- Email: [email protected]
Dietary patterns and attention deficit hyperactivity disorder among Iranian children
Nutrition 28 (2012) 242–249
Contents lists available at ScienceDirect
Nutrition journal homepage: www.nutritionjrnl.com
Applied nutritional investigation
Dietary patterns and attention deficit hyperactivity disorder among Iranian children Leila Azadbakht Ph.D. a, b, Ahmad Esmaillzadeh Ph.D. a, b, * a b
Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 December 2010 Accepted 1 May 2011
Objective: This study was conducted to assess the relation of major dietary patterns identified by factor analysis to attention-deficit/hyperactivity disorder (ADHD) in a group of Iranian school-age children. Methods: This cross-sectional study was conducted in 375 school-age children in Tehran, Iran. We assessed usual dietary intakes by a semiquantitative food-frequency questionnaire. The presence of ADHD was diagnosed using the questionnaire of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Major dietary patterns were identified by factor analysis. Results: The prevalence of ADHD was 9.7% in this population. We identified four major dietary patterns: “healthy,” “Western,” “sweet,” and “fast food.” After controlling for potential confounders, children in the top quintile of the sweet dietary pattern score had greater odds for having ADHD compared with those in the lowest quintile (odds ratio 3.95, 95% confidence interval 1.16–15.31, P for trend ¼ 0.03). Greater adherence to the fast-food dietary pattern was significantly associated with a higher risk of having ADHD (odds ratio 3.21, 95% confidence interval 1.05–10.90, P for trend ¼ 0.03). No overall significant associations were seen between the healthy or Western dietary pattern and ADHD. Conclusion: We found significant independent associations between the sweet and fast-food dietary patterns and the prevalence of ADHD. Prospective studies are required to confirm these findings. Ó 2012 Elsevier Inc. All rights reserved.
Keywords: Dietary patterns Attention-deficit/hyperactivity disorder Children Factor analysis
Introduction Attention-deficit/hyperactivity disorder (ADHD) is characterized by inattention, impulsivity, and hyperactivity [1]. Psychosocial function, learning, and cognition also are impaired in this condition [2]. This is the most common psychiatric disorder in children and is diagnosed in male two to nine times as often as in female patients. ADHD shows high comorbidity [3–5] and symptoms in 60% of children with ADHD will persist into adulthood [6]. Depression, anxiety, bipolar disorder, sensory integration disorder, learning disorder, and communication problems The data collection phase of the study was supported by a grant from the School of Nutrition and Food Science, Shaheed Beheshti University of Medical Sciences, Tehran, Iran. Financial support for the conception, design, data analysis, and manuscript drafting was provided from the Food Security Research Center and the School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran. * Corresponding author. Tel.: 311-792-2720; fax: 311-668-2509. E-mail address: [email protected] (A. Esmaillzadeh). 0899-9007/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2011.05.018
are some examples of ADHD comorbidities [7–9]. This can have a significant impact on emotional well-being [7] and the quality of life of patients and their families [8,9]. It has been reported that 3% to 7% of school-age children worldwide have this syndrome [1]. The prevalence in American studies has been reported to be in the range of 2% to 26% depending on the definition used [6]. Based on criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), 8.7% of U.S. children 8 to 15 y old are affected [6]. In Iran, ADHD has been estimated to affect 12.3% of preschool children [10] and 15.2% of elementary schoolboys [11]. Others have reported a prevalence of 10.1% in Shiraz, a major Iranian city [12]. Heterogeneous causality has been suggested for this syndrome [13]. Environmental and biological factors can affect the incidence of ADHD. Complications during pregnancy, at birth or shortly after birth, head injury, toxic chemicals in the environment, a decreased prefrontal cortex, and decreased medial temporal and inferior parietal lobes are some environmental and biological ADHD risks [13]. In the previous two decades, there has been an increasing
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
particular focus on the effects of diet on hyperactivity in children. Food additives [14,15], refined sugars [16], low-protein, high-carbohydrate diets [17], mineral imbalances [18,19], essential fatty acid and phospholipid deficiencies [20], amino acid deficiencies [21], and B-vitamin deficiencies [22] have been reported to have adverse effects on behavior. Although several dietary factors have been associated with this syndrome [16–22], comparatively little emphasis has been placed on the specific contribution of overall dietary characteristics. Assessing the overall diet instead of the effects of a single nutrient on the relation between diet and disease may be more informative. We are not aware of any study assessing the relation between major dietary patterns identified by factor or cluster analysis and ADHD. Some evidence has supported the possibility that a person’s dietary patterns would be best represented by using factor analysis [23,24]. The present study was conducted to assess the relation of major dietary patterns identified by factor analysis to ADHD in a representative group of Tehrani elementary school-age children.
243
Assessment of dietary intake Usual dietary intake was assessed by a semiquantitative food-frequency questionnaire (FFQ), which consisted of 134 food items that were commonly consumed by the Iranian children. All questionnaires were administered by a trained dietitian. Parents were requested to report the frequency of intakes of food items by their children on a daily (i.e., fruit), weekly (i.e., cheese), and monthly (i.e., noodle) basis during the previous year. The reported frequency for each food item was then converted to a daily intake. Portion sizes of consumed foods were converted to grams by using household measurements. We categorized foods into 31 groups for use in the dietary pattern analysis (Table 1). Defining the food groups was based on the nutrient similarity of foods. Each food and beverage was then coded according to the protocol and analyzed for the content of energy and other nutrients using Nutritionist III 7.0 (N-Squared Computing, Salem, OR, USA), which was designed for Iranian foods. The reliability of the FFQ in this study was evaluated in a randomly chosen subgroup of 52 children by comparing nutrient consumption determined by responses on the FFQ on two occasions. The FFQ had a high reliability for nutrients. For example, the correlation coefficients were 0.63 for dietary protein, 0.61 for zinc, and 0.65 for dietary calcium. Comparative validity was determined by comparison with intakes estimated from the average of six non-consecutive 24-h dietary recalls. We found that most nutrients were moderately correlated (all correlation coefficients >0.4) between these two methods after controlling for total energy intake. Overall, these data indicated that the FFQ provides reasonably valid measurements of average long-term dietary intake.
Materials and methods Anthropometric measurements This cross-sectional study was conducted in a representative sample of Tehrani elementary school-age children selected by a multistage, cluster, random-sampling method. The sample of 479 school-age children and one of their parents were invited to participate in this study. The parents of 421 children accepted participation in the study. After excluding those with uncompleted questionnaires, 375 children were included in the present study. Written informed consent was taken from each participant and his/her parents. The study was approved by the research council of postgraduate education of the School of Nutrition, Shaheed Beheshti University of Medical Sciences, Tehran, Iran and the committee of the Food Security Research Center and the School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Weight was measured in minimally clothed subjects and without shoes using digital scales and recorded to the nearest 100 g. Height was measured using a tape measure while the children were standing in a normal position and were not wearing shoes. Obesity was defined according to the definition of the International Obesity Task Force for children [25]. ADHD diagnosis The presence of ADHD was assessed using the DSM-IV [26]. According to the DSM-IV, a person with ADHD must have at least six of the listed symptoms of
Table 1 Food grouping used in dietary pattern analysis Food groups
Food items
Processed meats Red meats Fish Poultry Eggs Butter Margarine Dairy Ice cream Tea Coffee Fruit
Sausages Beef, lamb, hamburger, beef liver, beef kidney, beef heart Canned tuna fish and other fish Chicken Eggs Butter Margarine Milk, yogurt, dough (yogurt drink), cheese Different kinds of ice cream Tea Coffee 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, dates Apple juice, orange juice, grapefruit juice, other fruit juices Apple juice, orange juice, grapefruit juice, other fruit juices Cabbage, cauliflower, Brussels sprouts, kale, carrots, tomatoes, green leafy vegetables spinach, lettuce, cucumber, mixed vegetables, eggplant, celery, green peas, green beans, green pepper, turnip, corn, squash, mushrooms, onions, potato, garlic Legumes, beans, peas, lima beans, broad beans, lentils, soy Dark breads (Iranian), barley bread, popcorn, cornflakes, wheat germ, bulgur White breads (lavash, baguettes), noodles, pasta, rice, toasted bread, milled barley, sweet bread, white flour, starch, biscuits Pizza Potato chips, corn puffs, crackers, popcorn Peanuts, almonds, pistachios, hazelnuts, roasted seeds, walnuts Tomato sauces, mayonnaise, tomato paste, other sauces Dried figs, dried dates, dried mulberries, other dried fruit Chocolates, cookies, cakes, confections, jam, jelly, honey Sugars, candies, gaz (an Iranian confectionery made of sugar, nuts, tamarisk) Animal fat Hydrogenated fat Vegetable oils Soft drinks Salt Pickles
Homemade fruit juices Industrial fruit juices Vegetables Legumes Whole grains Refined grains Pizza Snacks Nuts Sauces Dried fruits Sweets and desserts Sugar Animal fat Hydrogenated fat Vegetable oil Soft drinks Salt Pickles
244
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
inattention or symptoms of hyperactivity–impulsivity that have persisted for at least 6 mo to a degree that is maladaptive and inconsistent with the person’s developmental level [26]. The reliability and validity of this questionnaire has been shown previously [26]. According to this questionnaire, the subtypes of this disorder were also identified. Therefore, the children were categorized as having ADHD and ADHD inattentive subtype, combined subtype, or hyperactive– impulsive subtype. In the present study, a psychiatrist made the ADHD diagnosis. There were newly diagnosed patients and patients with a known diagnosis in the present study sample. Assessment of other variables Sociodemographic status, socioeconomic status, and physical status information such as age, medical history, and current use of medications and family history of ADHD was obtained with pretested questionnaires [27]. Socioeconomic status was determined as low, moderate, or high based on the education and employment of the two parents. Statistical analysis To identify major dietary patterns, we used factor analysis with orthogonal transformation. Factors were retained using the Scree test, if their eigenvalues were >1 [27]. After the fourth factor, the eigenvalues of the factors decreased and remained similar to each other. Therefore, these four factors were considered major dietary patterns and were labeled based on our previous knowledge in nutrition. The factor score for each pattern was calculated by summing the intakes of food groups weighted by their factor loadings [28], and each child received a factor score for each specific pattern. Subjects were then categorized based on quintiles of dietary pattern scores. Significant differences in general characteristics across quintiles were examined by one-way analysis of variance with Tukey post hoc comparisons. Chi-square tests were used for assessing the distribution of categorical variables across quintiles. Energy-adjusted means for dietary variables across quintiles of dietary pattern scores were calculated. Energy adjustment was performed after entering the food groups in the factor analysis and after analyzing the dietary pattern. This idea of adjusting the energy intake before or after entering the food groups and analyzing the food pattern is currently under discussion. Most studies on dietary patterns have performed energy adjustment after the dietary pattern analysis. Therefore, we judged that it was not necessary to adjust for energy intake before entry into a principal component analysis to determine dietary patterns when using FFQ data. Multivariate logistic regression was used to identify the association of dietary pattern with the prevalence of ADHD and its subtypes. First, the crude odds ratios were adjusted for total energy intake. Additional adjustments were made for age (years), sex (male or female), socioeconomic status (low, moderate, high), and family history of ADHD (yes, no) in the second model. The first quintile of dietary pattern scores was considered a reference in all models. For assessing the overall trend of odds ratios across increasing quintiles of dietary pattern scores, the Mantel-Haenszel extension chi-square test was used. SPSS 9.05 (SPSS, Inc., Chicago, IL, USA) was used for all statistical analyses.
