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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Published in:Sensors (Basel, Switzerland) Vol. 22; no. 6; p. 2193
Main Authors: 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
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 11.03.2022
MDPI
Subjects:
Aged
Body mass index
Cross-Sectional Studies
Diabetes
Diabetes Mellitus, Type 2 - epidemiology
Diet
dietary pattern
Disease
Eating behavior
Eigenvalues
Feeding Behavior
Female
Food
Glucose
Health care
Humans
Italy - epidemiology
Machine learning
Male
Nutrition research
older adults
Overweight
Population
Principal components analysis
Public health
Questionnaires
Software
unsupervised learning approach
Unsupervised Machine Learning
Italy
older adults
dietary pattern
diabetes
unsupervised learning approach
ISSN:1424-8220, 1424-8220
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Summary: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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ISSN:1424-8220
1424-8220
DOI:10.3390/s22062193