Health inequalities for China's low-income population: trends, subgroup differences, and influencing factors,...

Health inequality is a global challenge, with low-income populations often facing higher health risks. This study aims to systematically analyze the current status, trends, and influencing factors of health inequalities for China's low-income population.

Utilizing panel data from the China Family Panel Studies (CFPS) from 2010 to 2022, the low-income population was identified using a threshold of 67% of median income. Health inequalities were measured across four dimensions: self-rated health, mental health, two-week health, and chronic diseases status, using the Erreygers Index (EI) and Wagstaff Index (WI). Recentered Influence Function (RIF) regression and RIF-Oaxaca decomposition were employed to examine influencing factors of health inequalities and sources of disparities across urban-rural, gender, and age dimensions.

From 2010 to 2022, the degree of health inequality was significantly higher for the low-income group compared to the middle and high-income groups in China. Inequalities in self-rated health and chronic diseases status showed an increasing trend for the low-income population. Per capita household income (PCHI) was a key factor, exhibiting a significant negative impact on inequalities in self-rated health and mental health (p < 0.01). Age had an inverted U-shaped effect on health inequalities, while household size significantly and negatively influenced disparities in self-rated health and two-week health (p < 0.01). Differences in the level of medical expertise of the visited institutions significantly affected chronic disease status inequalities (p < 0.01). The PCHI was the primary source of health inequality disparities across urban-rural, gender, and age groups, with the older adult low-income group experiencing significantly higher levels of health inequality compared to the non-older adult group.

Health inequalities for the low-income population in China are becoming increasingly severe, particularly pronounced among older adult and rural groups. The study recommends implementing interventions across multiple dimensions, including income support, healthcare accessibility, and family care support, while adopting differentiated policies tailored to the characteristics of various groups. Particular attention should be given to intersectionally disadvantaged groups such as low-income older adult individuals in rural areas.