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Child and Adolescent Psychiatry and Mental Health
Erschienen in: Child and Adolescent Psychiatry and Mental Health 1/2017

Open Access 01.12.2017 | Research Article

Dietary behaviour, psychological well-being and mental distress among adolescents in Korea

verfasst von: Seo Ah Hong, Karl Peltzer

Erschienen in: Child and Adolescent Psychiatry and Mental Health | Ausgabe 1/2017

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Abstract

Background

Dietary intake is important for physical and mental health. The aim of this investigation was to assess associations between dietary behaviours and psychological well-being and distress among school-going adolescents in Korea.

Methods

In a cross-sectional nationally representative survey, 65,212 students (Mean age = 15.1 years, SE = 0.02 and 52.2% male and 47.8% female) responded to a questionnaire that included measures of dietary behaviour, psychological well-being and mental distress.

Results

In logistic regression analyses, adjusted for age, sex, socioeconomic status, school level, school types, Body Mass Index, physical activity, and substance use, positive dietary behaviours (regular breakfast, fruit, vegetable, and milk consumption) were positively and unhealthy dietary behaviours (intake of caffeine, soft drinks, sweet drinks and fast food consumption) were negatively associated with self-reported health, happiness and sleep satisfaction. Positive dietary behaviours (regular breakfast, fruit, vegetable, and milk consumption) were negatively associated with perceived stress and depression symptoms. Unhealthy dietary behaviours (consumption of fast food, caffeine, sweetened drinks and soft drinks) were associated with perceived stress and depression symptoms.

Conclusions

The study found strong cross-sectional evidence that healthy dietary behaviours were associated with lower mental distress and higher psychological well-being. It remains unclear, if a healthier dietary behaviour is the cause or the sequela of a more positive well-being.
Abkürzungen
BMI
Body Mass Index
KYRBS
Korea Youth Risk Behavior Web-based Survey

Background

Recently, more studies have been trying to link dietary behaviour to psychological well-being and distress [1‐6]. Regular fruit, vegetable and breakfast intake (healthy dietary behaviours) have been found positively associated with self-reported health, happiness, and better sleep [1‐8], and regular fruit, vegetable and breakfast intake were negatively associated with perceived stress, mental distress and depression [1‐3, 9‐25]. Further, specific unhealthy dietary behaviours (consumption of soft drinks, fast food, sweets and snacks, skipping breakfast, and caffeine) were associated with unhappiness, perceived stress, mental or psychological distress, depression or poorer sleep [5, 8, 19, 24‐36]. Mixed results were found in relation to the consumption of milk and psychological well-being. One study found that increased milk product consumption was associated with depression [37], Meyer et al. [38] found milk consumption improves sleep quality, and Aizawa et al. [39] found that the frequency of fermented milk consumption was associated with higher Bifidobacterium counts and that patient with major depressive disorder have lower Bifidobacterium and/or Lactobacillus counts.
In a study among Iranian children and adolescents junk food consumption (such as fast foods, sweets, sweetened beverages, and salty snacks) was significantly associated with mental distress, including “worry, depression, confusion, insomnia, anxiety, aggression, and feelings of being worthless.” [26] Fast food consumption was associated with depression among adolescent girls in Korea [32], and among Chinese adolescents, snack consumption was associated with psychological symptoms [34]. The poor nutrient content of junk or fast foods may have an effect on normal brain functioning and, thus, have an effect on negative mood via the synthesis of neurotransmitters such as serotonin [40, 41]. In a study among adolescents in Norway, a J-shaped relationship between soft drink consumption and mental distress was found [42]. The effects of soft drink or sugar consumption on mental health may be mediated through other nutritional or behavioural factors [42]. Among secondary school students in Malaysia, regular breakfast consumption was negatively associated with mild or moderate stress [23]. In a large study of adolescent school-going children (N = 3071) from the United Kingdom, positive relationships between caffeine consumption and anxiety and depression were found [33]. It is possible that students used caffeinated products to cope with stress [33, 43].
We have limited information on the relationship between dietary behaviour, psychological well-being and mental distress among adolescents in Asia, which prompted this study. It was hypothesized that healthy dietary behaviour enhances psychological well-being and reduces mental distress, and unhealthy dietary behaviours reduce psychological well-being and increase mental distress.

Methods

Data sources

The data utilized for this study came from the 2016 12th “Korea Youth Risk Behavior Web-based Survey (KYRBS)” [44]. The KYRBS is an annual anonymous online self-reported cross-sectional survey on various health behaviours that uses a stratified cluster sampling procedure to source middle and high school students that are representative of the adolescent school population in Korea [44], more details under [44]. The online survey was administered during class after survey instructions had been given and written informed consent had been obtained [44]. In 2016, the survey included a total of 798 schools, and a total of 65,528 respondents participated, resulting in a response rate of 96.4% [44].

