Dietary Patterns in Acne and Rosacea Patients-A Controlled Study and Comprehensive Analysis.
Anne GuertlerArina VolskyQuirine EijkenboomTobias FiedlerLars E FrenchMarkus ReinholzPublished in: Nutrients (2023)
As the relationship between exposome factors and inflammatory skin diseases is gaining increasing attention, the objective of this study was to investigate dietary patterns among acne and rosacea patients and to establish the disease risk attributable to nutrition. In this cross-sectional, controlled study, patients' dietary habits were assessed via subjective ratings of beneficial and trigger foods, followed by standardized food frequency surveys (FFS). Scores for disease-specific risk stratification based on dietary habits were proposed. Clinical assessments, dermatologic examinations, and laboratory analyses were performed. A total of 296 patients (acne group (AG) n = 120, control group (ACG) n = 32; rosacea group (RG) n = 105, control group (RCG) n = 39) were included. The significant impact of diet on disease severity was self-reported by 80.8% of the AG and 70.5% of the RG. Leading dietary triggers were found in both groups, while beneficial food items were identified more clearly by the AG. FFS revealed significant dietary differences between the AG, RG, and control groups. Disease-specific scores showed greater precision for acne (odds ratio 14.5 AG, 5.5 RG). The AG had higher insulin-like growth factor (IGF)-1 levels correlating with dairy intake ( p = 0.006). Overall, this study underlines the influence of diet on acne and rosacea, providing valuable disease-specific scores for dietary risk stratification. Consuming vegetables, legumes, oily fish, olive oil, and nuts, and limiting meat, cheese, and alcohol appear to be beneficial for both acne and rosacea. Future studies can build on these data to further improve preventive and therapeutic strategies.
Keyphrases
- end stage renal disease
- chronic kidney disease
- ejection fraction
- newly diagnosed
- cross sectional
- peritoneal dialysis
- prognostic factors
- machine learning
- oxidative stress
- physical activity
- patient reported outcomes
- body mass index
- cell proliferation
- patient reported
- hidradenitis suppurativa
- artificial intelligence
- deep learning
- working memory
- growth hormone
- drinking water
- data analysis
- lactic acid