Research on the effect of work value perception on workers’ health, especially in emerging economies, is scarce. This study, therefore, explored how work value perception affects the physical and mental health of workers in China. We also examined the mediating role of life satisfaction in the relationship between work value perception and health. Taking a random sample of 16,890 individuals in China, we used ordered probit regression and instrumental variable ordered probit regression to test the links between work value perception and workers’ health based on existence, relatedness, and growth (ERG) theory. The results showed that work value perception significantly affected both the physical and mental health of workers; the results remained robust after solving the endogeneity problem. The subsample regression results showed that work value perception significantly affected the physical and mental health of female, male, married, unmarried, religious, and nonreligious workers. Furthermore, life satisfaction mediated the effect of work value perception on workers’ health. These results shed light on the relationship between work value perception and health and thus have implications for improving workers’ physical and mental health. This study can provide a reference for both governmental and corporate policymakers in emerging economies.

Background: Health inequality is seen as a challenge for implementing the Healthy China Strategy. This study analyzes the income-related health inequality among urban–rural resident basic medical insurance (URRBMI) participants. Methods: This study utilized data from the 2019 China Household Finance Survey (CHFS), and the concentration index (CI) was employed to estimate the effects of income-related health inequality on participants. Results: Our findings provide clear evidence that health inequality among participants has fluctuated—narrowing, widening, and then narrowing again—in the areas of the contribution, medical treatment, and reimbursement of URRBMI, respectively. Overall, the analysis indicates a widening of health inequality post-reimbursement, with results remaining consistent. A heterogeneity analysis shows that health inequality is most pronounced among women and those with less than a middle school education. Finally, our study reveals a pro-rich trend in the actual utilization of medical services among participants, with persistent disparities in outpatient and inpatient service usage even after standardization, further exacerbating income-related health inequality. Conclusions: We recommend that the URRBMI design take participants’ income levels into account, with policies favoring disadvantaged individuals to enhance their medical security, improve access to healthcare services, and ultimately reduce health inequality.