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Department of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27516
4To whom correspondence should be addressed. E-mail: popkin{at}unc.edu.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • diet quality • Diet Quality Index-International (DQI-I) • China • United States
The major focus of work in the area of dietary assessment in recent years has been to measure diet quality from diverse perspectives and in a comprehensive manner. Many suggest that a composite measure of diet is a preferred alternative to a single nutrient or food as a measure of diet quality (1,2). Scores for overall diet measures have been associated with plasma biomarkers related to diet (3) and are more strongly associated with disease risk than are single-index measures (4).
Several such overall diet measures have been developed, including the Diet Quality Index (DQI),4 the Healthy Eating Index (HEI) and the Institute of Nutrition and Food Hygiene-University of North Carolina at Chapel Hill Diet Quality Index (INFH-UNC-CH DQI). The DQI was created due to concerns related to the major, diet-related chronic diseases in the United States (5). In 1999, the DQI was revised to reflect then-current dietary guidelines and to promote other important aspects of a healthy diet (6). The HEI was constructed for monitoring dietary intake and nutrition promotion activities for the U.S. population (7). Similarly, the INFH-UNC-CH DQI was developed for the Chinese population based on the Chinese Food Guide Pagoda and Chinese and/or international dietary reference values (8). All of these instruments were useful in assessing variability within diet and overall dietary quality for individual populations.
Until this study, cross-national comparison of diet quality had rarely been attempted because no index had been developed to enable the comparison. Assessment of diet quality across diverse countries at different stages of the nutrition transition is especially valuable because it would provide information on dietary issues related to that transition. Therefore, this study developed an overall measure of diet quality called the Diet Quality Index-International (DQI-I) that can be used for international comparisons. The DQI-I focuses on concerns related not only to chronic diseases but also to problems of undernutrition, thus providing a global tool for monitoring healthfulness of diet and for exploring aspects of diet quality related to the nutrition transition. This paper demonstrates the construction of the DQI-I and illustrates its use by performing a cross-national comparison of diet quality between China and the United States, countries that differ greatly in economic status and culture.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Subjects for this study came from national in-depth surveys in the 1993 China Health and Nutrition Survey (CHNS) and the 1994–96 U.S. Continuing Survey of Food Intakes by Individuals (CSFII). The CHNS included 
14,000 individuals drawn by a multistage, random cluster process in eight provinces, whose socioeconomic and other related health, nutritional, and demographic factors varied substantially (9). The data collection for the CHNS followed human subject-approval procedures, authorized by the University of North Carolina at Chapel Hill School of Public Health and the Chinese Academy of Preventive Medicine Human Subjects Protection Committees. For the CSFII, >16,000 individuals were drawn by a complex, multistage, area probability sample design, thus constituting a national probability sample of the U.S. population. Among the total individuals in each survey, the study included adults 
20 y old who provided dietary data and who were not pregnant or lactating. This resulted in a sample size of 8352 from the CHNS and 9768 from the CSFII.
In the CHNS, dietary data were collected on three consecutive days by trained nutritionists using the 24-h recall method, during which detailed household food consumption was also assessed. Survey days were randomly allocated from Monday to Sunday and were almost equally balanced across the 7 d of the week for each sampling unit. Household food consumption was determined by examining changes in inventory from the beginning to the end of each day, in combination with a weighing and measurement technique (9). Dietary intake data were converted into nutrient values using the 1991 Food Composition Table (10).
In the CSFII, subjects were asked to provide information on food intake for 2 nonconsecutive days using a 24-h recall method administered in-person, spaced 3–10 d apart but not on the same day of the week. Telephone interviews were conducted with 5% of the households whose second in-person recall could not be administered.
Dietary data were available for 99% (n = 8269) of the CHNS sample for all three days, and 94.4% (n = 9218) of the CSFII sample for both days. More details of the surveys related to the methods of sampling and data collection appear elsewhere (9,11,12).
