Exploring two food composition databases to estimate nutritional components of whole meals

Detalhes bibliográficos
Autor(a) principal: Silva, Marta
Data de Publicação: 2021
Outros Autores: Ribeiro, Mafalda, Viegas, Olga, Martins, Zita E., Faria, Miguel, Casal, Susana, Pinto, Edgar, Almeida, Agostinho, Pinho, Olívia, Ferreira, Isabel M.P.L.V. O.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/20415
Resumo: The integration of foodomics data to explain the impact of diet on health requires a precise knowledge of nutrients composition of complex meals. This work assesses the adequacy of two food composition databases (FCDBs) for calculation of nutritional composition of whole meals, compared to the golden standard “lab chemical analyses” and search for predictive models to overcome some limitations of FCDBs. Six meals were designed by integrating healthy foods in a meal based on the “Western diet” pattern. The nutritional composition of each meal was i) chemically determined; ii) retrieved from the Portuguese food composition table (TCAP) and from iii) United States Department of Agriculture database (USDA). Compared to chemical analyses, both FCDBs significantly (p < 0.05) overestimate the amount of Na and vitamin B6; TCAP also overestimate the amount of Ca (p < 0.05), while USDA overestimate energy, fat, available carbohydrates, P, and Fe. Linear regression analyses were used to adjust nutrient values based on TCAP and USDA. Predictive models from both FCDBs were successfully obtained for reliable estimation of protein, PUFA, available carbohydrates, total carbohydrates, sugars, Zn, β-carotene, vitamin E, riboflavin, and niacin in meals with a given uncertainty, which is provided by the respective correction factors. Those predictive models are limited to the range of theoretical values of meals studied.
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spelling Exploring two food composition databases to estimate nutritional components of whole mealsPortuguese food composition tableUnited States department of agriculture databaseNutritional chemical analysisNutrients biasPredictive regression modelsThe integration of foodomics data to explain the impact of diet on health requires a precise knowledge of nutrients composition of complex meals. This work assesses the adequacy of two food composition databases (FCDBs) for calculation of nutritional composition of whole meals, compared to the golden standard “lab chemical analyses” and search for predictive models to overcome some limitations of FCDBs. Six meals were designed by integrating healthy foods in a meal based on the “Western diet” pattern. The nutritional composition of each meal was i) chemically determined; ii) retrieved from the Portuguese food composition table (TCAP) and from iii) United States Department of Agriculture database (USDA). Compared to chemical analyses, both FCDBs significantly (p < 0.05) overestimate the amount of Na and vitamin B6; TCAP also overestimate the amount of Ca (p < 0.05), while USDA overestimate energy, fat, available carbohydrates, P, and Fe. Linear regression analyses were used to adjust nutrient values based on TCAP and USDA. Predictive models from both FCDBs were successfully obtained for reliable estimation of protein, PUFA, available carbohydrates, total carbohydrates, sugars, Zn, β-carotene, vitamin E, riboflavin, and niacin in meals with a given uncertainty, which is provided by the respective correction factors. Those predictive models are limited to the range of theoretical values of meals studied.ElsevierRepositório Científico do Instituto Politécnico do PortoSilva, MartaRibeiro, MafaldaViegas, OlgaMartins, Zita E.Faria, MiguelCasal, SusanaPinto, EdgarAlmeida, AgostinhoPinho, OlíviaFerreira, Isabel M.P.L.V. O.2022-04-28T09:45:40Z2021-092021-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/20415engSilva, M., Ribeiro, M., Viegas, O., Martins, Z. E., Faria, M., Casal, S., Pinto, E., Almeida, A., Pinho, O., & Ferreira, I. M. P. L. V. O. (2021). Exploring two food composition databases to estimate nutritional components of whole meals. Journal of Food Composition and Analysis, 102, 104070. https://doi.org/https://doi.org/10.1016/j.jfca.2021.1040700889-157510.1016/j.jfca.2021.1040701096-0481metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:15:56Zoai:recipp.ipp.pt:10400.22/20415Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:40:29.906450Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Exploring two food composition databases to estimate nutritional components of whole meals
title Exploring two food composition databases to estimate nutritional components of whole meals
spellingShingle Exploring two food composition databases to estimate nutritional components of whole meals
Silva, Marta
Portuguese food composition table
United States department of agriculture database
Nutritional chemical analysis
Nutrients bias
Predictive regression models
title_short Exploring two food composition databases to estimate nutritional components of whole meals
title_full Exploring two food composition databases to estimate nutritional components of whole meals
title_fullStr Exploring two food composition databases to estimate nutritional components of whole meals
title_full_unstemmed Exploring two food composition databases to estimate nutritional components of whole meals
title_sort Exploring two food composition databases to estimate nutritional components of whole meals
author Silva, Marta
author_facet Silva, Marta
Ribeiro, Mafalda
Viegas, Olga
Martins, Zita E.