Measures

Three assessment measures of psychological well-being (self-rated health, happiness, and sleep satisfaction) and two questions on mental distress (perceived stress and depression symptoms) were used in this study.
Self-rated health was assessed with the question: “How healthy do you usually feel?” (Response option ranged from 1 = very healthy to 5 = very unhealthy) [44]. Responses were dichotomized into 1 or 2 = above average health and 3–5 = an average or below average health.
Perceived happiness was measured with the question: “How happy do you usually feel?” (Response options: (1) very happy, (2) happy, (3) average, (4) unhappy, or (5) very unhappy) [44]. Responses were dichotomized into 1–2 = above average happiness and 3–5 = average or below average happiness.
Sleep satisfaction was assessed with the question, “In the past 7 days, did you get adequate sleep to overcome fatigue?” (Response options ranged from 1 = Sufficient to 5 = Not sufficient at all) [44]. Responses were dichotomized into 1–2 = above average sufficient sleep and 3–5 = average or below average sufficient sleep.
Perceived stress was assessed with the question, “To what degree are you usually stressed?” (Response options arranged from 1 = very much to 5 = not at all) [44]. Responses were dichotomized into 1–2 = above average stress and 3–5 = average or below average stress.
Depression symptoms were assessed with the question, “Have you experienced sadness or despair to the degree that you stopped your daily routine for the recent 12 months?” (Response option, “Yes” or “No”) [44].

Dietary behaviours

To evaluate dietary behaviours, the regularity of breakfast meal time consumed over the past 7 days was surveyed with eight scales from 0 to 7 days. For food groups consumed over the past 7 days, the participants were asked the frequency of seven food groups, such as (1) soft drinks, (2) highly caffeinated drinks, (3) sweetened drinks, (4) fast food foods (such as pizza, hamburgers, or chicken), (5) fruits (not fruit juices), (6) vegetable dishes (excluding Kimchi), and (7) milk consumption during the past 7 days and the responses were from 1 = none, 2 = 1–2 times/week, 3 = 3–4 times/week, 4 = 5–6 times/week, 5 = once/day, 6 = twice/day, and 7 = 3 times or more/day [44].

Control variables

Sociodemographic variables included gender, age, geolocality (rural area, small or large city), maternal and paternal educational level, perceived socioeconomic status (SES), types of school (Boys only, girls only and mixed), school level (middle school and high school) [44].
The Body Mass Index (BMI) of students was calculated by dividing their self-reported weight in kilogrammes by their height in meters squared (kg/m2). According to age and gender, the students were categorized into “underweight (< 5th percentile), normal weight (5th ≤ BMI < 85th percentile), overweight (85th ≤ BMI < 95th percentile), and obese (≥ 95th percentile)”, following the BMI cut-off criteria set for Korean children by the 2007 Korean Growth Charts [45].
Physical activity was assessed in terms of the frequency of physical activity of ≥ 60 min per day during the past 7 days [44]. Responses were categorised into 1 = no days, 2 = 1–2 days, and 3 = 3–7 days.
Lifetime alcohol and tobacco use was measured with the questions, “Have you ever used alcohol?” and “Have you ever used tobacco?” (Response option, “Yes”, “No”) [44].

Data analysis

Descriptive statistics were used to present the proportion or mean of general subject characteristics and outcome variables. Logistic regression tests were performed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) after adjustment for selected covariates. Logistic regression analyses were conducted to calculate the association between the adolescents’ well-being and mental distress variables as the main outcome variables and dietary behaviour variables after adjustment for covariates selected from bivariate association analysis with outcome variables. All analyses conducted took the sampling design parameters, weighting, clustering, and stratification of the study survey into account. All values were weighted according to the participant’s probability of being chosen by sex-, grade-, and school type-specific distributions for the study region [46]. The “finite population correction (fpc) factor was used to avoid the overestimation, when developing variance estimates for population parameters” [47]. All statistical analyses was done by SAS 9.3 (SAS Institute, Cary, NC).

Results

Sample characteristics

The sample included 65,528 school-going adolescents (Mean age = 15.1 years, SE = 0.02; age range 12–18 years) from Korea. More than half of the sample (52.2%) were male, attended high school (54.6%), and a mixed school (62.0%). More than one-third (37.2%) of the students perceived to have a high or high-middle socioeconomic status, 63.4 and 56.0% had a father and had a mother, respectively, with college or higher education. Overall, 17.3% of the students were overweight or obese, 31.3% engaged in 60 min or more physical activity 3–4 times a week, 14.8% ever smoked and 38.8% ever drank alcohol (see Table 1).
Table 1
General characteristics of study participants
 
Unweighted frequency
Weighted %
Sex
 Boys
33,803
52.2
 Girls
31,725
47.8
 Age (years), mean (sd)
65,212
15.1 (0.02)
BMI
 Thinness (< 5th percentile)
3586
5.7
 Normal weight (5th ≤ BMI < 85th percentile)
48,979
77.0
 Overweight (85th ≤ BMI < 95th percentile)
2994
4.5
 Obesity (≥ 95th percentile)
8182
12.8
School
 High school
33,309
54.6
 Middle school
32,219
45.4
Types of school
 Mixed
41,445
62.0
 Boys only
12,032
19.3
 Girls only
12,051
18.7
Paternal education level
 High school or less
19,610
36.6
 College or higher
31,977
63.4
Maternal education level
 High school or less
23,497
44.0
 College or higher
28,860
56.0
Perceived socio-economic status
 High/high-middle
24,244
37.2
 Middle
31,056
47.3
 Low-middle/Low
10,228
15.6
Place of residence
 Rural area
4856
5.8
 Large city
29,046
43.3
 Medium-sized city
31,626
50.8
Physical activity (≥ 60 min)
 No
23,817
36.8
 1–2/week
20,859
32.0
 3+/week
20,852
31.3
 Ever smoking in lifetime (yes)
9511
14.8
 Ever alcohol drinking in lifetime (yes)
24,804
38.8
All values are presented as weighted Mean (SD) or weighted % as appropriate

