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ORIGINAL RESEARCH COMMUNICATION |
1 From the Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY (SEM, WEM, C-CH, JRM, and SBE); the Department of Social and Preventive Medicine, University at Buffalo, Buffalo, NY (MT and JLF); and the Department of Epidemiology, Italian National Cancer Institute Regina Elena, Rome, Italy (PM)
Background: Reduced rank regression (RRR) has been used to identify dietary patterns that predict variation in a selected risk factor and may be useful in describing dietary exposures associated with glycemic index (GI) and glycemic load (GL).
Objective: To estimate breast cancer risk, we compared the relative utility of RRR-derived dietary patterns predictive of GI and GL with those of simple GI and GL.
Design: RRR was used to identify dietary patterns predicting GI and GL from food-frequency data obtained in the Western New York Exposure and Breast Cancer Study (1166 cases, 2105 controls). Odds ratios (ORs) and 95% CIs were estimated with unconditional logistic regression, adjusted for energy and nondietary breast cancer risk factors.
Results: Sweets, refined grains, and salty snacks explained 34% of the variance in GI and 68% of the variance in GL. In general, breast cancer risks were not associated with GI, GL, or dietary pattern score. However, we observed a significant reduction in postmenopausal breast cancer risk with GI and GL pattern scores combined (OR: 0.68; 95% CI: 0.50, 0.93), especially in women with a body mass index (in kg/m2)
25 (OR: 0.64; 95% CI: 0.44, 0.93). Conversely, in premenopausal women, increased risks were associated with high GL pattern scores only for women with a body mass index
25 (OR: 2.21; 95% CI: 1.04, 4.69).
Conclusions: Although RRR may be useful in studies of diet and disease, our results suggest that RRR dietary patterns based on GI and GL provide similar information regarding the association between breast cancer, GI, and GL.
Key Words: Dietary patterns glycemic index glycemic load breast cancer body mass index
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