中国主要呼吸道传染病分布模式及其社会经济影响因素

发布时间：2018-05-31 12:18

本文选题：传染病 + 社会经济因素　；参考：《中华疾病控制杂志》2016年01期

【摘要】：目的本研究旨在探讨影响我国大陆五种主要呼吸道传染病(麻疹、肺结核、流行性脑脊髓膜炎、百日咳、猩红热)流行的社会经济因素。方法通过聚类分析和多维尺度分析,阐明五种呼吸道传染病的分布模式;采用主成分分析从社会经济数据中提取主成分;然后通过MANTEL检验和匹配分析量化发病与影响因素之间的相关关系。结果聚类分析和多维尺度分析结果显示各省可按发病率聚类为6组。MANTEL检验结果显示疾病非相似性矩阵与影响因素主成分矩阵之间的相关系数范围为0.220~0.375。而BIO-ENV匹配分析结果显示较好,相关系数范围为0.402~0.545,最匹配影响因素包括0~14岁人口比重、平均受教育年限、文盲人口占15岁以上人口比例、城镇人口比重、人均日生活用水量和失业率。结论 2009-2012年中国各省份主要呼吸道传染病的分布模式相对稳定,与同期的社会经济因素存在关联,可综合防治呼吸道传染病。
[Abstract]:Objective to explore the social and economic factors affecting the epidemic of five main respiratory infectious diseases (measles, tuberculosis, epidemic cerebrospinal meningitis, pertussis, scarlet fever) in the mainland of China. Methods the distribution patterns of five respiratory infectious diseases were elucidated by cluster analysis and multidimensional scale analysis, and the social and economic numbers were analyzed by principal component analysis. The correlation between the incidence and the influencing factors was quantified by MANTEL test and matching analysis. Results cluster analysis and multidimensional scale analysis showed that each province could cluster into 6 groups of.MANTEL tests according to the incidence of the disease and show the correlation coefficient between the disease non similarity matrix and the influencing factor principal component matrix. The results of 0.220~0.375. and BIO-ENV matching analysis show better, the correlation coefficient range is 0.402~0.545, the most matching factors include the proportion of the population of 0~14 years old, the average years of education, the proportion of the illiterate population in the population over 15 years, the proportion of urban population, the daily living water consumption and the unemployment rate per capita. The distribution pattern of the infectious diseases is relatively stable, which is related to the social and economic factors in the same period. It can comprehensively prevent and cure respiratory infectious diseases.
【作者单位】：中山大学公共卫生学院医学统计与流行病学系卫生信息研究中心广东省卫生信息学重点实验室;
【基金】：国家自然科学基金(81473064)
【分类号】：R56

【相似文献】