Prevalence of well-being and mental distress indicators

Regarding well-being indicators, 26.5% of the students perceived themselves to be “very healthy”, 28.1% as “very happy” and 25.8% had sufficient or quite sufficient sleep satisfaction. In terms of mental distress, 37.3% of students reported somewhat or very much “perceived stress”, while 25.5% reported depression symptoms (see Table 2).
Table 2
Prevalence of mental health among adolescents
 
Unweighted Frequency
Weighted  %
1. Well-being outcomes
 Perceived health
  Very healthy
17,586
26.5
  Healthy
29,647
45.3
  Fair
14,223
21.9
  Poor
3846
6.0
  Very poor
226
0.4
 Perceived happiness
  Very happy
18,992
28.1
  Happy
24,964
38.5
  Fair
16,743
25.8
  Unhappy
4102
6.4
  Very unhappy
727
1.1
 Sleep satisfaction (Fatigue recovery from sleep)
  Quite sufficient
5413
7.8
  Sufficient
12,081
18.0
  So So
20,705
31.7
  Not sufficient
18,296
28.4
  Not sufficient at all
9033
14.1
2. Mental distress outcomes
 Perceived stress
  Very much
6513
10.0
  Somewhat
17,833
27.3
  Average
28,021
42.9
  Not so much
10,772
16.2
  Not at all
2389
3.6
 Signs and symptoms of depression during the last year
  No
48,993
74.5
  Yes
16,535
25.5
All values are presented as weighted %

Associations between dietary behaviours with well-being and mental distress indicators

Tables 3 and 4 describe the bivariate associations with well-being and mental distress indicators, and Table 5 the adjusted analysis with well-being and mental distress indicators. In logistic regression analysis, adjusted for potential confounders, positive dietary behaviours (fruit and vegetable consumption, daily breakfast, milk consumption) were positively and unhealthy dietary behaviours (intake of caffeine, soft drinks, sweet drinks and fast food) were negatively associated with happiness or sleep satisfaction or self-reported health. Positive dietary behaviours (fruit and vegetable consumption, having daily breakfast, and milk consumption) were negatively associated with perceived stress and depression symptoms. Unhealthy dietary behaviours (fast food, caffeine, sweetened drinks and soft drinks consumption) were positively associated with perceived stress and depression symptoms (see Tables 3, 4, 5).
Table 3
Association between covariates and mental health among adolescents
 
Well-being outcomes
Mental distress outcomes
Perceived health
Perceived happiness
Sleep satisfaction
Perceived stress
Depression
Bad
Good
p-value
Unhappy
Happy
p-value
Insufficient
Sufficient
p-value
Less
Much
p-value
No
Yes
p-value
Sex (boys)
43.2
55.7
< .0001
47.2
54.7
< .0001
47.7
64.8
< .0001
57.9
42.5
< .0001
55.4
42.7
< .0001
Age (years), mean (SD)
15.4 (0.02)
15.0 (0.02)
< .0001
15.4 (0.02)
15.0 (0.02)
< .0001
15.3 (0.02)
15.0 (0.03)
< .0001
15.0 (0.02)
15.3 (0.02)
< .0001
15.0 (0.02)
15.3 (0.02)
< .0001
BMI
 Normal weight
71.4
79.2
< .0001
76.3
77.4
0.008
77.3
76.2
0.0239
77.8
75.6
< .0001
77.0
77.1
0.3670
 Thinness
7.3
5.1
 
5.8
5.6
 
5.6
6.0
 
5.8
5.5
 
5.8
5.5
 
 Overweight/obesity
21.3
15.7
 
18.0
17.0
 
17.1
17.9
 
16.4
18.8
 
17.2
17.5
 
School level
 High school
62.3
51.6
< .0001
62.4
50.7
< .0001
60.0
39.2
< .0001
51.9
59.2
< .0001
52.9
59.5
< .0001
 Middle school
37.7
48.4
 
37.6
49.3
 
40.0
60.8
 
48.1
40.8
 
47.1
40.5
 
Types of school
 Mixed
60.8
62.5
< .0001
61.1
62.5
< .0001
60.6
66.1
< .0001
62.6
61.0
< .0001
61.8
62.6
< .0001
 Boys only
16.8
20.3
 
18.0
19.9
 
18.5
21.4
 
21.3
15.9
 
20.7
15.2
 
 Girls only
22.4
17.2
 
21.0
17.6
 
20.9
12.5
 
16.0
23.2
 
17.5
22.1
 
Paternal education level
 High school or less
39.8
35.3
< .0001
39.4
35.2
< .0001
37.4
34.1
< .0001
35.7
37.9
< .0001
36.4
37.1
0.1642
 College or higher
60.2
64.7
 
60.6
64.8
 
62.6
65.9
 
64.3
62.1
 
63.6
62.9
 
Maternal education level
 High school or less
47.9
42.5
0.0009
47.4
42.4
< .0001
45.3
40.3
< .0001
42.9
45.8
< .0001
44.0
44.2
0.7602
 College or higher
52.1
57.5
 
52.6
57.6
 
54.7
59.7
 
57.1
54.2
 
56.0
55.8
 
Socio-economic status
 High/upper middle
27.3
41.0
< .0001
26.4
42.6
< .0001
34.6
44.5
< .0001
39.1
33.8
< .0001
38.0
34.6
< .0001
 Middle
50.1
46.1
 
50.4
45.7
 
48.5
43.7
 
48.2
45.7
 
48.1
44.7
 
 Lower middle/Low
22.6
12.8
 
23.2
11.7
 
16.9
11.8
 
12.7
20.5
 
13.8
20.8
 
Place of residence
 Rural area
5.4
6.0
0.0016
5.6
6.0
0.006
5.7
6.3
0.2566
5.7
6.1
0.1621
38.0
34.6
< .0001
 Large city
42.0
43.8
 