Faria, Miguel
Casal, Susana
Pinto, Edgar
Almeida, Agostinho
Pinho, Olívia
Ferreira, Isabel M.P.L.V. O.
author_role author
author2 Ribeiro, Mafalda
Viegas, Olga
Martins, Zita E.
Faria, Miguel
Casal, Susana
Pinto, Edgar
Almeida, Agostinho
Pinho, Olívia
Ferreira, Isabel M.P.L.V. O.
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Silva, Marta
Ribeiro, Mafalda
Viegas, Olga
Martins, Zita E.
Faria, Miguel
Casal, Susana
Pinto, Edgar
Almeida, Agostinho
Pinho, Olívia
Ferreira, Isabel M.P.L.V. O.
dc.subject.por.fl_str_mv Portuguese food composition table
United States department of agriculture database
Nutritional chemical analysis
Nutrients bias
Predictive regression models
topic Portuguese food composition table
United States department of agriculture database
Nutritional chemical analysis
Nutrients bias
Predictive regression models
description The integration of foodomics data to explain the impact of diet on health requires a precise knowledge of nutrients composition of complex meals. This work assesses the adequacy of two food composition databases (FCDBs) for calculation of nutritional composition of whole meals, compared to the golden standard “lab chemical analyses” and search for predictive models to overcome some limitations of FCDBs. Six meals were designed by integrating healthy foods in a meal based on the “Western diet” pattern. The nutritional composition of each meal was i) chemically determined; ii) retrieved from the Portuguese food composition table (TCAP) and from iii) United States Department of Agriculture database (USDA). Compared to chemical analyses, both FCDBs significantly (p < 0.05) overestimate the amount of Na and vitamin B6; TCAP also overestimate the amount of Ca (p < 0.05), while USDA overestimate energy, fat, available carbohydrates, P, and Fe. Linear regression analyses were used to adjust nutrient values based on TCAP and USDA. Predictive models from both FCDBs were successfully obtained for reliable estimation of protein, PUFA, available carbohydrates, total carbohydrates, sugars, Zn, β-carotene, vitamin E, riboflavin, and niacin in meals with a given uncertainty, which is provided by the respective correction factors. Those predictive models are limited to the range of theoretical values of meals studied.
publishDate 2021
dc.date.none.fl_str_mv 2021-09
2021-09-01T00:00:00Z
2022-04-28T09:45:40Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/20415
url http://hdl.handle.net/10400.22/20415
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Silva, M., Ribeiro, M., Viegas, O., Martins, Z. E., Faria, M., Casal, S., Pinto, E., Almeida, A., Pinho, O., & Ferreira, I. M. P. L. V. O. (2021). Exploring two food composition databases to estimate nutritional components of whole meals. Journal of Food Composition and Analysis, 102, 104070. https://doi.org/https://doi.org/10.1016/j.jfca.2021.104070
0889-1575
10.1016/j.jfca.2021.104070
1096-0481
dc.rights.driver.fl_str_mv metadata only access
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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