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Major Dietary Patterns among Female Adolescent Girls of Talaat Intelligent Guidance School, Tabriz, Iran.
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PMID:  22997560     Owner:  NLM     Status:  PubMed-not-MEDLINE    
BACKGROUND: Increasingly nutritional experts express the necessity of research on dietary patterns to identify numerous modifiable risk factors of disease. This study was conducted to identify major dietary patterns among adolescent girls in Talaat intelligent guidance school, Tabriz, Iran.
METHODS: Among 257 adolescent girls aged 11-15 years, usual dietary intakes were assessed using a 162-item semi-quantitative food frequency questionnaire (FFQ). Factor analysis was used to identify major dietary patterns in this Turkish population.
RESULTS: We identified 6 major dietary patterns:(1) Western pattern high in pizza, meats and fruit juice; (2) Sweat junk foods pattern high in dried fruits, jams, honey and sugar; (3) Asian pattern high in legumes, potato and other vegetables; (4) Salty junk foods pattern high in carrot, puffs and potato chips and (6) Iranian traditional dietary pattern high in hydrogenated fats, garlic and broth.
CONCLUSION: Our findings suggested that among the 6 major dietary patterns, Asian-like food was the healthiest one.
M Alizadeh; J Mohtadinia; B Pourghasem-Gargari; A Esmaillzadeh
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Type:  Journal Article     Date:  2012-07-30
Journal Detail:
Title:  Iranian Red Crescent medical journal     Volume:  14     ISSN:  2074-1812     ISO Abbreviation:  Iran Red Crescent Med J     Publication Date:  2012 Jul 
Date Detail:
Created Date:  2012-09-21     Completed Date:  2012-09-24     Revised Date:  2013-05-30    
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Nlm Unique ID:  101319850     Medline TA:  Iran Red Crescent Med J     Country:  United Arab Emirates    
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Languages:  eng     Pagination:  436-41     Citation Subset:  -    
Center for Food Sciences and Nutrition, Department of Nutrition and Biochemistry, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran.
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Journal ID (nlm-ta): Iran Red Crescent Med J
Journal ID (iso-abbrev): Iran Red Crescent Med J
Journal ID (publisher-id): Kowsar
ISSN: 2074-1804
ISSN: 2074-1812
Publisher: Kowsar
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Copyright © 2012, Kowsar Corp.
Received Day: 10 Month: 10 Year: 2011
Accepted Day: 12 Month: 1 Year: 2012
Print publication date: Month: 7 Year: 2012
Electronic publication date: Day: 30 Month: 7 Year: 2012
Volume: 14 Issue: 7
First Page: 436 Last Page: 441
ID: 3438437
PubMed Id: 22997560

Major Dietary Patterns among Female Adolescent Girls of Talaat Intelligent Guidance School, Tabriz, Iran Alternate Title:Dietary patterns among adolescents
M Alizadeh1
J Mohtadinia2
B Pourghasem-Gargari3
A Esmaillzadeh4*
1Center for Food Sciences and Nutrition, Department of Nutrition and Biochemistry, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran
2Department of Food Science and Technology, Tabriz University of Medical Sciences, Tabriz, Iran
3Department of Biochemistry and Dietetics, Nutrition Research Center, School of Health and Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran
4Food Security Research Center, Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
*Correspondence: Ahmad Esmaillzadeh, PhD, Department of Community Nutrition, School of Nutrition and Food Sciences, Isfahan University of Medical Sciences, PO Box: 81745, Isfahan, Iran. Tel.: +98-311-7922720, Fax: +98-311-6682509, E-mail:


The studies in nutritional epidemiology has emphasized on the role of nutrients and foods but the entire effect of foods can only be seen by considering them as dietary patterns.[1] Increasingly, nutritional experts express the necessity of research on dietary patterns to identify numerous modifiable risk factors of food related diseases.[2][3][4]

Most studies have focused on dietary patterns among adults but data on food intake patterns of children and adolescents are scarce. This is particularly relevant for Asian countries, where we are aware of no study to report major dietary patterns among adolescents. Although some data shows similar dietary patterns between adults and adolescents in western population,[5] it remains unknown if this would be the case for adolescents in Asian countries.

