Mansori Kamyar, Mosavi-Jarrahi Alireza, Ganbary Motlagh Ali, Solaymani-Dodaran Masoud, Salehi Masoud, Delavari Alireza, Sanjari Moghaddam Ali, Asadi-Lari Mohsen
Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran. Email:
Asian Pac J Cancer Prev. 2018 Apr 27;19(4):1099-1104. doi: 10.22034/APJCP.2018.19.4.1099.
Objectives: Colorectal cancer (CRC) may now be the second most common cancer in the world. The aim of this study was to determine whether clusters of high and low risk of CRC might exist at the neighborhood level in Tehran city. Methods: In this study, new cases of CRC provided from Cancer Registry Data of the Management Center of Ministry of Health and Medical Education of Iran in the period from March 2008 to March 2011 were analyzed. Raw standardized incidence rates (SIRs) were calculated for CRC in each neighborhood, along with ratios of observed to expected cases. The York and Mollie (BYM) spatial model was used for smoothing of the estimated raw SIRs. To discover clusters of high and low CRC incidence a purely spatial scan statistic was applied. Results: A total of 2,815 new cases of CRC were identified and after removal of duplicate cases, 2,491 were geocoded to neighborhoods. The locations with higher than expected incidence of CRC were northern and central districts of Tehran city. An observed to expected ratio of 2.57 (p<0.001) was found for districts of 2, 6 and 11, whereas, the lowest ratio of 0.23 (p<0.001) was apparent for northeast and south areas of the city, including district 4. Conclusions: This study showed that there is a significant spatial variation in patterns of incidence of CRC at the neighborhood level in Tehran city. Identification of such spatial patterns and assessment of underlying risk factors can provide valuable information for policymakers responsible for equitable distribution of healthcare resources.
结直肠癌(CRC)目前可能是世界上第二大常见癌症。本研究的目的是确定德黑兰市社区层面是否存在CRC高风险和低风险聚集区。方法:在本研究中,分析了2008年3月至2011年3月期间伊朗卫生和医学教育部管理中心癌症登记数据中提供的CRC新病例。计算每个社区CRC的原始标准化发病率(SIRs)以及观察病例与预期病例的比率。使用约克和莫利(BYM)空间模型对估计的原始SIRs进行平滑处理。为了发现CRC高发病率和低发病率的聚集区,应用了纯空间扫描统计量。结果:共识别出2815例CRC新病例,去除重复病例后,2491例进行了社区地理编码。CRC发病率高于预期的地区是德黑兰市的北部和中部地区。第2、6和11区的观察病例与预期病例之比为2.57(p<0.001),而该市东北部和南部地区(包括第4区)的最低比率为0.23(p<0.001)。结论:本研究表明,德黑兰市社区层面CRC发病率模式存在显著的空间差异。识别这种空间模式并评估潜在风险因素可为负责医疗资源公平分配的政策制定者提供有价值的信息。