The Nonlinear Association Between Internet Using Time for Non-Educational Purposes and Adolescent Health
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Objectives: This study was performed to consider the association between Internet using time for non-educational purposes and adolescent health, and to examine how health status differs between Internet users and non-users. Methods: We analyzed 2009 data from the Korea Adolescent Risk Behavior Web-Based Survey, conducted on a nationally representative sample of students in grades 7 to 12. A total of 75 066 adolescents were categorized into four groups according to their Internet using time excluding using for educational purposes: non-Internet users (NIUs),occasional Internet users (OIUs) (<1 h/d), moderate Internet users (MIUs) (≥1 and <2 h/d), and heavy Internet users (HIUs) (≥2 h/d). Health factors included eight health risk behavior indices, four mental health indices and six physical health indices. Results: The distribution of Internet use was as follows: NIUs 17.4%, OIUs 68.1%, MIUs 12.7%, and HIUs 1.7%. In multivariate analysis, using OIUs as a reference, U- or J-shaped associations were observed for five health risk behavior indices (current smoking, current drinking, drug abuse, sexual intercourse, sedentary behavior on weekdays) and four mental health indices (stressed, depressed, suicidal ideation, attempted suicide) in both genders. After removing confounding effects, including age, region, school type, subjective school record, subjective economic status, presence of parents, living with family, and sedentary behavior, these associations were still observed. Conclusions: Health professionals should consider both Internet non-users (for non-educational purposes) and heavy users to be high-risk groups in terms of health status. Also, more well-designed studies are needed to clarify what factors are working in these nonlinear associations.
Abstract
Objectives: This study was performed to consider the association between Internet using time for non-educational purposes and adolescent health, and to examine how health status differs between Internet users and non-users. Methods: We analyzed 2009 data from the Korea Adolescent Risk Behavior Web-Based Survey, conducted on a nationally representative sample of students in grades 7 to 12. A total of 75 066 adolescents were categorized into four groups according to their Internet using time excluding using for educational purposes: non-Internet users (NIUs),occasional Internet users (OIUs) (<1 h/d), moderate Internet users (MIUs) (≥1 and <2 h/d), and heavy Internet users (HIUs) (≥2 h/d). Health factors included eight health risk behavior indices, four mental health indices and six physical health indices. Results: The distribution of Internet use was as follows: NIUs 17.4%, OIUs 68.1%, MIUs 12.7%, and HIUs 1.7%. In multivariate analysis, using OIUs as a reference, U- or J-shaped associations were observed for five health risk behavior indices (current smoking, current drinking, drug abuse, sexual intercourse, sedentary behavior on weekdays) and four mental health indices (stressed, depressed, suicidal ideation, attempted suicide) in both genders. After removing confounding effects, including age, region, school type, subjective school record, subjective economic status, presence of parents, living with family, and sedentary behavior, these associations were still observed. Conclusions: Health professionals should consider both Internet non-users (for non-educational purposes) and heavy users to be high-risk groups in terms of health status. Also, more well-designed studies are needed to clarify what factors are working in these nonlinear associations.
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