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Dietary Diversity within Food Groups: An Indicator of Specific Nutrient Adequacy in Tehranian Women

Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, Tehran, IRAN

Address reprint requests to: Fereidoun Azizi, MD, Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, P.O. Box: 19395-4763, Tehran, I. R., IRAN. E-mail: Azizi{at}erc.ac.ir

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Objective: To determine the relationship between dietary diversity within food groups and dietary diversity score and the probability of nutrient adequacy in Tehranian women.

Design: Cross-sectional study assessing food intake by two 24-hour recalls questionnaires on two different occasions. Dietary diversity was defined according to diet quality index revised. The mean probability of adequacy across 14 nutrients was calculated using the Dietary Reference Intakes.

Setting: District 13 of Tehran, Iran.

Subjects: 286 females aged 18–80 years.

Results: Whole grain diversity score mostly correlated with protein and vitamin B₂ (r = 0.35, p < 0.05). Fruit diversity score was correlated with vitamin C (r = 0.44, p < 0.05). Dairy diversity score was correlated with calcium intake (r = 0.54, p < 0.05). Meat diversity score was correlated with protein intake (r = 0.34, p < 0.05). Most subjects failed to meet vitamin B₆, zinc, magnesium, calcium, copper, and vitamin B₁₂ adequacy. Energy intake was a strong predictor of the mean probability of adequacy in models controlled for age, BMI, education level and job status (model R² = 0.53). Adding the number of servings from each of the food group to the models significantly improved the model fit (model R² = 0.59). Adding the dietary diversity score improved the model fit significantly (model R² = 0.64). Dairy diversity score had the strongest association with improved nutrient adequacy.

Conclusion: Dietary diversity score is a useful indicator of specific nutrient adequacy in Tehranian women. However, to determine the adequacy of a specific nutrient, the diversity scores of specific food groups might be taken into account.

Key words: nutrient adequacy, diversity score, food group, Dietary Reference Intakes

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Nutrition scientists generally believe that healthy diets are the ones with most diverse diets. The nutrients essential for meeting nutritional requirements are not all usually found in a single food item; they are however present in a diet composed of a number of foods [1]. Diverse diets have been shown to protect against chronic diseases [2]. US dietary guidelines recommend using a variety of grains especially whole grains and a variety of fruits and vegetables. It is shown that dietary variety is associated with higher energy intake [3] as well as overweight and obesity [4], it therefore, seems that the new recommendation advocates consumption of a diverse diet while staying within energy needs. It is suggested that consumption of a varied diet reduces the risk of developing a deficiency or excess of any one nutrient [5]; it may therefore, somehow be associated to the dietary nutrient quality. The tendency of evaluating total diet quality is increased [6]. Assessing the probability of nutrient adequacy adds value to the food and nutrition monitoring systems in developing countries, where energy intake is the most important indicator of food security [7]. In developing countries, methods for evaluating nutrient adequacy should be simple and practical [8]. Hatloy et al showed that the food diversity scores could give a fairly good assessment of the nutritional adequacy of the diet [9]. Other researchers have also indicated that dietary diversity is a useful indicator of nutrient adequacy in adolescents or in adults. [8,10–13]. We suspect that many Tehranian women have inadequate intake of some nutrients. If dietary diversity after adjusting for the effect of energy could be correlated with the probability of nutrient adequacy, increasing the dietary diversity within the context of a diet that maintains the appropriate energy balance would be a good recommendation for this population. Besides the dietary diversity, the diversity score of food groups also is important. Because it is vital to determine that which food group variety is related to the adequacy of nutrients. However the diverse diet may have higher amounts of fat, sweets and refined grain which may be harmful to overall health. Although, researchers have also indicated that dietary diversity is a useful indicator of nutrient adequacy whether in adolescents or in adults [3,8–13], there is very little evidence to support a similar role for each group of diversity. It is not clear whether the variety of within food groups, independently, contribute to the adequacy of specific nutrients.

Availability of nutrient distributions allows the calculation of probability values for nutrient adequacy, which are more physiologically meaningful than ratios of intakes to the RDA [3]. Therefore, the purpose of this study was to determine the relationship between both the dietary diversity score and diversity within food groups consumed and the probability of nutrient adequacy in Tehranian women.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Subjects
This study has been conducted within the framework of Tehran Lipid and Glucose Study (TLGS), a prospective study performed on residents of district 13 of Tehran, with the aim of determining the prevalence of non-communicable disease-risk factors and developing strategies to promote healthy lifestyles to improve these risk factors [14].