42.2
43.9
 
43.3
43.3
 
43.8
42.6
 
48.1
44.7
 
 Medium-sized city
52.6
50.1
 
52.2
50.1
 
51.0
50.4
 
50.5
51.3
 
13.8
20.8
 
Physical activity (≥ 60 min)
 No
42.9
34.3
< .0001
41.0
34.7
< .0001
37.6
34.3
< .0001
35.8
38.4
< .0001
37.2
35.6
0.0011
 1–2/week
34.6
30.9
 
32.7
31.6
 
32.8
29.6
 
31.2
33.3
 
31.6
33.1
 
 3+/week
22.5
34.7
 
26.4
33.7
 
29.6
36.0
 
33.1
28.3
 
31.3
31.3
 
 Ever smoking (yes)
15.7
14.5
0.0013
17.7
13.4
< .0001
15.9
11.9
< .0001
13.9
16.4
< .0001
12.9
20.4
< .0001
 Ever alcohol drinking (yes)
42.0
37.5
< .0001
44.4
36.0
< .0001
41.7
30.4
< .0001
36.2
43.1
< .0001
35.5
48.3
< .0001
All values are presented as weighted mean ± SD or weighted % as appropriate
Table 4
Association between dietary behaviours and mental health among adolescents
Weighted %
Well-being outcomes
Mental distress outcomes
Perceived health
Perceived happiness
Sleep satisfaction
Perceived stress
Depression
Poor
Good
p-value
Unhappy
Happy
p-value
Insufficient
Sufficient
p-value
Less
Much
p-value
No
Yes
p-value
Breakfast
 0 day
14.9
16.8
14.1
< .0001
17.2
13.7
< .0001
15.5
13.1
< .0001
13.7
16.8
< .0001
14.3
16.7
< .0001
 1 day
6.0
7.0
5.6
 
6.9
5.5
 
6.3
5.0
 
5.6
6.6
 
5.6
6.9
 
 2 days
7.4
8.4
7.0
 
8.4
6.9
 
7.7
6.4
 
6.9
8.2
 
6.9
8.6
 
 3 days
7.5
8.0
7.3
 
8.5
7.0
 
7.8
6.8
 
7.2
8.1
 
7.3
8.0
 
 4 days
6.5
7.3
6.2
 
6.6
6.5
 
6.8
5.7
 
6.4
6.7
 
6.3
7.1
 
 5 days
10.7
11.7
10.3
 
11.2
10.4
 
11.2
9.1
 
10.5
10.9
 
10.5
11.2
 
 6 days
8.6
8.3
8.8
 
8.3
8.8
 
8.9
7.9
 
8.8
8.4
 
8.7
8.6
 
 7 days
38.4
32.6
40.8
 
33.0
41.2
 
35.8
46.0
 
40.9
34.3
 
40.3
32.9
 
Soft drinks
 I did not drink
24.2
24.5
24.1
< .0001
24.3
24.1
< .0001
23.8
25.2
< .0001
24.1
24.4
< .0001
24.8
22.4
< .0001
 1–2 times/week
48.7
47.0
49.4
 
46.7
49.8
 
48.7
49.0
 
49.7
47.1
 
49.4
46.7
 
 3–4 times/week
18.9
19.1
18.7
 
19.3
18.6
 
19.1
18.3
 
18.8
19.0
 
18.4
20.3
 
 5–6 times/week
4.3
4.7
4.2
 
4.9
4.0
 
4.5
3.9
 
4.0
4.8
 
4.0
5.2
 
 Once/day
2.0
2.3
1.9
 
2.4
1.9
 
2.0
2.0
 
1.8
2.4
 
1.9
2.5
 
 Twice/day
0.9
1.1
0.8
 
1.1
0.8
 
1.0
0.7
 
0.8
1.0
 
0.8
1.2
 
 3+ times/day
0.9
1.3
0.8
 
1.3
0.8
 
1.0
0.8
 
0.7
1.3
 
0.7
1.5
 
Highly caffeinated drink
 I did not drink
86.2
83.4
87.3
< .0001
83.0
87.8
< .0001
85.2
89.2
< .0001
88.4
82.5
< .0001
88.1
80.7
< .0001
 1–2 times/week
9.9
11.2
9.3
 
11.4
9.1
 
10.4
8.2
 
8.7
11.8
 
8.9
12.7
 
 3–4 times/week
2.2
2.8
2.0
 
3.1
1.8
 
2.5
1.5
 
1.6
3.2
 
1.8
3.4
 
 5–6 times/week
0.8
1.0
0.7
 
1.1
0.6
 
0.8
0.6
 
0.6
1.0
 
0.6
1.4
 
 Once/day
0.5
0.8
0.4
 
0.8
0.4
 
0.6
0.2
 
0.3
0.8
 
0.4
1.0
 
 Twice/day
0.2
0.4
0.1
 
0.3
0.1
 
0.2
0.1
 
0.1
0.3
 
0.1
0.4
 
 3+ times/day
0.2
0.3
0.2
 
0.3
0.2
 
0.2
0.2
 
0.2
0.4
 
0.1
0.5
 
Sweetened drinks
 I did not drink
15.4
15.1
15.5
< .0001
15.5
15.4
< .0001
14.4
18.2
< .0001
16.0
14.5
< .0001
16.3
12.8
< .0001
 1–2 times/week
43.2
41.3
43.9
 
