably rank the nutritional density of breakfast meals against a set of nutrient recommendations. It includes nutrients to limit along with protein, fiber, and a variable number of micronutrients to encourage. The flexible VMn sub-score allows for the evaluation of breakfast quality even when nutrient composition data are limited. Frontiers Media S.A. 2023-09-28 /pmc/articles/PMC10569224/ /pubmed/37841394 http://dx.doi.org/10.3389/fnut.2023.1213065 Text en Copyright © 2023 Poinsot, Maillot, Masset and Drewnowski. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Nutrition
Poinsot, Romane
Maillot, Matthieu
Masset, Gabriel
Drewnowski, Adam
A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title_full A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title_fullStr A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title_full_unstemmed A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title_short A three-component Breakfast Quality Score (BQS) to evaluate the nutrient density of breakfast meals
title_sort three-component breakfast quality score (bqs) to evaluate the nutrient density of breakfast meals
topic Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569224/
https://www.ncbi.nlm.nih.gov/pubmed/37841394
http://dx.doi.org/10.3389/fnut.2023.1213065
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