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Comparative analysis of scoring methods for the Healthy Eating Index-2015 across three dietary assessment instruments in IDATA

Principal Investigator
Name
Edwina Wambogo
Degrees
MS, MPH, RD, PhD candidate
Institution
National Institutes of Health
Position Title
Cancer Research Training Award Fellow
Email
About this CDAS Project
Study
IDATA (Learn more about this study)
Project ID
IDATA-26
Initial CDAS Request Approval
Sep 10, 2018
Title
Comparative analysis of scoring methods for the Healthy Eating Index-2015 across three dietary assessment instruments in IDATA
Summary
Since foods are consumed as components of meals, instead of single, or isolated nutrients, there has been considerable interest in investigations of dietary patterns and diet quality. Methods to determine dietary patterns include the use of diet indexes or scores that assess compliance with prevailing dietary guidance, such as the Healthy Eating Index (HEI)-2015. Dietary pattern analyses evaluate total dietary intakes of individuals or populations for the purpose of investigating differences by respondent characteristics and associations with health outcomes. We propose a data analyses of IDATA for an in-depth examination of dietary patterns, using the HEI-2015. We will use the Automated Self-Administered 24-hour dietary recalls (ASA24s), the Dietary History Questionnaire II (DHQ II), and the 4-Day Food Record (4DFRs) for these analyses. These instruments have distinct features as well as strengths and limitations. Two of the instruments capture detailed short-term dietary data (ASA24 and 4DFRs), while the DHQ II collects more long-term data (intake over the past year). We propose to compare the means and distributions for the HEI-2015 scores by scoring method (two simple methods, population ratio, bivariate and MCMC) as appropriate for each dietary assessment tool. We will also examine the HEI-2015 scores by other demographic or related dietary intake factors (such as age, BMI, weekend/weekday) available in the IDATA study.
Aims

• Compare means and distributions of the HEI-2015 using different scoring methods (two simple methods, population ratio, bivariate and MCMC).
• Determine differences in how these different HEI methods perform across the dietary assessment tools in IDATA and discuss the implications of these findings on their appropriate use.
• Perform more in-depth analysis of HEI scores by demographic characteristics and other diet related factors

Collaborators

Amy, Subar, PhD - DCCPS/NCI
Jill Reedy, PhD - DCCPS/NCI
Shams-While Marissa, PhD - DCCPS/NCI