Research Uses of the HEI

The Healthy Eating Index–2015 (HEI–2015) is the latest version of the HEI. The HEI–2015 and its predecessors, the HEI-2010 and the HEI–2005, are versatile metrics that can be used in many types of studies to answer a range of questions at multiple levels of the "food stream."

Each new version of the HEI provides an opportunity for further research in these areas, especially if the requisite supporting databases are made available. Collectively, such studies could add to our understanding of the food stream, the influence of different levels on food available to consumers, and the potential impact of environmental and policy changes at each level. View a list of selected HEI publications.

This page provides information about each level of the food stream, how the HEI could be used for research at each level of the food stream, and the basic steps for calculating HEI component and total scores and further details for calculating scores at different levels of analysis (i.e., national food supply, food processing, community food environment, and individual food intake). As all the instructions and tools on this page relate to the more recent versions of the HEI, and not the original, the term "HEI" -- if used alone -- refers to any of the HEI-2015, HEI-2010 or HEI-2005 versions.


What is the Food Stream?

Individuals do not make food choices in isolation. Rather, their eating behaviors are influenced by a myriad of contextual factors, including what types of food are available to them where they live, work, and shop. The food stream refers to the flow of foods from agricultural production, through processing and distribution channels, to the food that ends up on our plates.

Increasingly, nutrition researchers are realizing that if we can characterize all the points (sometimes referred to as "levels") along the food stream, we can build a better understanding of influences on consumer behavior. For example, examining the healthfulness of the U.S. food supply, the output from major producers, the menu of offerings in a school system, sales in a local grocery store, or individual-level diets could provide insights into the extent to which individuals have the capacity to make food choices that are consistent with dietary guidelines.

The versions of the HEI are especially valuable tools in this regard because each of them can be used to evaluate any mix of foods. Specifically, the standards used to assign HEI scores are not based on any specific requirements or recommendations. Rather, each of these indices relies on a universal set of standards that apply equally well to any set of foods along the food stream, including diets of individuals. This is a feasible approach because the standards are density-based and are set using age- and sex-specific recommendations that are similar per 1,000 calories.

Image: an arrow shows the flow of foods through the four levels of the food stream: National Food Supply, Food Processing, Community Food Environment, and Individual Food Intake.

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Calculating HEI Scores at Different Levels

Figure 1: summarizing the three steps for deriving HEI scores across each of the four levels of the food stream. Read the following sections for a complete explanation.

HEI Scoring Illustration
Click to enlarge.

Regardless of the level of the food stream, the basic steps for deriving HEI scores are the same. However, the food and nutrient databases required vary by level, as shown in the HEI Scoring Illustration on the right side of this web page.

Types of Studies at Various Levels

Any given set of foods at each level of the food stream can serve as the unit of analysis when employing recent versions of the HEI. At any single level, the index can be used to describe and evaluate a set of foods or to examine relationships between the quality of a set of foods and some other factor. Alternatively, it can be used to examine relationships among multiple levels of the food stream, such as the influence of changes in the quality of manufacturer's output on the quality of individual dietary intake. The interpretability and comparability of studies of this nature are simplified because the HEI can be applied in these various ways at multiple levels.

Additional details on the types of studies that can be conducted at the various levels of the food stream are provided below. The way the HEI is implemented and analyzed varies according to the type of study and level(s) being examined. For more information about this, see Choosing a Method.


National Food Supply

The amount and types of food available in the food supply are the result of domestic production and imports, after accounting for exports, nonfood uses, inventories, and farm uses. The food supply might be considered the "headwaters" of the food stream, as it represents the source of all agricultural commodities that flow downstream to manufacturers, food outlets, and markets, on their way to individuals. It makes sense that if all individuals are to have access to a healthy diet, this mix of commodities must be appropriately balanced.

