Jill Reedy

Update of the Healthy Eating Index: HEI-2010

The Healthy Eating Index (HEI) is a measure of diet quality in terms of conformance with federal dietary guidance. Publication of the 2010 Dietary Guidelines for Americans prompted an interagency working group to update the HEI. The HEI-2010 retains several features of the 2005 version: (a) it has 12 components, many unchanged, including nine adequacy and three moderation components; (b) it uses a density approach to set standards, eg, per 1,000 calories or as a percentage of calories; and (c) it employs least-restrictive standards; ie, those that are easiest to achieve among recommendations that vary by energy level, sex, and/or age. Changes to the index include: (a) the Greens and Beans component replaces Dark Green and Orange Vegetables and Legumes; (b) Seafood and Plant Proteins has been added to capture specific choices from the protein group; (c) Fatty Acids, a ratio of polyunsaturated and monounsaturated to saturated fatty acids, replaces Oils and Saturated Fat to acknowledge the recommendation to replace saturated fat with monounsaturated and polyunsaturated fatty acids; and (d) a moderation component, Refined Grains, replaces the adequacy component, Total Grains, to assess overconsumption. The HEI-2010 captures the key recommendations of the 2010 Dietary Guidelines and, like earlier versions, will be used to assess the diet quality of the US population and subpopulations, evaluate interventions, research dietary patterns, and evaluate various aspects of the food environment.

Dietary Sources of Energy, Solid Fats, and Added Sugars Among Children and Adolescents in the United States

OBJECTIVE The objective of this research was to identify top dietary sources of energy, solid fats, and added sugars among 2- to 18-year-olds in the United States. METHODS Data from the National Health and Nutrition Examination Survey, a cross-sectional study, were used to examine food sources (percentage contribution and mean intake with standard errors) of total energy (data from 2005-2006) and energy from solid fats and added sugars (data from 2003-2004). Differences were investigated by age, sex, race/ethnicity, and family income, and the consumption of empty calories-defined as the sum of energy from solid fats and added sugars-was compared with the corresponding discretionary calorie allowance. RESULTS The top sources of energy for 2- to 18-year-olds were grain desserts (138 kcal/day), pizza (136 kcal/day), and soda (118 kcal/day). Sugar-sweetened beverages (soda and fruit drinks combined) provided 173 kcal/day. Major contributors varied by age, sex, race/ethnicity, and income. Nearly 40% of total energy consumed (798 of 2,027 kcal/day) by 2- to 18-year-olds were in the form of empty calories (433 kcal from solid fat and 365 kcal from added sugars). Consumption of empty calories far exceeded the corresponding discretionary calorie allowance for all sex-age groups (which range from 8% to 20%). Half of empty calories came from six foods: soda, fruit drinks, dairy desserts, grain desserts, pizza, and whole milk. CONCLUSIONS There is an overlap between the major sources of energy and empty calories: soda, grain desserts, pizza, and whole milk. The landscape of choices available to children and adolescents must change to provide fewer unhealthy foods and more healthy foods with less energy. Identifying top sources of energy and empty calories can provide targets for changes in the marketplace and food environment. However, product reformulation alone is not sufficient-the flow of empty calories into the food supply must be reduced.

