Identification and analysis of influencing factors of multidimensional health poverty in rural areas of Northwest China

Abstract

Abstract Poverty alleviation remains an urgent issue in China’s rural areas, with health poverty being a critical dimension. This study analyzed the multidimensional health poverty status of 9,052 rural residents in Ningxia in 2019 and 7,910 in 2022, aiming to provide a reference for optimizing health poverty alleviation strategies. The A-F dual cutoff method was used to identify and measure multidimensional health poverty through dimensions such as health status, health service utilization capacity poverty, and health spending and security poverty. Logistic regression analysis was further applied to examine the influencing factors of multidimensional health poverty. The results indicate that when the k-value is set at 0.3, the incidence of multidimensional health poverty was 22.3% in 2019 and 7.7% in 2022. The corresponding multidimensional health poverty indices were 0.091 and 0.028, respectively. Furthermore, the level of multidimensional health poverty was higher among women than men. Chronic diseases were identified as a significant indicator of multidimensional health poverty. At the individual level, gender, age, education, government subsidies, family size, housing, and digital divide significantly effected health poverty. Although multidimensional health poverty has improved in rural northwest China, targeted measures remain essential, especially for rural women, individuals with chronic illnesses, and those facing challenges in accessing healthcare and digital connectivity. Sustainable multidimensional health poverty alleviation should prioritize remote rural areas, especially by enhancing healthcare resource utilization for rural women and individuals with chronic diseases. Additionally, increasing medical subsidies for marginalized groups is essential. Improving rural housing conditions, strengthening digital infrastructure, and raising digital health literacy are also critical steps.

Keywords

• Multidimensional health poverty
• Identification
• Influence mechanism
• Rural residents
• Panel data
• China