Gaussian graphical models identified food intake networks and risk of type 2 diabetes, CVD, and cancer in the EPIC-Potsdam study

Autor: Matthias B. Schulze, Khalid Iqbal, Clemens Wittenbecher, Lukas Schwingshackl, Carolina Schwedhelm, Marta Stelmach-Mardas, Cecilia Galbete, Anna Floegel, Heiner Boeing, Sven Knüppel
Rok vydání: 2018
Předmět:
Zdroj: European Journal of Nutrition. 58:1673-1686
ISSN: 1436-6215
1436-6207
Popis: The aim of the study was to investigate the association between the previously identified Gaussian graphical models’ (GGM) food intake networks and risk of major chronic diseases as well as intermediate biomarkers in the European Prospective Investigation into Cancer and nutrition (EPIC)-Potsdam cohort. In this cohort analysis of 10,880 men and 13,340 women, adherence to the previously identified sex-specific GGM networks as well as principal component analysis identified patterns was investigated in relation to risk of major chronic diseases, using Cox-proportional hazard models. Associations of the patterns with intermediate biomarkers were cross-sectionally analyzed using multiple linear regressions. Results showed that higher adherence to the GGM Western-type pattern was associated with increased risk (Hazard Ratio: 1.55; 95% CI 1.13–2.15; P trend = 0.004) of type 2 diabetes (T2D) in women, whereas adherence to a high-fat dairy (HFD) pattern was associated with lower risk of T2D both in men (0.69; 95% CI 0.54–0.89; P trend
Databáze: OpenAIRE