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Food and Nutrition Surveillance System markers predict diet quality

OBJECTIVE: To investigate the performance of food consumption markers of the Food and Nutrition Surveillance System (Sisvan) in assessing the overall dietary quality. METHODS: The study was carried out based on the reproduction of responses to markers in 24-hour recall data from 46,164 individuals a...

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Autores principales: Louzada, Maria Laura da Costa, Couto, Vanessa Del Castillo Silva, Rauber, Fernanda, Tramontt, Claudia Raulino, Santos, Thanise Sabrina Souza, Lourenço, Bárbara Hatzlhoffer, Jaime, Patrícia Constante
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Saúde Pública da Universidade de São Paulo 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631750/
https://www.ncbi.nlm.nih.gov/pubmed/37971176
http://dx.doi.org/10.11606/s1518-8787.2023057005087
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author Louzada, Maria Laura da Costa
Couto, Vanessa Del Castillo Silva
Rauber, Fernanda
Tramontt, Claudia Raulino
Santos, Thanise Sabrina Souza
Lourenço, Bárbara Hatzlhoffer
Jaime, Patrícia Constante
author_facet Louzada, Maria Laura da Costa
Couto, Vanessa Del Castillo Silva
Rauber, Fernanda
Tramontt, Claudia Raulino
Santos, Thanise Sabrina Souza
Lourenço, Bárbara Hatzlhoffer
Jaime, Patrícia Constante
author_sort Louzada, Maria Laura da Costa
collection PubMed
description OBJECTIVE: To investigate the performance of food consumption markers of the Food and Nutrition Surveillance System (Sisvan) in assessing the overall dietary quality. METHODS: The study was carried out based on the reproduction of responses to markers in 24-hour recall data from 46,164 individuals aged ≥ 10 years, from the 2017–2018 Household Budget Survey (POF). Seven Sisvan markers were evaluated, and two scores were calculated for each participant, based on the sum of the number of healthy food markers (beans, fruits, and vegetables, ranging from 0 to 3) and unhealthy (hamburgers/sausages, sweetened beverages, instant noodles/salt snacks/crackers, stuffed cookies/sweets/candies, ranging from 0 to 4) consumed. Linear regression analyses were used to assess the association between scores and diet quality indicators (ultra-processed foods, dietary diversity, and levels of saturated and trans fat, added sugar, sodium, potassium, and fiber in the diet). RESULTS: The score of healthy eating markers increased significantly with increasing dietary diversity and potassium and fiber contents in the diet, while the opposite trend was observed for the densities of added sugar, sodium, saturated and trans fat (p < 0.001). The score of unhealthy eating markers increased significantly with the increase in the consumption of ultra-processed foods and densities of added sugar, saturated and trans fat levels in the diet, while an inverse trend was observed for potassium and fiber (p < 0.001). The joint analysis of the combination of the two marker scores showed that individuals with better performance (3 in the healthy food score, and 0 in the unhealthy food score) have a lower number of inadequacies in nutrient consumption. CONCLUSION: Sisvan food consumption markers, quickly and easily applied and already incorporated into the Brazilian public health system, have good potential to reflect the overall dietary quality.
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spelling pubmed-106317502023-11-09 Food and Nutrition Surveillance System markers predict diet quality Louzada, Maria Laura da Costa Couto, Vanessa Del Castillo Silva Rauber, Fernanda Tramontt, Claudia Raulino Santos, Thanise Sabrina Souza Lourenço, Bárbara Hatzlhoffer Jaime, Patrícia Constante Rev Saude Publica Original Article OBJECTIVE: To investigate the performance of food consumption markers of the Food and Nutrition Surveillance System (Sisvan) in assessing the overall dietary quality. METHODS: The study was carried out based on the reproduction of responses to markers in 24-hour recall data from 46,164 individuals aged ≥ 10 years, from the 2017–2018 Household Budget Survey (POF). Seven Sisvan markers were evaluated, and two scores were calculated for each participant, based on the sum of the number of healthy food markers (beans, fruits, and vegetables, ranging from 0 to 3) and unhealthy (hamburgers/sausages, sweetened beverages, instant noodles/salt snacks/crackers, stuffed cookies/sweets/candies, ranging from 0 to 4) consumed. Linear regression analyses were used to assess the association between scores and diet quality indicators (ultra-processed foods, dietary diversity, and levels of saturated and trans fat, added sugar, sodium, potassium, and fiber in the diet). RESULTS: The score of healthy eating markers increased significantly with increasing dietary diversity and potassium and fiber contents in the diet, while the opposite trend was observed for the densities of added sugar, sodium, saturated and trans fat (p < 0.001). The score of unhealthy eating markers increased significantly with the increase in the consumption of ultra-processed foods and densities of added sugar, saturated and trans fat levels in the diet, while an inverse trend was observed for potassium and fiber (p < 0.001). The joint analysis of the combination of the two marker scores showed that individuals with better performance (3 in the healthy food score, and 0 in the unhealthy food score) have a lower number of inadequacies in nutrient consumption. CONCLUSION: Sisvan food consumption markers, quickly and easily applied and already incorporated into the Brazilian public health system, have good potential to reflect the overall dietary quality. Faculdade de Saúde Pública da Universidade de São Paulo 2023-10-30 /pmc/articles/PMC10631750/ /pubmed/37971176 http://dx.doi.org/10.11606/s1518-8787.2023057005087 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Louzada, Maria Laura da Costa
Couto, Vanessa Del Castillo Silva
Rauber, Fernanda
Tramontt, Claudia Raulino
Santos, Thanise Sabrina Souza
Lourenço, Bárbara Hatzlhoffer
Jaime, Patrícia Constante
Food and Nutrition Surveillance System markers predict diet quality
title Food and Nutrition Surveillance System markers predict diet quality
title_full Food and Nutrition Surveillance System markers predict diet quality
title_fullStr Food and Nutrition Surveillance System markers predict diet quality
title_full_unstemmed Food and Nutrition Surveillance System markers predict diet quality
title_short Food and Nutrition Surveillance System markers predict diet quality
title_sort food and nutrition surveillance system markers predict diet quality
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631750/
https://www.ncbi.nlm.nih.gov/pubmed/37971176
http://dx.doi.org/10.11606/s1518-8787.2023057005087
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