Results We identified four major dietary patterns using factor analysis: “sweet” (highly loaded with ice cream, refined grains, sweet desserts, sugar, and soft drinks), “fast food” (high in processed meat, commercially produced fruit juices, pizza, snacks, sauces, and soft drinks), “Western” (high in processed meat, red meat, butter, eggs, pizza, snacks, animal fat, and hydrogenated fat), and “healthy” (high in fruits, vegetable, vegetable oils, whole grains, legumes, and dairy). Table 2 presents the factor loading matrix for the major dietary patterns. Fifty-two percent of the children in the present study were boys and 48% were girls. The mean age of the children was 8 1 y. The prevalence of ADHD was 9.7% in this population. Characteristics of the study participants across quintiles of dietary pattern scores are presented in Table 3. Compared with those in the lowest quintile, individuals in the top quintile of the sweet dietary pattern were more likely to have a positive family history of ADHD. The prevalence of ADHD (all types) and obesity was higher in those in the highest quintile compared with those in the lowest quintile of the sweet dietary pattern. Furthermore, these subjects obtained a larger percentage of energy from carbohydrate and
Table 2 Factor loading matrix for major dietary patterns Food groups
Processed meats Red meats Fish Poultry Eggs Butter Margarine Dairy Ice cream Tea Coffee Fruit Homemade fruit juices Commercially fruit juices Vegetables Legumes Whole grains Refined grains Pizza Snacks Nuts Sauces Dried fruits Sweets and desserts, sugar Animal fat Hydrogenated fat Vegetable oil Soft drinks Salt Pickles Eigenvalues Percentage of variance explained
Dietary patterns Sweet
Fast food
Western
Healthy
0.24 0.24 0.10 0.22 0.23 0.21 0.09 0.22 0.49 0.36 0.05 0.29 0.25 0.28 0.21 0.22 0.21 0.38 0.23 0.26 0.12 0.19 0.39 0.52 0.21 0.24 0.21 0.41 0.28 0.21 2.29 0.076
0.53 0.32 0.21 0.29 0.39 0.29 0.06 0.21 0.23 0.29 0.04 0.22 0.11 0.43 0.25 0.23 0.24 0.30 0.55 0.54 0.17 0.48 0.25 0.32 0.35 0.38 0.24 0.39 0.29 0.22 2.96 0.098
0.42 0.41 0.12 0.21 0.34 0.44 0.17 0.28 0.26 0.33 0.14 0.20 0.23 0.22 0.22 0.26 0.29 0.31 0.33 0.34 0.19 0.27 0.11 0.29 0.40 0.43 0.23 0.28 0.24 0.11 2.39 0.079
0.31 0.24 0.36 0.39 0.23 0.23 0.27 0.36 0.24 0.24 0.11 0.45 0.31 0.29 0.47 0.48 0.38 0.24 0.19 0.18 0.19 0.13 0.13 0.23 0.15 0.22 0.39 0.23 0.17 0.12 2.30 0.076
protein than those in the lowest quintile. Obesity and all types of ADHD were also more prevalent in those in the highest quintile of the fast-food dietary pattern than in those in the lowest quintile. Information on the baseline characteristics and nutrient intakes of children with and without ADHD is presented in Table 4. As indicated in Table 4, the iron, zinc, calcium, vitamin B1, and vitamin B2 intakes were lower in children with ADHD. However, children with ADHD consumed larger amounts of sugar and hydrogenated vegetable oil. Multivariate-adjusted odds ratios for having ADHD across quintile categories of dietary pattern scores are listed in Tables 5 and 6. After controlling for energy intake, those in the highest quintile of the sweet dietary pattern had greater odds for having ADHD (odds ratio 4.05, 95% confidence interval 1.15–15.37). Further adjustment for age, sex, socioeconomic status, and family history of ADHD attenuated the associations but remained significant. We also entered body mass index in the model, but there were no significant changes in the result after adjusting for body mass index. Adherence to the fast-food dietary pattern was also associated with a greater risk of having ADHD even after controlling for potential confounders (3.21, 1.05–10.90). The healthy and Western dietary patterns were not associated with ADHD and its subtypes. No overall significant associations were found the sweet or fast-food dietary pattern and individual subtypes of ADHD. Nutrient-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of the sweet and fast-food dietary pattern scores are listed in Table 7. We provided five additional models in this table for analyzing two patterns (sweet and fast food). Based on the information presented in Tables 5 and 6, only these two models had significant associations with ADHD.
Table 3 Characteristics and dietary intakes of study participants by quintile categories of dietary pattern scores Sweet pattern Q1 (n ¼ 75)
Inattentive Hyperactive– impulsive Combined Obese (%) Current medication use for ADHD (%) Dietary intakes Total energy (kJ/d) Carbohydrate (%total energy) Fat (%total energy) Protein (%total energy) Vitamin C (mg) Vitamin B1 (mg) Vitamin B2 (mg) Vitamin B12 (mg) Calcium (mg) Zinc (mg) Simple Sugars (g) HVO (g)
71
P* 0.19 <0.05 <0.05
38 5
47 6
Q1 (n ¼ 75)
Western pattern
Q3 (n ¼ 75)
91 58 5
0.23 0.09 0.32
49 4
53 5
59 5
0.21 0.13 0.24
Q3 (n ¼ 75)
5
8
16
<0.05
8.4
11.2
11.2
0.06
11.7
9.2
9.2
0.07
1.4 1.3
5 2.0
8 2.6
<0.05 <0.05
2.6 1.3
4 2.6
8 4
<0.05 <0.05
4.5 1.3
6 2.6
6 2.6
0.10 0.17
6.1 1.3
4 2.6
4 2.6
0.11 0.21
1.3 6 3
2.3 8 5
3.5 11 7
<0.05 <0.05 0.08
1.3 7 4
1.3 9 5
4 10 6
<0.05 0.17 0.21
2.6 6 2
2.6 10 6
2.6 11 7
0.43 <0.05 <0.05
4.2 10 6
2.6 9 4
2.6 7 5
0.10 0.09 0.11
5818 53 1
6106 57 1
6299 64 1
0.09 <0.05
5931 58 1
5806 59 1
5989 59 1
5095 54 1
5525 58 1
5630 60 1
0.14 <0.05
5743 56 1
5521 59 1
5638 58 1
0.16 0.22
113 1.8 0.8 1.0 909 7 28 33
34 0.5 0.3 0.3 89 3 3 4
101 1.3 0.7 0.8 729 4 40 41
29 0.4 0.3 0.3 76 2 5 4
98 1.1 0.5 0.7 639 2 51 48
28 0.4 0.2 0.2 69 1 7 6
0.10 0.04 0.18 0.18 0.03 0.04 0.03 0.07
125 1.7 1.0 1.0 921 6 30 28
37 0.5 0.4 0.4 97 3 4 3
99 1.4 0.6 0.7 725 4 36 40
31 0.3 0.3 0.3 75 2 5 3
0.23 0.22
0.03 0.04 0.03 0.13 0.04 0.06 0.02 0.04
86 1.1 0.3 0.8 625 3 55 54
35 0.2 0.2 0.2 70 1 7 5
32 0.8 14 0.4 109 1.4 0.8 1.0 874 5 35 33
39 0.4 0.4 0.4 81 3 5 3
30 0.6 12 0.4 104 1.4 0.6 0.7 740 5 39 40
38 0.3 0.3 0.3 78 2 4 4
30 0.7 11 0.3
0.17 0.23
0.20 0.12 0.09 0.11 0.06 0.12 0.09 0.05
96 1.3 0.6 0.8 659 3 45 50
35 0.3 0.3 0.3 61 1 6 6
31 0.7 13 0.4 98 1.3 0.4 0.6 654 4 59 53
27 0.4 0.1 0.3 59 1 6 5
81
30 0.6 12 0.3 106 1.4 0.7 0.8 737 4 36 42
29 0.5 0.3 0.3 64 3 4 4
91
P
<0.05
31 0.7 10 0.2
71
Q5 (n ¼ 75)
14.1
30 0.7 11 0.3
51 6
81 44 5
Q1 (n ¼ 75)
P
9.3
31 0.6 12 0.3
65 6
0.21 <0.05 0.19
0.19 0.18
71
Q5 (n ¼ 75)
4
0.07 <0.05
91
Healthy pattern
Q3 (n ¼ 75)
49 7
28 0.7 9 0.2
71
Q1 (n ¼ 75)
P
40 4
31 0.7 12 0.3
61
Q5 (n ¼ 75)
91 62 9
33 0.8 14 0.4
81
Q5 (n ¼ 75)
30 0.7 12 0.4
0.27 0.26
0.23 0.17 0.04 0.04 0.05 0.21 0.04 0.03
110 1.5 1.0 1.1 883 5 26 27
31 0.5 0. 0. 80 3 3 2
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
Age (y) Boys (%) Family history of ADHD (%) ADHD (%) ADHD subtype
Fast-food pattern Q3 (n ¼ 75)
ADHD, attention-deficit/hyperactivity disorder; HVO, hydrogenated vegetable oil; Q, quintile Values are presented as mean SD, number, or percentage * Analysis of variance for quantitative variables and chi-square test for qualitative variables.
