A Posteriori Dietary Patterns and Rheumatoid Arthritis Disease Activity: A Beneficial Role of Vegetable and Animal Unsaturated Fatty Acids.
Valeria EdefontiMaria ParpinelMonica FerraroniPatrizia BoracchiTommaso SchioppoIsabella ScottiTania UbialiWalter CurrentiOrazio De LuciaMaurizio CutoloRoberto CaporaliFrancesca IngegnoliPublished in: Nutrients (2020)
To our knowledge, no studies have investigated the relationship between a posteriori dietary patterns (DPs)-representing current dietary behavior-and disease activity in patients with rheumatoid arthritis (RA). We analyzed data from a recent Italian cross-sectional study including 365 RA patients (median age: 58.46 years, 78.63% females). Prevalent DPs were identified through principal component factor analysis on 33 nutrients. RA activity was measured according to the Disease Activity Score on 28 joints (DAS28) and the Simplified Disease Activity Index (SDAI). Single DPs were related to disease activity through linear and logistic regression models, adjusted for the remaining DPs and confounders. We identified five DPs (~80% variance explained). Among them, Vegetable unsaturated fatty acids (VUFA) and Animal unsaturated fatty acids (AUFA) DPs were inversely related to DAS28 in the overall analysis, and in the more severe or long-standing RA subgroups; the highest score reductions (VUFA: 0.81, AUFA: 0.71) were reached for the long-standing RA. The SDAI was inversely related with these DPs in subgroups only. This Italian study shows that scoring high on DPs based on unsaturated fats from either source provides independent beneficial effects of clinical relevance on RA disease activity, thus strengthening evidence on the topic.
Keyphrases
- disease activity
- rheumatoid arthritis
- systemic lupus erythematosus
- fatty acid
- rheumatoid arthritis patients
- ankylosing spondylitis
- juvenile idiopathic arthritis
- end stage renal disease
- interstitial lung disease
- healthcare
- newly diagnosed
- chronic kidney disease
- ejection fraction
- electronic health record
- atomic force microscopy
- systemic sclerosis
- peritoneal dialysis
- machine learning
- prognostic factors
- mass spectrometry
- big data
- heavy metals
- risk assessment
- single molecule
- artificial intelligence
- drug induced
- patient reported outcomes
- idiopathic pulmonary fibrosis
- high speed