41.5
44.0
 
42.6
44.7
 
44.6
40.8
 
44.2
40.3
 
 3–4 times/week
26.4
26.4
26.5
 
26.6
26.4
 
27.0
24.7
 
26.1
27.1
 
25.8
28.5
 
 5–6 times/week
8.0
8.7
7.7
 
8.5
7.7
 
8.4
6.6
 
7.4
8.9
 
7.6
9.2
 
 Once/day
4.3
4.9
4.0
 
4.5
4.1
 
4.5
3.5
 
3.8
5.0
 
3.9
5.2
 
 Twice/day
1.5
1.9
1.4
 
1.8
1.4
 
1.7
1.1
 
1.2
2.1
 
1.3
2.3
 
 3+ times/day
1.2
1.7
1.0
 
1.5
1.0
 
1.2
1.1
 
0.9
1.7
 
1.0
1.8
 
Fast foods
 I did not eat
22.8
21.9
23.2
< .0001
22.3
23.1
< .0001
21.8
25.9
< .0001
23.4
22.0
< .0001
23.7
20.3
< .0001
 1–2 times/week
60.4
59.1
61.0
 
58.7
61.3
 
60.6
60.0
 
61.2
59.1
 
61.2
58.4
 
 3–4 times/week
13.7
15.1
13.1
 
14.9
13.0
 
14.4
11.5
 
12.8
15.1
 
12.7
16.5
 
 5–6 times/week
1.9
2.3
1.7
 
2.4
1.6
 
2.0
1.5
 
1.7
2.2
 
1.6
2.6
 
 Once/day
0.7
1.0
0.6
 
1.0
0.6
 
0.7
0.7
 
0.6
1.0
 
0.6
1.2
 
 Twice/day
0.2
0.3
0.2
 
0.3
0.2
 
0.2
0.2
 
0.2
0.3
 
0.2
0.4
 
 3+ times/day
0.2
0.3
0.2
 
0.4
0.2
 
0.3
0.2
 
0.2
0.4
 
0.1
0.6
 
Fruits (excluding fruit juices)
 I did not eat
8.6
11.7
7.4
< .0001
11.8
7.0
< .0001
9.1
7.5
< .0001
7.6
10.5
< .0001
8.3
9.7
< .0001
 1–2 times/week
28.7
32.1
27.4
 
32.3
27.0
 
30.0
25.1
 
27.7
30.4
 
28.3
29.9
 
 3–4 times/week
27.9
26.5
28.4
 
26.6
28.5
 
27.9
27.8
 
28.8
26.4
 
28.2
26.9
 
 5–6 times/week
11.5
10.4
12.0
 
10.4
12.1
 
11.3
12.2
 
11.9
11.0
 
11.8
10.8
 
 Once/day
12.6
10.8
13.4
 
10.6
13.6
 
12.2
14.0
 
13.1
11.8
 
12.8
12.2
 
 Twice/day
6.1
5.0
6.6
 
4.5
6.9
 
5.6
7.7
 
6.4
5.7
 
6.3
5.8
 
 3+ times/day
4.4
3.4
4.8
 
3.7
4.8
 
3.9
5.9
 
4.6
4.2
 
4.3
4.7
 
Vegetable (excluding Kimchi)
 I did not eat
3.8
5.6
3.1
< .0001
5.1
3.1
< .0001
4.0
3.0
< .0001
3.1
5.0
< .0001
3.5
4.5
< .0001
 1–2 times/week
15.5
19.4
13.9
 
18.5
14.0
 
16.5
12.7
 
14.7
16.8
 
15.0
17.0
 
 3–4 times/week
24.3
26.0
23.6
 
25.6
23.6
 
24.8
22.8
 
24.4
24.0
 
24.4
23.8
 
 5–6 times/week
14.2
13.3
14.5
 
13.6
14.4
 
14.0
14.5
 
14.5
13.6
 
14.4
13.5
 
 Once/day
13.0
12.0
13.4
 
12.5
13.3
 
12.9
13.4
 
13.4
12.4
 
13.0
13.0
 
 Twice/day
14.9
12.4
15.9
 
12.9
15.9
 
14.6
15.8
 
15.3
14.3
 
15.2
14.3
 
 3+ times/day
14.3
11.3
15.5
 
11.7
15.7
 
13.1
17.9
 
14.5
14.0
 
14.5
13.9
 
Milk
 I did not drink
16.2
20.7
14.4
< .0001
19.7
14.4
< .0001
17.2
13.2
< .0001
14.4
19.1
< .0001
15.5
18.1
< .0001
 1–2 times/week
22.6
25.3
21.5
 
24.4
21.6
 
23.8
19.2
 
21.9
23.7
 
22.2
23.7
 
 3–4 times/week
20.2
19.8
20.3
 
19.8
20.4
 
20.3
19.8
 
20.5
19.7
 
20.2
20.1
 
 5–6 times/week
14.3
13.1
14.7
 
13.4
14.7
 
14.0
15.1
 
14.8
13.4
 
14.6
13.2
 
 Once/day
16.0
12.9
17.2
 
13.7
17.1
 
15.3
18.1
 
16.9
14.4
 
16.5
14.7
 
 Twice/day
6.2
4.8
6.7
 
5.1
6.7
 
5.6
7.8
 
6.6
5.5
 
6.3
5.9
 
 3+ times/day
4.6
3.3
5.2
 
3.8
5.0
 
3.9
6.8
 
4.9
4.2
 
4.7
4.4
 
All values are presented as weighted %
Table 5
Adjusted odds ratios of well-being and mental distress indicators in relation to dietary behaviours among adolescents
 