Construction of the DQI-I
Overall structure and scoring system. The DQI-I focuses on four major aspects of a high-quality, healthy diet, i.e., variety, adequacy, moderation and overall balance, covering nutritional concerns of both developed and developing countries. Food intake patterns are likely to be more heterogeneous globally than nutrient intake patterns. Therefore, the DQI-I incorporates both nutrient and food perspectives of the diet in the assessment, providing a means with which to better describe the diversity of consumption from country to country.
Current worldwide and individual national dietary guidelines (13,14), the Food Pyramid Guide (15) and several other dietary indices [e.g., (5–8)] provided a basic rationale for the construction of the DQI-I, including the scoring system and the selection of the components. Dietary guidelines almost universally list consumption of a variety of foods as the number one recommendation. They also stress an adequate intake of key foods and nutrients such as fruits and vegetables, complex carbohydrates and protein from various sources. In recognition that overnutrition has replaced undernutrition as one of the major nutrition problems of current generations, the guidelines also encourage moderation, especially in intakes of fat, saturated fat, cholesterol, sodium and sugar. Overall balance is important to ensure that each element of the diet is well integrated in terms of proportionality. These four aspects of a healthy diet comprise the four main categories of the DQI-I. Under each of these categories, there are specific components of diet to be assessed. These distinctive categories help users to readily identify aspects of the diet that most need improvement. In some of the other diet indices, the adequacy and moderation components were combined into one component, making it impossible to determine whether a low diet quality score was due to deficit or excess in the diet.
Scores for each component are summarized in each of the four main categories, and the scores for all four categories are summed, resulting in the total DQI-I score, ranging from 0 to 100 (0 being the poorest and 100 being the highest possible score).
The four major categories
Variety. Variety in the diet is evaluated in two ways, i.e., overall variety and variety within protein sources, to assess whether intake comes from diverse sources both across and within food groups. Inclusion of at least one serving of food per day from each of the five food groups (meat/poultry/fish/egg, dairy/beans, grains, fruits, and vegetables) defines the maximum overall variety score. If intake of any of these food groups is missing, the score is reduced from the perfect score of 15 by 3 points each per food group (Table 1). Beans and dairy are combined into the same food group in the DQI-I, particularly for its intended use in cross-national comparisons. Because beans are one of the major sources of calcium in many developing countries in Asia and other regions, intake of dairy foods alone would considerably underrepresent true intakes of calcium-rich foods in developing countries.
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3 different sources of protein per day, the highest score of 5 points is given. When the number of different sources decreases to 2, 1 and 0, the scores are also decreased as 3, 1 and 0 points, respectively.
Adequacy.
This category evaluates the intake of dietary elements that must be supplied sufficiently to guarantee a healthy diet, as a precaution against undernutrition. The scores for the eight components in the category are assigned on the basis of the percentage attainment of the recommended intakes on a continuous scale, which ranges from 0 points for 0% to 5 points for 100%, with a cap at 5 points. The recommended intake of fruits, vegetables, grains and fiber is dependent on energy intake. A diet that contains 2 to 4 servings of fruits and 3 to 5 servings of vegetables, depending on three levels of energy intake [7118 kJ (1700 kcal), 9211 kJ (2200 kcal) and 11304 kJ (2700 kcal)] is given the highest score of 5 points. Daily intakes of 6, 9 and 11 servings from the grain group and >20, 25 and 30 g of fiber for the three energy intake categories, respectively, meet the criteria for the highest score for the grain and fiber components. Intake of protein is considered adequate when the proportion of total energy intake that comes from protein is >10%. The level of intake that defines the highest score for adequacy of iron, calcium and vitamin C is derived from the Dietary Reference Intakes (DRI), which vary by age and gender.