245
246
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
Table 4 Baseline characteristics and nutrient intakes in children with and without ADHD Variables
Age Boys (%) Low SES (%) Obesity Family history of ADHD (%) Total energy (kJ) Carbohydrate (%total energy) Fat (%total energy) Protein (%total energy) Vitamin C (mg) Vitamin B1 (mg) Vitamin B2 (mg) Vitamin B12 (mg) Calcium (mg) Zinc (mg) Iron (mg) Simple sugars (g) Hydrogenated vegetable oil (g)
Children with ADHD
Children without ADHD
Mean
Mean
SD
7 71 41 10 11 6048 62 30 8 82 0.7 0.3 0.6 611 3 6 55 52
2
4 1423 3 3 2 41 0.3 0.2 0.4 93 1 4 7 10
10 41 19 8 3 5948 54 32 14 106 1.6 1.1 0.7 902 8 12 24 28
P
SD 1
2 533 1 0.7 0.7 29 0.3 0.3 0.3 51 2 3 4 4
0.03 0.02 0.03 0.38 0.04 0.24 0.03 0.19 0.04 0.09 0.02 0.02 0.23 0.04 0.03 0.04 0.02 0.001
ADHD, attention-deficit/hyperactivity disorder; SES, socioeconomic status
In the first model, we adjusted for vitamin intakes. The second model was adjusted for mineral intakes, and the third and fourth models were adjusted for sugar and hydrogenated vegetable oil (the main source of trans fat intake in Iran). The fifth model included all the potential confounders. Adding each of these variables attenuated the model. In the sweet pattern, adding minerals and sugars attenuated the association. In the fast-food pattern, hydrogenated vegetable oil attenuated the association. However, even after adding all the variables, this association remained significant in the sweet and fast-food patterns.
Discussion We identified four major dietary patterns in this group of Iranian children. Just two major dietary patterns, namely sweet and fast food, were significantly associated with ADHD. We found no significant associations between the healthy or Western dietary pattern and ADHD. To our knowledge, this study is the first to link major dietary patterns and the prevalence of ADHD in children. However, there is a cohort study of adolescents that
suggested that ADHD in adolescents is linked to Western diets, which tend to be high in total fat, saturated fat, refined sugar, and sodium [29]. In general, few data on dietary patterns are available from Middle Eastern populations. These populations have their own dietary intake specifics, i.e., a high carbohydrate intake especially in the form of refined grain and a high intake level of hydrogenated fat [30,31]; therefore, dietary pattern analysis in these populations might provide additional information on the relations between diet and disease. The dietary pattern studies conducted in this region have focused mostly on the metabolic syndrome, obesity, and cardiovascular risk factors [29,32–34]. However, these studies have been confined to adult women and no data in children are available. The interaction among food components is an important issue that is taken into account in the dietary pattern approach. In this approach, the investigators investigate an entire diet and its components and different nutrients [35,36]. Previous studies have focused on behavior problems and not ADHD in particular [16–22]. Currently, less epidemiologic research has been performed on the diet and ADHD. Food additives [14,15], refined sugars [16], a low-protein, high-carbohydrate diet [17], and insufficient intakes of vitamins, minerals, amino acids, and essential fatty acids [18–22] have been reported as probable etiologic factors in the incidence of ADHD. However, the role of whole dietary patterns is still unknown. We found that the sweet dietary pattern was significantly associated with the greater risk of ADHD. This dietary pattern was greatly loaded with ice cream, refined grains, sweet desserts, sugar, and soft drinks. The nutrient-adjusted model for ADHD across quintile categories of the sweet dietary pattern revealed that this association was modified by minerals and sugars to some extent. The significant association between the fast-food dietary pattern and ADHD in the present study could also be attributed to the components of this dietary pattern. Processed meat and commercially produced fruit juices, pizza, snacks, sauces, and soft drinks that mainly comprise this pattern contain several additives and are high in refined and added sugars. Adherence to the fast-food dietary pattern may be associated with low intakes of vitamins, minerals, and essential fatty acids. The fast-food pattern is frequently followed by schoolchildren worldwide. Unfortunately, Iran has undergone a nutritional transition caused by a Westernization in lifestyle [37]. The availability of fast foods has extended the related problems [38]. Therefore, besides obesity-related metabolic abnormalities [38],
Table 5 Multivariate adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of sweet and fast-food dietary pattern scores Sweet pattern
ADHD (all types)* Crude Model 1y Model 2z ADHD (inattentive type) Crude Model 1y Model 2z ADHD (hyperactive–impulsive type) Crude Model 1y Model 2z
Fast-food pattern
Q1
Q3
Q5
P for trend
Q1
Q3
Q5
P for trend
1.00 1.00 1.00
2.47 (0.52–11.66) 2.42 (0.57–11.58) 2.29 (0.41–11.47)
4.12 (1.10–15.44) 4.05 (1.15–15.3) 3.95 (1.16–15.3)
0.01 0.02 0.03
1.00 1.00 1.00
1.54 (0.41–5.69) 1.48 (0.36–5.57) 1.33 (0.39–5.50)
3.38 (1.03–11.01) 3.33 (1.06–10.97) 3.21 (1.05–10.90)
0.01 0.03 0.03
1.00 1.00 1.00
2.05 (0.40–10.17) 2.02 (0.42–10.11) 1.96 (0.38–10.04)
3.17 (0.69–14.4) 3.12 (0.73–14.3) 3.04 (0.68–14.3)
0.10 0.11 0.09
1.00 1.00 1.00
2.07 (0.42–10.19) 2.03 (0.47–10.13) 1.94 (0.39–10.07)
3.18 (0.71–14.42) 3.14 (0.75–14.40) 3.07 (0.77–14.32)
0.12 0.11 0.12
1.00 1.00 1.00
2.0 (0.04–83.93) 1.98 (0.09–83.87) 1.93 (0.12–83.59)
2.02 (0.05–83.75) 1.99 (0.08–83.71) 1.91 (0.15–83.57)
0.38 0.32 0.28
1.00 1.00 1.00
2.02 (0.04–84.76) 1.99 (0.07–84.77) 1.92 (0.10–84.68)
3.08 (0.15–60.34) 3.06 (0.17–60.32) 2.99 (0.21–84.73)
0.19 0.21 0.18
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake. z Further adjusted for age, sex, socioeconomic status, and family history of ADHD.
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
247
Table 6 Multivariate-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of Western and healthy dietary pattern scores Western pattern
ADHD (all types)* Crude Model 1y Model 2z ADHD (inattentive type) Crude Model 1y Model 2z ADHD (hyperactive–impulsive type) Crude Model 1y Model 2z
Healthy pattern
Q1
Q3
Q5
P for trend
Q1
Q3
Q5
P for trend
1.00 1.00 1.00
1.43 (0.47–4.34) 1.40 (0.48–4.33) 1.33 (0.55–4.30)
1.43 (0.50–4.35) 1.42 (0.53–4.33) 1.34 (0.58–4.29)
0.18 0.16 0.12
1.00 1.00 1.00
0.75 (0.26–2.13) 0.78 (0.23–2.17) 0.83 (0.27–2.22)
0.75 (0.25–2.11) 0.77 (0.21–2.14) 0.84 (0.28–2.21)
0.19 0.21 0.29
1.00 1.00 1.00
1.35 (0.31–1.15) 1.34 (0.29–1.11) 1.28 (0.23–1.06)
1.34 (0.32–1.13) 1.32 (0.30–1.09) 1.25 (0.39–1.04)
0.28 0.26 0.21
1.00 1.00 1.00
0.73 (0.17–3.12) 0.76 (0.15–3.13) 0.81 (0.19–3.07)
0.75 (0.18–3.10) 0.77 (0.21–3.07) 0.81 (0.27–3.01)
0.22 0.20 0.26
1.00 1.00 1.00
2.02 (0.04–84.77) 1.99 (0.08–84.74) 1.90 (0.13–84.75)
2.04 (0.03–84.7) 2.02 (0.04–87.6) 1.98 (0.09–87.6)
0.31 0.29 0.28
1.00 1.00 1.00
2.01 (0.04–84.6) 2.0 (0.07–84.6) 1.95 (0.11–84.6)
2.02 (0.03–84.76) 1.99 (0.05–84.79) 1.93 (0.04–84.69)
0.27 0.29 0.28
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake. z Further adjusted for age, sex, socioeconomic status, and family history of ADHD.
the present study showed that the fast-food dietary pattern is significantly associated with ADHD. Consumption of the fastfood dietary pattern has been associated with greater intakes of trans fats [39]. Thus, future studies must focus on the association between trans fat consumption and the prevalence of ADHD. Two other dietary patterns, healthy and Western, were identified in this study, but neither pattern was significantly related to the prevalence of ADHD. Although food components of the Western dietary pattern were very similar to the fast-food dietary pattern, the loading factors for these food items were lower in the Western dietary pattern than that in the fast-food dietary pattern. This might explain our finding of a lack of a significant relation between the Western dietary pattern and ADHD. In the present study, we used a factor analysis method that categorized foods according to their loading factors. However, we do not consider the results significant; the odds for having ADHD increased across increasing quintiles of the Western diet. Although there were no significant differences between those in the highest quintile of the Western pattern compared with those in the first quintile, the odds ratio for having ADHD was higher compared with the first quintile. Regarding the healthy pattern, the odds ratios showed a protective effect for this pattern; however, this pattern was not significantly related to ADHD. Some unhealthy food items were
loaded in the healthy pattern, which may be responsible the lack of a significant association between this pattern and ADHD. There have been some reports on the benefits of fish consumption and polyunsaturated fatty acid intake and ADHD. Polyunsaturated fatty acid intake and fish consumption were major components in the healthy pattern. However, Iranians do not consume fish in large amounts. This may have resulted in lowering the loading factor for fish compared with other studies and therefore may be associated with no observable significant relation between the healthy pattern and ADHD. Without considering the significant results, we concluded that the healthy pattern might be protectively related to ADHD and the Western pattern might be associated with an increased risk of ADHD. Consuming more trans fat in the fast-food pattern may be related to the potential mechanisms underlying the observed association between the fast-food pattern and the risk of having ADHD. Furthermore, consuming more sugars in the sweet pattern may be related to the potential mechanisms underlying the observed association between the sweet pattern and the risk of ADHD. However, some intakes of nutrients such as vitamin B1, B2, zinc, iron, and calcium may be associated with the relation between certain dietary patterns and the risk of ADHD. Especially zinc deficiency has been reported in schoolgirls [40]. As a limitation, in the Iranian food composition table, we had no
Table 7 Nutrient-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of sweet and fast-food dietary pattern scores Sweet pattern
ADHD (all types)* Model 1y Model 2z Model 3x Model 4k Model 5{
Q1
Q3
1.00 1.00 1.00 1.00 1.00
2.23 2.17 1.97 1.99 1.85
Fast-food pattern Q5 (0.40–11.26) (0.35–11.41) (0.29–11.48) (0.34–11.37) (0.15–15.63)
3.88 3.85 3.78 3.79 3.66
(1.03–15.21) (1.11–15.30) (1.12–15.41) (1.07–15.32) (1.12–15.78)
P for trend
Q1
Q3
0.03 0.04 0.04 0.03 0.04
1.00 1.00 1.00 1.00 1.00
1.30 1.28 1.26 1.12 1.07
Q5 (0.38–5.73) (0.36–5.57) (0.39–5.50) (0.28–5.56) (0.25–5.40)
3.18 3.15 3.16 2.93 2.86
P for trend (1.03–11.01) (1.01–11.07) (1.02–11.15) (1.01–11.10) (0.88–11.16)
0.03 0.03 0.03 0.04 0.04
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus vitamins (B1, B2, and C). z Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus minerals. x Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus sugars. k Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus hydrogenated vegetable oil. { Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus vitamins, minerals, sugars, and hydrogenated vegetable oil.