Well-being outcomes
Mental distress outcomes
Perceived health (healthy)
Perceived happiness (happy)
Sleep satisfaction (sufficient)
Perceived stress (much)
Depression (yes)
aOR1)
(95% CI)
aOR1)
(95% CI)
aOR2)
(95% CI)
aOR2)
(95% CI)
aOR3)
(95% CI)
Dietary behaviors
 Breakfast
  0 day
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1 day
0.95
(0.85–1.05)
1.01
(0.92–1.11)
0.96
(0.85–1.09)
0.91
(0.83–1.00)
0.97
(0.89–1.06)
  2 days
1.04
(0.95–1.14)
1.06
(0.97–1.15)
0.99
(0.89–1.11)
0.95
(0.87–1.04)
1.02
(0.94–1.10)
  3 days
1.06
(0.97–1.17)
1.02
(0.94–1.11)
1.12
(1.01–1.25)
0.91
(0.84–0.99)
0.88
(0.82–0.96)
  4 days
0.98
(0.89–1.08)
1.22
(1.11–1.34)
0.99
(0.88–1.11)
0.83
(0.76–0.92)
0.94
(0.87–1.02)
  5 days
1.01
(0.94–1.10)
1.16
(1.07–1.25)
0.99
(0.91–1.09)
0.85
(0.79–0.91)
0.89
(0.83–0.96)
  6 days
1.22
(1.12–1.34)
1.30
(1.19–1.42)
1.13
(1.03–1.23)
0.76
(0.70–0.82)
0.86
(0.79–0.93)
  7 days
1.34
(1.25–1.43)
1.42
(1.34–1.51)
1.45
(1.35–1.56)
0.74
(0.70–0.78)
0.76
(0.72–0.81)
 Soft drinks
  I did not drink
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
1.04
(0.99–1.09)
1.08
(1.03–1.13)
0.90
(0.86–0.96)
0.97
(0.93–1.02)
1.05
(1.00–1.09)
  3–4 times/week
0.90
(0.84–0.96)
0.95
(0.89–1.01)
0.77
(0.72–0.82)
1.07
(1.01–1.14)
1.24
(1.17–1.31)
  5–6 times/week
0.83
(0.74–0.92)
0.82
(0.74–0.91)
0.70
(0.62–0.80)
1.39
(1.25–1.54)
1.44
(1.31–1.58)
  Once/day
0.73
(0.63–0.84)
0.76
(0.66–0.88)
0.77
(0.65–0.91)
1.47
(1.28–1.70)
1.57
(1.38–1.79)
  Twice/day
0.63
(0.50–0.79)
0.77
(0.62–0.94)
0.58
(0.44–0.77)
1.41
(1.12–1.78)
1.59
(1.34–1.89)
  3+ times/day
0.63
(0.50–0.78)
0.67
(0.53–0.84)
0.80
(0.63–1.01)
1.75
(1.41–2.18)
2.07
(1.75–2.44)
 Highly caffeinated drink
  I did not drink
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
0.77
(0.72–0.83)
0.73
(0.69–0.78)
0.68
(0.63–0.73)
1.50
(1.42–1.60)
1.50
(1.42–1.59)
  3–4 times/week
0.65
(0.57–0.74)
0.55
(0.49–0.62)
0.56
(0.48–0.66)
2.22
(1.96–2.52)
1.91
(1.71–2.13)
  5–6 times/week
0.58
(0.46–0.73)
0.55
(0.44–0.68)
0.70
(0.53–0.92)
1.96
(1.58–2.44)
2.66
(2.19–3.23)
  Once/day
0.44
(0.33–0.58)
0.43
(0.34–0.55)
0.40
(0.27–0.58)
3.43
(2.67–4.41)
2.62
(2.15–3.20)
  Twice/day
0.30
(0.19–0.45)
0.42
(0.26–0.69)
0.49
(0.26–0.96)
3.49
(2.28–5.34)
3.57
(2.38–5.34)
  3+ times/day
0.39
(0.25–0.62)
0.43
(0.28–0.68)
0.77
(0.45–1.32)
3.01
(1.85–4.89)
3.25
(2.24–4.71)
 Sweetened drinks
  I did not drink
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
1.01
(0.95–1.07)
1.06
(1.00–1.12)
0.87
(0.82–0.93)
0.99
(0.94–1.05)
1.12
(1.06–1.18)
  3–4 times/week
0.92
(0.86–0.99)
