PDF
ePub
Citation
Print
Introduction
The Internet has become an important tool for social interaction, information, and entertainment [1]. However, as the Internet has moved into homes, schools, Internet cafes, and businesses, the prevalence of Internet addiction has been increasing rapidly. Internet addiction is characterized as poorly controlled Internet use, and can lead to impulse-control disorders [2]. Recently, Internet addiction, especially among adolescents, has been recognized as an important social issue in various countries because of the high prevalence of depression, aggressive behavior, psychiatric symptoms, and interpersonal problems associated with this addiction [3,4]. The incidence of Internet addiction in adolescents was estimated to be approximately 11% in China [2], 8% in Greece [5], and 18.4% in Korea [1].
Adolescents are more vulnerable to Internet addiction than adults, and the social performance, psychology, and lifestyle habits of Internet addicts can be affected by this addiction [6]. Numerous cross-sectional studies have shown that Internet addiction has an adverse effect on several lifestyle-related factors in adolescents; it can result in irregular dietary habits, extended periods of time spent on the Internet [7], physical inactivity, short duration of sleep [2], and increased use of alcohol and tobacco [2,8,9]. Some studies have reported that the change in lifestyle-related factors caused by heavy Internet use could have an adverse impact on the growth and development of Internet addicts [2,7].
Nutritional status also plays a crucial role in growth and development during adolescence. Several studies have shown that malnutrition or unbalanced nutritional intake can reduce weight gain and decrease leg length in adolescents [9,10]. Optimal nutrition is therefore important for adolescents to grow and develop properly. Moreover, once dietary habits are formed during childhood, they tend to be carried on throughout adulthood, thus teaching adolescents to develop healthy eating habits is of critical importance [11].
Numerous studies have showed associations between Internet addiction and mental health problems, such as depression and psychiatric symptoms, among adolescents. However, information on the effects of Internet addiction on the dietary behavior of adolescents is limited. Therefore, in this study, we examined the dietary behavior of Korean adolescents according to their level of Internet addiction.
Subjects and Methods
Subjects
This cross-sectional study included 1,000 adolescents from grades 7 through 9 living in Seoul, Korea. Of 1,000 participants, 800 students were recruited from eight junior high schools. The remaining 200 subjects were recruited from the Korean Youth Counseling Institute (KYCI), where they had been diagnosed and were being treated as Internet addicts. The study was conducted from October 2008 to November 2008. The Institutional Review Board of Chung-Ang University (Seoul, Korea) deemed this study exempt from the requirement for informed consent. Of the 1,000 surveys administered and collected, 147 were excluded due to incomplete responses and difficulty in assessing the level of Internet addiction, thus a total of 853 samples were analyzed in this study.
Korean Internet addiction test (KS scale)
Internet addiction was evaluated using the Korean version of the Internet addiction self-scale short form (KS scale) for youth, which was developed by the Korea Agency for Digital Opportunity and Promotion [12]. In brief, the KS scale for adolescents is a 20-item self-report questionnaire, consisting of six core components: disturbance of daily routines, self-esteem, withdrawal, virtual interpersonal relationship, deviant behavior, and tolerance. Response to each question is on 4-point Likert scale where 1 corresponds to "not at all", 2 corresponds to "sometimes", 3 corresponds to "frequently", and 4 corresponds to "always". The level of Internet addiction was categorized as either high-risk, potential-risk, or no risk based on the total score and the score for the three components of disturbance of daily routines, withdrawal, and tolerance. Subjects were classified as high-risk Internet users if their total score was the same or greater than 52, and/or if the score for disturbance of daily routine, withdrawal, and tolerance was greater than 16, 10, and 12, respectively. Subjects were classified as potential-risk Internet users if their total score was greater than or equal to 48 and less than 52 and/or if their score for disturbance of daily routine, withdrawal, and tolerance was greater than 14, 9, and 11, respectively. Subjects were classified as no risk Internet users if their total score was less than 48.
Subject characteristics and lifestyle patterns
The following socio-demographic characteristics of subjects were used in this analysis: age at the time of recruitment, family income per month, and the education level of the parents. A lifestyle habit questionnaire assessed the regularity of bedtime, sleep disturbance, and the use of alcohol and tobacco.
