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Dietary Factors Associated with Attention Deficit Hyperactivity Disorder (ADHD) in School-aged Children

Dietary Factors Associated with Attention Deficit Hyperactivity Disorder (ADHD) in School-aged Children

Article information

Korean J Community Nutr. 2018;23(5):397-410
Publication date (electronic) : 2018 October 31
doi : https://doi.org/10.5720/kjcn.2018.23.5.397
1Graduate School of Kyung Hee University, Seoul, Korea, Student.
2Department of Food and Nutrition, Kyung Hee University, Seoul, Korea, Researcher.
3Department of Food and Nutrition, Sahmyook University, Seoul, Korea, Professor.
4Department of Preventive Medicine, Dankook University College of Medicine, Cheonan, Korea, Professor.
5Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea, Professor.
6Department of Pediatrics, Childhood Asthma Atopy Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea, Professor.
7Department of Food and Nutrition, Kyung Hee University, Seoul, Korea, Professor.
Corresponding author: Se-Young Oh. Department of Food and Nutrition, College of Human Ecology, Kyunghee University, Seoul 02447, Dongdaemun-gu, Korea. Tel: (02) 961-0602, Fax: (02) 959-0649, seyoung@khu.ac.kr
Received 2018 July 31; Revised 2018 September 07; Accepted 2018 September 07.

Abstract

Objectives

An association between dietary patterns and mental health in children has been suggested in a series of studies, yet detailed analyses of dietary patterns and their effects on ADHD (attention deficit hyperactivity disorder) are limited.

Methods

We included 4569 children who had dietary intake data as part of the CHEER (Children's Health and Environmental Research) study conducted nationwide from 2005 to 2010. We assessed ADHD (Attention Deficit Hyperactivity Disorder) by the DuPaul's ADHD Rating Scales and dietary intake by a semi-quantitative food frequency questionnaire. Using intake data, we constructed five dietary patterns: “Plant foods & fish,” “Sweets,” “Meat & fish,” “Fruits & dairy products,” and “Wheat based.”

Results

The overall proportion of ADHD was 12.3%. Boys (17.8%) showed a higher rate of ADHD than girls (6.5%). The total intake of calories (85 kcal) and plant fat (2g) in the ADHD group was significantly higher than that of the normal group. ADHD was significantly negatively associated with dietary habits such as having breakfast and meal frequency, and positively associated with eating speed, unbalanced diet, overeating, and rice consumption. Regarding dietary patterns, the “Sweets” category was relevant to high ADHD risk (OR 1.59, 95% CI: 1.18, 2.15 for Q5 vs. Q1) in a linear relationship. An inverse, non-linear association was found between “Fruits & dairy products” and ADHD (OR 0.55, 95% CI: 0.39, 0.76 for Q4 vs. Q1).

Conclusions

Our study confirms both positive and negative associations between diet and ADHD in elementary school age children. Moreover, linear or nonlinear associations between diet and ADHD draw attention to the possible threshold role of nutrients. Further studies may consider characteristics of diet in more detail to develop better intervention or management in terms of diet and health.

Acknowledgments

This research was supported by the Ministry of Environment, Korea.

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Article information Continued

Funded by : Ministry of Environmenthttps://doi.org/10.13039/501100003562

Fig. 1

Flow diagram of the study

Table 1

Food grouping used in the dietary pattern analysis

Table 1

Table 2

Percentage of children who diagnosed with attention deficit hyperactivity disorder (ADHD) and the subtypes of ADHD

Table 2

1) Abbrebiations: AD + HD = Attention deficit + Hyperactivity disorder, AD = Attention deficit, HD = Hyperactivity disorder

Table 3

General characteristics of the study participants by group (N=4,569)

Table 3

Table 4

Nutrients intakes assessed by semi-food frequency questionnaire (SFFQ) by group

Table 4

1) Analysis by T-test

2) Significantly different by student's t-test between ADHD and normal group (p<0.05)

3) Values are means ± SD

Table 5

Distribution of eating behaviors by group (N=4,569)

Table 5

1) chi-square test

Table 6

Factor loadings1) for the five dietary patterns derived from semi-food frequency questionnaire (SFFQ)

Table 6

1) Factor loadings ≥0.3 or ≤−0.3 are shown in bold and shaded

Table 7

Correlation coefficients of daily nutrient intakes and five dietary pattern (N=4,926)1)

Table 7

1) Adjusted for age as continuous variables and gender as categorical variables. Significantly different at *: P<0.05 and **: P<0.01

2) Values were shaded, if not significant (p<0.05)

Table 8

Daily nutrient intakes1) of Q1 and Q52) by the quintile of dietary pattern scores(N=4,926)

Table 8

1) Adjusted for age, gender, energy intake

2) Q1–Q5 : The values which estimated nutrient intakes from SFFQ divided into quintile categories. Q1 : the lowset, O5 : the highest

3) In each cell, value were shaded when Q1 is higher than Q5, if significant (p<0.001)

Table 9

Odds ratio of Dietary patterns1) on ADHD and subtypes of ADHD

Table 9

1) Adjusted for area, age, gender, married status, father education and passive smoking

2) Abbrebiations: AD + HD=Attention deficit + Hyperactivity disorder

AD = Attention deficit

HD = Hyperactivity disorder