Controlling for migration effects in ecological disease mapping of prostate cancer
Controlling for migration effects in ecological disease mapping of prostate cancer
复制标题
DOI：
10.1007/s00477-007-0148-8
复制
发表时间：
2007-05
影响因子：
4.2
通讯作者：
M. Tiefelsdorf
中科院分区：
文献类型：
--
作者：
M. Tiefelsdorf
分析性疾病制图的目的是将控制变量、接触潜在风险因素和保护因素与疾病事件的地理分布联系起来。其目标是(a)确定非典型的低和高疾病风险区域，以及(b)加强我们对潜在疾病产生过程的理解。然而，与分析性疾病制图中的许多其他障碍一样，区域间移徙掩盖了观察到的发病率与风险因素之间的任何直接区域关联。在1970-1994年报告期间，508个州经济区（SEA）的前列腺癌死亡率在生态回归模型中与假定影响因素的代理变量相关联。采用半参数地理滤波方法，利用1965-1970年东南亚区域间人口普查迁移流作为潜在的空间结构，控制混杂迁移效应。尽管有一些简化的假设，但这种方法可以评估潜在风险因素对前列腺癌空间变异性的直接影响，并使疾病发生过程的潜在空间维度可视化。结果表明，合并外生变量的相关性发生了变化。
Analytical disease mapping aims at linking control variables, the exposure to potential risk factors and to protective elements with the geographical distribution of disease events. Its goals are (a) to identify areas of atypical low and high disease risk and (b) to enhance our understanding of the underlying disease generating process. However, along with many other obstacles in analytical disease mapping, interregional migration masks for degenerative diseases with a long latency period any direct regional association between the observed disease rates and risks factors. Prostate gland cancer mortality rates of the 508 State Economic Areas (SEA) for the reporting period 1970–1994 are linked in an ecological regression model to proxy variables of putatively influential factors. A semi-parametric geographical filtering approach that uses the 1965–1970 interregional census migration flows among the SEA as underlying spatial structure is applied to control for confounding migration effects. This approach allows, despite some simplifying assumptions, to assess direct effects of potential risk factors on the spatial variability of prostate cancer and to visualize underlying spatial dimensions of the disease generating process. Results indicate a shift in relevance of the incorporated exogenous variables.