In the TLGS, 15005 people, aged 3 years and over, were selected by multistage cluster random sampling method. We randomly chose 1476 people, aged 3 years and over for nutritional surveys. 862 subjects, aged 18–80 years, were randomly selected for dietary assessment. Subjects with a prior history of cardiovascular disease, diabetes and stroke (23 subjects) were excluded because of possible changes in diet. We also excluded under and overreporters as we consider those under and above the cut-off points as under or overreporters. So subjects whose reported daily energy intakes were not between 800 kcal/d (3347 KJ/d) and 4200 kcal/d (17537 KJ/d) [15], were excluded (11 subjects). Of the 828 subjects, 581 subjects (286 women and 295 men) had all the relevant data on nutrient adequacy and diversity score. After excluding the men, 286 females were included in our study. The proposal of this study was approved by the ethical committee of endocrine research center of Shaheed Beheshti University of Medical Sciences, and informed written consent was obtained from all subjects.

Dietary Assessment
Dietary intake assessment was undertaken with two 24-hour recalls on two different occasions by expert dietitians, with at least five years of experience in the nationwide food consumption survey project [16]. 24-hour recalls were collected from all 286 subjects. There were two separate 24-hour recalls, spaced approximately 10 days apart. These two days, selected randomly, were both weekdays. The recall method is useful for estimating intakes in culturally diverse populations, such as Tehran, representing a wide range of foods and eating habits. The 24-hour recall is based on actual intake and may be used to estimate absolute rather than relative intake [17]. The 24-hour recall method is susceptible to recall bias, both for identification of foods eaten and for quantification of portion sizes. Collecting dietary data by highly trained interviewers in this study reduces this type of error. Although recalling two days cannot cover all day-to-day variations in dietary intake, using non-consecutive days enhances the coverage [18]. The 24-hour dietary recall describes reported intakes from midnight to midnight, meal after meal. As most of the woman cooked meals themselves they had a very good ability to remember foods and estimate portion size. The first recall was performed at subjects’ homes and the second during a clinic visit at the diet unit of TLGS. Individuals were questioned as to whether the day of recalls was a usual day or not; these two day recalls hence showed the usual intake of subjects. Standard reference tables were used to convert household portions to grams for computerization [19]. After coding the diaries, the dietary recall form was linked to a nutrient database (Nutritionist III) and nutrient intakes calculated using the Mosby Nutritract Software for conversion of quantity to serving of food consumed. For mixed dishes, food groups were calculated according to their ingredients. The data related to Nutritionist III was modified according to the Iranian Food Composition Table.

Dietary Diversity Score
To score dietary diversity, five groups of bread-grains, vegetables, fruits, meats, their substitutions and dairy foods, according to the USDA’S Food Guide Pyramid were used [20]. The main groups mentioned were divided into 23 subgroups according to Haines et al [21]. These categories show the dietary diversity across the main groups. We expanded the number of bread-grain group categories into seven groups (refined bread, biscuits, macaroni, whole bread, corn flakes, rice, and refined flour) to reflect the diversity and importance of plant-based foods. Fruit was divided into 2 subgroups (fruit and fruit juice, berries and citrus) and vegetables into 7 subgroups (Salad vegetables, potato, tomato, starchy vegetables, legumes, yellow vegetables, green vegetables i.e. mint, basil, tarragon, sweet fennel). Four subgroups of meat (red meat, poultry, fish, egg) and 3 subgroups for dairies (milk, yogurt, cheese) were considered.

To be counted as a "consumer" for any of the food group categories, a respondent needed to consume at least one-half serving of the main group as defined by the Food Pyramid quantity criteria, at any time during the 2-day survey period. It did not need to be eaten all at once. Each of the 5 broad food categories received a maximum diversity score of 2. For calculation the diversity score of each group, we divided the number of subgroups consumed by the total number of subgroups of each main group and then we multiplied this by 2. For example if a person consumed at least one-half serving from 2 of 7 possible bread-grain categories, she would receive a subgroup score of

x 2 = 0.57 and if a person consumed at least one-half serving from 2 of the possible meat categories he or she would receive a subgroup score of

x 2 = 1 [21]. Total score was the sum of the scores of the five main groups.

Probability of Adequacy
The mean probability of adequacy across 14 nutrients was calculated using the Dietary Reference Intakes [22]. The probability of adequacy was calculated according to the requirement distribution, described by Foote et al [3]. If the requirement distribution was normal, it was defined by the EAR (Estimated Average Intake) and its SD (Standard Deviation) [23–26]. By using the "probnorm" function in SAS [27], we calculated the probability of adequacy for 14 nutrients (vitamin A, vitamin B2, vitamin B1, Vitamin C, vitamin B6, vitamin B12, calcium, iron, zinc, phosphorus, magnesium, protein, niacin, copper), for each subject [28]. The resulting value for probability of adequacy ranged by definition, from 0 to 100%. We did not adjust intakes for the effect of day-to-day variation when computing the probability of adequacy for an individual on a single day, however this adjustment was done when estimating the prevalence of inadequacy for usual intakes within a population. The probability of adequacy for calcium was estimated using quartiles of the AI: 0% for calcium intakes < one-fourth AI, 25% for calcium intakes > one-half AI and < three-fourths AI, 75% for calcium intakes > three-fourths AI and < AI, and 100% for calcium intakes above the AI [3].

