Fred K Tabung1, Susan E Steck2, Jiajia Zhang3, Yunsheng Ma4, Angela D Liese5, Ilir Agalliu6, Melanie Hingle7, Lifang Hou8, Thomas G Hurley9, Li Jiao10, Lisa W Martin11, Amy E Millen12, Hannah L Park13, Milagros C Rosal4, James M Shikany14, Nitin Shivappa1, Judith K Ockene4, James R Hebert15. 1. South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. 2. South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia; Center for Research in Nutrition and Health Disparities, University of South Carolina, Columbia. Electronic address: ssteck@sc.edu. 3. Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia. 4. Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Boston. 5. Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia; Center for Research in Nutrition and Health Disparities, University of South Carolina, Columbia. 6. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY. 7. Department of Nutritional Sciences, College of Agriculture and Life Sciences, The University of Arizona, Tucson. 8. Department of Preventive Medicine and the Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL. 9. South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia. 10. Department of Medicine, Baylor College of Medicine, Houston, TX. 11. Cardiology Division, School of Medicine and Health Sciences, George Washington University, Washington, DC. 12. Department of Epidemiology and Environmental Health, University at Buffalo, The State University of New York, Buffalo. 13. Department of Epidemiology, School of Medicine, University of California at Irvine, Irvine. 14. Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham. 15. South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia; Center for Research in Nutrition and Health Disparities, University of South Carolina, Columbia.
Abstract
PURPOSE: Many dietary factors have either proinflammatory or anti-inflammatory properties. We previously developed a dietary inflammatory index (DII) to assess the inflammatory potential of diet. In this study, we conducted a construct validation of the DII based on data from a food frequency questionnaire and three inflammatory biomarkers in a subsample of 2567 postmenopausal women in the Women's Health Initiative Observational Study. METHODS: We used multiple linear and logistic regression models, controlling for potential confounders, to test whether baseline DII predicted concentrations of interleukin-6, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor alpha receptor 2, or an overall biomarker score combining all three inflammatory biomarkers. RESULTS: The DII was associated with the four biomarkers with beta estimates (95% confidence interval) comparing the highest with lowest DII quintiles as follows: interleukin-6: 1.26 (1.15-1.38), Ptrend < .0001; tumor necrosis factor alpha receptor 2: 81.43 (19.15-143.71), Ptrend = .004; dichotomized hs-CRP (odds ratio for higher vs. lower hs-CRP): 1.30 (0.97-1.67), Ptrend = .34; and the combined inflammatory biomarker score: 0.26 (0.12-0.40), Ptrend = .0001. CONCLUSIONS: The DII was significantly associated with inflammatory biomarkers. Construct validity of the DII indicates its utility for assessing the inflammatory potential of diet and for expanding its use to include associations with common chronic diseases in future studies.
PURPOSE: Many dietary factors have either proinflammatory or anti-inflammatory properties. We previously developed a dietary inflammatory index (DII) to assess the inflammatory potential of diet. In this study, we conducted a construct validation of the DII based on data from a food frequency questionnaire and three inflammatory biomarkers in a subsample of 2567 postmenopausal women in the Women's Health Initiative Observational Study. METHODS: We used multiple linear and logistic regression models, controlling for potential confounders, to test whether baseline DII predicted concentrations of interleukin-6, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor alpha receptor 2, or an overall biomarker score combining all three inflammatory biomarkers. RESULTS: The DII was associated with the four biomarkers with beta estimates (95% confidence interval) comparing the highest with lowest DII quintiles as follows: interleukin-6: 1.26 (1.15-1.38), Ptrend < .0001; tumor necrosis factor alpha receptor 2: 81.43 (19.15-143.71), Ptrend = .004; dichotomized hs-CRP (odds ratio for higher vs. lower hs-CRP): 1.30 (0.97-1.67), Ptrend = .34; and the combined inflammatory biomarker score: 0.26 (0.12-0.40), Ptrend = .0001. CONCLUSIONS: The DII was significantly associated with inflammatory biomarkers. Construct validity of the DII indicates its utility for assessing the inflammatory potential of diet and for expanding its use to include associations with common chronic diseases in future studies.
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