Development of the Healthy Eating Index-2005

The Healthy Eating Index (HEI) is a measure of diet quality as specified by Federal dietary guidance, and publication of the Dietary Guidelines for Americans 2005 necessitated its revision. An interagency working group based the HEI-2005 on the food patterns found in My-Pyramid. Diets that meet the least restrictive of the food-group recommendations, expressed on a per 1,000 calorie basis, receive maximum scores for the nine adequacy components of the index: total fruit (5 points), whole fruit (5 points), total vegetables (5 points), dark green and orange vegetables and legumes (5 points), total grains (5 points), whole grains (5 points), milk (10 points), meat and beans (10 points), and oils (10 points). Lesser amounts are pro-rated linearly. Population probability densities were examined when setting the standards for minimum and maximum scores for the three moderation components: saturated fat (10 points), sodium (10 points), and calories from solid fats, alcoholic beverages (ie, beer, wine, and distilled spirits), and added sugars (20 points). Calories from solid fats, alcoholic beverages, and added sugars is a proxy for the discretionary calorie allowance. The 2005 Dietary Guideline for saturated fat and the Adequate Intake and Tolerable Upper Intake Level for sodium, expressed per 1,000 calories, were used when setting the standards for those components. Intakes between the maximum and minimum standards are pro-rated. The HEI-2005 is a measure of diet quality as described by the key diet-related recommendations of the 2005 Dietary Guidelines. It has a variety of potential uses, including monitoring the diet quality of the US population and subpopulations, evaluation of interventions, and research.

Measures of the Food Environment: A Compilation of the Literature, 1990–2007

BACKGROUND Valid and reliable measures are required to assess any effect of the food environment on individual dietary behavior, and form the foundation of research that may inform obesity-related policy. Although many methods of measuring the food environment exist, this area of research is still relatively new and there has been no systematic attempt to gather these measures, to compare and contrast them, or to report on their psychometric properties. EVIDENCE ACQUISITION A structured literature search was conducted to identify peer-reviewed articles published between January 1990 and August 2007 that measured the community-level food environment. These articles were categorized into the following environments: food stores, restaurants, schools, and worksites. The measurement strategies in these studies were categorized as instruments (checklists, market baskets, inventories, or interviews/questionnaires) or methodologies (geographic, sales, menu, or nutrient analyses). EVIDENCE SYNTHESIS A total of 137 articles were identified that included measures of the food environment. Researchers focused on assessing the accessibility, availability, affordability, and quality of the food environment. The most frequently used measure overall was some form of geographic analysis. Eighteen of the 137 articles (13.1%) tested for any psychometric properties, including inter-rater reliability, test-retest reliability, and/or validity. CONCLUSIONS A greater focus on testing for reliability and validity of measures of the food environment may increase rigor in research in this area. Robust measures of the food environment may strengthen research on the effects of the community-level food environment on individual dietary behavior, assist in the development and evaluation of interventions, and inform policymaking targeted at reducing the prevalence of obesity and improving diet.

Evaluation of the Healthy Eating Index-2005

BACKGROUND The Healthy Eating Index (HEI), a measure of diet quality as specified by federal dietary guidance, was revised to conform to the Dietary Guidelines for Americans 2005. The HEI has several components, the scores of which are totaled. OBJECTIVE The validity and reliability of the HEI-2005 were evaluated. DESIGN Validity was assessed by answering four questions: Does the HEI-2005 1) give maximum scores to menus developed by experts; 2) distinguish between groups with known differences in diet quality-smokers and nonsmokers; 3) measure diet quality independently of energy intake, a proxy for diet quantity; and 4) have more than one underlying dimension? The relevant type of reliability, internal consistency, was also assessed. SUBJECTS Twenty-four-hour recalls from 8,650 participants, aged 2 years and older, in the National Health and Nutrition Examination Survey, 2001-2002 were analyzed to answer questions 2 to 4. Results were weighted to consider sample design and nonresponse. STATISTICAL ANALYSES T tests determined differences in scores between smokers and nonsmokers. Pearson correlation coefficients determined the relationship between energy intake and scores. Principal components analysis determined the number of factors that comprise the HEI-2005. Cronbachs coefficient alpha tested internal consistency. RESULTS HEI-2005 scores are at or very near the maximum levels for all sets of exemplary menus with one exception; the Harvard menus scored low on the milk component because these menus intentionally include only small amounts of milk products. Nine of 12 component scores were lower for smokers than nonsmokers. The correlations of component scores were virtually independent of energy intake (< I.22I). Multiple factors underlie the HEI-2005. Coefficient alpha was .43. The alpha value for all tests was .01. CONCLUSIONS The HEI-2005 is a valid measure of diet quality. Potential uses include population monitoring, evaluation of interventions, and research. The individual component scores provide essential information in addition to that provided by the total score.

