We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Age-Related Dietary Habits and Blood Biochemical Parameters in Patients with and without Steatosis—MICOL Cohort.
- Authors
Donghia, Rossella; Pesole, Pasqua Letizia; Castellaneta, Antonino; Coletta, Sergio; Squeo, Francesco; Bonfiglio, Caterina; De Pergola, Giovanni; Rinaldi, Roberta; De Nucci, Sara; Giannelli, Gianluigi; Di Leo, Alfredo; Tatoli, Rossella
- Abstract
Background: Steatosis is now the most common liver disease in the world, present in approximately 25% of the global population. The aim of this study was to study the association between food intake and liver disease and evaluate the differences in blood parameters in age classes and steatosic condition. Methods: The present study included 1483 participants assessed in the fourth recall of the MICOL study. Patients were subdivided by age (</>65 years) and administered a validated food frequency questionnaire (FFQ) with 28 food groups. Results: The prevalence of steatosis was 55.92% in the adult group and 55.88% in the elderly group. Overall, the results indicated many statistically significant blood parameters and dietary habits. Analysis of food choices with a machine learning algorithm revealed that in the adult group, olive oil, grains, processed meat, and sweets were associated with steatosis, while the elderly group preferred red meat, dairy, seafood, and fruiting vegetables. Furthermore, the latter ate less as compared with the adult group. Conclusions: Many differences were found between the two age groups, both in blood parameters and food intake. The random forest also revealed different foods predicted steatosis in the two groups. Future analysis will be useful to understand the molecular basis of these differences and how different food intake causes steatosis in people of different ages.
- Subjects
ITALY; BLOOD testing; FOOD habits; BIOCHEMISTRY; OLIVE oil; MEAT; VEGETABLES; PHENOMENOLOGICAL biology; FATTY liver; AGE distribution; MACHINE learning; FOOD preferences; DAIRY products; QUESTIONNAIRES; DISEASE prevalence; FRUIT; DESCRIPTIVE statistics; GRAIN; SEAFOOD; SECONDARY analysis; ALGORITHMS
- Publication
Nutrients, 2023, Vol 15, Issue 18, p4058
- ISSN
2072-6643
- Publication type
Article
- DOI
10.3390/nu15184058