2015-2019年四川省结直肠癌患者地理分布及空间流行特征分析

Geographical distribution and spatial epidemiological characteristics of colorectal cancer patients in Sichuan province from 2015 to 2019

目的 分析2015-2019年四川省结直肠癌患病率的空间分布特征与空间聚集性,为四川省结直肠癌防控措施以及卫生资源合理分配提供依据。方法 本研究数据来自四川省卫生健康委员会信息中心数据库。采用描述流行病学法和空间自相关分析法分析四川省结直肠癌患病率的地理分布与空间聚集性。结果 2015-2019年四川省共111 778例结直肠癌患者,5年患病率为24.5/10万,标化率为32.4/10万,患病率呈上升趋势,Z=2.20,P=0.03。全局Moran I自相关显示,四川省结直肠癌患病率整体空间自相关性不强,Moran I<0.01,P>0.05。局部Moran I自相关显示,患病率存在5个热点区域,分别位于成都平原地区(成都市、德阳市和眉山市)与川中丘陵地区(内江市和自贡市);1个冷点区域,位于川西高原地区(阿坝藏族羌族自治州)。结论 四川省结直肠癌患病率呈上升趋势,其患病率在市/州级别空间上呈随机分布,但存在独特的热点、冷点以及患病率高低交错的聚集区域。

Objective To explore the spatial distribution characteristics and spatial clustering of colorectal cancer(CRC) in Sichuan Province from 2015 to 2019,and provide evidence for the prevention and control of colorectal cancer and the rational allocation of health resources in Sichuan Province.Methods Data were obtained from the database of the Sichuan Provincial Health Commission Information Center.Descriptive epidemiological methods and spatial autocorrelation analysis were used to evaluate the geographic distribution and spatial clustering of CRC prevalence in Sichuan Province.Results From 2015 to 2019,there were 111 778 CRC patients, with a 5-year prevalence of 24.5 per 100 000.The age-standardized incidence rate by Chinese standard population was 32.4 per 100 000.The prevalence of CRC in Sichuan Province was on the rise(Z=2.20,P=0.03).The Global Moran I coefficients showed that the overall spatial autocorrelation of CRC prevalence was not strong(Moran I<0.01,P>0.05).Local Moran I autocorrelation showed that there were five hot spots in the prevalence of CRC,which were located in the Chengdu plain area(Chengdu, Deyang, Meishan) and the hilly area in central Sichuan(Neijiang, Zigong).One cold spot was in the western Sichuan Plateau(Aba Tibetan and Qiang Autonomous Prefecture).Conclusion The prevalence of CRC in Sichuan Province is rising, and its prevalence is randomly distributed at the city/state level.However, there are unique hot spots, cold spots, and clustering areas where the prevalence is staggered.