Psychological Health Categories and Influencing Factors of Elderly People in Urban and Rural Areas of China: A Dual-Variable Model Analysis

Background With the rapid development of China's socio-economy, mental health issues among middle-aged and elderly people in both urban and rural areas have gradually become a focal point of social concern. These individuals face significant life pressures and psychological adaptation challenges, directly impacting their overall quality of life. Methods This study is based on data from the Chinese Health and Retirement Longitudinal Study (CHARLS), using latent class analysis (LCA) to analyze the mental health categories and influencing factors of middle-aged and elderly people in urban and rural areas. The LCA method explains the relationships between manifest indicators through latent class variables, effectively identifying different potential mental health states. Results The study found that the optimal model includes four latent mental health categories. Further analysis revealed that individual characteristics such as age, gender, marital status, and education level significantly influence the mental health categories of middle-aged and elderly people in both urban and rural areas. Additionally, different mental health categories have varying degrees of impact on the health status of middle-aged and elderly people. Conclusion This study systematically reveals the distribution of mental health categories among middle-aged and elderly people in both urban and rural areas and their influencing factors, providing a scientific basis for formulating targeted mental health intervention policies. By improving community environments, enhancing social support, and boosting individual coping abilities, it is possible to effectively promote the mental health of middle-aged and elderly people in both urban and rural areas, thereby improving their quality of life.