Mental disorders rose to the sixth leading cause of global health loss in 2020, up from tenth in 2010, indicating their increasing impact on global health (1). Depression, one of the most common mental disorders, affected 325 million people worldwide, accounting for approximately 4.3% of the global population (1). Depression is often a recurrent and lifelong illness that impairs psychosocial functioning and reduces quality of life (2, 3). In 2020, it accounted for the largest share (36.4%) of disability-adjusted life years attributable to mental disorders (1).

The global employment-to-population ratio is approximately 60% (4), highlighting the significance of addressing depression in the working population. The prevalence of mental illness is notably high among the working population, with 15 percent of working-age adults experiencing mental disorder (5), which can reduce healthy life expectancy and productivity, with substantial health, social, and health consequences (6–8). Effectively preventing depression among workers not only improves their quality of life but also boosts economic productivity and enhances the well-being of their dependents.

Growing research attention on the social determinants of depression highlights the role of socioeconomic status (SES), often measured through education or income levels, as a key factor (9–11). Despite extensive research from high-income countries, low- and middle-income countries, which experience over 80% of the health loss from depression and face pronounced socioeconomic inequalities, remain insufficiently explored (12, 13).

China, a middle-income country, has experienced rapid economic growth accompanied by increasing income inequality (14). This context has fostered “involution (neijuan),” or intense internal competition (15), and a culture of overwork (16), contributing to the emergence of depression as a significant public health concern. In 2020, 51 million adults aged 20 and older in China were suffering from depressive disorders, representing 17.3% of global cases (1). The examination of socioeconomic inequalities in depression within China’s working population could enhance global discourse on this topic and offer insights for other emerging economies with similar economic dynamics and cultural backgrounds.

Identifying the mediators that link SES to depression is essential for a deeper understanding of the mechanisms underlying socioeconomic inequalities in depression. For the working population, job conditions may serve as a crucial mediator in the association between SES and depression. Drawing on the Job Demand-Resource model, job conditions can be categorized into job demands (also referred to as stressors) and job resources, offering a framework for understanding their impact (17).

Job demands, such as long working hours, irregular work schedules, and work-family boundary-crossing requirements, are challenging aspects of work that may lead to depression (17). Some Western studies suggest a “stress of higher status” pattern, in which increased job demands among higher SES individuals mask socioeconomic disparities in depression (18, 19). These concerns are rooted in Coser’s “greedy institution” theory (20) and Blair-Loy’s concept of the “work devotion schema” (21), which posits that higher-status workers face limitless demands for effort and energy due to the intense allegiance and unwavering commitment required of them (22). Conversely, other research indicates that lower SES individuals face heavier job demands, contributing to socioeconomic inequalities in depression, which suggest a “stress of lower status” pattern (23–25). While there is a lack of evidence from non-Western contexts to contribute to this debate, it is possible that higher SES individuals in China may experience increased depression due to the stressors associated with maintaining or improving their status in a highly competitive labor market, although further investigation is needed.

Job resources include beneficial aspects such as schedule control, job authority, and job security (26). It is hypothesized that an abundance of job resources that serve as a sense of mastery and perceived control among those with higher SES may contribute to their lower depression levels (27, 28), but empirical examination of job resources as a mediator in the SES-depression relationship has been limited, particularly in China.

It is crucial to separately investigate how income and education correlate with depression to fully understand how depression is distributed across SES. Each measure—education and income—captures a unique aspect of SES, potentially linking to depression through different mechanisms (12, 29, 30), and their impact can vary significantly across societies (31–34). Given the cultural emphasis on academic success in China (35, 36), we specifically investigate whether education is associated with lower depression levels, independent of income. Furthermore, a detailed examination of how job demands and resources mediate the relationships between education, income, and depression could reveal distinct pathways associated with depression. This analysis would complement existing research that has identified various patterns in how job conditions mediate these relationships (11).

In sum, the present study attempts to fill the gaps by investigating the following questions: For China’s working population, (1) What is the relationship between SES and depression? Both income and education are considered as SES indicators to obtain a complete picture from different dimensions of this relationship. (2) How do job conditions, divided into job demands and job resources, mediate the education- and income-depression relationship? We analyze the potential mediating effect of job conditions in the relationship between SES and depression to test whether the Chinese evidence favors the “stress of higher status” pattern or suggests an alternative explanation.

Using CFPS 2020 data, a nationally representative sample, we explore the relationships between SES, job conditions, and depression in the Chinese working population. Our first main finding is that both education and income are negatively associated with depression, with education’s association with depression remaining net of income, which is consistent with some Chinese evidence (60) while contradicting some studies from Western contexts, like Schieman and Koltai (11), which suggest that income fully accounts for the association between education and depression. This may stem from China’s cultural emphasis on education, which makes the benefits of education for mental health go well beyond the return on income and more to the self-fulfillment and social recognition that education directly brings (35, 36). Another potential explanation could be the unique relationships that education and income each have with job demands, given that job demands are closely associated with depression. This will be further explored in the subsequent discussion on the mediating role of job conditions in the SES-depression relationship.

