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Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic

机译:使用贝叶斯空间模型和空间扫描统计,探索德黑兰女性乳腺癌发病率的邻里不等式

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摘要

OBJECTIVES The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. METHODS The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR) of BC for each neighborhood was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by a Besag, York, and Mollie spatial model and the spatial empirical Bayesian method. The purely spatial scan statistic was used to identify spatial clusters. RESULTS There were 4,175 incident BC cases in the study area from 2008 to 2011, of which 3,080 were successfully geocoded to the neighborhood level. Higher than expected rates of BC were found in neighborhoods located in northern and central Tehran, whereas lower rates appeared in southern areas. The most likely cluster of higher than expected BC incidence involved neighborhoods in districts 3 and 6, with an observed-to-expected ratio of 3.92 (p<0.001), whereas the most likely cluster of lower than expected rates involved neighborhoods in districts 17, 18, and 19, with an observed-to-expected ratio of 0.05 (p<0.001). CONCLUSIONS Neighborhood-level inequality in the incidence of BC exists in Tehran. These findings can serve as a basis for resource allocation and preventive strategies in at-risk areas.
机译:目的这项研究的目的是探讨伊朗德黑兰邻里水平的雌性乳腺癌(BC)的空间模式。方法本研究包括从2008年3月至2011年3月到2011年3月的所有注册事件案件。通过比较观察到的案件,估计了每个社区的BC的原始标准化发病率(先生)通过比较预期案件。估计的原始SIR由BESAG,York和Mollie空间模型和空间经验贝叶斯方法进行平滑。使用纯粹的空间扫描统计来识别空间簇。结果2008年至2011年的研究区有4,175名事件,其中3,080件成功地地理统计到邻里。位于德黑兰北部和中部的社区中发现了BC的预期税率,而南部地区出现较低的利率。高于预期的BC发病率的最可能集群涉及地区3和6的社区,观察到的预期比率为3.92(P <0.001),而最可能的低于预期的速率涉及区域17的社区, 18和19,观察到的预期比为0.05(p <0.001)。结论德黑兰人中BC发病率中的邻域级不等式。这些发现可以作为风险地区资源分配和预防策略的基础。

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