Dietary patterns are major determinants of several chronic diseases[6] like obesity,[7] metabolic syndrome,[8] diabetes[9] and cardiovascular diseases.[10] Previous studies have shown that the prevalence of obesity and the metabolic syndrome among Iranian adolescents is as much as that in their counterparts in US.[11] To help prevent the increasing trend of these non-communicable diseases, the first step is to identify major dietary patterns among adolescents. This study was conducted to identify major dietary patterns among adolescent girls in Talaat Intelligent Guidance School in Tabriz, Iran.

Materials and Methods

This cross-sectional study (From April to July 2007) was conducted in Talaat Intelligent Guidance School among 257 adolescent girls (compromising all students in the school) aged 11-15 years. Students of this school came from all districts of Tabriz. The project was approved by the Ethics Committee of the School of Nutrition and Health, Tabriz University of Medical Sciences and informed written consent was obtained from each participant. Usual dietary intakes were assessed by using a validated 162-item semi quantitative food frequency questionnaire (FFQ). Participants were asked to report the frequency of consumption of a given food item during the previous year. The reported frequency for each food item was then converted to a daily intake. Foods from FFQ were classified into 40 food groups (Table 1). Validation study of this FFQ in previous studies had shown that this questionnaire could evaluate long-term dietary intakes reasonably.[12][13]

To identify major dietary patterns, we used principal component analysis, and the factors were rotated by varimax rotation. The natural interpretation of the factors in conjunction with Eigen values>1.5 determined whether a factor should be considered as major dietary patterns. We used SPSS software (version 9.05; SPSS Inc, Chicago IL) for all statistical analyses.


We identified six major dietary patterns by the use of factor analysis (Table 2): "Western-like pattern" that was high in pizza, organ meats, fruit juice, sweats and desserts, high-fat dairy products, poultry, processed meats, fruits, refined grains, low-fat dairy products, pickles and olive. "Sweet junk foods pattern" that was highly loaded with dried fruits, jams and honey, sugars, tea, sweats and desserts, fruit juice, egg, nuts, coffee, fruit and mayonnaise. "Asian-like pattern" greatly loaded with legumes, potato, other vegetables, dough, high-fat dairy products, margarine, refined and whole grains, low-fat dairy products, egg and butter. "Salty junk foods pattern" was high in carrot, puffs, Potato chips, popcorn, crackers, pickles, coffee, tomatoes and mayonnaise. "Low protein- soft drinks-oil pattern" was high in cruciferous vegetables, green leafy vegetables, soft drinks, tomatoes, other vegetables, vegetable oils, mayonnaise and dough and finally "Iranian traditional dietary pattern" was high in hydrogenated fats, garlic, broth, tea, poultry and red meats, respectively. These factors totally explained 39.4% of the variance.


Few data are available about dietary patterns of adolescents. Shin et al.[14] reported 3 major dietary patterns: (1) Korean healthy pattern; (2) Animal foods pattern and (3) Sweats pattern. Korean healthy, animal foods and sweats patterns are similar to Asian-like, western-like and sweat junk foods patterns in our study, respectively. McNaughton et al.[15] identified 3 dietary patterns labeled a fruit, salad, cereals and fish pattern; a high fat and sugar pattern; and a vegetable pattern. Marques et al.[16] identified four distinct dietary patterns: The first pattern was characterized by an energy-dense diet, the second pattern represented a healthy diet, the third pattern represented intake of soft drinks and the fourth pattern represented a diet rich in calories and sugars. Lozada et al.[17] identified 4 major dietary patterns: Pattern 1 had a positive loading factor on wheat products, desserts, and meat; pattern 2 was characterized by a high consumption of low-fat dairy and low-fiber breakfast cereals; pattern 3 had a high loading for sweetened beverages and industrialized foods and pattern 4 had a moderate loading on maize products and legumes. Ritchie et al.[5] showed that healthy pattern was characteristic of high intake of fruits, vegetables, dairy, grains without added fats, mixed dishes and soups, and a low intake of sweetened drinks, other sweets, fried foods, burgers, and pizza. These patterns are different from those obtained in our study. This can be explained by demographic, cultural and racial differences.