Anthropometric Data
Weight and height were measured according to standard protocols, as reported earlier [29] and body mass index (BMI) was calculated by dividing weight (kilograms) by the square of height (meter).

Statistical Analysis
Data was analyzed by SPSS (ver 9.05) statistical software program [30] and SAS software (version 8.2) [27]. Energy intake, educational level and job status were considered as control variables in multivariate analyses. Partial correlation adjusted for confounders (energy intake, educational level, job status) was used. Spearman’s correlation coefficient was used to assess the association between the probability of adequacy for each nutrient and the diversity score of each food group with and without adjustment for energy, and for energy plus socioeconomic factors like education and job status. As some variables were not normally distributed, we used Spearman’s correlations. To determine diversity score of which food groups plays the most important role in the probability of adequacy, linear regression in a stepwise model, was used. Base models were initially fit using the following independent variables: age, educational level, BMI, job status and energy intake. The 5 variables for the servings of food groups were included in the model, and then a variable for total dietary diversity score was added. Finally the total diversity score was replaced by each food group diversity score. Changes in R² values were used to assess the improvement in fit at each model-building step. The effect or combined effect of variables in the regression models was examined using contrast statements to compute an adjusted Wald statistic. A significant level of 0.05 was used for all analyses.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Mean and standard deviation of age and BMI was 41 ± 13 year and 27 ± 4 kg/m², respectively. Mean dietary diversity score was 6.01 ± 1.01. The maximum and minimum score of diversity was related to the fruit (1.42 ± 0.50) and bread-grain (0.87 ± 0.28) groups, respectively. Descriptive characteristics of subjects are shown in Table 1. The mean ± SD of total dietary diversity score and diversity scores of food groups are shown in Table 2. The lower mean of the diversity score was related to grain group and the higher one was for the fruit group. Table 3 shows the percentage of people who ate at least servings of food items during the 2 days. A considerable proportion of the women ate at least servings of rice, whole and refined bread, vegetables, tomato, green leaves, and meat during the 2 days. Table 4 shows Intake and probability of adequacy for selected nutrients among subjects. Correlations between the diversity scores of food groups and the probability of nutrient adequacy are shown in Table 5. Grain diversity score was correlated with probability of Vitamin B₂ (r = 0.33, p < 0.05), Protein (r = 0.33, p < 0.05), and carbohydrate adequacy (r = 0.22, p < 0.05). Vegetable diversity score was correlated with vitamin A (r = 0.32, p < 0.05), potassium (r = 0.19, p < 0.05) and vitamin C adequacy (r = 0.44, p < 0.05). Fruit diversity score was associated with the probability of vitamin A (r = 0.32, p < 0.05), vitamin C (r = 0.44, p < 0.05) and potassium (r = 0.39, p < 0.05) adequacy. Dairy diversity score was associated with calcium (r = 0.54, p < 0.05), phosphorus (r = 0.32, p < 0.05), protein (r = 0.34, p < 0.05), vitamin B₂ adequacy (r = 0.44, p < 0.05) and zinc adequacy (r = 0.24, p < 0.05). Meat diversity score was associated with the probability of vitamin B₆ (r = 0.22, p < 0.05), B₁₂ (r = 0.24, p < 0.05), iron (r = 0.24, p < 0.05), phosphorus (r = 0.23, p < 0.05) and protein adequacy (r = 0.34, p < 0.05).

View this table: [in this window] [in a new window]   TABLE 3 Components of Dietary Diversity Score and Percentage of Women Consuming at least Servings of Food Items during 2 Days

View this table: [in this window] [in a new window]   TABLE 5 Adjusted Correlations between the Diversity Scores of Food Groups and the Probability of Nutrient Adequacy* in 286 Women from The Tehran Lipid And Glucose Study (N = 286)

View this table: [in this window] [in a new window]   TABLE 7 Linear Regression Models of Factors Contributing to the Mean Probability of Adequacy for Subjects from Tehran Lipid and Glucose Study (N = 295) *