248
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
information regarding the trans fat content of different foods. Therefore, in this analysis, we considered the common source of trans fat (hydrogenated vegetable oil) and reported this instead of trans fat. Some points need to be considered in the interpretation of our findings. We used factor analysis to obtain the dietary patterns. Factor analysis is a statistical method used to decrease the number of variables and to categorize the variables into factors [41]. However, several subjective or arbitrary decisions in the use of factor analysis need to be considered. Dietary habits and lifestyle characteristics of Iranian children across different cities may be different from those in the present study [42,43]. Children obtain larger percentages of their energy from snacks, but we did not assess the meal and snack patterns in our study [44]. The present study was confined to school-age children, and ADHD may also be prevalent in preschoolers who may have different dietary patterns. Most preschool children consume their meals and snacks at home or some in the kindergartens, but school-age children may buy some snacks and foods from the school buffet. Thus, they may have a different eating pattern. Our findings can be extrapolated to all school-age children in Tehran because the participants in our study were selected from all socioeconomic districts of Tehran. The validity of the English-language version of the questionnaire for the diagnosis of ADHD has been evaluated, but the Persian version has not been validated. The cross-sectional nature of the study was another major limitation that does not allow cause-and-effect associations. A small percentage of the study population used medications for ADHD. Therefore, their parents were aware of the condition, which may have affected their food choices and any change to their child’s diet. We had no information on the use of a specific diet or a change in the diet because of the ADHD diagnosis. Therefore, any possible changes could influence the results. Limitations of the FFQ for assessing dietary intakes should also be taken into account. Although we controlled for the effect of potential confounders in the statistical methods, residual confounding because of unknown confounding factors cannot be excluded. Future recommendations could include extending confounders to parenting styles. Regarding the representativeness of the discussed dietary patterns in Iranian children, in Iran most children consume foods with their parents. The dietary patterns described in the present study are also seen in adults [32–34,45] and the results are in line with other studies of the dietary patterns in Iranian adolescents [46]. The resultant pattern in the present study is somewhat similar to the recently published patterns in Tehranian adults [45]. However, the present study was conducted in Tehranian children and the described pattern may be specific to Tehranian children and not all Iranian children and children in rural areas. According to the different eating patterns in rural areas, the present patterns may not be representative for all Iranian children. Therefore, this may be a limitation of the present study. In conclusion, our study showed that a greater adherence to the fast-food and sweet dietary patterns was associated with a higher prevalence of ADHD in Iranian children. Prospective studies are required to confirm these findings. References [1] American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000. [2] Biederman J, Faraone SV. Attention-deficit hyperactivity disorder. Lancet 2005;366:237–48.
[3] Kidd PM. Attention deficit/hyperactivity disorder (ADHD) in children: rationale for its integrative management. Altern Med Rev 2000;5:402–28. [4] Andersen SL, Teicher MH. Sex differences in dopamine receptors and their relevance to ADHD. Neurosci Biobehav Rev 2000;24:137–41. [5] Faraone SV. The scientific foundation for understanding attention-deficit/ hyperactivity disorder as a valid psychiatric disorder. Eur Child Adolesc Psychiatry 2005;14:1–10. [6] Froehlich TE, Lanphear BP, Epstein JN, Barbaresi WJ, Katusic SK, Kahn RS. Prevalence, recognition, and treatment of attention-deficit/hyperactivity disorder in a national sample of US children. Arch Pediatr Adolesc Med 2007;161:857–64. [7] Martel MM, Nigg JT. Child ADHD and personality/temperament traits of reactive and effortful control, resiliency and emotionality. J Child Psychol Psychiatry 2006;47:1175–83. [8] Harpin VA. The effect of ADHD on the life of an individual, their family, and community from preschool to adult life. Arch Dis Child 2005;90S:i2–7. [9] Riley AW, Spiel G, Coghill D, Döpfner M, Falissard B, Lorenzo MJ, et al, ADORE Study Group. Factors related to Health-Related Quality of Life (HRQoL) among children with ADHD in Europe at entry into treatment. Eur Child Adolesc Psychiatry 2006;15:i38–45. [10] Hebrani P, Abdolahian E, Behdani F, Vosoogh I, Javanbakht A. The prevalence of attention deficit hyperactivity disorder in preschool-age children in Mashhad, north-east of Iran. Arch Iran Med 2007;10:147–51. [11] Talaei A, Mokhber N, Abdollahian E, Bordbar MR, Salari E. Attention deficit/hyperactivity disorder: a survey on prevalence rate among male subjects in elementary school (7 to 9 years old) in Iran. J Atten Disord 2010; 13:386–90. [12] Ghanizadeh A. Distribution of symptoms of attention deficit-hyperactivity disorder in schoolchildren of Shiraz, south of Iran. Arch Iran Med 2008;11:618–24. [13] Thomas CL. Taber’s cyclopedic medical dictionary. 16th ed. Philadelphia, PA: F. A. Davis; 1989. p. 825. [14] McCann D, Barrett A, Cooper A, Crumpler D, Dalen L, Grimshaw K, et al. Food additives and hyperactive behaviour in 3-year-old and 8/9-year-old children in the community: a randomised, double-blinded, placebocontrolled trial. Lancet 2007;370:1560–7. [15] Sinn N. Nutritional and dietary influences on attention deficit hyperactivity disorder. Nutr Rev 2008;66:558–68. [16] Schardt D. Diet and behavior in children. Nutr Action Health Lett 2000;27:10–1. [17] Kidd PM. Attention deficit/hyperactivity disorder (ADHD) in children: rationale for its integrative management. Altern Med Rev 2000;5:402–28. [18] DiGirolamo AM, Ramirez-Zea M. Role of zinc in maternal and child mental health. Am J Clin Nutr 2009;89:940S–5S. [19] Kozielec T, Starobrat-Hermelin B. Assessment of magnesium levels in children with attention deficit hyperactivity disorder (ADHD). Magnes Res 1997;10:143–8. [20] Sinn N, Bryan J, Wilson C. Cognitive effects of polyunsaturated fatty acids in children with attention deficit hyperactivity disorder symptoms: a randomised controlled trial. Prostaglandins Leukot Essent Fatty Acids 2008;78:311–26. [21] Bornstein RA, Baker GB, Carroll A, King G, Wong JT, Douglass AB, et al. Plasma amino acids in attention deficit disorder. Psychiatry Res 1990;33:301–6. [22] Greenblatt J. Nutritional supplements in ADHD. J Am Acad Child Adolesc Psychiatry 1999;38:1209–11. [23] Newby PK, Muller D, Hallfrisch J, Andres R, Tucker KL. Food patterns measured by factor analysis and anthropometric changes in adults. Am J Clin Nutr 2004;80:504–13. [24] Newby PK, Muller D, Tucker KL. Associations of empirically derived eating patterns with plasma lipid biomarkers: a comparison of factor and cluster analysis methods. Am J Clin Nutr 2004;80:759–67. [25] Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240–3. [26] American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994. [27] Azadbakht L, Atabak S, Esmaillzadeh A. Soy protein intake, cardio-renal indices and C-reactive protein in type 2 diabetes with nephropathy: a longitudinal randomized clinical trial. Diabetes Care 2008;3:648–54. [28] Kim J-O, Mueller CW. Factor analysis: statistical methods and practical issues. Thousand Oaks, CA: Sage Publications; 1978. [29] Howard AL, Robinson M, Smith GJ, Ambrosini GL, Piek JP, Oddy WH. ADHD is associated with a ‘Western’ dietary pattern in adolescents. J Atten Disord 2011;15:403–11. [30] Azadbakht L, Esmaillzadeh A. Dietary diversity score is related to obesity and abdominal adiposity among Iranian female youth. Public Health Nutr 2011;14:62–9. [31] Azadbakht L, Esmaillzadeh A. Dietary and non-dietary determinants of central adiposity among Tehrani women. Public Health Nutr 2008;11:528–34. [32] Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary patterns and markers of systemic inflammation among Iranian women. J Nutr 2007;137:992–8.
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249 [33] Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary patterns, insulin resistance, and prevalence of the metabolic syndrome in women. Am J Clin Nutr 2007;85:910–8. [34] Esmaillzadeh A, Azadbakht L. Food intake patterns may explain the high prevalence of cardiovascular risk factors among Iranian women. J Nutr 2008;138:1469–75. [35] Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc 2004;104:615–35. [36] Jacobs DR Jr, Steffen LM. Nutrients, foods, and dietary patterns as exposures in research: a framework for food synergy. Am J Clin Nutr 2003;78(3 suppl):508S–13S. [37] Ghassemi H, Harrison G, Mohammad K. An accelerated nutrition transition in Iran. Public Health Nutr 2002;5:149–55. [38] Azadbakht L, Esmaillzadeh A. Fast foods and risk of chronic diseases. J Res Med Sci 2008;13:1–2. [39] Asgary S, Nazari B, Sarrafzadegan N, Saberi S, Azadbakht L, Esmaillzadeh A. Fatty acid composition of commercially available Iranian vegetable oils. J Res Med Sci 2009;14:211–5.
249
[40] Tupe R, Chiplonkar SA. Diet patterns of lactovegetarian adolescent girls: need for devising recipes with high zinc bioavailability. Nutrition 2010;26:390–8. [41] Kim JO, Mueller CW. Factor analysis: statistical methods and practical issues. Thousand Oaks, CA: Sage Publications; 1978. [42] Azadbakht L, Mirmiranr R, Azizi F. Predictors of cardiovascular risk factors in Tehranian adults: diet and lifestyle. East Mediterr Health J 2006;12:88–97. [43] Azadbakht L, Mirmiran P, Hosseini F, Azizi F. Diet quality status of most Tehranian adults needs improvement. Asia Pac J Clin Nutr 2005;14:163–8. [44] Tseng M. Validation of dietary patterns assessed with a food frequency questionnaire [letter]. Am J Clin Nutr 1999;70:422. [45] Rezazadeh A, Rashidkhani B, Omidvar N. Association of major dietary patterns with socioeconomic and lifestyle factors of adult women living in Tehran, Iran. Nutrition 2010;26:337–41. [46] Alizadeh M, Mohtadinia J, PourghasemGargari B, Esmaillzadeh A. Major dietary patterns among Iranian adolescents [in Farsi]. Med J Tabriz Univ Med Sci 2009;31:63–9.