0.99
(0.93–1.06)
0.77
(0.71–0.83)
1.14
(1.07–1.21)
1.34
(1.26–1.41)
  5–6 times/week
0.80
(0.73–0.87)
0.95
(0.87–1.03)
0.63
(0.57–0.71)
1.30
(1.21–1.41)
1.45
(1.35–1.57)
  Once/day
0.77
(0.69–0.86)
0.94
(0.84–1.05)
0.66
(0.59–0.75)
1.47
(1.33–1.62)
1.58
(1.44–1.73)
  Twice/day
0.65
(0.54–0.78)
0.81
(0.69–0.94)
0.57
(0.47–0.69)
1.82
(1.55–2.14)
2.04
(1.76–2.37)
  3+ times/day
0.58
(0.48–0.70)
0.68
(0.57–0.82)
0.82
(0.66–1.01)
2.08
(1.73–2.50)
1.97
(1.67–2.32)
 Fast foods
  I did not eat
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
1–2 times/week
0.97
(0.92–1.02)
1.05
(1.01–1.11)
0.85
(0.81–0.90)
1.01
(0.96–1.05)
1.08
(1.04–1.13)
  3–4 times/week
0.80
(0.75–0.86)
0.89
(0.83–0.95)
0.66
(0.62–0.72)
1.24
(1.16–1.32)
1.43
(1.35–1.52)
  5–6 times/week
0.69
(0.59–0.81)
0.71
(0.61–0.82)
0.70
(0.59–0.84)
1.49
(1.28–1.72)
1.80
(1.58–2.05)
  Once/day
0.50
(0.40–0.63)
0.52
(0.42–0.66)
0.78
(0.58–1.04)
2.03
(1.63–2.54)
2.30
(1.90–2.78)
  Twice/day
0.41
(0.25–0.69)
0.50
(0.31–0.82)
0.58
(0.33–1.02)
2.14
(1.35–3.39)
2.36
(1.66–3.37)
  3+ times/day
1.32
(0.67–2.59)
0.73
(0.42–1.25)
0.61
(0.32–1.19)
2.09
(1.24–3.52)
3.57
(2.62–4.87)
 Fruits (excluding fruit juices)
  I did not eat
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
1.32
(1.21–1.43)
1.45
(1.34–1.57)
1.08
(0.98–1.18)
0.77
(0.72–0.83)
0.88
(0.83–0.94)
  3–4 times/week
1.58
(1.46–1.72)
1.76
(1.62–1.90)
1.23
(1.12–1.35)
0.67
(0.62–0.72)
0.83
(0.77–0.88)
  5–6 times/week
1.61
(1.46–1.77)
1.77
(1.62–1.94)
1.29
(1.17–1.42)
0.68
(0.63–0.74)
0.83
(0.77–0.90)
  Once/day
1.80
(1.64–1.98)
2.04
(1.86–2.23)
1.42
(1.29–1.58)
0.66
(0.61–0.71)
0.86
(0.79–0.92)
  Twice/day
1.72
(1.54–1.93)
2.18
(1.95–2.44)
1.56
(1.39–1.75)
0.69
(0.62–0.76)
0.86
(0.78–0.94)
  3+ times/day
1.81
(1.58–2.07)
1.89
(1.67–2.14)
1.68
(1.49–1.90)
0.70
(0.63–0.78)
1.05
(0.95–1.17)
 Vegetable (excluding Kimchi)
  I did not eat
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
1.35
(1.21–1.51)
1.26
(1.12–1.40)
1.01
(0.88–1.15)
0.69
(0.62–0.77)
0.90
(0.82–1.00)
  3–4 times/week
1.68
(1.51–1.87)
1.49
(1.34–1.65)
1.17
(1.03–1.32)
0.63
(0.57–0.70)
0.79
(0.72–0.87)
  5–6 times/week
1.90
(1.69–2.14)
1.61
(1.44–1.80)
1.28
(1.12–1.46)
0.62
(0.56–0.70)
0.80
(0.72–0.88)
  Once/day
1.93
(1.73–2.16)
1.61
(1.44–1.81)
1.27
(1.11–1.45)
0.62
(0.55–0.69)
0.84
(0.76–0.93)
  Twice/day
2.22
(1.97–2.49)
1.87
(1.67–2.10)
1.35
(1.18–1.53)
0.61
(0.55–0.68)
0.78
(0.70–0.86)
  3+ times/day
2.21
(1.97–2.48)
1.96
(1.75–2.19)
1.56
(1.37–1.77)
0.66
(0.59–0.74)
0.83
(0.75–0.92)
 Milk
  I did not drink
1.00
 
