China's social deprivation: Measurement, spatiotemporal pattern and urban applications. (April 2017)

• Record Type: Journal Article
• Authors: Wan, Chen; Su, Shiliang
• Is Part Of: Habitat international. Volume 62(2017)
• Page Start: 22
• Page End: 42
• Publication Date: 2017-04
• Subjects: Social deprivation -- Spatial exploratory analysis -- Quantile regression -- Urbanization -- Social injustice -- Environmental inequalities; Human settlements -- Periodicals; 307
• DOI: 10.1016/j.habitatint.2017.02.007
• Languages: English
• ISSNs: 0197-3975

Abstract

Abstract: Expanding numbers of homogenous geographical units with social and economic shortages and disadvantages (defined as social deprivation in the literature) have emerged in many cities around the world, particularly in developing countries. Consensus has been reached on the acknowledgement of social deprivation as a major challenge for humanity and sustainability. It therefore requires strong knowledge to measure, identify, and target the deprived units at different scales. Based on census data at prefecture city level from 2000 to 2010, this paper employs the principle component analysis to formulate a family of indices to measure China's social deprivation. In particular, one integrated social deprivation index (ISDI) and five sub-indices (general socioeconomic deprivation, disadvantaged population, education deprivation, housing deprivation, and occupation deprivation) are developed. The Receiver Operating Characteristic curve confirms that the ISDI is valid and efficient in social deprivation measurement. Social deprivation shows obvious spatiotemporal heterogeneity across the 333 cities in China. It roughly presents the geography that cities with lower ISDI are mainly distributed in eastern and northeastern China, while cities of higher social deprivation are generally located in the central and western regions. Comparisons between 2000 and 2010 indicate that only the capital cities remain at lower levels in the five domains. Many cities have experienced increased levels in certain domains. Quantile regression is finally utilized to explore the applications of ISDI in three major urban issues (urban policy performances evaluation, environmental inequalities assessment, and social injustice evaluation). Social deprivation is negatively associated with urbanization indicators at 5 representative quantiles (the 10th, 25th, 50th, 75th and 90th quantile), annual mean PM2.5 concentration at first 10 percentiles and urban public green spaces (UPGS) at almost all percentiles. These results respectively donate that urbanization policy has played a positive role in eliminating social inequalities, the least deprived 30 cities in China could be exposed to higher PM2.5 concentrations, and the highly deprived cities have fewer urban public green spaces. Our study demonstrates that the ISDI has promising applicability in addressing urban issues in China. The methodological framework is not restricted in China and can be employed to other developing countries around the world. This paper is believed to offer new insights into habitat research.