Dietary patterns among children and adolescents are not the same across different studies while mostly the same patterns have been reported for adults.[1][8][18][19][20] This might be explained by adult attempts in adhering to a healthy lifestyle, while dietary patterns of adolescents can represent their selection of taste, family economical and cultural status. Western-like dietary pattern explains the most variance (16.6%), while traditional Iranian dietary pattern explains the least variance (3.8%). This finding indicates society transition from traditional to processed and western foods. As mentioned, traditional Iranian dietary pattern has less processed foods, while most of the foods in Western-like dietary pattern are processed foods. Although we can not call traditional Iranian dietary pattern as ideal pattern, in the same way, transition to Western-like pattern is not acceptable, too. Sweat junk foods pattern is the second pattern which explained high variance of the total diet. This pattern contains junk foods instead of main foods. High intakes of dried fruits, egg, nuts and fruits in sweat junk foods pattern represent this message that we can manage nutrition in adolescents with high intake of junk foods and gradually reduce simple sugars and replace them with dried fruits, nuts and fruit. Third pattern is Asian-like pattern which is the healthiest pattern among six patterns we identified. Subjects adhering this pattern were lactoovo-vegetarian with low intakes of meats and meat products. Asian-like pattern was high in carbohydrate and low in animal foods. Adding fruits combined with reducing refined cereals will make this dietary pattern as an ideal healthy dietary pattern. Salty junk foods pattern is the next dietary pattern. Most of foods loaded in this dietary pattern have similar tastes of salty; however adolescents adhering this pattern were eating carrot as much as puffs, chips, popcorn and cracker. Low protein-soft drinks-oil dietary pattern is fifth dietary pattern which is lowest in protein and highest in non-hydrogenated fats. Consumption of this dietary pattern was simultaneously associated with higher intakes of beverages such as soft drinks and dough, salad and mayonnaise. High consumption of vegetables and non-hydrogenated fats represents high consumption of fried vegetables such as squash, eggplant, celery, onion and mushroom. Simultaneous high consumption of vegetables, soft drinks and oil is complex paradox, which may be due to wrong nutritional knowledge or special taste. The last pattern is traditional Iranian dietary pattern which is high in hydrogenated fats, garlic, broth, tea, poultry and meats.

Several limitations need to be considered in the interpretation of our findings. First, we assessed dietary patterns by using food intake data only, whereas the inclusion of eating behaviors such as meal and snack patterns in dietary pattern analysis has been recommended.[21] Second, like any other measurements, dietary assessment also has its own measurement errors. Third, limitations of factor analysis that originate from several subjective or arbitrary decisions should also be taken into account.[22] Fourth, we can not generalize our findings to all adolescents in the country, because dietary intakes and other lifestyle measures in Tabriz who are a Turkish population are somewhat different from those in other parts of the country. Moreover, these dietary patterns are confined to adolescent girls. Furthermore, the uniform background of the study participants in terms of intelligence, sex, and education limits the extent to which we may generalize our findings. Our findings suggest that among the six major dietary patterns in Tabrizi adolescent girls: Asian-like pattern was the healthiest pattern among this population.


Conflict of Interest: None declared.

The authors would like to thank Roghayye Karimi and Nahid Hajiri for all their works and helps.

