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3 Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA; 4 Friedman School of Nutrition Science and Policy, Boston, MA; 5 Beth Israel Deaconess Medical Center, Boston, MA; 6 Tufts-New England Medical Center Hospital, Boston, MA; 7 School of Medicine, Tufts University, Boston, MA; and the 8 Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, GA
* To whom correspondence should be addressed. E-mail: paul.jacques{at}tufts.edu.
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Introduction |
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When the DGA was originally developed in 1980, there was no plan in place to evaluate its success (3). The first evaluation tool created to assess the DGA, the Healthy Eating Index (HEI), was developed by the USDA Center for Nutrition Policy and Promotion (7,8). The HEI included 10 components derived from the 1990 DGA, and was based on achieving the recommended number of servings for each of the items on the Food Guide Pyramid, as well as consideration of total fat, total cholesterol, saturated fat, sodium, and variety in the diet (8). Harnack et al. (9) published a revised index to assess adherence to the 2000 DGA, which contained items to represent all the recommendations except the new recommendation on food safety. The score for items that were not quantitative, such as "choose a diet low in saturated fat and cholesterol and moderate in total fat" used dietary recommendations provided by the National Research Council (10). These indices were used to assess the quality of the American diet (11–13) and to assess the association between diet quality and chronic disease (9,14–18).
We developed the 2005 Dietary Guidelines for Americans Adherence Index (DGAI) to reflect the substantial changes in these guidelines in 2005 with a focus on overconsumption and energy density (5).
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Materials and Methods |
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The DGA distinguishes between energy-specific food intake recommendations and healthy choice nutrient recommendations. The food intake recommendations are based on the energy needs of each individual and are assessed at the energy level that most closely represents the individual's needs. The healthy choice recommendations are given in absolute amounts or as a percentage of total energy, and are the same for all individuals.
An effort was made to limit interpretation of the guidelines, and when available, the DGAI used the cutoff values as specified in the guidelines. When an interpretation was necessary, a considerable effort was made to capture the spirit of that individual recommendation, using information from the 2005 DGA Advisory Committee Report (4) or from nationally representative population samples, such as the NHANES and Continuing Survey of Food Intake by Individuals (CSFII) (19–21).
An important goal in the development of the DGAI was to limit the likelihood that one could receive a higher score solely by consuming more food, which was a major shortcoming of previous indices (8,11). Thus, one of the central features of the DGAI is a penalty for consuming more than the recommended amount of discretionary energy and food groups that have, on average, higher energy per serving.
Recommended food pattern. The DGA report indicates a balanced diet can be achieved by 1 of 2 different approaches; the USDA food guide pattern or the Dietary Approaches to Stop Hypertension (DASH) diet serving recommendations (5). We chose the USDA food guide pattern for the DGAI as it gave specific recommendations for 12 different energy levels and is the system employed by MyPyramid.gov (6). Although USDA is moving away from using the term "servings" because it is considered vague and difficult for the public to understand (5), it was used in the Methods section of this article to represent the recommended amounts in the 2005 DGA.
Energy level assignment. For each participant, the appropriate energy level was determined using the estimated energy requirement (EER) equation based on height, weight, age, gender and an estimate of physical activity using the "walking equivalents method" as described in the energy section of the Dietary Reference Intakes (21). Based on this calculation, individuals were assigned to 1 of 10 USDA food guide energy-level food intake patterns recommended for adults in the DGA 2005 report, which ranged from 1400 to 3200 kcal (5.86–13.39 MJ). (5). Individuals with calculated needs below the minimum energy level were assessed at 1400 kcal (5.86 MJ), and those above the maximum level of 3200 kcal (13.39 MJ) were assessed at this level.
DGAI components and scoring. There are a total of 20 items on the DGAI. Eleven index items assess the energy-specific food intake recommendations and 9 assess the healthy choice nutrient recommendations. Each item has a maximum value of 1.0, so the maximum possible DGAI score is 20 points. An example of the index, based on the 1800 kcal (7.53 MJ) food pattern, is presented in the Appendix.
Food intake recommendations. The USDA food guide pattern includes intake recommendations for 5 vegetable subgroups, fruit, a variety of fruits and vegetables, meat and legumes, milk and milk products, grains, and discretionary energy (5). The DGA indicates that discretionary energy is intended to be used toward increased intake of the basic food groups; to allow flexibility in selection of foods that are higher in fat or with added sugar; to add oils, fats, or sugars to foods or beverages; or to use toward alcohol consumption (5).