Moderation. Moderation evaluates intake of food and nutrients that are related to chronic diseases and that may need restriction. Certain levels of total fat, saturated fat, cholesterol and sodium are necessary for the body to function normally, but when taken in excess may contribute to the onset of chronic diseases (16). The intake levels of these nutrients are categorized into three tiers, according to degree of effect on health. Those in the lowest tier include intakes below which a healthy person would show no evidence of harmful effect. Excess intake of those in the highest tier may be related to chronic health outcomes. The middle tier covers intakes between the lowest and highest tiers. The lowest intake category is given the highest score of 6 points, the highest intake category the lowest score of 0, and the middle tier a score of 3 points.
To emphasize the importance of moderation in fat intake, total fat intake in the DQI-I is evaluated using more stringent cut-off values than those found in other dietary indices. When energy from total fat is 
20% of total energy intake, the highest score is given; when >30%, the lowest score is given. Caution for intake of saturated fat is also evaluated on the basis of percentage of energy from saturated fat. Intakes of cholesterol and sodium are examined on the basis of the level of the intakes (see Table 1).
One of the unique components included in the DQI-I is the evaluation of intake of foods that are low in nutrient density, the so-called "empty calorie foods." This component assesses how much a person’s energy supply is dependent on low nutrient density foods, which provide only energy but insufficient nutrients. Foods such as table sugar, oil and alcohol are examples of empty calorie foods. The concept of nutrient density, the ratio of nutrients to energy in a certain amount of food consumed compared with the recommended levels, is used to define the empty calorie foods. For example, the vitamin C nutrient density of 100 g of apple consumed by a 20-y-old woman is 2.83. This figure was calculated using the following equation: (5.7 mg/75 mg)/(247 kJ/9211 kJ), where 5.7 mg and 247 kJ are the actual levels of vitamin C and energy in the apple, respectively, and 75 mg and 9211 kj are the recommended levels of vitamin C and energy intake for the individual, respectively. When the ratio for a nutrient is >1, the food intake is higher for the nutrient compared with its energy content, implying a higher quality diet. As illustrated in the example above, the nutrient density of food can be calculated for nutrients, given both the nutrient and energy contents of the food, and the recommended nutrient and energy intakes for the individual. In the DQI-I, if the sum of nutrient densities across nutrients examined in a food is <1, the food is considered to be an empty calorie food. When energy supplied by empty calorie foods is >10% of total energy intake per day, the lowest score is assigned.
Overall balance. The final category examines overall balance of diet in terms of proportionality in energy sources and fatty acid composition. Consistent findings in the literature emphasize the importance of balance among the energy-yielding macronutrients in terms of contribution to total energy intake (17). Recommendations vary slightly for the proportion of energy derived from each of the macronutrients. In this study, widely accepted general guidelines (13) were chosen as the desirable ranges for the proportions of energy from carbohydrates, protein and fat.
For fatty acids, a similar set of recommendations is available. Increased intake of saturated fatty acids (SFA) is a risk factor for several chronic diseases, especially cardiovascular diseases, whereas increased intakes of PUFA and monounsaturated fatty acids were found to be protective of these conditions (16). However, excess intake of any of these fatty acids is undesirable, and maintaining a balance among the intakes of these fatty acids is more critical to a healthy diet. Proportionality in energy sources and fatty acid composition each contributes to the total DQI-I by 6 and 4 points, respectively. The detailed cut-off values and corresponding scores are described in Table 1.
Application of the DQI-I to the datasets. The mean of the multiple days of intake data from CHNS and CSFII was used in assessing dietary quality of each country using the DQI-I. Data collection and dietary standards varied slightly in each country, which had to be taken into consideration in the comparison. The following section highlights strategies employed in the cross-national comparison.
In the variety and adequacy categories for some of the components, food group intake was evaluated on the basis of the number of servings consumed compared with the recommendations. To assess these components with comparable serving sizes, we used the U.S. Food Guide Pyramid serving size definitions (18) for both countries. That is, serving size data already available from CSFII were utilized for the United States. For China, the CHNS food intake data were converted into number of servings using the U.S. definitions.
