Income inequality and multimorbidity patterns in China: a micro-level analysis using CHARLS
Year: 2025
Type: article
Abstract: Introduction: Health inequality-particularly income-related health inequality-poses a global challenge, significantly affecting social and economic well-being. While previous research has investigated the link between income inequality and various health outcomes, including chronic diseases, studies focusing on multimorbidity remain limited. Methods: This study examines how income inequality affects multimorbidity in China, drawing on data from the China Health and Retirement Longitudinal Study. By employing the Kakwani Index, the analysis evaluates income inequality at the individual level and utilizes Latent Class Analysis to identify multimorbidity patterns. The research further explores how these effects vary across different age groups and regions. The study investigates the role of household economic decisions in shaping health outcomes. RIF regression is used to break down the contribution of income inequality to health disparities. Results: Lower relative wage income was strongly associated with an increased number of chronic diseases and heightened likelihood of specific multimorbidity patterns, particularly Respiratory-Cardiovascular diseases and overall disease burden. Redistribution of income partially alleviated the negative impact of income inequality on health outcomes. The effects of income inequality on health differ notably across age groups and geographical regions. Developmental expenditures (e.g., improving living conditions) were more effective in addressing income-related health disparities than direct increases in healthcare spending. Discussion: Policy responses need to focus on targeted income redistribution strategies and increased investment in developmental initiatives to address these growing health inequalities.
Source: Frontiers in Public Health
Authors: Mengqian Ouyang, Bowen Liu, Riping Xu
Institutions: Harvard University, Guangdong Medical College
Language: English
Subfield: Health
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4409516650
