Dietary patterns associated with diabetes in an older population from Southern Italy, using an unsupervised learning approach

Sensors - -2022

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

Abstract

BackgroundDiet and social determinants influence the state of human health. In older adults, the presence of social, physical and psychological barriers increases the probability of deprivation. This study investigated the relationship between social deprivation and eating habits in non-institutionalized older adults from Southern Italy, and identified foods and dietary habits associated with social deprivation.MethodsWe recruited 1,002 subjects, mean age 74 years, from the large population based Salus in Apulia Study. In this cross-sectional study, eating habits and the level of deprivation were assessed with FFQ and DiPCare-Q, respectively.ResultsDeprived subjects (n = 441) included slightly more females, who were slightly older and with a lower level of education. They consumed less fish (23 vs. 26 g), fruiting vegetables (87 vs. 102 g), nuts (6 vs. 9 g) and less “ready to eat” dishes (29 vs. 33 g). A Random Forest (RF) model was used to identify a dietary pattern associated with social deprivation. This pattern included an increased consumption of low-fat dairy products and white meat, and a decreased consumption of wine, leafy vegetables, seafood/shellfish, processed meat, red meat, dairy products, and eggs.ConclusionThe present study showed that social factors also define diet and eating habits. Subjects with higher levels of deprivation consume cheaper and more readily available food.

Download: [SENSORS2022]_Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach.pdf

DOI

https://doi.org/10.3389/fnut.2022.811076

BibTex references

@Article{TLBDCZTDSNLG22,
  author       = "Tatoli, Rossella and Lampignano, Luisa and Bortone, Ilaria and Donghia, Rossella and Castellana, Fabio and Zupo, Roberta and Tirelli, Sarah and De Nucci, Sara and Sila, Annamaria  and Natuzzi, Annalidia and Lozupone, Madia and Griseta, Chiara and Sciarra, Sabrina and Aresta, Simona and De Pergola, Giovanni and Sorino, Paolo and Lof\`u, Domenico and Panza, Francesco and Di Noia, Tommaso and Sardone, Rodolfo",
  title        = "Dietary patterns associated with diabetes in an older  population from Southern Italy, using an unsupervised  learning approach",
  journal      = "Sensors",
  year         = "2022",
  url          = "http://sisinflab.poliba.it/Publications/2022/TLBDCZTDSNLG22"

}