Dietary behaviors and diet quality
The dietary behavior questionnaire assessed recent changes in meal size, appetite, eating speed, frequency and reasons for skipping meals, and the frequency, type, and reasons for snacking. Diet quality was assessed by a 10-item mini-dietary assessment index. The mini-dietary assessment index was used to assess overall dietary quality based on the 2005 Dietary Guidelines and Food Tower for Koreans [13]. This index includes four food groups that should be consumed, four food groups that limited amounts of should be consumed, and two items regarding varied and regular diet. Responses to food items of which sufficient amounts should be consumed were reported using a 5-point Likert scale where 1=seldom, 3=sometimes, and 5=always. Responses to food items of which limited quantities should be consumed were also reported using a 5-point Likert scale where 1=always, 3=sometimes, and 5=seldom. The maximum possible score for diet quality is 50. In this study, diet quality was defined as "good" if the total score was greater than or equal to 30 [14].
Statistical analyses
All analyses were performed with a significance level of α=0.05 using the SPSS software package version 12.0 (SPSS Inc, Chicago, IL, USA). Relationships between levels of Internet addiction and socio-demographic characteristics, lifestyle patterns, and dietary behavior were analyzed using the chi-square test. The relationship between dietary quality and level of Internet addiction based on the self-scale rating system were analyzed using one-way ANOVA followed by Duncan's multiple range test for multiple comparisons.
Results
General characteristics of subjects
The general characteristics of the participants and the relationships between the level of Internet addiction and general characteristics are provided in Table 1. Subjects were between the ages of 13 and 15 years with a mean age of 14.0 years. More boys were high-risk Internet users than girls (31.4% vs.14.0%), and more girls were no risk Internet users than boys (74.7% vs. 58.9%). Younger adolescents were significantly more likely to be high-risk Internet users than older adolescents (P < 0.001). Household monthly income was significantly related to the level of Internet addiction; adolescents from households with a low monthly income (< 1,000 K won and 1,000 K-1,999 K won) were more likely to be high-risk Internet users (57.5% and 31.7%, respectively) than adolescents from households with a higher monthly income. Adolescents from households with high monthly incomes (3,000K-3,999K won and ≥4,000K won) were more likely to be no risk Internet users (76.4% and 74.3%, respectively). Parents' educational status also affected the level of Internet addiction. High-risk Internet users had parents whose highest level of education was high school graduation or less (27.2% in father and 22.4% in mother, respectively). In contrast, a high proportion of no risk Internet users had parents who were college graduates (72.2% in father and 71.9% in mother, respectively).
KS-scale score
The total KS-scale score and the scores of the six components of the KS-scale are presented in Table 2. High-risk Internet users had significantly higher total KS-scale scores and scores for the six main components than potential-risk Internet users and no risk Internet users (P < 0.05).
Lifestyle patterns
Lifestyle patterns, including bedtime, sleep disturbance, alcohol use, and tobacco use according to the level of Internet addiction are shown in Table 3. No risk Internet users had regular bedtime patterns (10.4% always had a regular bedtime and 41.8% often had a regular bedtime) while high-risk Internet users complained of irregular bedtime patterns (13.6% reported often irregular bedtimes and 11.4% reported always irregular bedtimes). Both high- and potential-risk Internet users suffered from sleep disturbances (81.1% and 76.7%, respectively). Similarly, 66% of high-risk Internet users and 64% of potential-risk Internet users had used alcohol. Fifty-two percent of high-risk Internet users had used tobacco while only 15.6% of no risk Internet users had used tobacco.
Dietary behavior and diet quality
Recent changes in eating habits among adolescents are provided in Table 4. More of high-risk Internet users answered that their dietary habits had been changed to have small meal sizes, a poor appetite, and irregular eating speeds than no risk Internet users (P=0.019, 0.001, and 0.002, respectively). High-risk Internet users had a high prevalence of skipping dinner (Table 5). High-risk Internet users snacked frequently, often snacking more than three times per day (15.8% vs. 9.7 % for no risk Internet users). Favorite snacks and reasons for snacking were not significantly different among adolescents based on levels of Internet addiction.
Diet quality based on levels of Internet addiction is shown in Table 6. The diet quality of high-risk Internet users was significantly lower than that of potential-risk Internet users and no risk Internet users, respectively (P < 0.05).
Discussion
In this study, we demonstrated that high-risk Internet users eat smaller meals, have less of an appetite, skip meals, and snack more than their potential-risk and normal-risk Internet user counterparts. Moreover, the diet quality of high-risk Internet users is poorer than that of potential-risk Internet users and no risk Internet users.