Researchers have used an earlier version of the index, the HEI–2005, to examine the healthfulness of the U.S. food supply for a single year (see Reedy et al.External Web Site Policy) and over several decades (see Krebs-Smith et al.External Web Site Policy). Results indicate that substantial shifts are necessary for the US food supply to align with current dietary guidance. In particular, the food supply needs to provide substantially more fruit, vegetables, whole grains, and fat-free milk and less salt and fewer empty calories. A similar analysis using the HEI–2010 and more recent food supply dataExternal Web Site Policy is available.

Steps
Steps 1 and 2: Identify the set of foods under consideration and determine the amount of each relevant dietary constituent in the set of foods

At the national food supply level, the first two steps in calculating HEI scores are intertwined because the databases used enumerate the set of foods and provide the necessary compositional information. In contrast to other levels, researchers do not need to capture food supply data de novo, but rather can rely on publicly available databases.

Analyses using the HEI at the national food supply level reflect the set of foods that enter retail distribution channels. In the United States, quantities of each commodity are estimated by summing total annual production, imports, and beginning inventories and then subtracting exports, ending inventories, and nonfood uses. By dividing these aggregate amounts by the estimated population of the country, per capita estimates can be derived. The U.S. Department of Agriculture (USDA) annually provides such data through their Food Availability DataExternal Web Site Policy series, and corresponding Nutrient Availability DataExternal Web Site Policy.

The USDA also provides Loss-Adjusted Food Availability Data (LAFAD)External Web Site Policy, which accounts for food spoilage, plate waste, and other losses. Waste is an important consideration in calculating the HEI because the components are density based, and differential losses across food categories, if unaccounted for, could lead to difficulties in interpretation. Another advantage of the LAFAD is that quantities are provided in units such as cups and ounces, rather than pounds per person per day, and this allows for simpler calculation of the HEI. Because the data represent individual commodities and do not include any mixed dishes, such as those that complicate analyses at other levels, no disaggregation of foods is needed.

The United Nations' Food and Agriculture Organization (FAO) also publishes Food Balance SheetsExternal Web Site Policy, which are comparable, but not identical, to the U.S. Food Availability Data in their derivation. The advantage of these data is that they are available for a wide range of countries, using a similar methodology, which makes them attractive for cross-country comparisons. However, because the associated nutrient data are limited and the waste adjustments used are not comprehensive, certain assumptions must be made and care is needed in interpretation.

Step 3: Derive pertinent ratios and score each HEI component using the relevant standard

For studies of the U.S. food supply, the relevant dietary constituents needed to calculate the HEI scores are derived from the LAFAD and the Nutrient Availability Data. The Nutrient Availability Data require calibration to the LAFAD because they are not adjusted for waste in the way the LAFAD data are. For variables requiring the LAFAD, some can be obtained directly, whereas others require the application of assumptions and/or imputations.

At the food supply level, the amount of each dietary constituent is summed over all food commodities in the food supply and expressed as a ratio to total energy or, in the case of fatty acids, to total fatty acids. The resulting ratios are compared with the applicable standards for scoring.

Using the Total Fruits component as an example:

Graphic showing the mathematical formula for the described process: Dividing the sum of F for the set by the sum of E for the set gives the Assign Score for the set.

Where F = total cups of fruit in the food supply for a given year and E = total energy content of the food supply for a given year.

Two SAS macros for implementing step 3 are available above.

For details on the analysis of food supply data using the HEI–2005, see Reedy et al.External Web Site Policy and Krebs-Smith et al.External Web Site Policy For details on the analysis of food supply data using HEI-2010, see Miller et al 2015External Web Site Policy.


Food Processing

The next stop along the food stream for many foods in the United States is the manufacturer level, where agricultural commodities are processed into food products. This is the one level of the food stream to which the HEI has not yet been applied, but studies characterizing the output of major manufacturers could be valuable, considering their early position in the food stream and potential influence on levels further downstream.