Contents lists available at ScienceDirect
Nutrition journal homepage: www.nutritionjrnl.com
Applied nutritional investigation
Dietary patterns and attention deficit hyperactivity disorder among Iranian children Leila Azadbakht Ph.D. a, b, Ahmad Esmaillzadeh Ph.D. a, b, * a b
Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 December 2010 Accepted 1 May 2011
Objective: This study was conducted to assess the relation of major dietary patterns identified by factor analysis to attention-deficit/hyperactivity disorder (ADHD) in a group of Iranian school-age children. Methods: This cross-sectional study was conducted in 375 school-age children in Tehran, Iran. We assessed usual dietary intakes by a semiquantitative food-frequency questionnaire. The presence of ADHD was diagnosed using the questionnaire of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Major dietary patterns were identified by factor analysis. Results: The prevalence of ADHD was 9.7% in this population. We identified four major dietary patterns: “healthy,” “Western,” “sweet,” and “fast food.” After controlling for potential confounders, children in the top quintile of the sweet dietary pattern score had greater odds for having ADHD compared with those in the lowest quintile (odds ratio 3.95, 95% confidence interval 1.16–15.31, P for trend ¼ 0.03). Greater adherence to the fast-food dietary pattern was significantly associated with a higher risk of having ADHD (odds ratio 3.21, 95% confidence interval 1.05–10.90, P for trend ¼ 0.03). No overall significant associations were seen between the healthy or Western dietary pattern and ADHD. Conclusion: We found significant independent associations between the sweet and fast-food dietary patterns and the prevalence of ADHD. Prospective studies are required to confirm these findings. Ó 2012 Elsevier Inc. All rights reserved.
Keywords: Dietary patterns Attention-deficit/hyperactivity disorder Children Factor analysis
Introduction Attention-deficit/hyperactivity disorder (ADHD) is characterized by inattention, impulsivity, and hyperactivity [1]. Psychosocial function, learning, and cognition also are impaired in this condition [2]. This is the most common psychiatric disorder in children and is diagnosed in male two to nine times as often as in female patients. ADHD shows high comorbidity [3–5] and symptoms in 60% of children with ADHD will persist into adulthood [6]. Depression, anxiety, bipolar disorder, sensory integration disorder, learning disorder, and communication problems The data collection phase of the study was supported by a grant from the School of Nutrition and Food Science, Shaheed Beheshti University of Medical Sciences, Tehran, Iran. Financial support for the conception, design, data analysis, and manuscript drafting was provided from the Food Security Research Center and the School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran. * Corresponding author. Tel.: 311-792-2720; fax: 311-668-2509. E-mail address: [email protected] (A. Esmaillzadeh). 0899-9007/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2011.05.018
are some examples of ADHD comorbidities [7–9]. This can have a significant impact on emotional well-being [7] and the quality of life of patients and their families [8,9]. It has been reported that 3% to 7% of school-age children worldwide have this syndrome [1]. The prevalence in American studies has been reported to be in the range of 2% to 26% depending on the definition used [6]. Based on criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), 8.7% of U.S. children 8 to 15 y old are affected [6]. In Iran, ADHD has been estimated to affect 12.3% of preschool children [10] and 15.2% of elementary schoolboys [11]. Others have reported a prevalence of 10.1% in Shiraz, a major Iranian city [12]. Heterogeneous causality has been suggested for this syndrome [13]. Environmental and biological factors can affect the incidence of ADHD. Complications during pregnancy, at birth or shortly after birth, head injury, toxic chemicals in the environment, a decreased prefrontal cortex, and decreased medial temporal and inferior parietal lobes are some environmental and biological ADHD risks [13]. In the previous two decades, there has been an increasing
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
particular focus on the effects of diet on hyperactivity in children. Food additives [14,15], refined sugars [16], low-protein, high-carbohydrate diets [17], mineral imbalances [18,19], essential fatty acid and phospholipid deficiencies [20], amino acid deficiencies [21], and B-vitamin deficiencies [22] have been reported to have adverse effects on behavior. Although several dietary factors have been associated with this syndrome [16–22], comparatively little emphasis has been placed on the specific contribution of overall dietary characteristics. Assessing the overall diet instead of the effects of a single nutrient on the relation between diet and disease may be more informative. We are not aware of any study assessing the relation between major dietary patterns identified by factor or cluster analysis and ADHD. Some evidence has supported the possibility that a person’s dietary patterns would be best represented by using factor analysis [23,24]. The present study was conducted to assess the relation of major dietary patterns identified by factor analysis to ADHD in a representative group of Tehrani elementary school-age children.
243
Assessment of dietary intake Usual dietary intake was assessed by a semiquantitative food-frequency questionnaire (FFQ), which consisted of 134 food items that were commonly consumed by the Iranian children. All questionnaires were administered by a trained dietitian. Parents were requested to report the frequency of intakes of food items by their children on a daily (i.e., fruit), weekly (i.e., cheese), and monthly (i.e., noodle) basis during the previous year. The reported frequency for each food item was then converted to a daily intake. Portion sizes of consumed foods were converted to grams by using household measurements. We categorized foods into 31 groups for use in the dietary pattern analysis (Table 1). Defining the food groups was based on the nutrient similarity of foods. Each food and beverage was then coded according to the protocol and analyzed for the content of energy and other nutrients using Nutritionist III 7.0 (N-Squared Computing, Salem, OR, USA), which was designed for Iranian foods. The reliability of the FFQ in this study was evaluated in a randomly chosen subgroup of 52 children by comparing nutrient consumption determined by responses on the FFQ on two occasions. The FFQ had a high reliability for nutrients. For example, the correlation coefficients were 0.63 for dietary protein, 0.61 for zinc, and 0.65 for dietary calcium. Comparative validity was determined by comparison with intakes estimated from the average of six non-consecutive 24-h dietary recalls. We found that most nutrients were moderately correlated (all correlation coefficients >0.4) between these two methods after controlling for total energy intake. Overall, these data indicated that the FFQ provides reasonably valid measurements of average long-term dietary intake.
Materials and methods Anthropometric measurements This cross-sectional study was conducted in a representative sample of Tehrani elementary school-age children selected by a multistage, cluster, random-sampling method. The sample of 479 school-age children and one of their parents were invited to participate in this study. The parents of 421 children accepted participation in the study. After excluding those with uncompleted questionnaires, 375 children were included in the present study. Written informed consent was taken from each participant and his/her parents. The study was approved by the research council of postgraduate education of the School of Nutrition, Shaheed Beheshti University of Medical Sciences, Tehran, Iran and the committee of the Food Security Research Center and the School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Weight was measured in minimally clothed subjects and without shoes using digital scales and recorded to the nearest 100 g. Height was measured using a tape measure while the children were standing in a normal position and were not wearing shoes. Obesity was defined according to the definition of the International Obesity Task Force for children [25]. ADHD diagnosis The presence of ADHD was assessed using the DSM-IV [26]. According to the DSM-IV, a person with ADHD must have at least six of the listed symptoms of
Table 1 Food grouping used in dietary pattern analysis Food groups
Food items
Processed meats Red meats Fish Poultry Eggs Butter Margarine Dairy Ice cream Tea Coffee Fruit
Sausages Beef, lamb, hamburger, beef liver, beef kidney, beef heart Canned tuna fish and other fish Chicken Eggs Butter Margarine Milk, yogurt, dough (yogurt drink), cheese Different kinds of ice cream Tea Coffee 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, dates Apple juice, orange juice, grapefruit juice, other fruit juices Apple juice, orange juice, grapefruit juice, other fruit juices Cabbage, cauliflower, Brussels sprouts, kale, carrots, tomatoes, green leafy vegetables spinach, lettuce, cucumber, mixed vegetables, eggplant, celery, green peas, green beans, green pepper, turnip, corn, squash, mushrooms, onions, potato, garlic Legumes, beans, peas, lima beans, broad beans, lentils, soy Dark breads (Iranian), barley bread, popcorn, cornflakes, wheat germ, bulgur White breads (lavash, baguettes), noodles, pasta, rice, toasted bread, milled barley, sweet bread, white flour, starch, biscuits Pizza Potato chips, corn puffs, crackers, popcorn Peanuts, almonds, pistachios, hazelnuts, roasted seeds, walnuts Tomato sauces, mayonnaise, tomato paste, other sauces Dried figs, dried dates, dried mulberries, other dried fruit Chocolates, cookies, cakes, confections, jam, jelly, honey Sugars, candies, gaz (an Iranian confectionery made of sugar, nuts, tamarisk) Animal fat Hydrogenated fat Vegetable oils Soft drinks Salt Pickles
Homemade fruit juices Industrial fruit juices Vegetables Legumes Whole grains Refined grains Pizza Snacks Nuts Sauces Dried fruits Sweets and desserts Sugar Animal fat Hydrogenated fat Vegetable oil Soft drinks Salt Pickles
244
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
inattention or symptoms of hyperactivity–impulsivity that have persisted for at least 6 mo to a degree that is maladaptive and inconsistent with the person’s developmental level [26]. The reliability and validity of this questionnaire has been shown previously [26]. According to this questionnaire, the subtypes of this disorder were also identified. Therefore, the children were categorized as having ADHD and ADHD inattentive subtype, combined subtype, or hyperactive– impulsive subtype. In the present study, a psychiatrist made the ADHD diagnosis. There were newly diagnosed patients and patients with a known diagnosis in the present study sample. Assessment of other variables Sociodemographic status, socioeconomic status, and physical status information such as age, medical history, and current use of medications and family history of ADHD was obtained with pretested questionnaires [27]. Socioeconomic status was determined as low, moderate, or high based on the education and employment of the two parents. Statistical analysis To identify major dietary patterns, we used factor analysis with orthogonal transformation. Factors were retained using the Scree test, if their eigenvalues were >1 [27]. After the fourth factor, the eigenvalues of the factors decreased and remained similar to each other. Therefore, these four factors were considered major dietary patterns and were labeled based on our previous knowledge in nutrition. The factor score for each pattern was calculated by summing the intakes of food groups weighted by their factor loadings [28], and each child received a factor score for each specific pattern. Subjects were then categorized based on quintiles of dietary pattern scores. Significant differences in general characteristics across quintiles were examined by one-way analysis of variance with Tukey post hoc comparisons. Chi-square tests were used for assessing the distribution of categorical variables across quintiles. Energy-adjusted means for dietary variables across quintiles of dietary pattern scores were calculated. Energy adjustment was performed after entering the food groups in the factor analysis and after analyzing the dietary pattern. This idea of adjusting the energy intake before or after entering the food groups and analyzing the food pattern is currently under discussion. Most studies on dietary patterns have performed energy adjustment after the dietary pattern analysis. Therefore, we judged that it was not necessary to adjust for energy intake before entry into a principal component analysis to determine dietary patterns when using FFQ data. Multivariate logistic regression was used to identify the association of dietary pattern with the prevalence of ADHD and its subtypes. First, the crude odds ratios were adjusted for total energy intake. Additional adjustments were made for age (years), sex (male or female), socioeconomic status (low, moderate, high), and family history of ADHD (yes, no) in the second model. The first quintile of dietary pattern scores was considered a reference in all models. For assessing the overall trend of odds ratios across increasing quintiles of dietary pattern scores, the Mantel-Haenszel extension chi-square test was used. SPSS 9.05 (SPSS, Inc., Chicago, IL, USA) was used for all statistical analyses.
