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Poverty is widely recognized as a multifaceted concept and has been extensively studied. However, less research has been conducted to explore multidimensional poverty in China. This article aims to investigate the measurements and determinants of multidimensional poverty in mountainous areas of Southeast China. The Alkire–Foster method and a logistic regression modeling technique are applied to examine multidimensional poverty and its determinants, respectively. Four dimensions (income, education, health, and living standards) and eight indicators are considered for the measurements of multidimensional poverty. By interviewing 198 rural households in Shouning County, Fujian Province of China, the article reveals about sixty percent of the sample households are found to experience multidimensional poverty, which is remarkably higher than previous studies. Deprivation in four dimensions is not homogeneous. The incidence of deprivation in education and health dimension are remarkably higher than dimensions of income and living standards. Results also reveal that health (34.27%) and education (27.45%) are the two most important contributors of multidimensional poverty, which jointly account for 61.72% of overall poverty. Living standards (23.25%) and income (15.03%) are the other two important contributors of multidimensional poverty. The important determinants of multidimensional poverty are the number of chronic patients, dependency ratio, elevation, and information accessibility. The results confirm that chronic disease or disability is the key determinant of poverty in rural areas of China. The study suggests that policy focus of poverty alleviation should be changed from income growth to health and education improvement. The provision and accessibility of health care services in rural areas need to be emphasized. Future research should focus on the heterogeneity of multidimensional poverty in China to expound the spatial difference and household difference in multidimensional poverty.
Wang et al. (Sun,) studied this question.