文章摘要
王晓风,张业武,马家奇.基于地理探测器的我国西南部分地区细菌性痢疾发病影响因素分析[J].中华流行病学杂志,2019,40(8):953-959
基于地理探测器的我国西南部分地区细菌性痢疾发病影响因素分析
Factors influencing the incidence of bacterial dysentery in parts of southwest China, using data from the geodetector
收稿日期:2019-01-11  出版日期:2019-08-19
DOI:10.3760/cma.j.issn.0254-6450.2019.08.015
中文关键词: 地理探测器  细菌性痢疾  发病  影响因素
英文关键词: Geographic detector  Bacterial dysentery  Incidence  Related factors
基金项目:国家自然科学基金联合基金项目(U1611264);国家重点研发计划(2016YFC1200703);国家科技重大专项(2017ZX10303401-005)
作者单位E-mail
王晓风 中国疾病预防控制中心信息中心, 北京 102206  
张业武 中国疾病预防控制中心信息中心, 北京 102206 zhangyw@chinacdc.cn 
马家奇 中国疾病预防控制中心信息中心, 北京 102206  
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中文摘要:
      目的 利用地理探测器分析我国西南部分地区细菌性痢疾(菌痢)发病与气象、环境和社会经济相关因素的关系。方法 利用中国传染病报告管理信息系统2005-2014年四川省、云南省和西藏自治区(西南地区)菌痢报告数据及气象数据、地形环境和社会经济因素数据,应用地理探测器模型中4种不同的工具进行数据分异性统计分析,评估疾病发病率与相关因子在空间分布的一致性,探讨不同因子对疾病分布的影响。结果 通过地理探测器分析发现,自变量对因变量的解释度(power of determinant,PD)最大值是平均海拔和民族,PD值分别为0.308和0.260,其次是夏季平均气温、地形、海拔标准差、坡度、人口密度,夏季平均相对湿度、夏季平均降水量、地区生产总值的PD值均<0.200。通过生态探测器发现,夏季平均降水量、地区生产总值与平均海拔、海拔标准差、坡度、地形和民族的PD值差异均有统计学意义(P<0.05)。通过交互探测器发现,夏季平均相对湿度与夏季平均气温、人口密度、地区生产总值的空间交互后PD值大于两因素PD值之和,呈现非线性叠加增强。通过风险区探测器发现,在夏季平均气温适中、夏季平均降水量少、夏季相对湿度适中、平均海拔高、海拔标准差大、坡度大、山地地形、藏缅语族居民,人口密度低、地区生产总值低的区域,菌痢发病率高。结论 我国西南地区的气象条件、地形环境状况决定了地区菌痢流行的人群基础,不同经济发展水平的人群社会经济行为、卫生条件的差异则直接影响菌痢在人群间传播,最终影响菌痢发病率的高低。因此,关注社会经济手段的传播干预将有利于控制菌痢流行。
英文摘要:
      Objective To analyze the relationship between the incidence of bacterial dysentery and related meteorological, environmental and socio-economic factors in parts of southwest China, under the geodetector. Methods Incidence data on bacillary dysentery from 2005 to 2014 was collected from the China infectious disease reporting system and meteorological, terrain environment and socio-economic related data were used for statistical analysis with geodetector also used, in Sichuan province, Yunnan province and the Tibet autonomous region (southwest China). Results Through geodetector model, results showed that the elevation maximum value of power of determinant (PD) (PD=0.308), ethnicity (PD=0.260), followed by summer mean temperature, topography, elevation standard deviation, slope, population density were noticed. The maximum value of PD of summer average relative humidity, summer average precipitation, and regional GDP were all less than 0.200. In the ecological detector model, value of PD appeared significantly different from multiple factors such as summer average precipitation, regional GDP, average altitude, elevation standard deviation, slope, terrain and ethnicity (P<0.05). In the interactive detector model, after the spatial interaction, factors as:value on PD of summer average relative humidity, population density and regional GDP were larger than the value on the sum of PD of two factors with nonlinear superposition enhancing trend. Results from the risk zone detection showed that areas of moderate average summer temperature, low average precipitation, moderate average summer relative humidity, high average altitude, large elevation standard deviation, high slope, mountain topography, Tibeto-Burmese of ethnicity, low population density, low regional GDP were all related to the high incidence rates of bacterial dysentery. Conclusions Meteorological conditions and topography environments were related to the bacterial dysentery in southwest China, socio-economic behaviors depends on the level of economic development and sanitary conditions etc. were all directing influencing the transmission and incidence of bacterial dysentery. For developing a better intervention programs on bacillary dysentery, socio-economic means should be used for the control of bacillary dysentery, in the region.
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