地理研究

地理研究 ›› 2014, Vol. 33 ›› Issue (11): 2115-2124.doi: 10.11821/dlyj201411011

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中国“癌症村”的聚集格局

董丞妍1(), 谭亚玲2, 罗明良1(), 翟有龙1   

  1. 1. 西华师范大学国土资源学院,四川 南充 637009
    2. 西华师范大学校医院,四川 南充 637009
  • 收稿日期:2014-04-04 修回日期:2014-07-25 出版日期:2014-11-10 发布日期:2014-11-10
  • 作者简介:

    作者简介：董丞妍(1989- ),女,河北邯郸人,硕士,主要从事GIS及环境保护等研究。E-mail:chengyan0214@yeah.net

  • 基金资助:
    国家自然科学基金项目(41101348);四川省科技厅应用基础研究规划项目(2010JY0089);四川省教育厅自然科学重点项目(2009ZA120)

Spatial aggregation pattern of “cancer village” in China

Chengyan DONG1(), Yaling TAN2, Mingliang LUO1(), Youlong ZHAI1   

  1. 1. Land and Resources School, China West Normal University, Nanchong 637009, Sichuan, China
    2. China West Normal University Hospital, Nanchong 637009, Sichuan, China
  • Received:2014-04-04 Revised:2014-07-25 Online:2014-11-10 Published:2014-11-10

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摘要：

“癌症村”反映了在一定时间和空间上癌症聚集发生、引起社会群体格外关心的公共卫生问题,具体表现为从某一年开始并持续多年的远高于正常水平的癌症发生率和死亡率。研究基于地理空间统计分析的局部自相关、点距离关联维及核密度等方法,从不同空间尺度分析了“癌症村”的分布状况。结果表明：“癌症村”聚集分布但区域差异显著,总体上自东向西梯度递减,局部自相关分析表明川陕晋冀津构成西部与东部之间低—高集聚分布的分界线;距离关联无标度区间为120~180 km,核密度分析显示“癌症村”集中于河流下游地区,及中部、沿海部分地区,多中心、集中分布格局明显。研究突出了“癌症村”地理多尺度分布特征的探索,可为相关环境污染整治工作提供参照。

关键词: “癌症村”, 空间分布, 局部自相关, 核密度, 中国

Abstract:

Cancer village, also known as cancer cluster in certain time and space, reflects one of great concerns for public health from society and population groups. Cancer village specifically refers to a much higher incidence and mortality of cancer than normal levels, which begins in a given year and lasts for many years. In this paper, some GIS technologies are used to investigate the spatial pattern of “cancer village”, such as local geo-spatial autocorrelation, correlation dimension based on point-point distances, and kernel density method. The pattern at provincial and regional scales is described, and the much larger scale depicted by kernel density analysis is also investigated with more emphasis. The results indicate that: (1) From viewpoint of the national scale, “cancer village” shows a clustered distribution, which means the number of “cancer village” in some provinces is much greater than that in other ones. Meanwhile, the difference of spatial distribution of “cancer village” is significant at regional scale, for example, there is an obvious decreasing trend from eastern to western China. (2) When local autocorrelation analysis is used, there is a demarcation line between low and high aggregation levels of “cancer village” in the rendered map. The region demarcation line is formed by the provincial units of Sichuan, Shanxi, Shaanxi, Hebei and Tianjin. To the left part of demarcation line, there is a much lower incidence of cancer, or without “cancer village” reported in provinces such as Qinghai and Gansu. (3) We also calculated the Euclid distances between every pair of “cancer village” points, and the statistical results show that the scale-free range of the distance associated is about 120-180 km with a relatively significant correlation dimension of 1.25. The correlation dimension also indicates a certain spatial distance constraint of “cancer village”. (4) Based on kernel density analysis, we can find that “cancer village” clustered at the lower reaches of rivers, some parts of central China and coastal regions of China. The aggregation morphology shows a pattern of multi-center and aggregation distribution. The aggregation region mainly covers some lower reaches of rivers including the Yellow River, Huaihe River and Yangtze River, and also appears near the Dongting Lake and Poyang Lake. This study explores the geographical distribution of “cancer village” with multi-scale methods, and will provide some references in related environmental regulation work.

Key words: “cancer village”, spatial distribution, local autocorrelation, kernel density, China