For each of the food items, there are 3 possible values. Individuals whose food intake meets the recommendation receive 1 point. We defined an intermediate category for those who did not meet the recommendation, but consumed 
>33% of the recommended amount. Individuals meeting these criteria receive 0.5 points. Those consuming <33% of the recommended amount received 0 points. The 33% cutoff was chosen because it provided an approximately equal division of individuals not meeting the recommendation into the low and intermediate intake categories across all food intake items. (We used a percentage of the recommended intake, rather than an absolute value, to simplify the index because of the different recommended number of servings and serving units across food items. We defined the actual cutoff value as the number of servings, rounded to the nearest half serving, that most closely approximated 33% of the recommended intake. Consequently, the lowest possible cutoff for defining the intermediate category was 0.5 servings.)
We also categorized food items according to their mean energy density. For those foods considered energy dense, we imposed an overconsumption penalty for those who exceeded the recommended intake by 
0.5 servings by assigning only 0.5 points. Foods defined as energy dense for these analyses included meat, dairy, grains, and starchy vegetables. All other vegetables and fruit were not classified as energy dense and did not receive a penalty for overconsumption. To determine what food groups to classify as energy dense, we analyzed the mean energy contribution of a serving of each food group using serving sizes obtained from the 2005 DGA and MyPyramid.gov (5,6). Energy per serving was determined using the USDA Standard Reference 16 via the Nutritionist V software (First Data Bank). Only the food items from each food group included in the 1988 Harvard semiquantitative FFQ were included for the present analyses (22,23) because this was the dietary assessment tool to which the DGAI was initially applied (see Dietary Assessment below). Because of the lack of an existing standard definition of energy-dense food, we defined the energy-dense food groups as those that, on average, had >50 kcal per serving based on the distribution of values for the different food groups.
The USDA food guide pattern divides vegetables into 5 categories based on their color and nutrient composition. These include orange vegetables, dark green vegetables, legumes, starchy vegetables, and other vegetables. There is an index item to assess each of the 5 vegetable groups on a per week basis. One index item assesses fruit and fruit juice intake per day, consistent with the USDA food guide recommendation.
Variety is stressed in the DGA, as indicated by the recent change to the USDA food guide to include 5 different vegetable groups. Thus, an additional index item is included to give credit to those who eat a variety of vegetables and fruit, but who do not necessarily meet the recommendation for each of the 5 vegetable items and the fruit item. Those who receive a score of 0.5 on each individual fruit and vegetable index item receive 1.0 point. Those who meet this criterion for 5 of the 6 fruit and vegetable index items receive a score of 0.5. Those who receive 0.5 points on 
4 items receive a score of 0.
The index includes one item for meat and legumes and one for milk and milk products. To be consistent with the USDA food guide, all meat and dairy products, both high and low-fat, count toward the recommended servings for these items. Total intake was assessed on a per-day basis. A second item that addresses the healthy choice recommendation to make choices that are lean, low-fat, or fat-free when selecting and preparing meat, poultry, and milk or milk products is described below. The DGA report indicates that legumes can count toward either the meat or legume recommendation. For the DGAI, legumes were counted toward the meat recommendation if they were needed to meet the 1.0-point criteria for the meat item. Legume servings not needed to attain the recommended servings of meat were counted toward the legume recommendation and did not cause a person to exceed their meat recommendation. We chose to assign legumes to the meat item first so that those who consume legumes in place of meat could achieve their recommended intake as lean meats.
There is one index item to assess the recommendation for total grain intake on a per-day basis. The DGA recommendation, that 50% of the total grain intake come from whole grains, is not dependent on energy level and therefore is considered with the healthy choice recommendations.
Discretionary energy. The revised DGA emphasizes nutrient density by including a recommendation for discretionary energy. The 2005 DGA quantifies discretionary energy as both absolute energy intake and as "grams of solid fat" and "grams of added sugar" (5). In the DGAI, discretionary energy is represented using the latter approach. The mean percentage of energy allowed from solid fat for the 10 adult USDA food patterns was 8.5%. Because solid fat is included in the saturated fat item in the index, an additional index item was not added to account for discretionary energy from solid fat. The recommended "grams of added sugar" as discretionary energy is intended to include sugars added to foods and beverages by individuals or during processing. For the 10 USDA food guide energy levels, the percentage of energy allowed from added sugar ranges from 3 to 12% with a mean of 7.0%. For the DGAI, the level of 5% of total energy from "added sugar" was selected to assess discretionary energy intake. Information from NHANES III and CSFII (11,19) indicates that few individuals consume less than 5% of total energy from added sugar; therefore, a partial credit of 0.5 points was awarded to anyone who consumed <8.5%, the 50th percentile from NHANES III, but >5.0%.
