Background
The Coronavirus disease 2019 (COVID-19) is an infectious disease presenting a major threat to public health. This study aims to assess Internet use characteristics and objectively examine the potential psychological factors associated with Internet addiction (IA) during the COVID-19 epidemic.
Methods
A cross-sectional, anonymized, self-reported survey was conducted among Chinese children and adolescents aged 6 to 18 years old. Participants completed questionnaires containing Young’s Internet Addiction Test (IAT) and the Depression, Anxiety, and Stress Scale (DASS-21), and questions regarding demographic information and Internet use characteristics.
Results
A total of 2050 participants (mean age:12.34 ± 4.67 years old, female: 48.44%) were enrolled. Fifty-five (2.68%) participants met the criterion for addictive Internet use (IAT≥70), while 684 (33.37%) participants were classified as problematic Internet users (69≥IAT≥40). Internet usage had grown during the COVID-19 epidemic, including the frequency and duration of recreational Internet use, and the frequency of stay-up Internet use. A linear regression analysis showed female gender (β=-0.091, p<0.001), age (β=0.066, p=0.001), depression (β=0.257, p<0.001), and stress (β=0.323, p<0.001) were significantly correlated with the IAT total scores (R=0.539, R
2 =
0.291, p<0.001).
Conclusions
We observed excessive Internet use among Chinese children and adolescents during the outbreak of COVID-19. Age, gender, depression, and stress were the potential key factors affecting IA. Extended family and professional support should be considered for vulnerable individuals during these unprecedented times.
BackgroundAutism is a neurodevelopmental disorder with an unclear etiology. Pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) have been suggested to play a role in the etiology of autism. The current study explores the associations among maternal pre-pregnancy BMI, GWG and the risk of autism in the Han Chinese population.MethodsDemographic information, a basic medical history and information regarding maternal pre-pregnancy and pregnancy conditions were collected from the parents of 705 Han Chinese children with autism and 2236 unrelated typically developing children. Binary logistic regressions were conducted to calculate the odds ratio (OR) for the relationship among pre-pregnancy BMI, GWG and the occurrence of autism. The interaction between pre-pregnancy BMI and GWG was analyzed by performing stratification analyses using a logistic model.ResultsAfter adjusting for the children’s gender, parental age and family annual income, excessive GWG was associated with autism risk in the entire sample (OR = 1.327, 95% CI: 1.021–1.725), whereas the relationship between maternal pre-pregnancy BMI and autism was not significant. According to the stratification analyses, excessive GWG increased the risk of autism in overweight/obese mothers (OR = 2.468, 95% CI: 1.102–5.526) but not in underweight or normal weight mothers.ConclusionsThe maternal pre-pregnancy BMI might not be independently associated with autism risk. However, excessive GWG might increase the autism risk of offspring of overweight and obese mothers.Electronic supplementary materialThe online version of this article (10.1186/s12888-018-1593-2) contains supplementary material, which is available to authorized users.
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