Results We identified four major dietary patterns using factor analysis: “sweet” (highly loaded with ice cream, refined grains, sweet desserts, sugar, and soft drinks), “fast food” (high in processed meat, commercially produced fruit juices, pizza, snacks, sauces, and soft drinks), “Western” (high in processed meat, red meat, butter, eggs, pizza, snacks, animal fat, and hydrogenated fat), and “healthy” (high in fruits, vegetable, vegetable oils, whole grains, legumes, and dairy). Table 2 presents the factor loading matrix for the major dietary patterns. Fifty-two percent of the children in the present study were boys and 48% were girls. The mean age of the children was 8 1 y. The prevalence of ADHD was 9.7% in this population. Characteristics of the study participants across quintiles of dietary pattern scores are presented in Table 3. Compared with those in the lowest quintile, individuals in the top quintile of the sweet dietary pattern were more likely to have a positive family history of ADHD. The prevalence of ADHD (all types) and obesity was higher in those in the highest quintile compared with those in the lowest quintile of the sweet dietary pattern. Furthermore, these subjects obtained a larger percentage of energy from carbohydrate and
Table 2 Factor loading matrix for major dietary patterns Food groups
Processed meats Red meats Fish Poultry Eggs Butter Margarine Dairy Ice cream Tea Coffee Fruit Homemade fruit juices Commercially fruit juices Vegetables Legumes Whole grains Refined grains Pizza Snacks Nuts Sauces Dried fruits Sweets and desserts, sugar Animal fat Hydrogenated fat Vegetable oil Soft drinks Salt Pickles Eigenvalues Percentage of variance explained
Dietary patterns Sweet
Fast food
Western
Healthy
0.24 0.24 0.10 0.22 0.23 0.21 0.09 0.22 0.49 0.36 0.05 0.29 0.25 0.28 0.21 0.22 0.21 0.38 0.23 0.26 0.12 0.19 0.39 0.52 0.21 0.24 0.21 0.41 0.28 0.21 2.29 0.076
0.53 0.32 0.21 0.29 0.39 0.29 0.06 0.21 0.23 0.29 0.04 0.22 0.11 0.43 0.25 0.23 0.24 0.30 0.55 0.54 0.17 0.48 0.25 0.32 0.35 0.38 0.24 0.39 0.29 0.22 2.96 0.098
0.42 0.41 0.12 0.21 0.34 0.44 0.17 0.28 0.26 0.33 0.14 0.20 0.23 0.22 0.22 0.26 0.29 0.31 0.33 0.34 0.19 0.27 0.11 0.29 0.40 0.43 0.23 0.28 0.24 0.11 2.39 0.079
0.31 0.24 0.36 0.39 0.23 0.23 0.27 0.36 0.24 0.24 0.11 0.45 0.31 0.29 0.47 0.48 0.38 0.24 0.19 0.18 0.19 0.13 0.13 0.23 0.15 0.22 0.39 0.23 0.17 0.12 2.30 0.076
protein than those in the lowest quintile. Obesity and all types of ADHD were also more prevalent in those in the highest quintile of the fast-food dietary pattern than in those in the lowest quintile. Information on the baseline characteristics and nutrient intakes of children with and without ADHD is presented in Table 4. As indicated in Table 4, the iron, zinc, calcium, vitamin B1, and vitamin B2 intakes were lower in children with ADHD. However, children with ADHD consumed larger amounts of sugar and hydrogenated vegetable oil. Multivariate-adjusted odds ratios for having ADHD across quintile categories of dietary pattern scores are listed in Tables 5 and 6. After controlling for energy intake, those in the highest quintile of the sweet dietary pattern had greater odds for having ADHD (odds ratio 4.05, 95% confidence interval 1.15–15.37). Further adjustment for age, sex, socioeconomic status, and family history of ADHD attenuated the associations but remained significant. We also entered body mass index in the model, but there were no significant changes in the result after adjusting for body mass index. Adherence to the fast-food dietary pattern was also associated with a greater risk of having ADHD even after controlling for potential confounders (3.21, 1.05–10.90). The healthy and Western dietary patterns were not associated with ADHD and its subtypes. No overall significant associations were found the sweet or fast-food dietary pattern and individual subtypes of ADHD. Nutrient-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of the sweet and fast-food dietary pattern scores are listed in Table 7. We provided five additional models in this table for analyzing two patterns (sweet and fast food). Based on the information presented in Tables 5 and 6, only these two models had significant associations with ADHD.
Table 3 Characteristics and dietary intakes of study participants by quintile categories of dietary pattern scores Sweet pattern Q1 (n ¼ 75)
Inattentive Hyperactive– impulsive Combined Obese (%) Current medication use for ADHD (%) Dietary intakes Total energy (kJ/d) Carbohydrate (%total energy) Fat (%total energy) Protein (%total energy) Vitamin C (mg) Vitamin B1 (mg) Vitamin B2 (mg) Vitamin B12 (mg) Calcium (mg) Zinc (mg) Simple Sugars (g) HVO (g)
71
P* 0.19 <0.05 <0.05
38 5
47 6
Q1 (n ¼ 75)
Western pattern
Q3 (n ¼ 75)
91 58 5
0.23 0.09 0.32
49 4
53 5
59 5
0.21 0.13 0.24
Q3 (n ¼ 75)
5
8
16
<0.05
8.4
11.2
11.2
0.06
11.7
9.2
9.2
0.07
1.4 1.3
5 2.0
8 2.6
<0.05 <0.05
2.6 1.3
4 2.6
8 4
<0.05 <0.05
4.5 1.3
6 2.6
6 2.6
0.10 0.17
6.1 1.3
4 2.6
4 2.6
0.11 0.21
1.3 6 3
2.3 8 5
3.5 11 7
<0.05 <0.05 0.08
1.3 7 4
1.3 9 5
4 10 6
<0.05 0.17 0.21
2.6 6 2
2.6 10 6
2.6 11 7
0.43 <0.05 <0.05
4.2 10 6
2.6 9 4
2.6 7 5
0.10 0.09 0.11
5818 53 1
6106 57 1
6299 64 1
0.09 <0.05
5931 58 1
5806 59 1
5989 59 1
5095 54 1
5525 58 1
5630 60 1
0.14 <0.05
5743 56 1
5521 59 1
5638 58 1
0.16 0.22
113 1.8 0.8 1.0 909 7 28 33
34 0.5 0.3 0.3 89 3 3 4
101 1.3 0.7 0.8 729 4 40 41
29 0.4 0.3 0.3 76 2 5 4
98 1.1 0.5 0.7 639 2 51 48
28 0.4 0.2 0.2 69 1 7 6
0.10 0.04 0.18 0.18 0.03 0.04 0.03 0.07
125 1.7 1.0 1.0 921 6 30 28
37 0.5 0.4 0.4 97 3 4 3
99 1.4 0.6 0.7 725 4 36 40
31 0.3 0.3 0.3 75 2 5 3
0.23 0.22
0.03 0.04 0.03 0.13 0.04 0.06 0.02 0.04
86 1.1 0.3 0.8 625 3 55 54
35 0.2 0.2 0.2 70 1 7 5
32 0.8 14 0.4 109 1.4 0.8 1.0 874 5 35 33
39 0.4 0.4 0.4 81 3 5 3
30 0.6 12 0.4 104 1.4 0.6 0.7 740 5 39 40
38 0.3 0.3 0.3 78 2 4 4
30 0.7 11 0.3
0.17 0.23
0.20 0.12 0.09 0.11 0.06 0.12 0.09 0.05
96 1.3 0.6 0.8 659 3 45 50
35 0.3 0.3 0.3 61 1 6 6
31 0.7 13 0.4 98 1.3 0.4 0.6 654 4 59 53
27 0.4 0.1 0.3 59 1 6 5
81
30 0.6 12 0.3 106 1.4 0.7 0.8 737 4 36 42
29 0.5 0.3 0.3 64 3 4 4
91
P
<0.05
31 0.7 10 0.2
71
Q5 (n ¼ 75)
14.1
30 0.7 11 0.3
51 6
81 44 5
Q1 (n ¼ 75)
P
9.3
31 0.6 12 0.3
65 6
0.21 <0.05 0.19
0.19 0.18
71
Q5 (n ¼ 75)
4
0.07 <0.05
91
Healthy pattern
Q3 (n ¼ 75)
49 7
28 0.7 9 0.2
71
Q1 (n ¼ 75)
P
40 4
31 0.7 12 0.3
61
Q5 (n ¼ 75)
91 62 9
33 0.8 14 0.4
81
Q5 (n ¼ 75)
30 0.7 12 0.4
0.27 0.26
0.23 0.17 0.04 0.04 0.05 0.21 0.04 0.03
110 1.5 1.0 1.1 883 5 26 27
31 0.5 0. 0. 80 3 3 2
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
Age (y) Boys (%) Family history of ADHD (%) ADHD (%) ADHD subtype
Fast-food pattern Q3 (n ¼ 75)
ADHD, attention-deficit/hyperactivity disorder; HVO, hydrogenated vegetable oil; Q, quintile Values are presented as mean SD, number, or percentage * Analysis of variance for quantitative variables and chi-square test for qualitative variables.
245
246
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
Table 4 Baseline characteristics and nutrient intakes in children with and without ADHD Variables
Age Boys (%) Low SES (%) Obesity Family history of ADHD (%) Total energy (kJ) Carbohydrate (%total energy) Fat (%total energy) Protein (%total energy) Vitamin C (mg) Vitamin B1 (mg) Vitamin B2 (mg) Vitamin B12 (mg) Calcium (mg) Zinc (mg) Iron (mg) Simple sugars (g) Hydrogenated vegetable oil (g)
Children with ADHD
Children without ADHD
Mean
Mean
SD
7 71 41 10 11 6048 62 30 8 82 0.7 0.3 0.6 611 3 6 55 52
2
4 1423 3 3 2 41 0.3 0.2 0.4 93 1 4 7 10
10 41 19 8 3 5948 54 32 14 106 1.6 1.1 0.7 902 8 12 24 28
P
SD 1
2 533 1 0.7 0.7 29 0.3 0.3 0.3 51 2 3 4 4
0.03 0.02 0.03 0.38 0.04 0.24 0.03 0.19 0.04 0.09 0.02 0.02 0.23 0.04 0.03 0.04 0.02 0.001
ADHD, attention-deficit/hyperactivity disorder; SES, socioeconomic status
In the first model, we adjusted for vitamin intakes. The second model was adjusted for mineral intakes, and the third and fourth models were adjusted for sugar and hydrogenated vegetable oil (the main source of trans fat intake in Iran). The fifth model included all the potential confounders. Adding each of these variables attenuated the model. In the sweet pattern, adding minerals and sugars attenuated the association. In the fast-food pattern, hydrogenated vegetable oil attenuated the association. However, even after adding all the variables, this association remained significant in the sweet and fast-food patterns.