There are foods that do not clearly fall into any of the USDA food guide groups (e.g., many snack and dessert items like cakes, cookies, brownies, hard candy, etc.). These foods contribute to total energy and macronutrient information, but do not contribute to any food group. Their consumption is included in the calculation of the discretionary energy items and all of the healthy choice items (6).
Healthy choice recommendations. There are 9 DGAI items to assess healthy choice nutrient-based recommendations that are not dependent on estimated energy needs: percentage of grains that are whole grain, fiber intake, 5 recommendations related to fat and cholesterol intake including low-fat milk and meat choices, sodium intake, and alcohol consumption. For each of the above items there were either 2 or 3 choices, described below for each item. In general, an intermediate category that gave a partial score to those not meeting the recommendations was included and was based on intake distributions from nationally representative samples. If the majority of Americans met the recommendation (as indicated by the 50% percentile being lower than the recommendation), an intermediate category for that particular item was not included.
One item addresses the percentage of total grain consumed as whole grain. Whole-grain foods were identified from the foods listed in the DGA report and on MyPyramid.gov, and from previous studies done using the Harvard FFQ (5,6,14,24). The percentage of total grains consumed in the form of whole grains was determined by dividing servings of whole-grain foods by all grain-based foods. This denominator included many snack and dessert items, like cakes, cookies, and brownies that were not counted as "grain" servings under the food intake recommendations (6,24). One point is assigned for consuming 50% of grains as whole grains, thus meeting the whole-grain recommendation. Most Americans fail to meet this recommendation (25), so an intermediate score of 0.5 is given for consuming at least 10% of total grains as whole grains but <50%, based on the distribution of whole-grain intake in the CSFII (25), and 0 was given for consuming <10% of total grains as whole grains.
The fiber recommendation is represented by one index item. A score of 1 is given for meeting the recommendation of consuming 14 g of fiber/1000 kcal (4.184 MJ). A score of 0.5 is given for consuming 9 g, but <14 g of fiber/1000 kcal based on the NHANES III 50th percentile for fiber intake (21). A score of 0 is awarded for consuming <9 g fiber/1000 kcal.
Fat intake is recommended to be <35% of total energy to avoid increased risk of major chronic disease but at least 20% of total energy to meet the minimum needs for essential fats and fat-soluble vitamins (5,21). Information from the CSFII (1994–96) indicates that only a small percentage of the population failed to meet the recommended range of total energy from total fat (21). Thus, the total-fat index item is a dichotomous variable with a score of 1 for meeting the recommendation and a score of 0 for consuming less than the recommended minimum 20% or greater than the maximum value of 35%. The DGA recommends <10% of total energy from saturated fat. Only a small proportion of the U.S. population meets this recommendation. The 50th percentile intake from the CSFII is 12% of total energy from saturated fat. Therefore, those who consume <12% but more than the recommended 10% receive an intermediate score of 0.5, and those who consume <10% receive 1.0 points, whereas those who consume >12% receive 0 points.
The DGA recommends keeping trans fat fatty acid consumption as low as possible. The qualitative nature of this key recommendation does not provide numeric criteria for meeting this recommendation. However, the Institute of Medicine concluded that "diets can be planned that provide <1% of energy from trans fatty acids, provided that the only sources of trans fatty acids are naturally occurring (i.e., in meat and dairy products)" (26). Thus this quantitative recommendation was used for the trans fat index item. No partial credit is given for higher intakes of trans fat, as there are few published population data on which to base an intermediate cutoff value.
The DGA recommendation is <300 mg of cholesterol/d. Because 50% of Americans meet this recommendation based on the CSFII (21), this is assessed in the index as a dichotomous variable, with those who achieve this intake receiving a full score of 1, whereas those who do not receive a score of 0.
