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Area Deprivation and Liver Cancer Prevalence in Shenzhen,China: A Spatial Approach Based on Social Indicators
Authors:Min Weng  Jianhua Pi  Bingqing Tan  Shiliang Su  Zhongliang Cai
Institution:1.School of Resource and Environmental Sciences,Wuhan University,Wuhan,China;2.Key Laboratory of Geographical Information Systems, Ministry of Education,Wuhan University,Wuhan,China;3.Collaborative Innovation Center of Geospatial Technology,Wuhan University,Wuhan,China;4.Key Laboratory of Digital Mapping and Land Information Application Engineering, National Administration of Surveying, Mapping and Geoinformation,Wuhan University,Wuhan,China
Abstract:Cancer has become an alarming threat to human health and well-being worldwide. Examining the social determinants of cancer prevalence should effectively inform the practices and strategies on cancer treatment and prevention. However, rather few studies have conducted in this regard for developing countries. This paper attempts to characterize the association between area deprivation and liver cancer prevalence using a case of Shenzhen, China. Data from 2009 to 2011 provided by Shenzhen’s Health Information Center are used to calculate the incidence rate of liver cancer at district level. An area deprivation index (ADI) at district level is established by integrating 13 indicators of 5 domains (income, employment, education, housing and demography). The weight for each indicator is determined by two typical subjective methods (AHP and fuzzy AHP) and two common objective methods (Entropy and Coefficient Variation). Quantitative comparisons indicate that the four methods are highly consistent though they assign different weight to the indicators. Spatial lag regression identifies significantly positive linear relationships between ADIs and liver cancer incidence rate from 2009 and 2010. It suggests that greater possibility of liver cancer prevalence would be expected in districts of higher social deprivation. The results also denote that the obtained relationships are insensitive to weight determination method and temporal dimension. Our study demonstrates that spatial autocorrelation should be incorporated for better understanding the association between area deprivation and liver cancer prevalence at district level. This paper provides some new insights into social indicators research.
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