My Pyramid Equivalents Database 2.0 (MPED) components
The United States Department of Agriculture (USDA) MPED 2.0 (MPED) includes 32 per 100 grams equivalent food grouping measures. The MPED components are the building blocks of many dietary pattern scoring systems, such as but not limited to, the Healthy Eating Index 2005 (HEI-2005), HEI-2010, HEI-2015. The HEI-2005, HEI-2010 and HEI-2015scores are based on the USDA 2005, 2010 and 2015 Dietary Guidelines for Americans, respectively. The MPED components are based on dietary assessment data from the National Health and Nutrition Examination Survey (NHANES) nutrition component, What We Eat in America.
- For documentation of the WHI MPED components, see For the WHI FFQ: My Pyramid Equivalents Database 2.0 (MPED 2.0).
- For more information about the USDA MPED components, see the MyPyramid Equivalents Database, 2.0 for USDA Survey Foods, 2003-2004: Documentation and User Guide , which is posted to the USDA website.
- Suggested citation for the MPED components used in the WHI: Bowman SA, Friday JE, Moshfegh A. (2008). MyPyramid Equivalents Database, 2.0 for USDA Survey Foods, 2003-2004 [Online] Food Surveys Research Group. Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD. Available at: http://www.ars.usda.gov/ba/bhnrc/fsrg
- The Food Patterns Equivalents Database (FPED) is a newer food grouping system that is very similar to the MPED. The FPED converts the foods and beverages in the Food and Nutrient Database for Dietary Studies (FNDDS) to the 37 USDA Food Patterns components.. The MPED and FPEDs are sufficiently similar that the WHI retains the MPED for computing dietary indices. FPED components are not available among the WHI variables.
Dietary Quality Indices
Several dietary quality indices have been computed from the MPED components and FFQ nutrients. See below for ReadMe files with details about the computations. For the aMed and DASH, scores are dependent on the analytic sample, and thus for these two indices SAS code and computational instructions are provided and not the data. The data can be downloaded from the Download page by investigators with approved access and logins.
- Healthy Eating Index 2005 (HEI-2005)
- Healthy Eating Index 2010 (HEI-2010)
- Healthy Eating Index 2015 (HEI-2015)
- Alternative Healthy Eating Index-2010 (AHEI-2010)
- Alternate Mediterranean Diet Score (aMed; SAS code and computational instructions)
- Dietary Approaches to Stop Hypertension (DASH; SAS code and computational instructions)
- Dietary Inflammatory Index (DII) and Energy-Adjusted DII (E-DII) Index (see below)
Resources and Guidelines for working with the WHI dietary data
- FFQ Analysis of Folate
- Biomarker Calibration Information (★new version, January 2018★)
- WHI FFQ Diet-Disease Analysis Guidelines
- WHI FFQ Nutrient Database Estimations – considerations for researchers
- Glycemic Index and Glycemic Load Development Methods
Dietary Inflammatory Index (DII) and Energy-Adjusted DII (E-DII) Index (University of South Carolina)
The dietary inflammatory index (DII®) and energy-adjusted DII (E-DII™) scores, which are computed from food frequency questionnaire (FFQ) data by Dr. Hébert et al., are posted to the WHI website as a courtesy to streamline DII and E-DII data access for approved users. Use of the DII and E-DII data is contingent upon having (1) an approved WHI paper proposal that includes use of the DII and/or E-DII, (2) a signed WHI Data Use Agreement (DUA), and (3) assigned DII Materials Transfer and Data Use Agreement (MTDUA) from the University of South Carolina that is administered by Dr. Hébert et al.’s team. Please contact Drs. Nitin Shivappa (shivappa@email.sc.edu) or James Hébert (jhebert@sc.edu) for all questions about the DII and E-DII data and the DII and E-DII MTDUA.
DII and E-DII files.
Access to the DII datasets are available through the WHI Data Repository once data access requirements are met.
REFERENCES
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Hebert JR, Shivappa N, Wirth MD, Hussey JR, Hurley TG. Perspective: The Dietary Inflammatory Index (DII®): Lessons Learned, Improvements Made and Future Directions. Adv Nutr 2019;10(2):185-95.
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Tabung FK, Steck SE, Zhang J, Ma Y, Liese AD, Agalliu I, Hingle M, Hou L, Hurley TG, Jiao L, Martin LW, Millen AE, Park HL, Rosal MC, Shikany JM, Shivappa N, Ockene JK, Hebert JR. Construct validation of the dietary inflammatory index among postmenopausal women. Ann Epidemiol 2015;25(6):398-405.
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Shivappa N, Steck SE, Hurley TG, Hussey JR, Hebert JR. Designing and developing a literature-derived population-based dietary inflammatory index. Public Health Nutr 2014;17(6):1689-96.