For example, the HEI could be useful in examining the effects of the Healthy Weight CommitmentExternal Web Site Policy. That effort involves about 150 food companies who have collectively pledged to remove 1.5 trillion calories from the food supply by 2015; by 2017, these companies had removed 6.4 trillion calories from the food supply. Although the HEI is not necessary to evaluate whether or not they meet that goal, it could be used to examine whether their collective output has a higher diet quality after this effort is realized than before.

Obstacles to employing the HEI at this level relate to the lack of available data. For example, companies do not typically release information quantifying their total output of products. Even if such amounts could be obtained or reasonably estimated, data also are lacking on the composition of processed unprepared foods, such as macaroni and cheese or cake mix, which represent many of the foods associated with this level.

To calculate an HEI score, compositional data are needed in terms of both nutrients and food groups. For all packaged foods, the requisite nutrient composition data are available on the Nutrition Facts Panel, but data on the quantities of fruits, vegetables, whole grains, added sugars, and other components that also are required to calculate the HEI are not. Estimation of these components requires a specialized database that can disaggregate the product into its ingredients and tally the quantities of those ingredients with those of similar items. As described below, that type of database is available for ready-to-eat foods from Community Food Environment outlets and the Individual Food Intake level, but it is lacking for less-than-fully-prepared foods at the Food Processor level.

Steps
Step 1: Identify the set of foods under consideration

At the food processing level, the set of foods under consideration might be the output of a given manufacturer or group of companies, such as those taking part in the Healthy Weight Commitment. The ideal way to capture such data would be to get them directly from the manufacturer(s). Methods for researchers to gather this information themselves, using available data on foods in the marketplace, have not been developed, as research at this level has been held back by a lack of available nutrient and food group compositional databases.

Step 2: Determine the amount of each relevant dietary constituent in the set of foods

One publicly available (fee-based) resource that provides data for packaged food and beverage products sold in the United States is the Gladson Nutrition DatabaseExternal Web Site Policy. It supplies ingredient content and nutrient composition for several nutrients including energy, fatty acids and sodium. Therefore, all the nutrient information needed to calculate the HEI is available. However, compositional databases on the food group content of packaged foods are missing. If such a database could be made available, research using the HEI at this level would be greatly facilitated.

Step 3: Derive pertinent ratios and score each HEI component using the relevant standard

Once food group compositional databases are available at this level, calculation of the variables, ratios, and scores will be straightforward. The same SAS macros provided for implementing this step at the food supply level could be used at this level.


Community Food Environment

The Community Food Environment represents all of the places where individuals acquire food. These places can be broadly divided into markets, where consumers purchase food to prepare or serve at home, and outlets and other settings where consumers purchase or are served ready-to-eat food. At any of these locations, the HEI can be applied to either the set of foods available or the set of foods sold or served. The set of foods available -- using, for example, the menu at a fast food restaurant -- corresponds to the choices offered to consumers by the market or outlet. The set of foods served -- using, for example, sales data for the same restaurant in a given neighborhood -- represents the impact the location is having on eating habits there.

Markets
As mentioned in the section on Food Processing, compositional data are needed in terms of both nutrients and food groups in order to calculate HEI scores. Studies of markets, such as grocery or convenience stores, have been hampered because compositional data on many of the HEI components are lacking for many items -- namely, the unprepared foods. These types of stores also sell many ready-to-eat foods, for which the necessary data are available, but because unprepared foods make up a large portion of foods available and sold in markets, such studies are painstaking. Nonetheless, Volpe and OkrentExternal Web Site Policy assessed the healthfulness of consumers' grocery purchases (market baskets) using the HEI–2005 and found a similar pattern of discordance with recommendations as found at other levels (e.g., the food supply) -- too few fruits, vegetables, whole grains and too many refined grains, fats, and sugars/sweets. They also determined that the healthfulness of purchases varies across geographic regions and markets. Another group, Jahns et al.External Web Site Policy, examined grocery store circulars using the HEI-2010 and found the circulars had lower scores than the U.S. population scores.