The adequacy of intake for some nutrients was examined on the basis of the percentage attainment of a recommendation. For these nutrients, each country’s own recommended intake levels, the DRI of the United States (19–22) and China (23), were used as a standard. The Chinese DRI were developed following the same steps used to create the U.S. DRI; therefore, they carry the same meaning as those in the United States (personal communication, Dr. Ge, K., Institute of Nutrition and Food Hygiene, Chinese Academy of Preventive Medicine, Beijing, China, 2001). Conceptually, when an individual’s usual intake is at or above the recommended level, the Recommended Dietary Allowance (RDA) in the United States and Recommended Nutrient Intake (RNI) in China, a high level of confidence in the adequacy of the intake is achieved. The index components were intended to assess "adequacy" rather than "inadequacy"; therefore, a perfect score was given to those intakes above the RDA rather than the Estimated Average Intake (EAR). In the DRI, when evidence was insufficient for establishing RDA/RNI for a nutrient, Adequate Intake (AI) was set instead. Therefore, in the United States, RDA was used to evaluate adequacy for iron and vitamin C, and AI for calcium; in China, the RNI was used for vitamin C, and AI for calcium and iron.
For the evaluation of energy from empty calorie food in the moderation category, nutrient density of food was calculated for 15 nutrients in both China and the United States. Due to a difference in availability of recommendations and values from the food composition tables, the nutrients considered in the components differed slightly for each country. For the United States, nutrient density was calculated for protein, vitamin A, thiamin, riboflavin, vitamin B-6, vitamin B-12, niacin, folate, vitamin C, vitamin E, calcium, phosphorus, iron, magnesium and zinc. The same set of nutrients was also measured in China, but potassium, copper and selenium were substituted for vitamin B-6, vitamin B-12 and folate.
Statistical methods.
The scores of the DQI-I and its four main categories were descriptively summarized separately by country. The mean of the scores for China and the United States were compared using a t test. These analyses were performed using SAS statistical software: SAS/STAT Release 8.2 (24). The continuous measure of the total DQI-I scores was categorized into quartiles for further analyses. In the lowest quartile score group, the scores of the four categories were also dichotomized into good and poor categories, using the cut-off point of 60% of full scores. The absolute cut-off point was chosen over one based on distribution in distinguishing good and poor quality diets to provide a standard that was meaningful for comparative purposes rather than a data-driven criterion determined by specific country’s data distribution. To determine trends of the mean intake of nutrients and foods across ordered groups of DQI-I scores, a nonparametric test (nptrend, an extension of the Wilcoxon rank sum test) was conducted (25). A P-value 0.0001 was used to denote significant differences in all analyses. The stringent P-value gave protection for overall level of significance because a large number of comparisons were made.
In both datasets, data were collected from multiple members of the same households. Because the diets of members from the same household were expected to correlate, a Huber correction was used to control for the correlation of dietary intakes. Results were also adjusted for the sampling weights available from the CSFII survey data to make the results representative of the total population of the United States, using a series of survey commands from the Stata statistical software (Stata 7; College Station, TX). The survey commands were also used to control for design effects for CHNS data.
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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The total score of the DQI-I reached 60% of the possible score in both countries, but was slightly higher in China than in the United States (Table 2). The difference in the total DQI-I scores was small; the scores of each component as well as of the four categories of DQI-I, however, varied significantly by country. Compared with the perfect score for each category, the adequacy category was best achieved in China, followed by the moderation and variety categories. In the United States, variety was the strongest quality of diet among the four categories, followed by adequacy. Overall balance was the weakest area in both countries. The United States scored higher in the variety category; China scored higher in the moderation and overall balance categories.
