Regional interaction of lung cancer incidence influenced by PM2.5 in China

城市化 中国 肺癌 工业化 人口 入射(几何) 地理 环境卫生 经济增长 医学 经济 肿瘤科 市场经济 光学 物理 考古
作者
Jiqun Wen,Xiaowei Chuai,Runyi Gao,Baoxin Pang
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:803: 149979-149979 被引量:21
标识
DOI:10.1016/j.scitotenv.2021.149979
摘要

PM2.5 is the key pollutant threatening human health and can even cause lung cancer. Pollution is the most serious problem in China with its fast industrialisation, urbanisation and high population density. This pollutant is conveyed through the atmosphere, trade and the embodied emission flow amongst regions. Scientific evaluation of the responsibility for regional lung cancer by considering both internal and external influences seems to be meaningful in addressing regional inequity. This study develops a relatively convenient and practical method to evaluate the regional inequity reflected by lung cancer associated with PM2.5 pollution in China. Results show that PM2.5 emissions and concentrations have similar distribution patterns: high values were predominant in the east and south where has high population density, while the west had low values. The cancer incidence rate showed high values mainly in eastern and central China. At a provincial scale, the lung cancer incidence rate was significantly correlated with PM2.5 concentration levels, and a high correlation was also found between PM2.5 concentration and emissions, indicating that emission reduction is the key to lung cancer prevention. Due to domestic trade, some developed regions more pulled lung cancer in less developed regions, and some less developed regions also have an obvious influence on external regions. Spatially, provinces in northern and central China are always more influenced by external regions. Lung cancer inequity analysis shows that coastline regions are more advantaged, while the reverse applies to inland China. The central government needs to further strengthen regional coordinated development measures, such as economic compensation for medical care and adjustments to industry structure. It should optimise spatial allocation and comprehensively consider regional inequity and character.
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