Associations between internet addiction, screen time and depressive symptoms.
10.3760/cma.j.cn112338-20220330-00246
- Author:
Wen Xiu DU
1
;
Ye Qing GU
2
;
Ge MENG
3
;
Qing ZHANG
4
;
Li LIU
4
;
Han Zhang WU
1
;
Kai Jun NIU
5
Author Information
1. Nutritional Epidemiology Institute/School of Public Health, Tianjin Medical University, Tianjin 300070, China School of Public Health of Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
2. Nutrition and Radiation Epidemiology Research Center, Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China.
3. Nutritional Epidemiology Institute/School of Public Health, Tianjin Medical University, Tianjin 300070, China.
4. Health Management Centre, Tianjin Medical University General Hospital, Tianjin 300052, China.
5. Nutritional Epidemiology Institute/School of Public Health, Tianjin Medical University, Tianjin 300070, China School of Public Health of Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China Nutrition and Radiation Epidemiology Research Center, Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China Health Management Centre, Tianjin Medical University General Hospital, Tianjin 300052, China.
- Publication Type:Journal Article
- MeSH:
Adult;
Humans;
Screen Time;
Internet Addiction Disorder;
Self Report
- From:Chinese Journal of Epidemiology
2022;43(11):1731-1738
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To understand the associations between internet addiction, screen time (computer/mobile devices use and television watching time) and depressive symptoms in adults. Methods: A total of 6 932 adults aged <60 years from the Tianjin Chronic Low-grade Sgstemic Inflammation and Health (TCLSIH) Cohort of 2013-2019 were surveyed. The information about their computer/mobile devices use and television watching time were collected by using a self-reported questionnaire. The depressive symptoms were assessed using the self-rating depression scale (SDS). The adults surveyed were divided into two groups: non-depressive symptom group (SDS score <45) and depressive symptom group (SDS score ≥45). The associations between internet addiction, screen time and depressive symptoms were estimated using Cox proportional hazard regression models, with adjusting for multiple confounders. Results: After adjusting for confounding factors, the hazard ratios (HRs) of depressive symptom in the adults who had internet addiction before, had light internet addiction and had moderate or severe internet addiction were 0.83 (95%CI: 0.56-1.23) , 1.20 (95%CI: 1.03-1.41) for light and 1.48 (95%CI: 1.16-1.89), respectively, compared with those without internet addiction. The linear trend test results of the association between internet addiction and depressive symptoms was significant (trend P<0.001). Compared with the adults who used computer/mobile devices for <1 hour/day, the HRs of depressive symptoms in those who used computer/mobile devices for >1 hour, >3 hours, >5 hours and >10 hours were 0.59 (95%CI: 0.40-0.88), 0.58 (95%CI: 0.40-0.85), 0.52 (95%CI: 0.36-0.76) and 0.69 (95%CI: 0.45-1.05) respectively, a U-shaped association was found between computer/mobile devices use time and depressive symptoms (trend P<0.001). Compared with the adults who never watch TV, the HR of depressive symptoms was 1.36 (95%CI:1.09-1.69) for those watching TV for ≥3 hours/day in crude model and 1.34 (95%CI: 1.07-1.68) for those watching TV for ≥3 hours/day in adjusted model (trend P<0.001). Conclusion: Our findings suggested that internet addiction and television watching time were associated with an increased risk of depressive symptoms, while computer/mobile device use time was associated with a reduced risk of depressive symptoms.