1.00
 
1.00
 
1.00
 
1.00
 
  1–2 times/week
1.15
(1.08–1.24)
1.15
(1.08–1.22)
1.00
(0.93–1.08)
0.84
(0.79–0.89)
0.93
(0.88–0.98)
  3–4 times/week
1.28
(1.20–1.36)
1.28
(1.20–1.36)
1.09
(1.01–1.18)
0.82
(0.77–0.87)
0.93
(0.88–0.99)
  5–6 times/week
1.33
(1.23–1.44)
1.32
(1.23–1.41)
1.07
(0.98–1.16)
0.80
(0.75–0.86)
0.89
(0.84–0.95)
  Once/day
1.50
(1.39–1.61)
1.41
(1.32–1.51)
1.18
(1.09–1.28)
0.77
(0.72–0.82)
0.90
(0.85–0.96)
  Twice/day
1.48
(1.33–1.64)
1.36
(1.22–1.51)
1.21
(1.10–1.34)
0.83
(0.76–0.91)
1.02
(0.94–1.11)
  3+ times/day
1.54
(1.36–1.74)
1.37
(1.22–1.53)
1.46
(1.31–1.63)
0.90
(0.82–1.00)
1.06
(0.96–1.17)

Discussion

This study found in agreement with previous studies [1‐3] that a dose–response relationship between healthy dietary behaviours (regular fruit, vegetable, breakfast, and milk consumption) and well-being outcomes (perceived health, happiness and sleep satisfaction). In particular, the linear association with positive perceived health and happiness were stronger in fruit and vegetable consumption. A study among ASEAN university students showed a significant association but no dose–response relationship between fruits and vegetable consumption and positive self-rated health status [6]. Hoefelmann et al. [48] also found that higher fruit and vegetables consumption was associated with better sleep quality among Brazilian workers. Reasons for this finding are not clear and need further investigations.
Recent meta-analyses confirmed an inverse association of healthy dietary patterns [49, 50] with poor mental health outcomes, like depression in adults. However, the findings in adolescents remained inconsistent. In agreement with previous studies [1‐3, 9‐25], this study found that healthy dietary behaviours (regular fruit, vegetable, breakfast, and milk consumption) were negatively associated with perceived stress and depression symptoms, despite no linear associations of consumption of fruit, vegetable, and milk. A population-based study among Swiss people aged 15+ years showed those fulfilling the 5-a-day fruit and vegetable consumption had lower odds of being highly or moderately distressed than individuals consuming less fruit and vegetables (OR  =  0.82 for moderate distress, and OR  =  0.55, for high distress compared to low distress) [31]. It is possible that due to the consumption of fruits and vegetables, being rich in antioxidants, folic acid and anti-inflammatory components, human optimism or happiness is enhanced [28] and the development of negative mood or depression symptoms decreased [29].
In agreement with previous studies [8, 24‐31, 35] unhealthy dietary behaviours (consumption of soft drinks, caffeine, fast food, sweets and snacks, and skipping breakfast) were associated with low self-rated health, unhappiness, and low sleep satisfaction. Although the association became weaker at three or more times consumption of fast foods, increased unhealthy dietary behaviours were inversely associated with positive well-being outcomes, in particular, perceived health and happiness. On the other hand, a dose–response relationship between unhealthy dietary behaviours, such as consumption of soft drinks, highly caffeinated drinks, sweetened drinks, and fast food, and inversely, frequency of breakfast consumption as a health dietary behaviour with depression was observed in this study. These findings are consistent with a prospective Australian adolescents study [51] and a prospective cohort study also showed a positive association of fast food and commercial baked foods with depression in adults [52]. However, in a study among university students in ASEAN countries an inverse dose–response relationship between eating breakfast and sugared coffee/tea and a positive linear association between the consumption of snacks, fast foods, soft drinks and depression symptoms [6]. Although the relationship between sugar consumption and major depression seems to have been confirmed in cross-national observations in Asian countries [53], a study among ASEAN university students has shown an inverse dose–response relationship between sugared coffee/tea consumption and depression symptoms [6]. These findings emphasize the need for further investigations.
Nevertheless, some studies have suggested that an increase in carbohydrate-dense but nutrient-poor foods, such as fast food, sweets and snacks, may be used by individuals to cope with negative mood and elevate mood by increasing brain serotonin levels [42]. Several other studies among adolescents [54] and young adults [55] also found an association between caffeine consumption and low sleep satisfaction or poor sleep quality. A study among adolescents in Germany suggested that later bed and rise times were associated with increased consumption of caffeinated drinks and fast food [56]. The biological mechanism to explain this includes that caffeine increases alertness and increased energy as a function of its interactions with adenosine receptors in the brain [57]. However, caffeine use seems to only reduce sleep quality in individuals that are sensitive to the adenosine effects of caffeine [58]. In addition, the German study reported reduced consumption of dairy products was also associated with later bed and rise times [56]. Our study findings supported this study by showing that frequent milk consumption (once per day or more) was associated with sufficient sleep satisfaction. Further, as the practice of skipping breakfast may increase poor sleep quality [30], our study also showed a positive association between regular breakfast consumption and sleep satisfaction. In terms of fast foods, less frequent consumption of fast foods (less than once per day) showed an inverse association, but among those having once per day or more fast foods the association disappeared. This study may lead to a need for a prospective study to examine the causality, since strong relationships with a dose–response relationship between healthy dietary behaviours and well-being parameters and between unhealthy dietary behaviours and mental distress were found.

Study limitations

The cross-sectional design does not explain if positive well-being promotes a healthier dietary behaviour or healthier dietary patterns lead to more positive well-being. Some of the concepts assessed in this study used single item measures such as depression symptoms, happiness and perceived stress, and future studies should include multiple item measures to assess key concepts. Despite the limitations, the inclusion of data from 65,528 adolescents from a nationally representative sample in South Korea supports the external validity of the study results.

Conclusions

In a large nationally representative sample of adolescent in Korea, strong cross-sectional evidence was found that increased unhealthier dietary behaviour was associated with higher mental distress, while healthier dietary behaviour showed a dose–response relationship with higher psychological well-being. It remains unclear, if a healthier dietary behaviour is the cause or the sequela of a more positive well-being.

Authors’ contributions

All authors contributed to the conception and design of the study. SAH analysed the data. KP and SAH were involved in writing and revision of the manuscript. Both authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data are available from the Korea Centers for Disease Control and Prevention for Institutional Data Access. The dataset is publicly available via http://​yhs.​cdc.​go.​kr. Access to the dataset requires an application process via the official website.
In the last ethics approval, the study protocol was approved by the “Institutional Review Board of the Korean Centers for Disease Control and Prevention (KCDC)” (2014-06EXP-02-P-A). Prior to the survey, each respondent was asked for written informed consent to participate in the survey.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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Metadaten
Titel
Dietary behaviour, psychological well-being and mental distress among adolescents in Korea
verfasst von
Seo Ah Hong
Karl Peltzer
Publikationsdatum
01.12.2017
Verlag
BioMed Central
Erschienen in
Child and Adolescent Psychiatry and Mental Health / Ausgabe 1/2017
Elektronische ISSN: 1753-2000
DOI
https://doi.org/10.1186/s13034-017-0194-z

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