The frequency of skipping dinner in high-risk Internet users was significantly higher than that in no risk Internet users. This finding is consistent with a study by Kim and Chun that reported a high incidence of meal skipping in Internet addicts [7]. The high frequency of skipping dinner could be related to snacking; more frequent snacking was observed in high-risk Internet users than no risk Internet users. Savige et al. also reported that adolescent heavy snackers skipped dinner more frequently than their non- or light-snacker adolescent counterparts [15]. Moreover, the favorite snacks of our participants were confectionery and fast food, which are nutritionally poor foods with high calories provided by fats and simple sugars but with few other nutrients such as vitamins and minerals. Thus high-risk Internet users have improper dietary behaviors that could impact their growth and development.
The quality of the diet of high-risk Internet users as measured using a mini-dietary assessment index was poor. The mini-dietary assessment index that we used is a Korean version of the Healthy Eating Index in which scores over 30 indicate a good quality diet. In high-risk Internet users, the average total score was 28.38, which indicates an "inappropriate" diet quality. High-risk Internet users had the lowest meal regularity score, reflected by a higher rate of skipping dinner in high-risk Internet users than no risk Internet users. Moreover, high-risk Internet users did not consume enough milk and dairy products, meat and fish, and fruits and vegetables compared with no risk Internet users. Proper intake of milk and dairy products as major sources of calcium during childhood is crucial for achieving optimal peak bone mass and maintaining and repairing bone tissue [16]. In addition, low consumption of fruits and vegetables in high-risk Internet users suggests low intake of vitamins, minerals, and fiber in these individuals. Vitamins and minerals play a crucial role in energy production, maintenance of bone health, adequate immune function, and protection against oxidative stress [17,18]. Several studies have shown that proper fruit and vegetable intake can prevent health problems such as obesity and cardiovascular diseases [19-21].
High-risk Internet users not only consumed too little of the recommended food groups; they consumed more than the recommended daily quantities of fatty foods, fried foods, salt, and foods high in simple sugars. High fat and simple sugar intake increase the chance of being overweight or obese. Obese children and adolescents can have various adverse health outcomes, including diabetes, hypertension, dyslipidemia, and metabolic syndrome [22-24]. Furthermore, obese children have a higher risk of cardiovascular mortality when they reach adulthood [22,23]. The diet of high-risk Internet users, though it may meet their energy requirements, is lacking in nutritional value, and may therefore not support the growth spurt during adolescence and may cause nutrition-related health problems.
High-risk Internet users drank and smoked more and had a poorer quality diet and higher frequency of meal skipping than no risk Internet users. Results from two cross-sectional studies on Korean high school students [8] and Taiwanese high school students [2] found a strong association between Internet addiction and high use of alcohol and tobacco. Alcohol and tobacco companies use the Internet to promote and advertise their products by using themes and icons of youth popular culture, games and contests, and commercially-sponsored websites and homepages [25]. Therefore, because high-risk Internet users are more likely to be exposed to tobacco and alcohol advertisements, they are more likely to drink and smoke than other Internet users. Furthermore, high frequency of use of tobacco and alcohol can exacerbate diet-related problems, because smoking and drinking are negatively associated with diet quality and dietary behaviors such as meal regularity [26,27].
High-risk Internet users reported more irregular sleep patterns and more episodes of sleep disturbance than no risk Internet users. This is consistent with a previous study of Korean adolescents that showed that Internet addiction was associated with insomnia, apnea, and nightmare [8]. In addition, sleep disturbance could increase the risk of mental health problems as well as substance abuse [6,28,29,30]. Hence, high-risk Internet users are more likely to experience physical and mental health problems.
This study has some limitations. First, this study was a cross-sectional study, therefore we could not confirm causal associations between Internet addiction and dietary behavior. Second, the questionnaire was self-reported. It is therefore possible that some of the adolescents may not have admitted to using alcohol and tobacco due to social restrictions, even though this study was anonymous.
High-risk Korean adolescent Internet users had improper dietary behavior and a poorer diet quality than their no risk Internet counterparts. To ensure that the growth and development of high-risk Internet users is not adversely impacted, their diets should be supplemented with the nutrients that they are lacking. Interventions to improve both dietary behavior and treat Internet addiction may have synergistic health benefits.
In conclusion, the results of this study suggest that children should be educated as to what a balanced diet and optimum physical activity routine is to remain healthy and grow. Furthermore, the government should take an active role in designing and evaluating Internet addiction-related health intervention strategies. Given the likely adverse effects of Internet addiction on adolescents' development because of poor dietary behavior, it is critical to raise awareness about Internet addiction. Close attention should be paid to students at risk of Internet addiction, as well as students at low risk to prevent them from becoming addicted to the Internet.
XML Download