Mental health problems have become a major public health problem worldwide and are more common among middle-aged and elderly people in China. Research on the effect of education on depression is limited, and whether the relationship between education and depression changes over the life course remains unclear. This study was based on the cross-sectional data of 15,767 middle-aged and elderly individuals in the 2018 tracking survey (Wave 4) of the China Health and Retirement Longitudinal Study (CHARLS) database. Multiple linear regression and bootstrap methods were developed to detect the mediating effect of education on depression. In all samples or different age groups, education was significantly positively associated with depression. Three mediators (economic level, health-related lifestyle, and cognitive level) were significantly positively associated with depression, and cognitive level had a greater effect on depression than economic level and health-related lifestyle. The total, direct, and indirect effects of the whole samples and elderly samples were significant; however, the direct effect of the middle-aged samples was insignificant, and the total and indirect effects of the three mediating pathways were all significant, that is, economic level, health-related lifestyle, and cognitive level should produce complete mediation. The multiple linear regression and bootstrap methods could successfully detect the mediating effect of education on depression. On the basis of the education, economic level, health-related lifestyle, cognitive level, and depression of middle-aged and elderly people, we established and compared the total, direct, and mediating effects of education on depression under the life course. The mediating variables should be further increased, and the measurement methods of depression should be developed to improve the credibility of the research results.

There has been controversy in theory and practice among studies about the governance of the “River Chief System” (RCS) policy and the watershed management issues behind it. This paper uses the regression discontinuity (RD) method and the water pollution monitoring data of 150 state-controlled monitoring points in China from 2007 to 2018 at the China National Environmental Monitoring Station to empirically study the effect of the “River Chief System” on water pollution treatment and the influencing factors behind the effect of the “River Chief System”. The results show that the “River Chief System” policy has a positive impact on river pollution treatment in the observation term. The implementation effectiveness of the “River Chief System” is limited by factors such as the boundaries of the river chief’s jurisdictions, the administrative conflict among river chiefs, local government environmental expenditure capacity, and environmental pressure. It is believed that the key to basin governance is to further improve the synergistic model of basin governance among regions.

In the era of the digital economy, how digital transformation (DT) contributes to economic development has become a topic of growing interest. This study focuses on business model innovation (BMI) driven by DT in the manufacturing sector. From this perspective, we aim to explore how DT can reshape the fundamental connotation of economic development. To this end, we construct a mathematical model grounded in a Multi-Structural Economic System framework and employ econometric models focusing on fixed effects, mediation effects, and moderation effects. We also compile a panel dataset using data from China spanning from 2008 to 2024. The empirical findings reveal that BMI serves as a mediation mechanism between the DT and competitive advantage (CA) of manufacturing enterprises. However, competitive imitation of BMI by peer enterprises partially offsets this effect, weakening the relationship between DT and enhanced CA. These findings offer evidence-based insights into the role of BMI in the digital era. For policymakers and industry regulators, this study provides practical implications for promoting knowledge spillovers from BMI, thereby fostering market dynamism and enabling structural transformation in the manufacturing industry.