Volume 44 Issue 9
Sep.  2023
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Article Contents
YUAN Wen, JIANG Jianuo, QIN Yang, WANG Ruolin, ZHANG Yi, ZHANG Yihang, CHEN Li, LIU Jieyu, GUO Tongjun, YANG Tian, ZHANG Xiuhong, SONG Yi, MA Jun, DONG Yanhui. Co-occurrence trend and association study of Internet addiction and depressive symptoms among students in Inner Mongolia Autonomous Region[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(9): 1294-1298. doi: 10.16835/j.cnki.1000-9817.2023.09.004
Citation: YUAN Wen, JIANG Jianuo, QIN Yang, WANG Ruolin, ZHANG Yi, ZHANG Yihang, CHEN Li, LIU Jieyu, GUO Tongjun, YANG Tian, ZHANG Xiuhong, SONG Yi, MA Jun, DONG Yanhui. Co-occurrence trend and association study of Internet addiction and depressive symptoms among students in Inner Mongolia Autonomous Region[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(9): 1294-1298. doi: 10.16835/j.cnki.1000-9817.2023.09.004

Co-occurrence trend and association study of Internet addiction and depressive symptoms among students in Inner Mongolia Autonomous Region

doi: 10.16835/j.cnki.1000-9817.2023.09.004
  • Received Date: 2023-07-19
  • Rev Recd Date: 2023-08-31
  • Available Online: 2023-09-28
  • Publish Date: 2023-09-25
  •   Objective  To investigate the prevalence of Internet addiction and depression of students, and to analyze the co-occurrence and trend, so as to provide a theoretical basis for prevention and controlling measures of Internet addiction and depression.  Methods  A total of 6 317, 7 152, 81 808, 71 180 and 89 932 students aged 10 to 24 years from 12 leagues (103 banners) in Inner Mongolia Autonomous Region were selected by stratified random cluster sampling in September each year from 2017 to 2021. The Internet Addiction Scale and the Central for Epidemiologic Studies Depression Scale(CES-D) was used to measure Internet addiction and depression. And the annual inspection rate, group difference and annual change trend in students were calculated. Multivariate linear regression and restricted cubic spline analysis were used to estimate the linear and non-linear associations between Internet addiction and depression in students.  Results  The Internet addiction proportion in students gradually decreased from 4.1% in 2017 to 2.1% in 2020, but increased to 3.9% in 2021. And the depressive symptoms proportion increased from 20.9% in 2017 to 28.0% in 2020 and 27.0% in 2021. The detection rate of Internet addiction and depression co-morbidities remained at 1.8% to 2.5%. The Internet addiction proportion in boys was higher than that in girls(χ2=42.82, P < 0.05). The depressive symptoms prevalence in girls was higher than that in boys(χ2=553.90, P < 0.05). Taking reversal in prevalence of Internet addiction in urban and rural areas was observed in 2019. The detection rates of depressive symptoms and comorbidity were higher in urban areas than these in suburban counties on the whole, and the difference showed a trend of decreasing or even equalizing year by year. Internet addiction was positively correlated with depressive symptoms score (B=1.67, 95%CI=1.64-1.71), the proportion of depressive symptoms (OR=1.39, 95%CI=1.38-1.41) and the proportion of major depressive symptoms (OR=1.35, 95%CI=1.33-1.36) among students in 2021 (P < 0.05). An N-shaped curve was found in the significant nonlinear associations between internet addiction and depression across sex, region and school stage.  Conclusion  Internet addiction and depression in students show significant linear and non-linear associations, which are consistent in different sexes, regions and school stages. Therefore, relevant measures should be made and implemented in each region, especially in suburb areas, so as to prevent the increasingly development of adolescents and children's Internet addiction and depression.
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