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广州市登革热发病影响因素的病例对照研究
引用本文:蔡小双,肖建鹏,宋铁,刘涛,曾韦霖,彭志强,李杏,胡建雄,林华亮,李志浩,张永慧,马文军.广州市登革热发病影响因素的病例对照研究[J].华南预防医学,2021,47(1):35-39.
作者姓名:蔡小双  肖建鹏  宋铁  刘涛  曾韦霖  彭志强  李杏  胡建雄  林华亮  李志浩  张永慧  马文军
作者单位:1.广东省疾病预防控制中心 广东省公共卫生研究院,广东 广州 511430;2.广东省疾病预防控制中心;3.中山大学公共卫生学院;4.南方医科大学公共卫生学院
基金项目:国家重点研发计划项目(2018YFA0606202,2018YFB0505500,2018YFB0505503);国家自然科学基金项目(81773497,41701460);广东省自然科学基金项目(2018A030313729);广东省科技计划项目(2018B020207006)。
摘    要:目的 探索登革热发病的影响因素,为制定登革热防控措施提供参考依据。方法 采用成组匹配的病例对照研究设计,对调查对象进行问卷调查及实验室检测。采用随机森林模型、单因素分析和多因素Logistic回归等方法分析登革热发病的影响因素。结果 病例组病例294例(男158例,女136例),平均年龄(37.0±13.8)岁;对照组691例(男329例,女362例),平均年龄(36.6±13.2)岁。将随机森林模型筛选出的前20个潜在影响登革热发病的重要变量引入Logistic回归模型,结果显示:外出采取防蚊措施(OR=0.29,95%CI:0.20~0.43)、知道登革热传播途径(OR=0.40,95%CI:0.25~0.64)、蚊虫孳生地认知得分高(OR=0.67,95%CI:0.50~0.89)、夏天家中常使用空调(OR=0.60,95%CI:0.38~0.90)、家中安装纱门(OR=0.52,95%CI:0.34~0.79)、小区或家周围及时清理垃圾(OR=0.43,95%CI:0.23~0.79)、工作场所室内有空调(OR=0.46,95%CI:0.30~0.72)能够降低登革热发病风险;家人罹患登革热(OR=6.94,95%CI:2.91~16.56)、朋友或同事罹患登革热(OR=2.71,95%CI:1.56~4.72)人群发病风险高。结论 登革热的发病与个人防病知识、防蚊措施、居住环境以及工作环境密切相关,针对高危因素采取防控措施对于减少登革热的发生至关重要。

关 键 词:登革热  影响因素  病例对照研究  随机森林模型  
收稿时间:2020-03-15

A case-control study on the impact factors of dengue fever in Guangzhou
CAI Xiao-shuang,XIAO Jian-peng,SONG Tie,LIU Tao,ZENG Wei-lin,PENG Zhi-qiang,LI Xing,HU Jian-xiong,LIN Hua-liang,LI Zhi-hao,ZHANG Yong-hui,MA Wen-jun.A case-control study on the impact factors of dengue fever in Guangzhou[J].South China JOurnal of Preventive Medicine,2021,47(1):35-39.
Authors:CAI Xiao-shuang  XIAO Jian-peng  SONG Tie  LIU Tao  ZENG Wei-lin  PENG Zhi-qiang  LI Xing  HU Jian-xiong  LIN Hua-liang  LI Zhi-hao  ZHANG Yong-hui  MA Wen-jun
Institution:1. Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;2. Guangdong Provincial Center for Disease Control and Prevention;3. School of Public Health, Sun Yat-sen University;4. School of Public Health, Southern Medical University
Abstract:Objective To identify impact factors of dengue fever and provide evidence and support for developing control and prevention strategies. Methods A frequency-matching case-control study was adopted to conduct questionnaire survey and laboratory test on the subjects. Random forest model,single factor analysis and multivariate Logistic regression analysis were carried out to identify the impact factors of dengue fever. Results A total of 294 cases(158 males and 136 females)were included in the case group with an average age of(37.0±13.8)years,and 691 cases(329 males and 362 females)were included in the control group with an average age of(36.6±13.2)years. The first 20 variables selected by the random forest model were introduced into the multivariate Logistic regression model. Multivariate Logistic regression analysis showed that a total of seven factors were independent protecting factors including taking preventive measures outdoors(OR=0.29,95% CI:0.20-0.43),knowing spreading vectors of dengue fever(OR=0.40,95% CI:0.25-0.64)and mosquitoes’ habitats(OR=0.67,95% CI:0.50-0.89),using air-conditioning in summer(OR=0.60,95%CI:0.38-0.90),using screen windows and doors at home(OR=0.52,95% CI:0.34-0.79),cleaning up the garbage in time(OR=0.43,95%CI:0.23-0.79)and working indoors with air-conditioning(OR=0.46,95% CI:0.30-0.72). However,people whose family members(OR=6.94,95% CI:2.91-16.56)or friends or colleagues(OR=2.71,95% CI:1.56-4.72)suffered from dengue fever were at higher risk for dengue infection. Conclusion The infection of dengue fever is highly associated with individual recognition of the disease,mosquito preventive measures,household environment and working environment.It is essential to take preventive measures targeting thesefactors to decrease the risk of dengue infection.
Keywords:Dengue fever  Impact factor  Case-control study  Random forest model
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