A database of all types of foods available in markets, including both ready-to-eat foods and unprepared foods, linked to compositional data on nutrients and dietary guidance-based food components would facilitate the expansion of research at this level.

Food Outlets & Other Settings Where People Purchase or Are Served Ready-To-Eat Food
Studies of food outlets and other settings where people purchase or are served ready-to-eat food -- such as cafés, restaurants, and schools -- do not have the same limitations regarding compositional databases as those of food markets, because the foods served are ready-to-eat, which enables the comprehensive databases that have been developed for the individual level generally to suffice. Reedy et al.External Web Site Policy described the methods for conducting an analysis of a food outlet with the HEI–2005, and Kirkpatrick et al.External Web Site Policy used that approach to compare the healthfulness of menus at five major fast food restaurants.

When sufficient compositional data can be obtained to calculate HEI scores, studies employing the HEI at this level could:

  • examine the healthfulness of a set of foods marketed by major grocery chains (say, by tracking foods featured in weekly newspaper ads) (see Jahns et al.External Web Site Policy);
  • determine how well foods offered in the café at a local health care facility conform to recommendations;
  • assess the healthfulness of packages provided by food banks and food pantries (see Nanney et al.External Web Site Policy); or
  • compare the diet quality of in-flight offerings across major airline carriers.

Steps
Step 1: Identify the set of foods under consideration

Aspects of the community food environment that could be evaluated with the HEI include the set of foods offered, served or sold at markets, outlets, schools and other institutions. Foods offered can be operationalized by enumerating the set of foods and beverages on a menu (for example, from a school's lunch program) or otherwise offered for sale (for example, in a grocery store's weekly ad). Foods served could be defined, for example, as the total foods actually served by a school over a given period. Likewise, foods sold could be represented by the total sales for a neighborhood grocery store. It is generally easier to obtain information on food offered than on foods served or sold, as the latter are not as readily available and generally require cooperation from the market, outlet, or institution.

Step 2: Determine the amount of each relevant dietary constituent in the set of foods

Nutrient and food group composition data are needed to calculate HEI scores. Values for energy and the relevant nutrients may be available from package labeling or nutrient composition databases. However, determining the values for the other relevant dietary constituents means that any food mixture containing ingredients from multiple food groups (pizza, for example), must be disaggregated into component ingredients before it can be tallied appropriately. Also, if necessary, yield factors must be applied so the amounts of cooked and raw foods are on an equivalent basis. This requires a database, such as the MyPyramid Equivalents Database (MPED) (see section below on individual food intake) that translates the foods into equivalent amounts of fruits, vegetables, added sugars, and so on.

If the set of foods under consideration represents an outlet or institution that sells or serves only ready-to-eat food, databases that have been developed for individual-level analyses can be used. However, no databases are available currently to translate unprepared foods (such as raw meats and untrimmed produce) and processed but not fully prepared foods (such as cake mixes) into appropriate food group equivalents. This is a limitation for studying markets that sell these foods. If the set of foods is small, this step can be done by hand, but this is a painstaking process. Studies of the total inventories of large grocery stores will be impracticable until market-appropriate databases are available.

Step 3: Derive pertinent ratios and score each HEI component using the relevant standard

At the community food environment level, the amount of each dietary constituent is summed over all foods in the set under consideration and expressed as a ratio to total energy or, in the case of fatty acids, to total fatty acids. The resulting ratios are compared with the applicable standards for scoring (link to HEI standards).

Using the Total Fruits component as an example:

Graphic showing the mathematical formula for the described process: Dividing the sum of F for the set by the sum of E for the set gives the Assign Score for the set.

Where F = total cups of fruit in the set of foods and E = total energy content of the set of foods.

Two SAS macros for implementing step 3 are available.

See the methods sections of Volpe and OkrentExternal Web Site Policy, Reedy et al.External Web Site Policy, and Kirkpatrick et al.External Web Site Policy for examples of analyses using the HEI–2005 at the community food environment level.