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The total adequacy scores for both countries did not differ; the scores of the subcomponents, however, varied significantly. The most drastic difference between China and the United States was seen in the intakes of the grain and fruit groups. For the grain group intake, <1% in China failed to meet the criteria for the perfect score, compared with >90% in the United States. For the fruit group intake, the United States scored much higher than China; this food group, however, was the weakest component in the adequacy category in both countries. Vegetable intake was high in China, with >80% reaching the goal. In the United States, although 40% achieved the goal for vegetable group intake, 10% had only 0–1 serving of vegetables per day. The majority in both countries (96% in China and 86% in the United States) failed to meet the recommended level of fiber intake. Similarly, only 3% in China and 16% in the United States met the recommendation for calcium. In both countries, adequacy for protein intake was achieved in most of the populations, and adequacy for iron in 70%.
The scores for all of the components in the moderation category, except sodium intake, were far higher in China than in the United States, although even in China the overall mean reached only 60% of the goal. For the total fat intake, 34% in China but only 5.5% in the United States achieved the goal; for saturated fat intake, nearly 60% in China but only 11% in the United States achieved the goal. More than two thirds of the population in both countries met the recommendation for cholesterol intake. For sodium intake, 80% in China and 40% in the United States had the lowest score; >35% in the United States and 5% in China obtained >3% of daily total energy from empty calorie foods.
Last, the goals for the balance among energy-yielding nutrients as well as among fatty acids were very poorly met in both countries. In the United States, failure to meet the recommended proportionality in macronutrient intake was due primarily to the deviation of actual intake from the recommended ranges of intake for fats and carbohydrates. Due to the high intake of saturated fat, the ratio of the intake of PUFA to SFA was <1 in the majority of the U.S. sample, resulting in low scores in the fatty acid ratio balance component also.
To examine problem areas of diet more closely in each country, we looked at the group of individuals in the lowest DQI-I score quartile (Fig. 1). Overall, across all four categories, the United States had higher proportions of poor scores (defined as 60% of the perfect score) in the lowest DQI-I score quartile than did China. In both countries, everyone in the lowest quartile had a poor overall balance score; adequacy was the least problematic area of diet.
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The DQI-I scores were examined in terms of how they reflected variation in the individual components on which the index was based, as well as in terms of differences in nonindex measures of dietary quality. When the mean intakes of food and nutrients were presented by subgroups of the population, the DQI-I scoring successfully captured variability in intakes of the food and nutrients (Table 3). Both countries showed the same trends; therefore, we present only the results from the United States for the interest of the larger audience. In both countries, as the total DQI-I score increased, the scores of the four main categories increased consistently. As the scores of the DQI-I moved from lower to higher levels, desirable intakes (e.g., fruit and vegetable) increased steadily. Conversely, intakes of less desirable nutrients and food (e.g., fat, SFA) gradually declined. Mean intakes of various nutrients that were not incorporated into the index (e.g., riboflavin) also tended to increase as the scores of the DQI-I moved from lower to higher levels.
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Because the DQI-I assessed various aspects of diet with a strict set of standards, especially for the fat components, the mean of the DQI-I score in both countries reached only 60% of the highest possible score. Surprisingly, the overall DQI-I scores did not differ greatly between China and the United States. An investigation into the major categories, however, revealed interesting differences between the countries, reflecting each country’s nutritional status and concerns. Diet is multidimensional, and quite different strengths and weaknesses of the dietary patterns of each country were well conceptualized by the specific major categories of the DQI-I. The higher variety score and the lower moderation score in the United States correspond to what is observed through the stages of the nutrition transition. With economic development comes increased food availability, which leads to greater food security and thus dietary variety and adequacy (26). Overnutrition, which is lack of moderation, is the predominant nutrition problem in the United States. The disparity between availability and prudence in intake appears to cause imbalance in the diet, as shown in the lower overall balance scores in the United States. In China, food security is less well established; therefore, the Chinese diet often lacks variety. Lack of moderation in some dietary components, such as fat, has also become a nutritional concern in China (27). One of the notable findings in the DQI-I evaluation was that the proportion of people with intakes less than the recommended intakes was high for many nutrients in both countries (Table 4). Although the focus in the field of nutrition has shifted in the past several decades from undernutrition to overnutrition, the problem of undernutrition is still very real, even in the United States. The between-country differential for probabilities of inadequacy of B vitamins may be due largely to differences in consumption patterns of fortified food products; in the United States, intake of fortified cereal products and baked goods is extensive, whereas in China, food fortification remains insignificant, particularly at the time the survey was conducted.