1. Fung TT,Rim EB,Spiegelman D,Rifai N,Tofler GH,Willet WC,Hu FB. Association between dietary patterns and plasma biomarkers of obesity and cardiovascular disease risk.Am J Clin NutrYear: 20017361711124751
2. Sonnenberg L,Pencina M,Kimokoti R,Quatromoni P,Nam BH,D'Agostino R,Meigs JB,Ordovas J,Cobain M,Millen B. Dietary Patterns and the Metabolic Syndrome in Obese and Non-obese Framingham Women.Obes ResYear: 2005131536210.1038/oby.2005.2015761175
3. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology.Curr Opin lipidolYear: 2002133910.1097/00041433-200202000-0000211790957
4. Randall E,Marshal JR,Graham S. Dietary patterns and colon cancer in western New York.Nutr CancerYear: 1992182657610.1080/016355892095142271296200
5. Ritchie LD,Spector P,Stevens MJ,Schmidt MM,Schreiber GB,Striegel-Moore RH,Wang MC,Crawford PB. Dietary Patterns in Adolescence Are Related to Adiposity in Young Adulthood in Black and White Females.J NutrYear: 200713739940617237318
6. Millen BA,Quatromoni PA,Pencina M,kimokoti R,Nam B,Cobain S,Kozak W,Appugliese DP,Ordovas J,D’Agostino RB. Unique Dietary Patterns and Chronic Disease Risk Profiles of Adult Men: The Framingham Nutrition Studies.J Am Diet AssocYear: 200510517233410.1016/j.jada.2005.08.00716256756
7. Esmaillzadeh A,Azadbakht L. Major dietary patterns in relation to general obesity and central adiposity among Iranian women.J NutrYear: 20081383586318203904
8. Esmaillzadeh A,Kimiagar M,Mehrabi Y,Azadbakht L,Hu FB,Willet WC. Dietary patterns, insulin resistance, and prevalence of the metabolic syndrome in woman.Am J Clin NutrYear: 200785910817344515
9. McNaughton SA,Mishra GD,Brunner EJ. Dietary Patterns, Insulin Resistance, and Incidence of Type 2 Diabetes in the Whitehall II Study.Diabetes CareYear: 2008311343810.2337/dc07-194618390803
10. Heidemanne C,Schulze MB,franco OH,van Dam RM,Mantzoros CS,Hu FB. Dietary patterns and risk of mortality from cardiovascular disease, cancer, and all causes in a prospective cohort of women.CirculationYear: 2008118230710.1161/CIRCULATION-AHA.108.77188118574045
11. Esmaillzadeh A,Mirmiran P,Azadbakht L,Etemadi A,Azizi F. High Prevalence of the Metabolic Syndrome in Iranian Adolescents.Obesity (Silver Spring)Year: 2006143778210.1038/oby.2006.5016648607
12. Azadbakht L,Mirmiran P,Esmaillzadeh A,Azizi F. Dairy consumption is inversely associated with the prevalence of the metabolic syndrome in Tehranian adults.Am J Clin NutrYear: 2005825233016155263
13. Esmaillzadeh A,Mirmiran P,Azizi F. Whole-grain intake and the prevalence of hypertriglyceridemic waist phenotype in Tehranian adults.Am J Clin NutrYear: 200581556315640460
14. Shin KO,Oh S,Park HS. Empirically derived major dietary patterns and their associations with overweight in Korean preschool children.Br J NutrYear: 2007984162110.1017/S000711450772022617433127
15. McNaughton SA,Ball K,Mishra GD,Crawford DA. Dietary patterns of adolescents and risk of obesity and hypertension.J NutrYear: 20081383647018203905
16. Lera Marqués L,Olivares Cortés S,Leyton Dinamarca B,Bustos Zapata N. Dietary patterns and its relation with overweight and obesity in Chilean girls of medium-high socioeconomic level.Arch Latinoam NutrYear: 2006561657017024962
17. Lozada AL,Flores M,Rodríguez S,Barquera S. Dietary patterns in Mexican adolescent girls. A comparison of two methods. National Nutrition Survey, 1999.Salud Publica MexYear: 2007492637317710275
18. Hu FB,Rimm EB,Stampfer MJ,Ascherio A,Spiegelman D,Willett WC. Prospective study of major dietary patterns and risk of coronary heart disease in men.Am J Clin NutrYear: 2000729122111010931
19. Fung TT,Willett WC,Stampfer MJ,Manson JE,Hu FB. Dietary patterns and the risk of coronary heart disease in women.Arch Intern MedYear: 200116118576210.1001/archinte.161.15.185711493127
20. Esmaillzadeh A,Kimiagar M,Mehrabi Y,Azadbakht L,Hu FB,Willett WC. Dietary patterns and markers of systemic inflammation among Iranian women.J NutrYear: 2007137992817374666
21. Tseng M. Validation of dietary patterns assessed with a food frequency questionnaire.Am J Clin NutrYear: 19997042210479207
22. Martinez ME,Marshall JR,Sechrest L. Invited commentary: factor analysis and the search for objectivity.Am J EpidemiolYear: 199814817910.1093/oxford-journals.aje.a0095529663398