Individual Food Intake

When interest is in describing the diet quality of an individual, data must be collected at the individual level. Most of the time, researchers are interested in describing or making inferences about groups of individuals, or populations. A dietitian might also be interested in the HEI for clinical use to assess diet quality for an individual client. In this section, we describe individual level dietary data, and the uses of such data pertaining to the HEI.

Data collected at the individual level commonly use food frequency questionnaires (FFQ), 24 hour dietary recalls, or food records. Before diet quality can be assessed using the HEI, the intake reported by these methods must be summarized into nutrients and food groups. Data collected at the individual level through 24-hour recall methodology are often coded using either the USDA's Food and Nutrient Database for Dietary Studies (FNDDS)External Web Site Policy or the Nutrition Coordinating Center's (NCC's) Nutrition Data System for Research (NDSR; fee-based). Both of these databases provide compositional information for a full array of nutrients. However, the HEI requires food serving equivalents in addition to nutrients. The FNDDS links to the Food Patterns Equivalents DatabaseExternal Web Site Policy (FPED, formerly the MyPyramid Equivalents Database, MPED), which characterizes the foods reported according to components needed to calculate the HEI. The NDSR has some food component information as well, and has developed a guide to help users create the variables needed to calculate scores using data from NDSR output filesExternal Web Site Policy. Data collected through a food frequency questionnaire (FFQ) that links to FNDDS can similarly be linked to the FPED and be used to estimate HEI scores. Data from FFQs that have not been linked with FNDDS would have to be appropriately coded to capture and summarize each of the dietary components required to calculate the HEI. Researchers interested in how to apply HEI scoring should see Overview of the Methods and Calculations for details regarding scoring and analysis..

Population or Group Level Intake
Studies at the population or group level represent the most frequent type of HEI application. In these studies, individual persons are the units of data collection; however, inference about the HEI is made at the population level. Researchers interested in employing the HEI with data analyzed at the group level can use it to: describe the diet quality of the population overall or for subgroups defined by income, race/ethnicity, and other characteristics; examine relationships between overall diet quality and outcomes, such as mortality or incidence of some chronic disease; or describe the impact of dietary interventions.

Many studies have been conducted using the HEI–2005 and the HEI–2010. USDA has published a brief report on HEI–2010 population scores for 2007 - 2008 and 2001 - 2002 [PDF]External Web Site Policy. Similar to findings at other levels, the overall U.S. population scores are suboptimal compared to federal dietary guidance. Americans consume far too few fruits, vegetables, whole grains, and milk products or fortified soy beverages, while over-consuming refined grains, solid fat, and added sugars.

Individual Food Intake
Individual-level food intake data can also be used to calculate HEI scores for a given person, for example, within a clinical setting. However, there are caveats in interpretation of the scores at the individual level. The application of the HEI does not involve the comparison of a person's intake to his or her individual requirements, but rather to standards based on national recommendations based on the minimal criterion. Furthermore, the recommendations upon which the HEI is based are meant to be met over time, not every day. An individual's HEI score based on a given day's intake would not necessarily reflect the score based on his/her usual or habitual intake, particularly for components that are episodically consumed such as whole grains.

Researchers interested in employing the HEI at the individual level can use it to:

  • describe the diet quality of the population or subgroups defined by income, race/ethnicity, and other characteristics; or
  • examine relationships between overall diet quality and outcomes, such as mortality or incidence of some chronic disease.

Steps
The total foods and beverages consumed by individuals is the subject of interest at this level. Most often, researchers are interested in the usual (or long-run average) diets of groups of individuals to assess diet quality. However, sometimes information about diets of individual persons on a given day or days is the exposure of interest.

