Background: In previous studies, dietary patterns were derived in different populations without regard to a specific outcome.
Objective: The objective was to apply a new statistical method to construct a specific dietary pattern that is strongly associated with the risk of coronary artery disease (CAD).
Design: We applied reduced rank regression to a sample of 200 cases and 255 controls from the Coronary Risk Factors for Atherosclerosis in Women (CORA) Study. The CAD-specific dietary pattern was constructed by choosing intake data for 49 food groups as predictors and 5 established biomarkers for CAD as responses.
Results: A high score for the constructed dietary pattern was characterized by high intakes of meat, margarine, poultry, and sauce and low intakes of vegetarian dishes, wine, vegetables, and whole-grain cereals. After adjustment for known CAD risk factors, the relative risks from the lowest to the highest quintiles of the pattern score were 1.0, 1.1, 3.6, 6.2, and 12.3 (95% CI: 4.9, 30.9; P for trend < 0.0001). There was an approximate 4.5-fold difference in C-reactive protein and a 2-fold difference in C-peptide between the highest and lowest score quintiles of the study population. HDL-cholesterol concentrations ranged from 70 mg/dL in the lowest quintile to 49 mg/dL in the highest quintile of dietary pattern score.
Conclusion: The new statistical method, reduced rank regression, may be a useful tool for identifying dietary patterns that simultaneously affect the concentrations of known CAD biomarkers and the risk of developing CAD.