论文部分内容阅读
目的探讨用模糊物元法对疾病监测点布点进行优化与选择的可行性。方法采用模糊物元法对某地的慢性病监测资料进行监测点的分类和优选,并用方差分析法和系统聚类加以验证。结果某地28个监测点可以被模糊物元法分为四类,根据当年疾病监测资料所优选出的10个监测点仍可作为次年的优选监测点;多元方差分析法结果显示模糊物元法优选出的10个监测点与原28个监测点差异无统计学意义;系统聚类法与模糊物元法对监测点的分类较为一致。结论模糊物元法对疾病监测点的优化具有一定的稳定性,代表性较好,可作为疾病监测点优选时的一种推荐方法。
Objective To explore the feasibility of using fuzzy matter-element method to optimize and select the distribution points of disease surveillance sites. Methods The fuzzy matter-element method was used to classify and optimize the monitoring points of chronic disease surveillance in a certain area, and verified by variance analysis and system clustering. Results A total of 28 monitoring sites in a certain area could be divided into four categories by fuzzy matter-element method. According to the monitoring data of the year, 10 monitoring sites were selected as the optimal monitoring points in the following year. Multivariate analysis of variance showed that the fuzzy matter- There was no significant difference between the 10 monitoring points selected by the method and the original 28 monitoring points. The systematic clustering method and the fuzzy matter-element method were more consistent with the classification of monitoring points. Conclusion The fuzzy matter-element method has certain stability to the optimization of disease monitoring points, and has good representativeness. It can be used as a recommended method for optimizing disease monitoring points.