[TableWrap ID: s2tbl1] Table 1  Food grouping used in factor analysis.
Food groups Food items
Processed meats Sausages, hamburger
Red Meat Beef, lamb
Organ meats Beef liver
Fish Canned tuna fish, other fish
Poultry Chicken with or without skin
Eggs Eggs
Butter Butter
Margarine Margarine
Low fat dairy Skim or low-fat milk, low-fat yogurt
High fat dairy High-fat milk, whole milk, chocolate milk, cream, high-fat yogurt, cream, yogurt, cream cheese, other cheeses, ice cream
Tea Tea
Coffee Coffee
Fruits Pears, apricots, cherries, apples, raisins or grapes, bananas, cantaloupe, watermelon, oranges, grapefruit, kiwi, strawberries, peaches, nectarine, tangerine, mulberry, plums, persimmons, pomegranates, lemons, pineapples, fresh figs and dates
Fruit juices Apple juice, orange juice, grapefruit juice, other fruit juices
Cruciferous vegetables Cabbage, cauliflower, Brussels sprouts, kale
Yellow vegetables Carrots
Tomato Tomatoes, tomato sauce, tomato pasta
Green leafy vegetables Spinach, lettuce
Other vegetables Cucumber, mixed vegetables, eggplant, celery, green peas, green beans, green pepper, turnip, corn, squash,  mushrooms, onions
Legumes Beans, peas, lima beans, broad beans, lentils, soy
Garlic Garlic
Potato Potatoes
Whole grain Dark breads (Iranian), barley bread, popcorn, cornflakes, wheat germ, bulgur
Refined grains White breads (lavash, baguettes), noodles, pasta, rice, toasted bread, milled barley, sweet bread, white flour, starch, biscuits
Pizza Pizza
Snacks Potato chips, corn puffs, crackers, popcorn
Nuts Peanuts, almonds, pistachios, hazelnuts, roasted seeds, walnuts
Mayonnaise Mayonnaise
Dried fruits Dried figs, dried dates, dried mulberries, other dried fruit
Olive Olives, olive oils
Sweets and desserts Chocolates, cookies, cakes, confections
Hydrogenated fats Hydrogenated fats, animal fats
Non-hydrogenated fats Vegetable oils (except for olive oil)
Sugars Sugars, candies, gaz (an Iranian confectionery made of sugar, nuts, and tamarisk)
Condiments Jam, jelly, honey
Soft drinks Soft drinks
Dough (Yoghurt drink) Dough (Yoghurt drink)
Broth Broth
Salt Salt
Pickle Pickle

[TableWrap ID: s3tbl2] Table 2  Factor-loadinga matrix form major dietary patterns.
Western-like Sweat junk foods Asian-like Salty junk foods Low protein- soft drinks-oil Traditional
Pizza 0.66 - - 0.25 - -
Organ meats 0.60 - - - - -
Fruit juices 0.60 0.36 - - 0.237 -
Sweets and desserts 0.58 0.37 - - - -
High fat dairy 0.48 - 0.46 - - -
Poultry 0.46 - - - - 0.42
Processed meats 0.46 0.20 - 0.26 - -
Fruits 0.45 0.33 0.26 - - -
Refined grains 0.42 - 0.39 - - -
Low fat dairy 0.36 0.36 - - -
Pickle 0.34 - - 0.38 - -
Olive 0.33 - - - 0.22 -
Nuts 0.29 0.34 - - 0.23 -
Coffee 0.28 0.33 - 0.37 0.26 -
Snacks 0.27 - - 0.80 - -
Butter 0.25 - 0.34 0.29 - 0.27
Sugars 0.25 0.60 - - - 0.24
Dough (Yoghurt drink) 0.24 - 0.48 - 0.30 -
Whole grain 0.22 - 0.37 - - -
Mayonnaise 0.22 0.30 - 0.33 0.31 -
Margarine -0.21 0.41 0.27 - -
Red meat - 0.20 0.31 - -0.20 0.30
Fish - - - - - -
Eggs - 0.35 0.36 - - -
Tea - 0.43 - - - 0.47
Cruciferous vegetables - - - - 0.58 -
Yellow vegetables - - - 0.83 - -
Tomato - - 0.20 0.34 0.42 0.29
Green leafy vegetables - 0.26 0.25 - 0.58 -
Other vegetables - 0.21 0.51 - 0.35 0.249
Legumes - - 0.62 - - -
Garlic - - - - 0.21 0.51
Potato - - 0.57 - - -
Dried fruits - 0.74 - - - -
Hydrogenated fats - - - - - 0.58
Non-hydrogenated fats - - - - 0.34 -
Condiments - 0.63 - - - -
Soft drinks - - - 0.26 0.49 -
Broth - - - - - 0.47
Salt - - - - - -
Percent of variance explained 16.6 5.6 4.7 4.4 4.0 3.8

Fs3tbl2aa Factor loadings <0.2 are omitted for simplicity. Total variance explained by six factors: 39.4.

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Keywords: Dietary patterns, Factor analysis, Adolescents, Girls, Dietary intake.

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