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Mediators in the Relationship between Internet Addiction and Body Mass Index: A Path Model Approach Using Partial Least Square.
Journal of Research in Health Sciences 2018 August 19
BACKGROUND: Adolescence obesity has now become an epidemic. In recent years, Internet addiction has been identified as a risk factor for obesity. We aimed to evaluate the role of some mediators such as sleep quality, physical activity and fast food consumption in the relation between internet addiction and Body Mass Index (BMI) among adolescents.
STUDY DESIGN: A cross-sectional study.
METHODS: Overall, 928 students, aged between 13 and 17 yr, were randomly selected in Behbahan, southwestern Iran from Oct 2017 to Dec 2017. Data were collected using a demographic survey, Young's internet addiction, Pittsburgh sleep quality, and food frequency, questionnaires. Data analysis was performed using Partial Least Squares (PLS) path analysis.
RESULTS: PLS path analysis revealed that the direct effect of Internet addiction on BMI was (Path Coefficient = 0.16, [95% CI: 0.12- 0.21]). Moreover, the indirect effect of internet addiction on BMI through sleep quality was (f2 = 0.12 (P<0.001)), physical activity (f2 =0.04 (P<0.001)), and fast food consumption ( f2 = 0.05 (P<0.001)).
CONCLUSIONS: Results of this study regarding the relationship between internet addiction and BMI and the effect of this phenomenon on sleep quality, physical activity and dietary habits suggest planning prevention and treatment programs to reduce the prevalence of this phenomenon in schools.
STUDY DESIGN: A cross-sectional study.
METHODS: Overall, 928 students, aged between 13 and 17 yr, were randomly selected in Behbahan, southwestern Iran from Oct 2017 to Dec 2017. Data were collected using a demographic survey, Young's internet addiction, Pittsburgh sleep quality, and food frequency, questionnaires. Data analysis was performed using Partial Least Squares (PLS) path analysis.
RESULTS: PLS path analysis revealed that the direct effect of Internet addiction on BMI was (Path Coefficient = 0.16, [95% CI: 0.12- 0.21]). Moreover, the indirect effect of internet addiction on BMI through sleep quality was (f2 = 0.12 (P<0.001)), physical activity (f2 =0.04 (P<0.001)), and fast food consumption ( f2 = 0.05 (P<0.001)).
CONCLUSIONS: Results of this study regarding the relationship between internet addiction and BMI and the effect of this phenomenon on sleep quality, physical activity and dietary habits suggest planning prevention and treatment programs to reduce the prevalence of this phenomenon in schools.
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