Because the HEI is most frequently applied to usual diet, it is usually calculated on the basis of the long-term average dietary intake of an individual or group of individuals. Food frequency questionnaires (FFQs) attempt to directly capture usual intake by asking respondents to estimate averages across a long time period. Other dietary assessment tools, such as 24-hour recalls (24HRs) or food records (FRs), capture short-term intakes rather than average intakes, and the resulting data are subject to day-to-day variation in diet. However, with repeat non-consecutive measurements per person, it is possible to estimate usual intake through averaging multiple 24HRs or FRs within a person. When we average on the person level, we eliminate within-person variation, such as day-to-day variability in intake, resulting in estimates that are closer to usual intake. It is also possible to apply statistical methods to isolate between-person variation from within-person variation even with a small number of days per person. These are termed “usual intake methods.”

Step 1: Identify the set of foods under consideration

Information on foods consumed by people on a day or over a longer period of time can be collected using various methods. The most commonly used methods are 24-hour recall, food record, or food frequency questionnaire. For example, HEI scores can be calculated using recall data collected in the What We Eat in America component of the National Health and Nutrition Examination Survey (NHANES)External Web Site Policy or using the Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool. Both of these sources of data can be linked to appropriate databases, including the Food and Nutrient Database for Dietary Surveys and the Food Patterns Equivalents Database. Food frequency data can also be used to calculate HEI scores if linkages to appropriate databases can be made (see step 2).

Calculating HEI scores requires information on the total diet; thus, data from brief instruments, such as screeners, which capture only particular aspects of the diet cannot be used for this purpose. View a table outlining recommended methods to calculate Healthy Eating Index scores depending on the main purpose of the study and the dietary assessment tool utilized. For more information about selecting dietary assessment tools, see the Dietary Assessment PrimerExternal Web Site Policy.

Step 2: Determine the amount of each relevant dietary constituent in the set of foods

Determining the amounts of each dietary constituent contained in the total quantity of foods under consideration requires linking to relevant databases. Values for energy and the relevant nutrients can be obtained from a nutrient composition database. Obtaining values for the other relevant dietary constituents requires a database that translates the foods into amounts of fruits, vegetables, lean meat, and so on. One publicly available database designed for this purpose is the Food Patterns Equivalents Database (FPED)External Web Site Policy, formerly known as the MyPyramid Equivalents Database (MPED). The FPED links to the USDA's Food and Nutrient Database for Dietary Studies (FNDDS)External Web Site Policy and has been used to evaluate the U.S. diet in relation to dietary guidance such as the USDA food patterns, which are part of the Dietary Guidelines for AmericansExternal Web Site Policy. It translates the amounts of foods, as eaten, into cup and ounce equivalents that are consistent with the units of measure used for the HEI scoring standards.

  • If the FPED is used, no additional steps are required to determine the amount of each food-based constituent required to calculate HEI scores. Note that for the HEI-2005 and HEI-2010, beans and peas had to be allocated to the proper component; this is not the case for HEI-2015. In the HEI-2005 and HEI-2010, beans and peas are first counted toward the protein groups, with any amount left after the Total Proteins Food standard is met counting toward the vegetables groups. NCI has developed programs for the HEI-2005 and the HEI-2010 to complete this allocation.

Once the databases are identified, each food item or line item must be linked to each nutrient and food group that comprise the HEI. For each day (or relevant time period), these values are summed across all identified food groups (see HEI Scoring Illustration). The outputs of step 2 are the values for each dietary constituent that makes up the HEI score for each person for each day. The way in which these components are scored will vary dependent on the goal of the analysis and the statistical method utilized (see Step 3).

Step 3: Derive pertinent ratios and score each HEI component using the relevant standard

Although the HEI dietary constituents corresponding to each HEI component are scored according to the HEI scoring standards, the way in which person-level data are aggregated and scored, including the exact constituents used and the construction of ratios, differs in relation to the goal of the population-based analysis and hence the analytic method chosen, the dietary assessment method used, and the number of repeats of the dietary assessment measure in the case of short-term methods. The purpose of the analysis as well as the data structure must be considered in deciding upon the most appropriate method to estimate the HEI score.

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