Objective: To analyze the prevalence trend of scoliosis among myopic students in Inner Mongolia Autonomous Region during 2019-2022, to explore the common etiology of myopia and scoliosis co-morbidities, so as to provide a reference for the development of relevant measures. Methods: The method of stratified random cluster sampling was used to select 181 533, 141 552 , 200 987, 190 918 primary and secondary school students from 12 leagues(103 banners) in Inner Mongolia Atuonomous Region in September each year from 2019 to 2022. And scoliosis screening, vision examination and questionnaire survey were conducted among students in the included studies. The χ 2 test was used to analyze the data, and the binary multivariate Logistic regression model was used to screen the influencing factors of scoliosis and myopia co-morbidities. Results: From 2019 to 2022, the myopia rate of primary and secondary school students in Inner Mongolia Autonomous Region was 55.55%-59.72%, scoliosis rate was 1.56 %-2.81% and the rates of scoliosis and myopia co-morbidities were 1.14%-1.95%, and the difference between different years was statistically significant ( χ 2=595.01, 775.56, 461.84, P < 0.05 ). In 2022, the co-morbidity rate was higher in girls than in boys(1.32% vs 0.97%), the rate of urban areas was higher than that of rural areas(2.57% vs 0.62%), the rate of students in vocational high school and high school was higher than that in junior high school and primary school (3.82%,2.47% vs 1.70%,0.42%), the rate of over developed areas was higher than that of poor areas (1.21% vs 0.99%)( χ 2=52.19, 1 269.82, 1 361.52, 17.29, P < 0.05 ). Logistic regression analysis showed that at least 1 h of moderate and high intensity exercise every day on weekends, the number of physical education classes per week was more than 3 sessions, the height of desks and chairs was adjusted according to height, resting outdoors, limiting screen time, and strictly requiring standing and sitting posture were the negative correlated with scoliosis and myopia, and the OR value was 0.65-0.90, reading books or electronic screens while participating in cram classes, walking or riding in the car were positively correlated with comorbid scoliosis and myopia, and the OR values were 1.27 and 1.13 ( P < 0.05), respectively. Conclusion Behavioral habits severely affect scoliosis and myopic of students. Prevention and control of scoliosis and myopia co-morbidity should start with students behavioral habits, early screening and early intervention.

Objective: To analyse associated factors of campus bullying in schools, and to construct a nomogram model to predict the risk of campus bullying, so as to provide a theoretical basis for campus bullying prevention and control. Methods: In September 2023, 89 117 middle and high school students were selected by stratified cluster random sampling method within 12 cities (103 counties) in Inner Mongolia, and were surveyed with self administered questionnaire. Among them, there were 62 381 participants in the training set and 26 736 participants in the testing set. Statistical analysis was conducted using χ 2 test and multiple Logistic regression, and a nomogram model was drawn for predicting campus bullying. Results: The prevalence of campus bullying was 3.49%. Living in a suburban county, living in an unstable family, not the only child, having a father with a college degree or above, sometimes or never eating breakfast, being overweight or obese, living on campus, being scolded by parents in the past 30 days, smoking, Internet addiction, experiencing depression, anxiety symptoms, recreational soluble solvents use, cough medicine abuse, nonprescribed use of sedatives were all positively correlated with campus bullying ( OR =1.18, 1.40, 1.12, 1.33, 1.13, 1.72 , 1.12, 1.17, 1.82, 1.32, 1.83, 3.92, 2.40, 2.25, 1.51, 1.63, P <0.01).There were a negative correlation between high school students, female students, and the number of physical education classes per week (2-3, ≥4) with campus bullying ( OR =0.67, 0.58, 0.72, 0.83, P <0.01). The prediction model of campus bullying risk was established by nomogram model. The area under curve (AUC) was 0.82, and the calibration curve showed that the predicted value was close to the actual value. Conclusions Bullying among middle and high school students are related to family intimacy, poor daily behaviour and psychological factors. Targets of bullying intervention in schools should be identified, and preventive and control measures against bullying in secondary schools should be formulated, so as to reduce the occurrence of campus bullying.