Identification of prognostic risk factors associating with lifestyle contributing to the development of health disorders in 9–11 grades students

Abstract

Introduction. The development of society is largely determined by the level of population health of adolescents, which has a significant impact on the health of the nation as a whole and forms its cultural, intellectual, industrial, military, and reproductive potential. Studying the causes that contribute to the development of health disorders in students will help to identify the main health risk factors to justify priority areas of preventive work among children and adolescents. Materials and methods. Object of the study were 9–11 grades students. Research method: survey. To identify the complex influence of lifestyle risk factors on the likelihood of developing psychoneurological borderline disorders, the method of multivariate binary logistic regression analysis was used. To assess the quality of the models, the ROC curve analysis method was used. Results. The main predictors contributing to the development of psychoneurological borderline disorders in students in grades 9–11 include: being girl, life dissatisfaction, low support for the student from teachers, students being “busy” with electronic media for a long time, manifested by intensive use and preference for online communication; lack of sleep and walks on school days, participation in bullying as a victim or aggressor, lack of intense physical activity; low support for the student from family members, and smoking. The contribution of factors influencing the dependent variables ranged from 26.4% to 35.8%. Limitations. Model construction was based on data collected through an online questionnaire; there was an imbalance in the frequency distribution of syndrome variables. Conclusion. The prognostic risk factors for adolescent lifestyle influencing the development of disorders of well-being in students were determined. There was used multivariate regression analysis allowed identifying the independent impact of each risk factor for the health in students on the outcome, taking into account the correction for other factors included in the model. The results obtained can be used in the future to develop scientifically based recommendations for the prevention of health disorders in students.