Frontiers in Public Health (Mar 2023)
Quality of life assessment and its spatial correlation in impoverished districts and counties: A case study of Guizhou Province
Abstract
China’s rapid urbanization has greatly boosted the quality of life of its traditionally impoverished regions. Research into the spatial distribution characteristics, evolution and spatial correlation of the quality of life in impoverished regions can help illuminate the experience of successful development and construct a knowledge base for authorities to devise development strategies. This study focuses its attention on the historically impoverished districts and counties (which are designated as parallel administrative units in China) of Guizhou Province in southwestern China. Extensively citing official statistics on districts and counties released by China’s National Bureau of Statistics and local governments, it assesses the quality of life of those places in the 3 years of 2000, 2010, and 2020 from the four dimensions of economy, society, culture, and environment. The aim is to illustrate the distribution characteristics and the evolution of quality of life in Guizhou’s historically impoverished districts and counties. In order to understand the characteristics of spatial clustering as well as the patterns of evolution of the quality of life of Guizhou’s impoverished districts and counties, the study incorporates spatial autocorrelation analysis into a spatio-temporal analysis of local quality of life. It could presumably help enrich the knowledge base that local authorities draw on to formulate development strategies that are scientific and adapted to local conditions. The study found that while the overall quality of life in all the impoverished districts and counties of Guizhou Province has improved, large gaps in quality of life between eastern and western regions of the province persisted. In addition, the driving force behind the evolution in the overall quality of life of those places changed with time, as did the characteristics of the spatial aggregation in quality of life.
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