Household income, income inequality, and health-related quality of life measured by the EQ-5D in Shaanxi, China: a cross-sectional study

• Main Authors: Zhijun Tan, Fuyan Shi, Haiyue Zhang, Ning Li, Yongyong Xu, Ying Liang
• Format: Article
• Language: English
• Published: BMC 2018-03-01
• Series: International Journal for Equity in Health
• Online Access: http://link.springer.com/article/10.1186/s12939-018-0745-9

Abstract Background In advanced economies, economic factors have been found to be associated with many health outcomes, including health-related quality of life (HRQL), and people’s health is affected more by income inequality than by absolute income. However, few studies have examined the association of income inequality and absolute income with HRQL in transitional economies using individual data. This paper focuses on the effects of county or district income inequality and absolute income on the HRQL measured by EQ-5D and the differences between rural and urban regions in Shaanxi province, China. Methods Data were collected from the 2008 National Health Service Survey conducted in Shaanxi, China. The EQ-5D index based on Japanese weights was employed as a health indicator. The income inequality was calculated on the basis of self-reported income. The special requirements for complex survey data analysis were considered in the bivariate analysis and linear regression models. Results The mean of the EQ-5D index was 94.6. The EQ-5D index of people with low income was lower than that in the high-income group (for people in the rural region: 93.2 v 96.1, P < 0.01; for people in the urban region: 95.5 v 96.8, P < 0.01). Compared with people with moderate inequality, the EQ-5D index of those with high inequality was relatively lower (for people living in the rural region: 91.1 v 95.8, P < 0.01; for people living in the urban region: 95.6 v 97.3, P < 0.01). Adjusted by age, gender, education, marital status, employment, medical insurance, and chronic disease, all the coefficients of the low-income group and high income inequality were significantly negative. After stratifying by income group, all the effects of high income inequality remained negative in both income groups. However, the coefficients of the models in the high income group were not statistically significant. Conclusion Income inequality has damaging effects on HRQL in Shaanxi, China, especially for people with low income. In addition, people living in rural regions were more vulnerable to economic factors.