The design of the DQI-I to be sensitive to various dietary issues around the world, allowing for greater flexibility in describing the elements of a healthy diet, makes the DQI-I an effective tool for cross-national comparisons in particular. For example, in assessing variety, we used slightly different food groupings to make a careful evaluation of the intake of the food groups according to key nutrient profiles in the setting of an international comparison. In addition, the inclusion of both foods and nutrients in the assessment accommodates diversity of consumption across countries. For instance, the empty calorie food component provides a unique, single measure of moderation of diet at the food level, approximating the concept of the tip of the Food Guide Pyramid (15). The component successfully identifies foods that belong to the tip of the Pyramid, but have been missed in many previous assessments of dietary moderation (e.g., sweets, high fat dressings, soft drinks). The component was especially useful in this cross-national comparison because it captured the consumption of foods that are more culture specific such as strong alcoholic beverages in China and sweets in the United States, without relying on assessment of single nutrient or food item.
The use of country-specific recommendations as a standard in the evaluation of adequacy for some nutrients in the DQI-I is worth addressing. We used country-specific DRI as a standard for each population because each country has used the best scientific knowledge available for its population in making the recommendations (e.g., bioavailability of the nutrients, clinical signs of subpopulation groups whose intake level is known); therefore the country-specific approach provides the best set of guidelines with which to evaluate dietary adequacy in each population. For example, the use of country-specific recommendations was beneficial in dealing with the rather complex issue of bioavailability of iron. Although equations to estimate bioavailable iron have been recommended, recent evidence suggests that the currently recommended equations may not work for every population, and each population would require a different equation to best estimate the bioavailable iron (28). Considering that most countries do not have country-specific equations to estimate iron bioavailability, it is unrealistic to use bioavailable estimates of iron in the evaluation of its adequacy. The RDA for iron in China was set much higher than that of the United States due to lower bioavailability of iron in typical Chinese diets. The use of country-specific recommendations that already took bioavailability into account as a standard of evaluation removes the complex issue of having to estimate bioavailable levels using different equations in each country.
One of the weaknesses of this study is the use of the mean of two or three 24-h recalls as an estimate of usual intake. Variety among the categories of the DQI-I would have been most prone to a misclassification error because a short-term dietary intake was used in the assessment. Also, some important aspects of diet could not be included in the DQI-I due to limited data availability, e.g., trans-fatty acids, whose intake is suggested to be a risk factor for chronic diseases including type 2 diabetes (29) and cardiovascular diseases (30). In addition, insufficient food composition data such as poorly measured fiber contents in the Chinese food composition table may have resulted in considerable underestimation of fiber intake in China. It is unlikely that the actual level of fiber intake was lower in China than in the United States, considering China’s high consumption of food from the vegetable and grain groups.
Regardless of these issues, distinctive characteristics of the diets in China and the United States resulted in clearly different performances in some of the DQI-I components. Although not presented in the results, the scores of the DQI-I differed by income levels (unpublished data, Kim, S., Symons, M. & Popkin, B.M. University of North Carolina, Chapel Hill, 2002) and also seemed to capture well-known regional differences in dietary intake across regions in China. Variety scores of southern provinces were higher than those of northern provinces, which agrees with their typical patterns (personal communication, Dr. S. Du, Chinese Center for Disease Control, Beijing, China, 2003). It is especially meaningful considering the situation in China where regional differences have become smaller due to new technologies in food production, processing and transportation. In addition, the CHNS data were collected in autumn, a period in which food availability differences are minimized because key fruits and vegetables are available in all regions of China. The nutrition problems in these countries are summarized as low intake of fruits and high intake of sodium in China, and the lack of moderation in fat, saturated fat, and empty calorie foods intakes, and therefore an overall imbalance, in the United States. Although food scarcity may still be a problem in some regions in China, this study shows that increase in variety is an important issue in the Chinese diet. In the United States, achieving overall balance through increased consumption of fresh fruits, vegetables and grains as well as moderation in fat intake is desired.
