Multi-study factor regression model: an application in nutritional epidemiology

• DOI: 10.48550/arxiv.2304.13077
• Publication Date: 2023-01-01
• Authors: Roberta De Vito; Alejandra Avalos‐...
• Keywords: Demographics; Nutritional Epidemiology

Diet is a risk factor for many diseases. In nutritional epidemiology, studying reproducible dietary patterns critical to reveal important associations with health. However, it challenging: diverse cultural and ethnic backgrounds may critically impact eating patterns, showing heterogeneity, leading incorrect obscuring the components shared across different groups or populations. Moreover, covariate effects generated from observed variables, such as demographics other confounders, can further bias these patterns. Identifying group-specific essential drive accurate conclusions. To address issues, we introduce new modeling regression, Multi-Study Factor Regression (MSFR) model. The MSFR model analyzes populations simultaneously, achieving three goals: capturing component(s) populations, identifying structures, correcting effects. We use this novel method derive common ethnic-specific in multi-center epidemiological study Hispanic/Latinos community. Our improves accuracy of group signals yields better prediction than techniques, revealing significant summary, provide tool integrate groups, giving crucial inform public health policy.