Higher Diet Quality Is Associated with Decreased Risk of All-Cause, Cardiovascular Disease, and Cancer Mortality among Older Adults

Increased attention in dietary research and guidance has been focused on dietary patterns, rather than on single nutrients or food groups, because dietary components are consumed in combination and correlated with one another. However, the collective body of research on the topic has been hampered by the lack of consistency in methods used. We examined the relationships between 4 indices--the Healthy Eating Index-2010 (HEI-2010), the Alternative Healthy Eating Index-2010 (AHEI-2010), the alternate Mediterranean Diet (aMED), and Dietary Approaches to Stop Hypertension (DASH)--and all-cause, cardiovascular disease (CVD), and cancer mortality in the NIH-AARP Diet and Health Study (n = 492,823). Data from a 124-item food-frequency questionnaire were used to calculate scores; adjusted HRs and 95% CIs were estimated. We documented 86,419 deaths, including 23,502 CVD- and 29,415 cancer-specific deaths, during 15 y of follow-up. Higher index scores were associated with a 12-28% decreased risk of all-cause, CVD, and cancer mortality. Specifically, comparing the highest with the lowest quintile scores, adjusted HRs for all-cause mortality for men were as follows: HEI-2010 HR: 0.78 (95% CI: 0.76, 0.80), AHEI-2010 HR: 0.76 (95% CI: 0.74, 0.78), aMED HR: 0.77 (95% CI: 0.75, 0.79), and DASH HR: 0.83 (95% CI: 0.80, 0.85); for women, these were HEI-2010 HR: 0.77 (95% CI: 0.74, 0.80), AHEI-2010 HR: 0.76 (95% CI: 0.74, 0.79), aMED HR: 0.76 (95% CI: 0.73, 0.79), and DASH HR: 0.78 (95% CI: 0.75, 0.81). Similarly, high adherence on each index was protective for CVD and cancer mortality examined separately. These findings indicate that multiple scores reflect core tenets of a healthy diet that may lower the risk of mortality outcomes, including federal guidance as operationalized in the HEI-2010, Harvards Healthy Eating Plate as captured in the AHEI-2010, a Mediterranean diet as adapted in an Americanized aMED, and the DASH Eating Plan as included in the DASH score.

Income and Race/Ethnicity Are Associated with Adherence to Food-Based Dietary Guidance among US Adults and Children

BACKGROUND Income and race/ethnicity are associated with differences in dietary intakes that may contribute to health disparities among members of the US population. OBJECTIVE To examine alignment of intakes of food groups and energy from solid fats, added sugars, and alcohol with the 2005 Dietary Guidelines for Americans and MyPyramid, by family income and race/ethnicity. DESIGN Data from the National Health and Nutrition Examination Survey, a cross-sectional, nationally representative survey, for 2001-2004. PARTICIPANTS/SETTING Persons aged ≥2 years for whom reliable dietary intake data were available (n=16,338) were categorized by income (lowest, middle, and highest) and race/ethnicity (non-Hispanic white, non-Hispanic black, and Mexican American). STATISTICAL ANALYSES PERFORMED The National Cancer Institute method was used to estimate the proportions of adults and children in each income and race/ethnic group whose usual intakes met the recommendations. RESULTS Higher income was associated with greater adherence to recommendations for most food groups; the proportions meeting minimum recommendations among adults in the highest income group were double that observed for the lowest income group for total vegetables, milk, and oils. Fewer differences by income were apparent among children. Among the race/ethnic groups, the proportions meeting recommendations were generally lowest among non-Hispanic blacks. Marked differences were observed for milk-15% of non-Hispanic black children met the minimum recommendations compared with 42% of non-Hispanic white children and 35% of Mexican-American children; a similar pattern was evident for adults. One in five Mexican-American adults met the dry beans and peas recommendations compared with approximately 2% of non-Hispanic whites and non-Hispanic blacks. Most adults and children consumed excess energy from solid fats and added sugars irrespective of income and race/ethnicity. CONCLUSIONS The diets of some subpopulations, particularly individuals in lower-income households and non-Hispanic blacks, are especially poor in relation to dietary recommendations, supporting the need for comprehensive strategies to enable healthier dietary intake patterns.