In summary, the DQI-I provides a useful tool for global dietary assessment. The cross-national comparison identifies areas of diet needing improvement in each country and provides a general picture of global nutrition issues related to the nutrition transition. The results offer insights that can be used for developing public health programs to encourage healthy dietary patterns, not only in the countries studied but also in other countries experiencing similar transitions.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Supported in part by the Institute of Nutrition Fellowships for 1999/2000, University of North Carolina, and US National Institutes of Health (NIH) (R01-HD30880 and R01-HD38700).
3 Part of a doctoral dissertation presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Nutrition, School of Public Health, at the University of North Carolina, Chapel Hill, NC.
5 Abbreviations used: AI: Adequate Intake; CHNS: China Health and Nutrition Survey; CSFII: Continuing Survey of Food Intakes by Individuals; DQI: Diet Quality Index; DQI-I: Diet Quality Index-International; DRI: Dietary Reference Intake; EAR: Estimated Average Requirement; HEI: Healthy Eating Index; INFH-UNC-CH DQI: Institute of Nutrition and Food Hygiene-University of North Carolina at Chapel Hill Diet Quality Index; RDA: Recommended Dietary Allowance; RNI: Recommended Nutrient Intake; SFA: saturated fatty acid.
Manuscript received 5 November 2002. Initial review completed 3 December 2002. Revision accepted 1 September 2003.
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LITERATURE CITED |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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1. Kant, A. K. (1996) Indexes of overall diet quality: a review. J. Am. Diet. Assoc. 96:785-791.[Medline]
2. Gerber, M. (2001) The comprehensive approach to diet: a critical review. J. Nutr. 131(suppl. 11):3051S-3055S.
3. Hann, C. S., Rock, C. L., King, I. & Drewnowski, A. (2001) Validation of the Healthy Eating Index with use of plasma biomarkers in a clinical sample of women. Am. J. Clin. Nutr. 74:479-486.
4. Kant, A. K., Schatzkin, A. & Ziegler, R. G. (1995) Dietary diversity and subsequent cause-specific mortality in the NHANES I epidemiologic follow-up study. J. Am. Coll. Nutr. 14:233-238.[Abstract]
5. Patterson, R. E., Haines, P. S. & Popkin, B. M. (1994) Diet Quality Index: Capturing a multidimensional behavior. J. Am. Diet. Assoc. 94:57-64.[Medline]
6. Haines, P. S., Siega-Riz, A. M. & Popkin, B. M. (1999) The Diet Quality Index-Revised: A measurement instrument for populations. J. Am. Diet Assoc. 99:697-704.[Medline]
7. Kennedy, E. T., Ohls, J., Carlson, S. & Fleming, K. (1995) The Healthy Eating Index: design and applications. J. Am. Diet Assoc. 95:1103-1108.[Medline]
8. Stookey, J. D., Wang, Y., Ge, K., Lin, H. & Popkin, B. M. (2000) Measuring diet quality in China: The INFH-UNC-CH Diet Quality Index. Eur. J. Clin. Nutr. 54:811-821.[Medline]
9. The China Health and Nutrition Survey. Carolina Population Center. The University of North Carolina at Chapel Hill http://www.cpc.unc.edu/projects/china/ (accessed November 20, 2001).
10. Institute of Food and Nutrition Hygiene at Chinese Academy of Preventive Medicine (1991) Food Composition Table 1991 People’s Medical Publishing House Beijing, China.