As noted above, all high- and low-fat meat, milk, and milk products count toward the total recommended servings of these items. A second index item addresses the recommendation that states "when selecting and preparing meat, poultry, dry beans, and milk or milk products, make choices that are lean, low-fat, or fat-free" (5). Foods were identified as "lean" and "low-fat" based on the DGA (5). We quantified the recommendation by defining 75% to designate "most choices" were lean and 50–74% to designate the "majority of choices" were lean. The scoring of this item is based on separate scores for meat and milk products. A maximum of 0.5 points is given for the individual meat or milk score when 75% of choices (i.e., most choices) met the lean and low-fat criteria. Those who consumed 50% of their choices (i.e., majority of the choices) from low-fat and lean choices, but did not meet the 75% cutoff, receive a score of 0.25 for lean meat and 0.25 for low-fat milk. Zero points were given for those who consumed <50% of their choices as low fat or lean. Summing the individual meat and milk scores allows for a maximum of 1 point on this index item for those meeting the 75% criteria for both meat and milk products.
The DGA key recommendation for sodium recommends consuming <2300 mg sodium/d. Based on the NHANES III data, the intake of the U.S. population is much higher than the recommendation (27). For the purposes of the present study, 1 point was given for those with reported sodium intakes below the DGA recommendation of 2300 mg/d, which was higher than the median intake in the Framingham Offspring Cohort using the Harvard FFQ. Zero points were awarded to those exceeding the recommended intake.
The DGA key recommendation for alcohol consumption provides cutoff points of 2 drinks/d for men and 1 drink/d for women. The index item for alcohol consumption was dichotomous insofar as there was conflicting evidence as to the amount of alcohol that exhibits a positive effect on major chronic disease risk (28). Zero points were awarded for exceeding this recommendation, and 1 point was awarded for consuming equal to or less than the recommendation.
Participants. We applied the DGAI to dietary data from the Framingham Heart Study (FHS) Offspring Cohort using the 1988 Harvard FFQ (22,23). The Framingham Offspring Study is a longitudinal community-based study of cardiovascular disease that began in 1971 among 5124 adult offspring (and the offspring's spouses) of the original Framingham Heart Study Cohort participants (29). The offspring cohort undergoes repeat examination approximately every 3–4 y. During the 5th examination cycle (1991–1995), a total of 3799 participants were examined. Usable FFQ data were available for 3418 offspring participants. The participants missing the covariates (height, weight, age, gender, or physical activity score) necessary to determine which food pattern was appropriate for them were excluded (n = 95), leaving 3323 participants available for analysis. The procedures and protocols for this study were approved by the Institutional Review Boards for Human Research at Boston Medical Center and Tufts-New England Medical Center.
Dietary assessment.
Dietary intake was assessed using the semiquantitative FFQ (1988-GP version) developed by Willett et al. (22,23). The questionnaires were mailed to the participants before the examination and the participants were asked to bring the completed questionnaires with them to their appointment. The FFQ consisted of 126 items, including a list of foods with a standard serving size and a selection of 9 frequency categories ranging from never or <1 serving/mo to 6 servings/d. Participants were asked to report their frequency of consumption for each food item during the last year. Questions concerning the use of vitamin and mineral supplements, type of breakfast cereal most commonly consumed, and write-in questions for foods often consumed that were not listed on the FFQ were also included. Dietary information was judged as unreliable and excluded from further analysis if reported energy intakes were <600 kcal/d (2.51 MJ/d) or >4000 kcal/d (16.74 MJ/d) for women and >4200 kcal/d (17.57 MJ/d) for men, or if 12 food items were left blank (n = 381). Dietary intake data were usable by these criteria for 90% of the total population included in the study. Participants who met the energy intake criteria, and had <12 blank items, were included in analyses and were considered to be nonconsumers of the blank items.
Statistical analyses. The DGAI scores were normally distributed. DGAI scores were used as a continuous measure and were also divided into approximate quintile categories for analyses. Analysis of covariance was used to compare demographic and health variables across DGAI score quintile categories, with adjustment for age and gender. Analysis of covariance also was used to examine the associations between DGAI scores in quintile categories and intakes of selected nutrients from food only (excluding intake from supplements) while adjusting for energy intake, age, and gender.
The P-value for trends across the range of DGAI scores was determined using the DGAI score in its continuous form. It represented the P-value associated with the linear regression coefficient for the DGAI score for continuous dependent variables and the logistic regression coefficient for the DGAI score for dichotomous dependent variables.
Spearman rank correlation coefficients were used to examine the associations between the total DGAI score, the food intake and healthy choice subscores, and the individual index items.
