A065: Analysis of the Prediction of Adolescent Depressive Diseases andthe Mediating Effect of Exercise Factors Based on Basic Census Data

<bold>Objective:</bold> By analyzing census databases, we aimed to understand the correlation between depression and other psychological and physiological diseases. Further, we expanded our research to the correlation with physiology, lifestyle habits, and other aspects. At the same time, we attempted to use artificial intelligence methods to predict the risk of depression, obtain relevant models, and derive depression. <bold>Methods:</bold> Data from census databases were used in this research. Traditional data analysis methods were used for basic quantitative analysis, and highly correlated data with depression was selected for prediction model building. <bold>Results:</bold> (1) Analysis showed a significant correlation between depression and other diseases such as anxiety and hyperactivity disorder (=0.535, 0.231, 0.284; p &lt; 0.01). Besides, physiological and life-related issues may become the cause of depression. The prediction model established through big data can better predict and detect depressive tendencies. (2) There was a positive correlation between adolescent living standards and depressive psychology (r &gt; 0.85, r &gt; 0.87). Exercise levels and dietary levels were mediating variables between adolescent living standards and depressive psychology, with the mediating effect accounting for 33.6% of the total effect. <bold>Conclusion:</bold> Physiological trauma, personality traits, and lifestyle habits of close relationships among adolescents may become factors that trigger psychological disorders in adolescents. Teenagers' exercise and dietary levels play a mediating role between their living standards and depressive psychology.