Evaluating geostatistical modeling of exceedance probability as the first step in disease cluster investigations: very low birth weights near toxic Texas sites.
Evaluating geostatistical modeling of exceedance probability as the first step in disease cluster investigations: very low birth weights near toxic Texas sites.
复制标题
DOI：
10.1186/1476-069x-13-47
复制
发表时间：
2014-06-07
期刊：
影响因子：
--
通讯作者：
Sweeney AM
中科院分区：
文献类型：
--
作者：
Thompson JA;Bissett WT;Sweeney AM
评估潜在的疾病地理集群的第一步要求对疾病风险进行评估，将确定位置的风险与相邻位置的风险进行比较。然而，环境暴露是指整个空间的连续暴露水平，而不是具有明显边界的暴露。本研究的目的是调整、应用和评价用于确定疾病群的地统计方法。极低出生体重（VLBW; < 1.5 kg）婴儿的死亡概率使用内在条件自回归模型绘制。这些数据被应用到一个20 × 20的网格中，网格的像素为1平方公里，中心位于德克萨斯州哈里斯县的13个国家优先级超级基金网站中的每一个。在13个超级基金场址中的4个场址附近发现了大群极低体重生物。三个与疾病集群相关的超级基金站点位于休斯顿市中心，这些站点可能被一个单一的融合疾病集群所包围。对极低出生体重婴儿死亡概率的地统计学建模确定了德克萨斯州哈里斯县超级基金站点附近不同大小、形状和统计确定性的疾病群。该方法提供了相当大的潜力，作为调查潜在疾病群的第一步。
The first step in evaluating potential geographic clusters of disease calls for an evaluation of the disease risk comparing the risk in a defined location to the risk in neighboring locations. Environmental exposures, however, represent continuous exposure levels across space not an exposure with a distinct boundary. The objectives of the current study were to adapt, apply and evaluate a geostatistical approach for identifying disease clusters. The exceedance probability for very low birth weight (VLBW; < 1.5 kg) infants was mapped using an Intrinsic Conditional Autoregressive model. The data were applied to a 20 by 20 grid of 1 km2 pixels centered on each of the 13 National Priority List Superfund Sites in Harris County, Texas. Large clusters of VLBW were identified in close proximity to four of the 13 Superfund Sites. Three of the Superfund Sites, associated with disease clusters, were located close together in central Houston and these sites may have been surrounded by a single, confluent disease cluster. Geostatistical modeling of the exceedance probability for very low birth weights identified disease clusters of varying size, shape and statistical certainty near Superfund Sites in Harris County, Texas. The approach offers considerable potential as the first step for investigating potential disease clusters.