Discussion We identified four major dietary patterns in this group of Iranian children. Just two major dietary patterns, namely sweet and fast food, were significantly associated with ADHD. We found no significant associations between the healthy or Western dietary pattern and ADHD. To our knowledge, this study is the first to link major dietary patterns and the prevalence of ADHD in children. However, there is a cohort study of adolescents that
suggested that ADHD in adolescents is linked to Western diets, which tend to be high in total fat, saturated fat, refined sugar, and sodium [29]. In general, few data on dietary patterns are available from Middle Eastern populations. These populations have their own dietary intake specifics, i.e., a high carbohydrate intake especially in the form of refined grain and a high intake level of hydrogenated fat [30,31]; therefore, dietary pattern analysis in these populations might provide additional information on the relations between diet and disease. The dietary pattern studies conducted in this region have focused mostly on the metabolic syndrome, obesity, and cardiovascular risk factors [29,32–34]. However, these studies have been confined to adult women and no data in children are available. The interaction among food components is an important issue that is taken into account in the dietary pattern approach. In this approach, the investigators investigate an entire diet and its components and different nutrients [35,36]. Previous studies have focused on behavior problems and not ADHD in particular [16–22]. Currently, less epidemiologic research has been performed on the diet and ADHD. Food additives [14,15], refined sugars [16], a low-protein, high-carbohydrate diet [17], and insufficient intakes of vitamins, minerals, amino acids, and essential fatty acids [18–22] have been reported as probable etiologic factors in the incidence of ADHD. However, the role of whole dietary patterns is still unknown. We found that the sweet dietary pattern was significantly associated with the greater risk of ADHD. This dietary pattern was greatly loaded with ice cream, refined grains, sweet desserts, sugar, and soft drinks. The nutrient-adjusted model for ADHD across quintile categories of the sweet dietary pattern revealed that this association was modified by minerals and sugars to some extent. The significant association between the fast-food dietary pattern and ADHD in the present study could also be attributed to the components of this dietary pattern. Processed meat and commercially produced fruit juices, pizza, snacks, sauces, and soft drinks that mainly comprise this pattern contain several additives and are high in refined and added sugars. Adherence to the fast-food dietary pattern may be associated with low intakes of vitamins, minerals, and essential fatty acids. The fast-food pattern is frequently followed by schoolchildren worldwide. Unfortunately, Iran has undergone a nutritional transition caused by a Westernization in lifestyle [37]. The availability of fast foods has extended the related problems [38]. Therefore, besides obesity-related metabolic abnormalities [38],
Table 5 Multivariate adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of sweet and fast-food dietary pattern scores Sweet pattern
ADHD (all types)* Crude Model 1y Model 2z ADHD (inattentive type) Crude Model 1y Model 2z ADHD (hyperactive–impulsive type) Crude Model 1y Model 2z
Fast-food pattern
Q1
Q3
Q5
P for trend
Q1
Q3
Q5
P for trend
1.00 1.00 1.00
2.47 (0.52–11.66) 2.42 (0.57–11.58) 2.29 (0.41–11.47)
4.12 (1.10–15.44) 4.05 (1.15–15.3) 3.95 (1.16–15.3)
0.01 0.02 0.03
1.00 1.00 1.00
1.54 (0.41–5.69) 1.48 (0.36–5.57) 1.33 (0.39–5.50)
3.38 (1.03–11.01) 3.33 (1.06–10.97) 3.21 (1.05–10.90)
0.01 0.03 0.03
1.00 1.00 1.00
2.05 (0.40–10.17) 2.02 (0.42–10.11) 1.96 (0.38–10.04)
3.17 (0.69–14.4) 3.12 (0.73–14.3) 3.04 (0.68–14.3)
0.10 0.11 0.09
1.00 1.00 1.00
2.07 (0.42–10.19) 2.03 (0.47–10.13) 1.94 (0.39–10.07)
3.18 (0.71–14.42) 3.14 (0.75–14.40) 3.07 (0.77–14.32)
0.12 0.11 0.12
1.00 1.00 1.00
2.0 (0.04–83.93) 1.98 (0.09–83.87) 1.93 (0.12–83.59)
2.02 (0.05–83.75) 1.99 (0.08–83.71) 1.91 (0.15–83.57)
0.38 0.32 0.28
1.00 1.00 1.00
2.02 (0.04–84.76) 1.99 (0.07–84.77) 1.92 (0.10–84.68)
3.08 (0.15–60.34) 3.06 (0.17–60.32) 2.99 (0.21–84.73)
0.19 0.21 0.18
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake. z Further adjusted for age, sex, socioeconomic status, and family history of ADHD.
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
247
Table 6 Multivariate-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of Western and healthy dietary pattern scores Western pattern
ADHD (all types)* Crude Model 1y Model 2z ADHD (inattentive type) Crude Model 1y Model 2z ADHD (hyperactive–impulsive type) Crude Model 1y Model 2z
Healthy pattern
Q1
Q3
Q5
P for trend
Q1
Q3
Q5
P for trend
1.00 1.00 1.00
1.43 (0.47–4.34) 1.40 (0.48–4.33) 1.33 (0.55–4.30)
1.43 (0.50–4.35) 1.42 (0.53–4.33) 1.34 (0.58–4.29)
0.18 0.16 0.12
1.00 1.00 1.00
0.75 (0.26–2.13) 0.78 (0.23–2.17) 0.83 (0.27–2.22)
0.75 (0.25–2.11) 0.77 (0.21–2.14) 0.84 (0.28–2.21)
0.19 0.21 0.29
1.00 1.00 1.00
1.35 (0.31–1.15) 1.34 (0.29–1.11) 1.28 (0.23–1.06)
1.34 (0.32–1.13) 1.32 (0.30–1.09) 1.25 (0.39–1.04)
0.28 0.26 0.21
1.00 1.00 1.00
0.73 (0.17–3.12) 0.76 (0.15–3.13) 0.81 (0.19–3.07)
0.75 (0.18–3.10) 0.77 (0.21–3.07) 0.81 (0.27–3.01)
0.22 0.20 0.26
1.00 1.00 1.00
2.02 (0.04–84.77) 1.99 (0.08–84.74) 1.90 (0.13–84.75)
2.04 (0.03–84.7) 2.02 (0.04–87.6) 1.98 (0.09–87.6)
0.31 0.29 0.28
1.00 1.00 1.00
2.01 (0.04–84.6) 2.0 (0.07–84.6) 1.95 (0.11–84.6)
2.02 (0.03–84.76) 1.99 (0.05–84.79) 1.93 (0.04–84.69)
0.27 0.29 0.28
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake. z Further adjusted for age, sex, socioeconomic status, and family history of ADHD.
the present study showed that the fast-food dietary pattern is significantly associated with ADHD. Consumption of the fastfood dietary pattern has been associated with greater intakes of trans fats [39]. Thus, future studies must focus on the association between trans fat consumption and the prevalence of ADHD. Two other dietary patterns, healthy and Western, were identified in this study, but neither pattern was significantly related to the prevalence of ADHD. Although food components of the Western dietary pattern were very similar to the fast-food dietary pattern, the loading factors for these food items were lower in the Western dietary pattern than that in the fast-food dietary pattern. This might explain our finding of a lack of a significant relation between the Western dietary pattern and ADHD. In the present study, we used a factor analysis method that categorized foods according to their loading factors. However, we do not consider the results significant; the odds for having ADHD increased across increasing quintiles of the Western diet. Although there were no significant differences between those in the highest quintile of the Western pattern compared with those in the first quintile, the odds ratio for having ADHD was higher compared with the first quintile. Regarding the healthy pattern, the odds ratios showed a protective effect for this pattern; however, this pattern was not significantly related to ADHD. Some unhealthy food items were
loaded in the healthy pattern, which may be responsible the lack of a significant association between this pattern and ADHD. There have been some reports on the benefits of fish consumption and polyunsaturated fatty acid intake and ADHD. Polyunsaturated fatty acid intake and fish consumption were major components in the healthy pattern. However, Iranians do not consume fish in large amounts. This may have resulted in lowering the loading factor for fish compared with other studies and therefore may be associated with no observable significant relation between the healthy pattern and ADHD. Without considering the significant results, we concluded that the healthy pattern might be protectively related to ADHD and the Western pattern might be associated with an increased risk of ADHD. Consuming more trans fat in the fast-food pattern may be related to the potential mechanisms underlying the observed association between the fast-food pattern and the risk of having ADHD. Furthermore, consuming more sugars in the sweet pattern may be related to the potential mechanisms underlying the observed association between the sweet pattern and the risk of ADHD. However, some intakes of nutrients such as vitamin B1, B2, zinc, iron, and calcium may be associated with the relation between certain dietary patterns and the risk of ADHD. Especially zinc deficiency has been reported in schoolgirls [40]. As a limitation, in the Iranian food composition table, we had no
Table 7 Nutrient-adjusted odds ratios (95% confidence intervals) for ADHD across quintile categories of sweet and fast-food dietary pattern scores Sweet pattern
ADHD (all types)* Model 1y Model 2z Model 3x Model 4k Model 5{
Q1
Q3
1.00 1.00 1.00 1.00 1.00
2.23 2.17 1.97 1.99 1.85
Fast-food pattern Q5 (0.40–11.26) (0.35–11.41) (0.29–11.48) (0.34–11.37) (0.15–15.63)
3.88 3.85 3.78 3.79 3.66
(1.03–15.21) (1.11–15.30) (1.12–15.41) (1.07–15.32) (1.12–15.78)
P for trend
Q1
Q3
0.03 0.04 0.04 0.03 0.04
1.00 1.00 1.00 1.00 1.00
1.30 1.28 1.26 1.12 1.07
Q5 (0.38–5.73) (0.36–5.57) (0.39–5.50) (0.28–5.56) (0.25–5.40)
3.18 3.15 3.16 2.93 2.86
P for trend (1.03–11.01) (1.01–11.07) (1.02–11.15) (1.01–11.10) (0.88–11.16)
0.03 0.03 0.03 0.04 0.04
ADHD, attention-deficit/hyperactivity disorder; Q, quintile * Includes the inattentive type, the hyperactive–impulsive type, and the combined type. y Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus vitamins (B1, B2, and C). z Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus minerals. x Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus sugars. k Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus hydrogenated vegetable oil. { Adjusted for energy intake, age, sex, socioeconomic status, and family history of ADHD (all the mentioned confounders in the last model in Table 5) plus vitamins, minerals, sugars, and hydrogenated vegetable oil.
