应用地理信息系统技术分析新疆糖尿病的空间分布

发布时间：2018-06-24 11:11

  本文选题：糖尿病 + 空间自相关分析　； 参考：《新疆医科大学》2015年硕士论文

【摘要】：目的:本研究运用地理信息系统技术,了解新疆糖尿病的地理分布情况,分析糖尿病的高发地区和低发地区,从而探讨地区糖尿病的聚集性问题,为新疆糖尿病的空间分布情况提供数据支持,为该地区公共卫生政策的制定和糖尿病的防控提供理论依据,也可以为同类研究提供参考。方法:采用新疆维吾尔自治区疾病与防治中心慢性病科提供的新疆地区2014年糖尿病患病数据,并获得1:100万的新疆地区矢量地图,在Excel中输入各地区的代码、发病数据,并把Excel文件转变成可供使用的shp格式的地理属性文件,对其进行全局空间自相关分析、局部空间自相关分析和空间回归分析,上述方法均使用ArcGIS10.1软件和GeoDaTM0.9.5i软件完成。结果:1.2014年新疆地区糖尿病登记人数为318704例,患病率为142.74/万。新疆94个县(市、区)全局型Moran’s I指数为0.232558,Z值为8.2932,P0.001,Moran’s I指数大于0,且有统计学意义,说明2014年糖尿病患病率在新疆各区域内的分布呈聚集性分布,具有明显的正向空间自相关性。2.全局G统计量分析结果显示,新疆94个县(市、区)糖尿病患病率的全局型G统计值为0.1242,Z值为3.1015,P值0.001925(P0.01),新疆全区域内糖尿病患病率的分布不仅存在聚集性,而且存在高值聚集区。3.局域型Moran’s I结果显示,局部Moran’s I值有统计学意义的区域有33个县(市、区),其中为负值且有统计学意义的区域有6个县(市、区)表现为负相关性,值最低的区域为阿勒泰地区的福海县,聚集类型为“高-低”和“低-高”,其余27个区域的自相关性表现为正相关性,局部Moran’s I值较高的地区为塔什库尔干塔吉克自治县等区域,聚集类型为“高-高”和“低-低”。4.局域型G统计结果:将2014年新疆地区糖尿病患病率进行局部G统计量分析,结果中Z(Gi)值为正值的且有统计学意义的区域有49个县(市、区),其中最大值为4.9832(库尔勒市),Z(Gi)界于2.0012~4.9832。这些区域形成高患病率的聚集区域,称为热点区域。Z(Gi)值为负值且有统计学意义的地区有21个县(市、区),其中Z(Gi)最小的为-4.3567(阿克陶县),这些区域形成低患病率的聚集区域,称为冷点区域。5.空间归回分析结果:通过空间滞后模型发现,人均地区生产总值对新疆各县(市、区)糖尿病的患病率有影响,人均地区生产总值高的地区,糖尿病的患病率也高,而死亡率和少数民族比例与糖尿病未见有明显的关系。结论:1.新疆94县(市、区)2014年糖尿病的分布具有明显的正向空间自相关性,呈聚集性分布。2.新疆各县区内糖尿病患病率的分布存在高值聚集区和低值聚集区,对高值聚集地区应采取预防措施,着重控制危险因素。在低值聚集区域应该及时发现控制疾病的有利因子,为疾病预防工作提供指导作用。3.新疆各县(市、区)2014年糖尿病的患病率分布的高低与人均地区生产总值水平有关,人均地区生产总值高的地区糖尿病的患病率也高。研究结果显示了新疆糖尿病患病率的空间分布规律,为糖尿病的综合性防治措施的有效实施提供了理论依据。
[Abstract]:Objective: To study the geographical distribution of diabetes in Xinjiang, analyze the geographical distribution of diabetes, analyze the high incidence area of diabetes and low hair area, and discuss the problem of the accumulation of diabetes in the region, provide data support for the spatial distribution of diabetes in Xinjiang, the formulation of public health policy and the prevention of diabetes in this area. Control provides theoretical basis, and can also provide reference for similar studies. Methods: using the data of diabetes prevalence in the Xinjiang area of the Xinjiang Uygur Autonomous Region disease and prevention center of the Xinjiang Uygur Autonomous Region in 2014, and obtaining the vector map of Xinjiang area in the region of Xinjiang, input the code of all regions in the region, the data of the disease, and the transformation of the Excel files into the data. The geographic attribute files of the available SHP format were used to carry out global spatial autocorrelation analysis, local spatial autocorrelation analysis and spatial regression analysis. The above methods were all completed by ArcGIS10.1 software and GeoDaTM0.9.5i software. Results: the number of diabetes registrants in Xinjiang area was 318704 cases in 1.2014 years, the prevalence rate was 142.74/ million. 94 in Xinjiang. The county (city, district) global Moran 's I index is 0.232558, Z is 8.2932, P0.001, Moran' s I index is more than 0, and has statistical significance. It shows that the distribution of diabetes prevalence in Xinjiang region in 2014 is aggregated distribution, and there is obvious positive spatial autocorrelation.2. global G statistic results show that 94 counties (cities, districts) of Xinjiang. The statistical value of the global G for the prevalence of diabetes was 0.1242, the Z value was 3.1015, the P value 0.001925 (P0.01), the distribution of the prevalence of diabetes in the whole region of Xinjiang was not only aggregable, but the.3. local Moran 's I in the high value aggregation region showed that there were 33 counties (cities and regions) in the region of local Moran' s I. There are 6 counties (cities and districts) with negative correlation in the region of statistical significance. The lowest value area is Fuhai County in Aletai area, the type of "high low" and "low high", the other 27 regions have positive correlation, and the region with high local Moran 's I value is the region of Tajik Tajik Autonomous County and so on. The aggregated type of "high to high" and "low to low".4. local G statistical results: the prevalence of diabetes in Xinjiang in 2014 was analyzed by local G statistics. The results showed that there were 49 counties (cities, districts) with positive and statistically significant Z (Gi) values in the region with the maximum value of 4.9832 (Korla), and Z (Gi) boundary in these regional forms. There are 21 counties (cities and regions) in the area of high incidence of high prevalence, called the negative.Z (Gi) value and statistically significant, of which Z (Gi) is the smallest -4.3567 (aktao county), which forms a low prevalence area of aggregation, known as the result of the.5. space return analysis in the cold point region: the per capita area is found through the spatial lag model, and the per capita area is found. The prevalence of diabetes in all counties (cities and districts) in Xinjiang has an impact on the prevalence of diabetes. The prevalence of diabetes is also high in areas with high GDP per capita, and there is no significant relationship between the mortality and the proportion of ethnic minorities with diabetes. Conclusion: the distribution of diabetes in the 94 counties (cities and districts) of 1. in 2014 has obvious positive spatial autocorrelation in the distribution of diabetes in 2014. The distribution of the prevalence of diabetes in the districts of.2. Xinjiang county is high value aggregated area and low value aggregated area. The prevention measures should be taken to control the risk factors in high value aggregated areas. In the low value aggregated area, the favorable factors to control the disease should be found in time to provide guidance for the disease prevention and prevention work in the counties of Xinjiang (cities, cities, cities, cities, and counties). The prevalence of diabetes in 2014 is related to the level of per capita GDP, and the prevalence of diabetes in areas with high GDP per capita is also high. The results of the study show the spatial distribution of the prevalence of diabetes in Xinjiang, which provides a theoretical basis for the effective implementation of the comprehensive prevention and control measures of diabetes.
【学位授予单位】：新疆医科大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：R587.1
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本文编号：2061326