To examine the sensitivity of the DGAI to decisions made in its development regarding the overconsumption penalty and the discretionary energy item, we made modifications to the index by removing or changing these features. We then compared the original and modified index scores with Spearman rank correlation coefficients to determine whether the original index was sensitive to the modification based on a change in the rank order of the index scores.
SAS statistical software (version 9.1) was used for all analyses. Unless otherwise noted, statistical significance was defined as P < 0.05.
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Results |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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The impact of the overconsumption penalty on the index, both overconsumption of individual energy-dense food items as well as discretionary energy, was examined. When the index was modified to give full credit to those who consumed equal to or greater than the recommended amount of each of the food groups, the correlation between this modified index (with the overconsumption penalty removed) and the original index was 0.99. The impact of adding a penalty for overconsumption of the food groups that did not receive a penalty in the original index (fruits, orange, dark green and other vegetables, and legumes) was examined and the rank correlation between this modified index and the original index was 0.96. Finally, when the discretionary energy intake item (percentage of energy from added sugar) was removed, the correlation between the index with and without the discretionary energy item was 0.99.
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Discussion |
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TOPABSTRACTIntroductionMaterials and MethodsResultsDiscussionLITERATURE CITED |
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The most unique features of the DGAI relative to earlier DGA indices and measures of diet quality include: 1) the update to assess each of the 5 vegetable groups separately, 2) a penalty for overconsumption of certain food groups, and 3) the assessment of discretionary energy. The greater emphasis that the 2005 DGA places on limiting energy-dense foods and the observation that the HEI developed for the 1990 DGA tends to be positively correlated with energy intake led us to design this new index so that individuals who consume greater amounts of food could not achieve a higher score simply as a consequence of a higher energy intake (8,11). In addition, the use of sugar to capture discretionary energy intake is also an energy-dependent penalty associated with the consumption of foods not included in the USDA food patterns.
However, our comparison of the index with and without the energy-dependent penalties suggests that these explicit penalties may not affect the overall ranking of individuals and therefore may not be a critical component of the DGAI. We have, nevertheless, maintained these penalties related to overconsumption in the index because the emphasis on energy density is integral to any measure of adherence with the 2005 DGA. The failure to see an effect of the overconsumption penalty was not because individuals were not exceeding the recommended intakes. In fact, 38% of the study participants exceeded the meat recommendation and 27% exceeded the starchy vegetable recommendation. Only 7 and 2%, respectively, exceeded the grain and dairy recommendations. There are 2 reasons that removal of the energy-dependent items may not have affected the overall ranking of our participants. First, individuals who adhere to one DGA key recommendation are more likely to adhere to others. Second, each item makes only a small contribution to the overall index score. Additional analyses (not presented) to determine the effects of the addition or removal of other individual components of the index on the overall score also were not reflected in the overall index ranking. However, when we gave individual index items a greater weight relative to the other index items, the exclusion of the weighted item did affect the ranking of index scores. These observations suggest that the insensitivity of the individual items does not reflect their inability to assess the specific recommendation, but rather the small contribution of each item to the overall score. Thus, as intended by the DGA, the DGAI reflects the sum of many healthy dietary practices, and adherence to many key recommendations leads to a healthy diet and a high score on the DGAI.
We designed the DGAI to assess only the key dietary recommendations of the 2005 DGA. Among the key recommendations not included in the index are those related to physical activity and weight management. The relation between disease and both body weight and physical activity is well established. Harnack et al. (9) demonstrated that weight and physical activity were responsible for associations between cancer risk and an index developed for the 2000 version of the DGA that included body weight and physical activity measures in the index. Our intent was to design an index that focused on the potential benefits of a healthy diet to ascertain whether the current dietary recommendations might, after accounting for physical activity and body weight, affect the risk of major chronic disease. Thus, rather than include these factors in the index, we suggest that they be adjusted for in analyses using the DGAI to lessen the possibility that adherence to the dietary recommendations of the DGA would be confounded by physical activity or weight.