Need for Technological Innovation in Dietary Assessment

In 2007, the National Institutes of Health developed the Genes, Environment and Health Initiative (GEI) (www.gei.nih.gov) to promote research to better understand the genetic and environmental contributions to health and disease. GEI funded technology-driven methodology to improve measures of diet, physical activity, chemical exposures, psychosocial measures, and biological response indicators for use in future large-scale population studies. Similarly, since 2004, the National Cancer Institute (NCI) has internally funded the development of another technology advance in dietary assessment: an automated self-administered 24-hour dietary recall (ASA). The purpose of this paper is to briefly overview issues related to the uses of technology in dietary assessment, as a backdrop for advances in the field.

Index-based Dietary Patterns and Risk of Colorectal Cancer The NIH-AARP Diet and Health Study

The authors compared how four indexes-the Healthy Eating Index-2005, Alternate Healthy Eating Index, Mediterranean Diet Score, and Recommended Food Score-are associated with colorectal cancer in the National Institutes of Health-AARP Diet and Health Study (n = 492,382). To calculate each score, they merged data from a 124-item food frequency questionnaire completed at study entry (1995-1996) with the MyPyramid Equivalents Database (version 1.0). Other variables included energy, nutrients, multivitamins, and alcohol. Models were stratified by sex and adjusted for age, ethnicity, education, body mass index, smoking, physical activity, and menopausal hormone therapy (in women). During 5 years of follow-up, 3,110 incident colorectal cancer cases were ascertained. Although the indexes differ in design, a similarly decreased risk of colorectal cancer was observed across all indexes for men when comparing the highest scores with the lowest: Healthy Eating Index-2005 (relative risk (RR) = 0.72, 95% confidence interval (CI): 0.62, 0.83); Alternate Healthy Eating Index (RR = 0.70, 95% CI: 0.61, 0.81); Mediterranean Diet Score (RR = 0.72, 95% CI: 0.63, 0.83); and Recommended Food Score (RR = 0.75, 95% CI: 0.65, 0.87). For women, a significantly decreased risk was found with the Healthy Eating Index-2005, although Alternate Healthy Eating Index results were similar. Index-based dietary patterns that are consistent with given dietary guidelines are associated with reduced risk.

Addressing Current Criticism Regarding the Value of Self-Report Dietary Data

Recent reports have asserted that, because of energy underreporting, dietary self-report data suffer from measurement error so great that findings that rely on them are of no value. This commentary considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy. Topics discussed include what is known and what can be done about the measurement error inherent in data collected by using self-report dietary assessment instruments and the extent and magnitude of underreporting energy compared with other nutrients and food groups. Also discussed is the overall impact of energy underreporting on dietary surveillance and nutritional epidemiology. In conclusion, 7 specific recommendations for collecting, analyzing, and interpreting self-report dietary data are provided: (1) continue to collect self-report dietary intake data because they contain valuable, rich, and critical information about foods and beverages consumed by populations that can be used to inform nutrition policy and assess diet-disease associations; (2) do not use self-reported energy intake as a measure of true energy intake; (3) do use self-reported energy intake for energy adjustment of other self-reported dietary constituents to improve risk estimation in studies of diet-health associations; (4) acknowledge the limitations of self-report dietary data and analyze and interpret them appropriately; (5) design studies and conduct analyses that allow adjustment for measurement error; (6) design new epidemiologic studies to collect dietary data from both short-term (recalls or food records) and long-term (food-frequency questionnaires) instruments on the entire study population to allow for maximizing the strengths of each instrument; and (7) continue to develop, evaluate, and further expand methods of dietary assessment, including dietary biomarkers and methods using new technologies.