Applications of the Healthy Eating Index for Surveillance, Epidemiology, and Intervention Research: Considerations and Caveats

Abstract

The Healthy Eating Index (HEI) is a measure of diet quality that can be used to examine alignment of dietary patterns with the Dietary Guidelines for Americans. The HEI is made up of multiple adequacy and moderation components, most of which are expressed relative to energy intake (ie, as densities) for the purpose of calculating scores. Due to these characteristics and the complexity of dietary intake data more broadly, calculating and using HEI scores can involve unique statistical considerations and, depending on the particular application, intensive computational methods. The objective of this article is to review potential applications of the HEI, including those relevant to surveillance, epidemiology, and intervention research, and to summarize available guidance for appropriate analysis and interpretation. Steps in calculating HEI scores are reviewed and statistical methods described. Consideration of salient issues in the calculation and interpretation of scores can help researchers avoid common pitfalls and reviewers ensure that articles reporting on the use of the HEI include sufficient details such that the work is comprehensible and replicable, with the overall goal of contributing to knowledge on dietary patterns and health among Americans.

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults

“…Dietary assessment methods aim to measure usual consumption, with minimal measurement error and bias [19]. Most diet quality indexes are derived from 24-h food recalls, which reflect dietary intake over the short-term, or food frequency surveys, which reflect dietary intakes usually over 1 year [36]. Each of these two methods can be time intensive, memory-demanding, cognitively challenging, and are subjective to measurement errors [19].…”

“…With the dietary data available, the next step is how to combine the foods or food groups into a diet quality index that represents the totality of the foods and beverages habitually consumed [36]. Theoretically driven or a priori assumptions are based on an evidence analyses of healthy eating research [37] such as the HEI from the Dietary Guidelines for Healthy Americans [16], the diet quality index for adolescents based on nutrient recommendations of the Belgian Health Council [38] or the DII based on extensive review of diet components associated with inflammatory biomarkers [17].…”

Occurrence of and Reasons for “Missing Events” in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies

“…Eating may seem to be one of the simplest behaviors, yet it is quite complex [ 1 - 3 ], involving up to 200 decisions a day [ 4 ]. Although methodological challenges exist in accurately measuring food intake in community dwellings [ 5 , 6 ], analyzing data on food intake is important for our understanding of diet-disease relationships and the refinement of nutrition guidelines [ 7 ], which provide essential information for surveillance, planning interventions, and policy [ 8 ].…”

Diet quality and Gleason grade progression among localised prostate cancer patients on active surveillance

“…We examined two models in the analyses: (1) age-and energyadjusted model (base model) 22 and (2) a model additionally adjusted for baseline clinicopathologic factors including PSA and summary tumour length ("base + clinical characteristics model"). We additionally evaluated other clinical, lifestyle, and demographic factors potentially related to diet quality and grade progression, including tumour stage, smoking status, race, BMI, hypertension, diabetes, alcohol consumption and statin use.…”