Data analysis, depression, logistic regression models
Abstract
The purpose of this study was to analyze the influencing factors of depression through logistic regression model, and to provide doctors with recommendations for the prevention and treatment of depression based on the analysis results. Depression is a global mental health problem that affects the lives of more than 300 million people, and its incidence continues to rise. The causes of depression are complex and involve the interplay of biological, psychological, social, and environmental factors. Studies have shown that many factors such as genetics, neuroendocrine, immune system, and social environment can influence the onset and progression of depression. To better prevent and treat depression, researchers have proposed a variety of methodological pathways, such as linear mixed-effects (LME) models, and interventions by improving physical health and promoting physical activity. In addition, understanding the symptoms and effects of depression and how to provide help is critical for public education and early intervention. By delving into the multifactorial nature of depression, this paper can better understand its causes and provide new ideas and approaches for prevention and treatment.
