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Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach

Dietary behaviour is a core element in diabetes self-management. There are no remarkable differences between nutritional guidelines for people with type 2 diabetes and healthy eating recommendations for the general public. This study aimed to evaluate dietary differences between subjects with and wi...

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Autores principales: Tatoli, Rossella, Lampignano, Luisa, Bortone, Ilaria, Donghia, Rossella, Castellana, Fabio, Zupo, Roberta, Tirelli, Sarah, De Nucci, Sara, Sila, Annamaria, Natuzzi, Annalidia, Lozupone, Madia, Griseta, Chiara, Sciarra, Sabrina, Aresta, Simona, De Pergola, Giovanni, Sorino, Paolo, Lofù, Domenico, Panza, Francesco, Di Noia, Tommaso, Sardone, Rodolfo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949084/
https://www.ncbi.nlm.nih.gov/pubmed/35336365
http://dx.doi.org/10.3390/s22062193
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author Tatoli, Rossella
Lampignano, Luisa
Bortone, Ilaria
Donghia, Rossella
Castellana, Fabio
Zupo, Roberta
Tirelli, Sarah
De Nucci, Sara
Sila, Annamaria
Natuzzi, Annalidia
Lozupone, Madia
Griseta, Chiara
Sciarra, Sabrina
Aresta, Simona
De Pergola, Giovanni
Sorino, Paolo
Lofù, Domenico
Panza, Francesco
Di Noia, Tommaso
Sardone, Rodolfo
author_facet Tatoli, Rossella
Lampignano, Luisa
Bortone, Ilaria
Donghia, Rossella
Castellana, Fabio
Zupo, Roberta
Tirelli, Sarah
De Nucci, Sara
Sila, Annamaria
Natuzzi, Annalidia
Lozupone, Madia
Griseta, Chiara
Sciarra, Sabrina
Aresta, Simona
De Pergola, Giovanni
Sorino, Paolo
Lofù, Domenico
Panza, Francesco
Di Noia, Tommaso
Sardone, Rodolfo
author_sort Tatoli, Rossella
collection PubMed
description Dietary behaviour is a core element in diabetes self-management. There are no remarkable differences between nutritional guidelines for people with type 2 diabetes and healthy eating recommendations for the general public. This study aimed to evaluate dietary differences between subjects with and without diabetes and to describe any emerging dietary patterns characterizing diabetic subjects. In this cross-sectional study conducted on older adults from Southern Italy, eating habits in the “Diabetic” and “Not Diabetic” groups were assessed with FFQ, and dietary patterns were derived using an unsupervised learning algorithm: principal component analysis. Diabetic subjects (n = 187) were more likely to be male, slightly older, and with a slightly lower level of education than subjects without diabetes. The diet of diabetic subjects reflected a high-frequency intake of dairy products, eggs, vegetables and greens, fresh fruit and nuts, and olive oil. On the other hand, the consumption of sweets and sugary foods was reduced compared to non-diabetics (23.74 ± 35.81 vs. 16.52 ± 22.87; 11.08 ± 21.85 vs. 7.22 ± 15.96). The subjects without diabetes had a higher consumption of red meat, processed meat, ready-to-eat dishes, alcoholic drinks, and lower vegetable consumption. The present study demonstrated that, in areas around the Mediterranean Sea, older subjects with diabetes had a healthier diet than their non-diabetic counterparts.
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spelling pubmed-89490842022-03-26 Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach Tatoli, Rossella Lampignano, Luisa Bortone, Ilaria Donghia, Rossella Castellana, Fabio Zupo, Roberta Tirelli, Sarah De Nucci, Sara Sila, Annamaria Natuzzi, Annalidia Lozupone, Madia Griseta, Chiara Sciarra, Sabrina Aresta, Simona De Pergola, Giovanni Sorino, Paolo Lofù, Domenico Panza, Francesco Di Noia, Tommaso Sardone, Rodolfo Sensors (Basel) Article Dietary behaviour is a core element in diabetes self-management. There are no remarkable differences between nutritional guidelines for people with type 2 diabetes and healthy eating recommendations for the general public. This study aimed to evaluate dietary differences between subjects with and without diabetes and to describe any emerging dietary patterns characterizing diabetic subjects. In this cross-sectional study conducted on older adults from Southern Italy, eating habits in the “Diabetic” and “Not Diabetic” groups were assessed with FFQ, and dietary patterns were derived using an unsupervised learning algorithm: principal component analysis. Diabetic subjects (n = 187) were more likely to be male, slightly older, and with a slightly lower level of education than subjects without diabetes. The diet of diabetic subjects reflected a high-frequency intake of dairy products, eggs, vegetables and greens, fresh fruit and nuts, and olive oil. On the other hand, the consumption of sweets and sugary foods was reduced compared to non-diabetics (23.74 ± 35.81 vs. 16.52 ± 22.87; 11.08 ± 21.85 vs. 7.22 ± 15.96). The subjects without diabetes had a higher consumption of red meat, processed meat, ready-to-eat dishes, alcoholic drinks, and lower vegetable consumption. The present study demonstrated that, in areas around the Mediterranean Sea, older subjects with diabetes had a healthier diet than their non-diabetic counterparts. MDPI 2022-03-11 /pmc/articles/PMC8949084/ /pubmed/35336365 http://dx.doi.org/10.3390/s22062193 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tatoli, Rossella
Lampignano, Luisa
Bortone, Ilaria
Donghia, Rossella
Castellana, Fabio
Zupo, Roberta
Tirelli, Sarah
De Nucci, Sara
Sila, Annamaria
Natuzzi, Annalidia
Lozupone, Madia
Griseta, Chiara
Sciarra, Sabrina
Aresta, Simona
De Pergola, Giovanni
Sorino, Paolo
Lofù, Domenico
Panza, Francesco
Di Noia, Tommaso
Sardone, Rodolfo
Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title_full Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title_fullStr Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title_full_unstemmed Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title_short Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach
title_sort dietary patterns associated with diabetes in an older population from southern italy using an unsupervised learning approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949084/
https://www.ncbi.nlm.nih.gov/pubmed/35336365
http://dx.doi.org/10.3390/s22062193
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