248
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249
information regarding the trans fat content of different foods. Therefore, in this analysis, we considered the common source of trans fat (hydrogenated vegetable oil) and reported this instead of trans fat. Some points need to be considered in the interpretation of our findings. We used factor analysis to obtain the dietary patterns. Factor analysis is a statistical method used to decrease the number of variables and to categorize the variables into factors [41]. However, several subjective or arbitrary decisions in the use of factor analysis need to be considered. Dietary habits and lifestyle characteristics of Iranian children across different cities may be different from those in the present study [42,43]. Children obtain larger percentages of their energy from snacks, but we did not assess the meal and snack patterns in our study [44]. The present study was confined to school-age children, and ADHD may also be prevalent in preschoolers who may have different dietary patterns. Most preschool children consume their meals and snacks at home or some in the kindergartens, but school-age children may buy some snacks and foods from the school buffet. Thus, they may have a different eating pattern. Our findings can be extrapolated to all school-age children in Tehran because the participants in our study were selected from all socioeconomic districts of Tehran. The validity of the English-language version of the questionnaire for the diagnosis of ADHD has been evaluated, but the Persian version has not been validated. The cross-sectional nature of the study was another major limitation that does not allow cause-and-effect associations. A small percentage of the study population used medications for ADHD. Therefore, their parents were aware of the condition, which may have affected their food choices and any change to their child’s diet. We had no information on the use of a specific diet or a change in the diet because of the ADHD diagnosis. Therefore, any possible changes could influence the results. Limitations of the FFQ for assessing dietary intakes should also be taken into account. Although we controlled for the effect of potential confounders in the statistical methods, residual confounding because of unknown confounding factors cannot be excluded. Future recommendations could include extending confounders to parenting styles. Regarding the representativeness of the discussed dietary patterns in Iranian children, in Iran most children consume foods with their parents. The dietary patterns described in the present study are also seen in adults [32–34,45] and the results are in line with other studies of the dietary patterns in Iranian adolescents [46]. The resultant pattern in the present study is somewhat similar to the recently published patterns in Tehranian adults [45]. However, the present study was conducted in Tehranian children and the described pattern may be specific to Tehranian children and not all Iranian children and children in rural areas. According to the different eating patterns in rural areas, the present patterns may not be representative for all Iranian children. Therefore, this may be a limitation of the present study. In conclusion, our study showed that a greater adherence to the fast-food and sweet dietary patterns was associated with a higher prevalence of ADHD in Iranian children. Prospective studies are required to confirm these findings. References [1] American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000. [2] Biederman J, Faraone SV. Attention-deficit hyperactivity disorder. Lancet 2005;366:237–48.
[3] Kidd PM. Attention deficit/hyperactivity disorder (ADHD) in children: rationale for its integrative management. Altern Med Rev 2000;5:402–28. [4] Andersen SL, Teicher MH. Sex differences in dopamine receptors and their relevance to ADHD. Neurosci Biobehav Rev 2000;24:137–41. [5] Faraone SV. The scientific foundation for understanding attention-deficit/ hyperactivity disorder as a valid psychiatric disorder. Eur Child Adolesc Psychiatry 2005;14:1–10. [6] Froehlich TE, Lanphear BP, Epstein JN, Barbaresi WJ, Katusic SK, Kahn RS. Prevalence, recognition, and treatment of attention-deficit/hyperactivity disorder in a national sample of US children. Arch Pediatr Adolesc Med 2007;161:857–64. [7] Martel MM, Nigg JT. Child ADHD and personality/temperament traits of reactive and effortful control, resiliency and emotionality. J Child Psychol Psychiatry 2006;47:1175–83. [8] Harpin VA. The effect of ADHD on the life of an individual, their family, and community from preschool to adult life. Arch Dis Child 2005;90S:i2–7. [9] Riley AW, Spiel G, Coghill D, Döpfner M, Falissard B, Lorenzo MJ, et al, ADORE Study Group. Factors related to Health-Related Quality of Life (HRQoL) among children with ADHD in Europe at entry into treatment. Eur Child Adolesc Psychiatry 2006;15:i38–45. [10] Hebrani P, Abdolahian E, Behdani F, Vosoogh I, Javanbakht A. The prevalence of attention deficit hyperactivity disorder in preschool-age children in Mashhad, north-east of Iran. Arch Iran Med 2007;10:147–51. [11] Talaei A, Mokhber N, Abdollahian E, Bordbar MR, Salari E. Attention deficit/hyperactivity disorder: a survey on prevalence rate among male subjects in elementary school (7 to 9 years old) in Iran. J Atten Disord 2010; 13:386–90. [12] Ghanizadeh A. Distribution of symptoms of attention deficit-hyperactivity disorder in schoolchildren of Shiraz, south of Iran. Arch Iran Med 2008;11:618–24. [13] Thomas CL. Taber’s cyclopedic medical dictionary. 16th ed. Philadelphia, PA: F. A. Davis; 1989. p. 825. [14] McCann D, Barrett A, Cooper A, Crumpler D, Dalen L, Grimshaw K, et al. Food additives and hyperactive behaviour in 3-year-old and 8/9-year-old children in the community: a randomised, double-blinded, placebocontrolled trial. Lancet 2007;370:1560–7. [15] Sinn N. Nutritional and dietary influences on attention deficit hyperactivity disorder. Nutr Rev 2008;66:558–68. [16] Schardt D. Diet and behavior in children. Nutr Action Health Lett 2000;27:10–1. [17] Kidd PM. Attention deficit/hyperactivity disorder (ADHD) in children: rationale for its integrative management. Altern Med Rev 2000;5:402–28. [18] DiGirolamo AM, Ramirez-Zea M. Role of zinc in maternal and child mental health. Am J Clin Nutr 2009;89:940S–5S. [19] Kozielec T, Starobrat-Hermelin B. Assessment of magnesium levels in children with attention deficit hyperactivity disorder (ADHD). Magnes Res 1997;10:143–8. [20] Sinn N, Bryan J, Wilson C. Cognitive effects of polyunsaturated fatty acids in children with attention deficit hyperactivity disorder symptoms: a randomised controlled trial. Prostaglandins Leukot Essent Fatty Acids 2008;78:311–26. [21] Bornstein RA, Baker GB, Carroll A, King G, Wong JT, Douglass AB, et al. Plasma amino acids in attention deficit disorder. Psychiatry Res 1990;33:301–6. [22] Greenblatt J. Nutritional supplements in ADHD. J Am Acad Child Adolesc Psychiatry 1999;38:1209–11. [23] Newby PK, Muller D, Hallfrisch J, Andres R, Tucker KL. Food patterns measured by factor analysis and anthropometric changes in adults. Am J Clin Nutr 2004;80:504–13. [24] Newby PK, Muller D, Tucker KL. Associations of empirically derived eating patterns with plasma lipid biomarkers: a comparison of factor and cluster analysis methods. Am J Clin Nutr 2004;80:759–67. [25] Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240–3. [26] American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994. [27] Azadbakht L, Atabak S, Esmaillzadeh A. Soy protein intake, cardio-renal indices and C-reactive protein in type 2 diabetes with nephropathy: a longitudinal randomized clinical trial. Diabetes Care 2008;3:648–54. [28] Kim J-O, Mueller CW. Factor analysis: statistical methods and practical issues. Thousand Oaks, CA: Sage Publications; 1978. [29] Howard AL, Robinson M, Smith GJ, Ambrosini GL, Piek JP, Oddy WH. ADHD is associated with a ‘Western’ dietary pattern in adolescents. J Atten Disord 2011;15:403–11. [30] Azadbakht L, Esmaillzadeh A. Dietary diversity score is related to obesity and abdominal adiposity among Iranian female youth. Public Health Nutr 2011;14:62–9. [31] Azadbakht L, Esmaillzadeh A. Dietary and non-dietary determinants of central adiposity among Tehrani women. Public Health Nutr 2008;11:528–34. [32] Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary patterns and markers of systemic inflammation among Iranian women. J Nutr 2007;137:992–8.
L. Azadbakht, A. Esmaillzadeh / Nutrition 28 (2012) 242–249 [33] Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary patterns, insulin resistance, and prevalence of the metabolic syndrome in women. Am J Clin Nutr 2007;85:910–8. [34] Esmaillzadeh A, Azadbakht L. Food intake patterns may explain the high prevalence of cardiovascular risk factors among Iranian women. J Nutr 2008;138:1469–75. [35] Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc 2004;104:615–35. [36] Jacobs DR Jr, Steffen LM. Nutrients, foods, and dietary patterns as exposures in research: a framework for food synergy. Am J Clin Nutr 2003;78(3 suppl):508S–13S. [37] Ghassemi H, Harrison G, Mohammad K. An accelerated nutrition transition in Iran. Public Health Nutr 2002;5:149–55. [38] Azadbakht L, Esmaillzadeh A. Fast foods and risk of chronic diseases. J Res Med Sci 2008;13:1–2. [39] Asgary S, Nazari B, Sarrafzadegan N, Saberi S, Azadbakht L, Esmaillzadeh A. Fatty acid composition of commercially available Iranian vegetable oils. J Res Med Sci 2009;14:211–5.
249
[40] Tupe R, Chiplonkar SA. Diet patterns of lactovegetarian adolescent girls: need for devising recipes with high zinc bioavailability. Nutrition 2010;26:390–8. [41] Kim JO, Mueller CW. Factor analysis: statistical methods and practical issues. Thousand Oaks, CA: Sage Publications; 1978. [42] Azadbakht L, Mirmiranr R, Azizi F. Predictors of cardiovascular risk factors in Tehranian adults: diet and lifestyle. East Mediterr Health J 2006;12:88–97. [43] Azadbakht L, Mirmiran P, Hosseini F, Azizi F. Diet quality status of most Tehranian adults needs improvement. Asia Pac J Clin Nutr 2005;14:163–8. [44] Tseng M. Validation of dietary patterns assessed with a food frequency questionnaire [letter]. Am J Clin Nutr 1999;70:422. [45] Rezazadeh A, Rashidkhani B, Omidvar N. Association of major dietary patterns with socioeconomic and lifestyle factors of adult women living in Tehran, Iran. Nutrition 2010;26:337–41. [46] Alizadeh M, Mohtadinia J, PourghasemGargari B, Esmaillzadeh A. Major dietary patterns among Iranian adolescents [in Farsi]. Med J Tabriz Univ Med Sci 2009;31:63–9.