Additionally, this study examines the mediating role of job conditions, encompassing job demands and job resources, between SES and depression. Our findings reveal that job demands may act differently in the education and income’s association with depression. As for the mediating role of job demands in the education-depression association, compared to those with less than a high school degree, better educated people have fewer working hours, and those with a 4-year college degree have less likelihood of on-call duty. This contributes to the observed gap in depression between those with lower and higher education levels, suggesting a “stress of lower status” pattern. Regarding the association between income and depression, were it not for the significantly longer working hours required of the second lowest and middle earners and the marginally significantly longer working hours required of the highest earners, as well as the greater likelihood of on-call duty required of the middle earners, the depression gap between these groups of higher earners and the lowest earners would have been even greater, providing partial support to the “stress of higher status” hypothesis. This variation helps clarify the unique relationships that education and income each have with depression. Given that the mediating effects are not consistently significant across all SES levels when compared to the lowest level, these findings should be interpreted with caution. Furthermore, we found no support for a mediating effect of nightshift and weekend shift frequency in either the education-depression or income-depression association.

One possible reason for the lower job demands of the better educated is that higher educational attainment provides an advantage in the employment market, allowing these highly educated individuals to gravitate toward less demanding jobs during the job search phase (61, 62).

Meanwhile, in accord with the existing American evidence (11), our study shows that the income-based differences in depression levels appear to be obscured by some job demands. In our study, higher earners, affected by a sluggish economy and Confucian success values, seem willing to engage in more time-intensive work as a self-motivated trade-off for higher salaries. This self-exploitation benefits the “greedy institutions” but may contribute to the burnout and depression amidst accelerating demands and self-imposed expectations.

Job resources may also mediate the SES-depression association, though the evidence is relatively weak, as most changes in the coefficients for education or income categories after accounting for job resource measures do not reach statistical significance or are only marginally significant. One exception is the mediating effect of job security on the depression difference between the most and least educated groups; specifically, the most educated have higher job security, which may partially explain their lower depression levels compared to the least educated. However, the mediating effect of schedule flexibility in the depression difference between the most and least educated groups is only marginally significant, requiring further investigation to confirm its role. Similarly, higher job security and moderate schedule flexibility among the highest income earners may partially explain their lower depression levels compared to the lowest income earners, but these effects are only marginally significant and warrant further investigation. In addition, we found no support for a mediating effect of holding a direct supervisory role—another job resource measure—in either the education-depression or income-depression association. The preliminary findings highlight the need for societal awareness and action, as poorly educated and low-income workers appear to have fewer job resources, potentially leading to higher levels of depression.

In summary, the association between education and depression persists even when accounting for income can be partly explained by the fact that higher earners are more exposed to some increased job demands, which leads to depression. Conversely, the well-educated generally benefit from less demanding jobs thanks to their advanced level of education.

Our study has several limitations that should be acknowledged. First, we conduct a cross-sectional analysis using the most recent available CFPS data because our primary objective is to examine the distribution of depression across SES and the mediating role of job conditions. This approach helps identify which SES groups are most disadvantaged and the underlying reasons. Additionally, only CFPS 2020 includes certain job demands variables, such as on-call duty, shift work frequency, and schedule flexibility. As a result, we could not use earlier wave data to predict depression outcomes, limiting our ability to perform a longitudinal study. Due to the cross-sectional design, our study does not establish causal relationships. Further longitudinal research is necessary to fully understand the associations between SES and depression. Second, this study does not encompass all typical job demands and resources outlined in the JD-R model. While the JD-R model highlights the importance of interpersonal support from supervisors and colleagues as job resources, and subjective job stress and work–family conflict as key job demands, we were unable to explore their mediating effects due to data limitations. Similarly, for psychological workload, we used measures such as self-reported working hours as its proxies, acknowledging that this approach may be somewhat tenuous. Future research is needed to better align with the JD-R model when more comprehensive Chinese data, including a wider range of job conditions, becomes available. Third, although occupational status is also an important measure of SES, we treat employees’ occupations as a control variable rather than investigating the occupation-depression relationship and how job conditions mitigate this relationship. Given the study’s scope and feasibility, we decided to focus on the association between education, income, and depression. Including occupation as an additional variable of SES could have added complexity beyond our research’s intended scope, which could be investigated in future research.

The present study sheds light on the SES-depression relationship in the Chinese workforce, revealing the nuanced roles of education and income, and, in particular, highlighting the mediating role of job conditions. This study provides preliminary evidence of distinctive patterns of greater job demands (i.e., working hours and on-call duty) associated with lower education and higher income, and the disadvantaged job resources (i.e., schedule flexibility and job security) associated with lower SES that lead to depression, contributing to the understanding of socioeconomic inequalities in depression in a non-Western context. While the negative associations between SES and depression are robust, the mediating effects of job conditions—particularly job resources—are less conclusive, as the mediating effects of most job resource measures only reach marginal or no statistical significance. Consequently, the findings related to the mediation analysis should be interpreted with caution and further research is needed. Based on these preliminary results, policymakers are encouraged to consider adopting regulations that enhance work-life balance, especially for high earners and less educated individuals, who tend to face higher job demands. Efforts are also needed to reduce the potential disparities in job resources across different SES groups to alleviate the socioeconomic inequalities in depression.