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作 者:刘伦皓[1] 李娜[2] 王丽艳[3] 罗映娟[1] 胡莹[1] 裴晓迪[1] 梁莉[1] 刘莉[1]
机构地区:[1]四川省疾病预防控制中心,四川成都610041 [2]彭州市疾病预防控制中心,四川彭州611930 [3]中国疾病预防控制中心,北京102206
出 处:《疾病监测》2015年第7期599-601,共3页Disease Surveillance
摘 要:目的应用捕获-再捕获方法估计2012 2013年彭州市全死因死亡率,评价死亡漏报情况,同时对应用效果进行评估。方法从死因监测系统、乡镇计划生育办公室、村委会3个途径获取2012 2013年常住人口在彭州市的全死因死亡记录。在不同来源的数据记录之间,用姓名、姓名拼音字母、性别、出生日期、居住乡镇进行匹配。采用连接函数为对数(log)的线性模型对3个样本进行拟合,估计全死因死亡人数。结果应用捕获-再捕获方法估计全死因死亡人数13 594人(95%CI:13 537~13 651),死亡率为1.77%,高于网报登记死亡率1.41%和合并样本死亡率1.68%。捕获-再捕获方法估计的死亡人数作为分母,计算3样本合并后的漏失率为5.29%;死因监测系统漏报率为20.37%,高于样本合并后的死亡人数作为分母的死因网报漏报率(15.92%)。结论任何一个样本,死亡记录都不完整,即使3个样本合并后仍然存在漏失的情况,捕获-再捕获方法可以用来校正由于死因监测系统漏报造成的误差,更准确地评价实际死亡水平。Objective To understand the underreporting of all death cause mortality in Pengzhou,Sichuan province,from 2012 to 2013. Methods The all death cause mortality data among the local residents during this period w ere collected from local death cause surveillance system,tow nship family planning offices and village committees. in Pengzhou the data from different sources w ere matched w ith the names,name's phonetic letters,sex,date of birth and living address of death cases. Log-liner model w as used for fitting the data from 3 sources to estimate the all death cause mortality. Results By using capture and recapture strategy,it w as estimated the all death cause mortality w as 13 594( 95% CI: 13 537- 13 651),and the mortality rate was 1. 77%,higher than that in death cause registry( 1. 41%) and the average of samples( 1. 68%). By using the mortality estimated by capture and recapture strategy as denominator,the underreporting rate of average samples w as 5. 29%; the underreporting rate of death cause surveillance w as 20. 37%,higher than the rate( 15. 92%) by using average samples as denominator. Conclusion Any samples of death are incomplete,even three samples w ere used,the underreporting still exists. Capture recapture method can be used to correct the error caused by underreporting death by death surveillance system,and the number of death can be estimated more accurately.
分 类 号:R195[医药卫生—卫生统计学]
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