ABSTRACT
Objective To analyze the status, changing trends and determinants of mental health of migrant adolescents in junior high schools. Methods All of the data came from China Education Panel Survey (CEPS). CEPS baseline survey was conducted during the 2013-2014 school year by using a stratified multistage probability sampling design. 10 279 nationally representative adolescents from the seventh grade in junior high schools were enrolled in the base school year of data collection and 9 449 participants were followed up at the second wave of data collection during the 2014-2015 school year. Our analytic sample (n=1 645) included all the migrant adolescents who had valid data on mental health. Based on CEPS self-reported mental health scale, t-test method and multivariate linear regression model were used to examine the determinants of mental health of migrant adolescents by performing univariate analysis and multivariate analysis. Results The baseline mental health score of migrant adolescents was (8.33±3.31), higher than that of non-migrant adolescents, and significantly increased to (8.60±3.79) in the follow-up school year. 43.3% of participants had negative mental status at higher frequency as time went on. Sex, cognitive skills, co-residence arrangements, numbers of siblings and school rankings were significant influencing factors for mental health score of migrant adolescents. Conclusions The mental health status of migrant adolescents are more vulnerable than that of non-migrant adolescents and continue deteriorating. Among migrant adolescents, female, those with weak cognitive skills, those who do not live with both parents, those who are not only children and those in schools ranking medium and above are more likely to have a poor mental health state.
ABSTRACT
Objective To investigate the prevalence of overweight and obesity in Chinese ninth grade students and to analyze the influential factors that contribute to this situation. Methods A total of 5 967 students were selected from the 2016 China Education Panel Survey. Chi-square test was used to examine the differences in the prevalence of overweight and obesity among different groups and Logistic regression models were used to analyze the factors affecting obesity in boys and girls. Results The prevalence of overweight and obesity was 15.23%, 18.55% and 11.84% in total, male and female ninth grade students respectively. The multiple Logistic regression analysis indicated that the risk factors between boys and girls were significantly different. The main factors affecting boys obesity rate were one-child, boarding, both parents obesity, taking health education courses, having indoor stadium and screen time. Meanwhile, for girls the factors were boarding, both parents obesity and sports time. Conclusions Schools should arrange the schedule of boarding students and offer health education courses based on the characteristics of boys and girls. Meanwhile schools should unite parents to control adolescents’ screen time and nutrition balance, which is benefit for preventing adolescents overweight and obesity.
ABSTRACT
Objectives: To analyze the prevalence of bullying behavior among students of 9th grade across China in 2016 and to determine the impact of different types of bullying on students’physical and mental health. Methods:This paper adopted the China Education Panel Survey ( CEPS) conducted in 2016 using the sample design of PPS and cluster sampling. The survey population involved students of 9th grade and 8600 of them were respondents of the prepared questionnaire. Opting for the survey questionnaires to collect the basic information from the survey subjects, the study measured and compared the prevalence of physical, verbal, social and cyber bullying observed in 2016. Therefore, impacts of bullying on physical and mental/psychological health of students were respectively examined u-sing multiple OLS regression model and multi-factor sequential logit model. Results: The results of the survey found that during the past academic year, 49. 29% of students suffered verbal bullying, 37. 69% experienced social bull-ying followed by 18. 41% for those who caught physical bullying and finally 14. 08% were cyber bullied. The results of the multiple OLS regression analysis indicated that being bullied was a risk factor for students’ mental health, and social bullying was the most deleterious, followed by verbal bullying. The multi-factor sequential logit model results showed that the risk of illness was higher for students who were bullied than for those who were not bullied and verbal bullying was a notable health risk factor for physical health of students. Conclusions: Currently, verbal bullying is the most prevalent of the existing types of bullying in schools while new problems emerged with cyber bullying. Being bul-lied has a negative effect on both physical and mental health of students. The main risk factor for mental health is so-cial bullying and verbal bullying presents higher risks for physical health of students.