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作 者:于绍轶[1] 陈远银[1] 徐颖[1] 刘海韵[1] 薛健 王茂波[1] YU Shao-yi;CHEN Yuan-yin;XU Ying;LIU Hai-yun;XUE J ian;WANG Mao-bo(Yantai Center for Disease Control and Prevention,Yantai 264000,P.R.China)
机构地区:[1]烟台市疾病预防控制中心,山东烟台264000
出 处:《中华肿瘤防治杂志》2018年第15期1055-1059,共5页Chinese Journal of Cancer Prevention and Treatment
基 金:山东省医药卫生科技发展计划(2014WS0262);烟台市科学技术发展计划[(卫生项目)2014WS052]
摘 要:目的地理信息系统(geographic information system,GIS)技术及其空间统计分析方法,为肿瘤的空间流行病学研究开辟了新的途径。本研究采用GIS技术对烟台市2012-2014年恶性肿瘤发病资料进行空间分布特征分析,了解烟台市恶性肿瘤空间分布现状,为制订恶性肿瘤防控政策提供依据。方法收集2012-2014年烟台市肿瘤登记报告资料,采用GIS描述恶性肿瘤发病率的空间分布特征,并进行空间自相关和单纯空间扫描分析,以确定恶性肿瘤发病的分布及空间聚集情况。结果 2012-2014年烟台市恶性肿瘤报告发病率259.63/10万,中标率为110.03/10万,世标率为122.53/10万。恶性肿瘤总体发病率从2012年的234.70/10万上升到2014年的292.39/10万,增长了24.58%。全局Moran’s I为0.1576,P<0.001;局部自相关分析显示,共23个高-高区域,均P值<0.001;单纯空间扫描分析共得到3个有统计学意义的高发病率聚集区。结论烟台市恶性肿瘤的分布具有一定的空间聚集性,应重点关注肿瘤发病的高风险地区。OBJECTIVE Geographic information system(GIS) provides a new approach to explore spatial distribu- tion of cancer. This study aimed to analyze the geographical distribution of malignant neoplasms in Yantai city in order to provide scientific basis for policy-making. METHODS The registration data from Yantai cancer registry from 2012 to 2014 were reviewed. The distribution of malignant neoplasms was described basing on GIS. Moran's I and Local Moran's I indexes were implemented to evaluate the pattern of spatial clustering of malignant neoplasms. RESULTS The crude in cidence rate was 259. 63/10^5 and age-standardized incidence rates by Chinese population and world population were 110.03/105 and 122.53/10s in Yantai city from 2012 to 2014. The cancer incidence increased from 234.70/10s in 2012 to 292.39/10s in 2014, which increased 24.58%. Global spatial autocorrelation indication was 0. 157 6 (P〈0. 001 ). Accord- ing to local spatial autocorrelation analysis, there ware 23 high-high regions. The purely spatial scan statistics indicated that there were 3 statistically significant clusters. CONCLUSIONS The incidence of malignant neoplasms is of obviously geographical distribution in Yantai city. We should pay more attention to the areas with higher risk of malignant neo- plasms.
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