Development and Validation of an Empirical Dietary Inflammatory Index

BACKGROUND: Knowledge on specific biological pathways mediating disease occurrence (e.g., inflammation) may be utilized to construct hypotheses-driven dietary patterns that take advantage of current evidence on disease-related hypotheses and the statistical methods of a posteriori patterns. OBJECTIVE: We developed and validated an empirical dietary inflammatory index (EDII) based on food groups. METHODS: We entered 39 pre-defined food groups in reduced rank regression models followed by stepwise linear regression analyses in the Nurses' Health Study (NHS, n = 5230) to identify a dietary pattern most predictive of 3 plasma inflammatory markers: interleukin-6 (IL-6), C-reactive protein (CRP), and tumor necrosis factor α receptor 2 (TNFαR2). We evaluated the construct validity of the EDII in 2 independent samples from NHS-II (n = 1002) and Health Professionals Follow-up Study (HPFS, n = 2632) using multivariable-adjusted linear regression models to examine how well the EDII predicted concentrations of IL-6, CRP, TNFαR2, adiponectin, and an overall inflammatory marker score combining all biomarkers. RESULTS: The EDII is the weighted sum of 18 food groups; 9 are anti-inflammatory and 9 proinflammatory. In NHS-II and HPFS, the EDII significantly predicted concentrations of all biomarkers. For example, the relative concentrations comparing extreme EDII quintiles in NHS-II were: adiponectin, 0.88 (95% CI, 0.80, 0.96), P-trend = 0.003; and CRP, 1.52 (95% CI, 1.18, 1.97), P-trend = 0.002. Corresponding associations in HPFS were: 0.87 (95% CI, 0.82, 0.92), P-trend