	DISCUSSION

The results of the present study showed a positive significant correlation between the diversity score of grains and protein, calcium and vitamin B₂ intake. Grain had the minimum diversity score. This may be due to culture, dietary habits and the limited number of bread-grain products such as whole grain cereals, fortified macaroni, and whole grain biscuits in Iran as compared with the developed countries [31]. A previous study showed that the grain group had the lowest diversity score among Iranian adolescents [10] as well as Iranian men (unpublished data). While, Dietary Guidelines for Americans 2000 emphasize the need to select a diet varied in whole grains, fruits and vegetables to improve fiber intake, limit fat intake and obtain nutrients concentrated in whole grains, different fruits and vegetables. Significant positive correlation between diversity score of vegetable and vitamin C and A as well as diversity score of fruit and the vitamins mentioned showed that by increasing the diversity score of fruit and vegetable we could increase the amount of these antioxidant vitamins, and therefore, improve cardiovascular health while preventing cancer as well. Diversity score of dairy products was correlated with the probability of vitamin B₂, protein, zinc, calcium and phosphorus adequacy. Therefore, education for individuals regarding the consumption of low-fat yogurt, milk and cheese is highly recommended to ensure adequate calcium and protein intakes, which play an essential role in bone health [32]. Needless to say, attention must be paid to the percent of fat from dairy and the importance of emphasizing low fat dairy products. [33].

Although there are few studies about the effect of dietary diversity on chronic disease [34,35], the present study has shown that higher diversity score of each food group contributes to adequate amount of nutrients, which may have a favorably association with some chronic diseases such as CVD, cancer and osteoporosis. Of course these correlations have not been shown yet and they need to be studied.

Of course, about the importance of diversity scores of food groups, we should consider that only when all the foods in a food group are good sources of a specific nutrient, increasing the diversity score of each food group, would be associated with increasing that specific nutrient adequacy. But if only few of the foods in a food group are good sources of specific nutrients, there is no association between diversity score of that group and that nutrient adequacy.

It is important to note that dietary diversity score, food group intake, and nutrient adequacy all strongly correlate with energy intake. Indeed, energy intake plus 4 non-dietary variables (age, BMI, education and job status) explained 53% of the variance in the mean probability of nutrient adequacy. After adjusting for energy, the association between varieties of groups with nutrient adequacy became weaker. This association of dietary diversity score with energy can be considered as a reason not to recommend dietary diversity score and only recommend it within the context of a diet that maintains appropriate energy balance. In spite of adjusting for the effect of confounders, the association of dietary diversity score and nutrient adequacy remained. According to the results of linear regression, the diversity score of dairy was the strongest predictors of nutrient adequacy, and contributed most to the dietary quality. Hence it is also practical to use DDS as a tool to predict dietary quality. Dietary diversity score is considered to be practical method and can be used to estimate nutrient adequacy in populations.

There was a positive correlation between energy and DDS as well as the diversity scores of different food groups, which is similar to the results of [10,12] other studies. This result is logical because the Food Guide pyramid is not a pattern for calorie control, but shows nutritional adequacy and balance [35]. Therefore, this may prove to be a limitation for dietary diversity in health promotion. Differences between the results of our study and other studies in this field may be due to different scoring methods. Furthermore the action of many nutrients is dependent on the presence of others and the balance between nutrients in food is important. As evidence on diet and health accumulates, it becomes clearer that although individual nutrients are important, they work most effectively in the context of a complex dietary pattern that includes maintaining balance of nutrients obtained from a diversity of healthful foods.

Limitations of this study include the cross-sectional nature of data collection, and difficulties in choosing a standard method for scoring diversity of food groups; there are different scoring methods in literature, but no standard method of determining dietary diversity score for Tehranian people, which complicates estimations. Cross-sectional studies allow for associations to be illustrated, but not for identification of causal relationships. So, it is better to evaluate the effect of varied diets in longitudinal studies. Of course, for future studies assessment of the varieties of food groups according to the new suggested Food Guide Pyramid of Harvard University and its relation to diet quality is recommended.

	CONCLUSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
The findings of this study demonstrate that dietary diversity score is significantly associated with the probability of the specific nutrient adequacy among Tehranian women.

	ACKNOWLEDGMENTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
This work was supported by a grant from Endocrine Research Center (ERC) of Shaheed Beheshti University of Medical Sciences. This research project has been supported by grant No 121 NRCI Research Projects and with the support of National Research Council of Islamic Republic of Iran. We express appreciation to the participants for their enthusiastic cooperation with this study and also the staff of ERC, for their valuable support. We acknowledge the assistance of Dr. LE Torheim from Akershus University College, Lillestrom, Norway, in sending us her valuable PhD thesis and papers in the field of dietary diversity score; this was most helpful.

Received July 6, 2004. Accepted May 31, 2006.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION ACKNOWLEDGMENTS REFERENCES

 

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