There are three types of nutrient and dietary data (nutrients, items and My Pyramid Equivalents Database 2.0 (MPED) components) posted to the WHI website. All three types of nutrient and dietary data are from the Food Frequency Questionnaire (FFQ) – Form 60. Dietary quality indices, based on these three data types, are available at the 'Download Data' page and summarized below. WHI FFQ data for nutrients, items, MPED components and dietary quality indices data are available for investigator use upon approval for WHI papers or ancillary studies.
My Pyramid Equivalents Database 2.0 (MPED)
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-2015 scores 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.
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.
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 (University of South Carolina)
FFQ Analysis of Folate
Biomarker Calibration Information (★new version, January 2018★)
W8 Nutritional Biomarkers Study (NBS) Information and Data
AS218 Nutrition and Physical Activity Assessment Study (NPAAS) Information and Data
WHI FFQ Diet-Disease Analysis Guidelines
WHI FFQ Nutrient Database Estimations – considerations for researchers
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, (2) a signed
WHI Data Use Agreement (DUA), and (3) a signed 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 (firstname.lastname@example.org) or James Hébert (email@example.com) for all questions about the DII and E-DII data and the DII and E-DII MTDUA.
Please click to view the
DII and E-DII data dictionary.
1. 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.
2. 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.
3. 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.