There are potential limitations associated with the index and the method of dietary assessment used in the present analysis. First, we lacked a "gold standard" for the 2005 DGA against which we could evaluate or calibrate a new instrument. Thus, it is important as a first step to assess the "face" validity of the DGAI. Face validity is the ability of an instrument to relate with factors in ways that one would expect based on prior experience (30). When new methods are developed, face validity is often used as an initial step in assessing a tool's validity (31,32). The DGAI does demonstrate face validity. We have shown that the DGAI score relates as expected to many participant characteristics and to nutrient intake. For example, one would expect that women, older individuals, nonsmokers, leaner individuals, and vitamin supplement users consume a higher-quality diet, as seen with the DGAI. Again, we observed that the DGAI score is positively associated with intakes of most micronutrients and macronutrients in ways that one would expect. These results are consistent with the finding of previous studies using other indices. Higher HEI and Harnack scores were related to both positive lifestyle choices and healthier micro- and macronutrient intake (9,14–18). The USDA Center for Nutrition Policy and Promotion is in the process of revising and updating the original HEI to reflect the changes in the 2005 DGA (33). Strong correlations between the DGAI and the revised HEI, 2 independently constructed indices of diet quality and consistency of dietary intake with the 2005 DGA, would provide further support for the validity of both of these instruments.
A second possible limitation is that some of the index items are correlated, which can result in some recommendations contributing greater weight to the overall index score (34). For example, we see moderate correlations between the fat items and between the variety item and some of the vegetable items. Although an ideal index may have items that are not correlated, we tried to adhere as closely as possible to the DGA key recommendations, and this overlap in dietary behaviors is inherent in the DGA.
A third potential limitation is the categorization of food and nutrient intake into dichotomies of "met" or "did not meet" the recommendations (35). Such categorization can conceal the true variability in the intake data and diminish the range of scores. In an attempt to balance simplicity and measured variability, we included a third score category to many of our index items.
A fourth potential limitation of diet quality indices, such as the DGAI, is the fact they do not necessarily represent optimum dietary patterns (36). Although we certainly agree that this may limit our ability to see associations with health outcomes, in the case of DGA indices, such as the DGAI and HEI, any such limitation would arise largely from the DGA. Examining these limitations of the DGA is one major purpose for the development of diet quality indices.
A fifth limitation of this study is the application of the DGAI to retrospective data. Such an application is not a true test of "compliance" or "adherence" to the 2005 DGA insofar as these guidelines were not released until after our data were collected. This study assessed the association of a diet consistent with the recommendations in the current version of the DGA. Whether the DGAI will perform in a similar manner in populations attempting to adhere to the 2005 DGA, remains to be demonstrated.
Finally, the dietary assessment method used to examine the DGAI was a semiquantitative FFQ, which is limited in its ability to accurately classify energy intake. Thus, there may be some residual confounding associated with energy intake when the index is used in conjunction with dietary data from an FFQ. The inability of the FFQ to measure energy intake has cast doubt on the overall validity of this method (37). However, there is also ample evidence on the validity of the Harvard FFQ for assessing food and nutrient intake relative to long-term diet records. Salvini et al. (38) compared food intake from 7-d diet records collected 4 times over a 1-y period and the Harvard FFQ administered at the end of the year. Median Pearson correlations between the 2 methods were 0.63 for fruits and vegetables, 0.58 for meats, fish, and eggs, 0.78 for dairy products, and 0.79 for breads. A second validation study using similar methods reported correlations between methods of 0.67 for total fat intake, 0.75 for saturated fat intake, 0.76 for cholesterol intake, 0.68 for dietary fiber, and 0.60 for sodium (23). McCullough et al. (15) also adapted the original HEI for use with the Harvard FFQ and were able to show that it correlated well with the HEI calculated from food record data (Pearson correlation coefficient = 0.72) . These studies demonstrated the relative validity of the information from the FFQ used in determining food intake and healthy choice items and the ability of an index of this nature to capture this information.
Current knowledge regarding diet and chronic-disease risk suggests that use of the 2005 DGA is a well-researched and reasonable approach to reducing the chronic disease burden among Americans. However, there is limited information concerning adherence to prior versions of the DGA as they relate to the risk of chronic disease. Tools such as the DGAI will be useful in the critical assessment of the 2005 DGA.
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FOOTNOTES |
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2 Supplemental Table 1 is available with the online posting of this paper at jn.nutrition.org.
9 Abbreviations used: CSFII, Continuing Survey of Food Intake by Individuals; DGA, Dietary Guidelines for Americans; DGAI, Dietary Guidelines Adherence Index; EER, Estimated Energy Requirement; HEI, Healthy Eating Index.
Manuscript received 2 May 2006. Initial review completed 19 June 2006. Revision accepted 26 August 2006.
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