Background: A paucity of data has made it challenging to construct a deprivation index at the lowest administrative, or county, level in China. An index is required to guide health equity monitoring and resource allocation to regions of greatest need. This study used China's 2010 census data to construct a county-level area-deprivation index (CADI).
Methods: Data for 2869 counties from China's 2010 census were used to generate a CADI. Eleven indicators across four domains of deprivation were selected for principal component analysis with standardisation of the first principal component. Sensitivity analysis was used to test whether the population size and weighting method affected the index's robustness. Deprived counties identified by the CADI were then compared with China's official list of poverty-stricken counties.
Results: The first principal component explained 60.38% of the total variation in the deprivation indicators. The CADI ranged from the least deprived value of -2.71 to the most deprived value of 2.92, with SD of 1. The CADI was found to be robust against county-level population size and different weighting methods. When compared with the official list of poverty-stricken counties in China, the deprived counties identified by the CADI were found to be even more deprived.
Conclusion: Constructing a robust area-deprivation index for China at the county level based on population census data is feasible. The CADI is a potential policy tool to identify China's most deprived areas. In the future, it may support health equity monitoring and comparison at the national and subnational levels.
Keywords: Health inequalities; deprivation; geography; health policy; social inequalities.
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