11. Popkin, B. M., Keyou, G., Zhai, F., Guo, X., Ma, H. & Zohoori, N. (1993) The nutrition transition in China: a cross-sectional analysis. Eur. J. Clin. Nutr. 47:333-346.[Medline]
12. Cypel, Y. S. Tippett, K. S. eds. Design and Operation: the Continuing Survey of Food Intakes by Individuals and the Diet and Health Knowledge Survey, 1994–96. NFS Report No. 96-1 1997 U.S. Department of Agriculture, ARS Beltsville, MD. .
13. World Health Organization (1996) Preparation and Use of Food-Based Dietary Guidelines. Report of a Joint FAO/WHO Consultation 1996 Nicosia, Cyprus.
14. Dietary Guidelines from Around the World Food and Nutrition Information Center. U.S. Department of Agriculture http://www.nal.usda.gov/fnic/dga/index.html (accessed July 20, 2001).
15. U.S. Department of Agriculture (1992) The Food Guide Pyramid. Home and Garden Bulletin no. 252 1992 USDA Washington, DC.
16. Weisburger, J. H. (2000) Prevention of cancer and other chronic diseases worldwide based on sound mechanisms. Biofactors 12:73-81.[Medline]
17. Weisburger, J. H. (2000) Eat to live, not live to eat. Nutrition 16:767-773.[Medline]
18. USDA (1994) Food Survey Research Group ARS CSFII 1994: Pyramid Servings 1994 USDA CD-ROM Beltsville, MD .
19. Institute of Medicine, National Academy of Sciences (2001) Dietary Reference Intakes: Applications in Dietary Assessment 2001 National Academy Press Washington, DC.
20. Institute of Medicine, National Academy of Sciences (2001) Dietary Reference Intakes for Vitamin C, Vitamin E, Selenium, and Carotenoids 2001 National Academy Press Washington, DC.
21. Institute of Medicine, National Academy of Sciences (2001) Dietary Reference Intakes for Vitamin A, Vitamin K, Arsenic, Boron, Chromium, Copper, Iodine, Iron, Manganese, Molybdenum, Nickel, Silicon, Vanadium, and Zinc 2001 National Academy Press Washington, DC.
22. Institute of Medicine, National Academy of Sciences (2001) Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D, and Fluoride 2001 National Academy Press Washington, DC.
23. Chinese Nutrition Society (2000) Chinese Dietary Reference Intakes 2000 China Light Industry Publishing House Beijing, China.
24. SAS Institute Inc. (2001) SAS/STAT Software. Version 8.2 2001 SAS Institute Cary, NC.
25. Stata Corporation (2001) Stata Statistical Software: Release 7.0 2001 Stata Corporation College Station, TX.
26. Drewnowski, A. & Popkin, B. M. (1997) The nutrition transition: new trends in the global diet. Nutr. Rev. 55:31-43.[Medline]
27. Du, S., Lu, B., Zhai, F. & Popkin, B. M. (2002) A new stage of the nutrition transition in China. Public Health Nutr. 5(1A):169-174.[Medline]
28. Du, S., Zhai, F., Wang, Y. & Popkin, B. M. (2000) Current methods for estimating dietary iron bioavailability do not work in China. J. Nutr. 130:193-198.
29. Salmeron, J., Hu, F. B., Manson, J. E., Stampfer, M. J., Colditz, G. A., Rimm, E. B. & Willett, W. C. (2001) Dietary fat intake and risk of type 2 diabetes in women. Am. J. Clin. Nutr. 73:1019-1026.
30. Oomen, C. M., Ocke, M. C., Feskens, E. J., van Erp-Baart, M. A., Kok, F. J. & Kromhout, D. (2001) Association between trans-fatty acid intake and 10-year risk of coronary heart disease in the Zutphen Elderly Study: a prospective population-based study. Lancet 357:746-751.[Medline]
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