首页> 外文OA文献 >Propensity score weighting for addressing under-reporting in mortality surveillance:a proof-of-concept study using the nationally representative mortality data in China
【2h】

Propensity score weighting for addressing under-reporting in mortality surveillance:a proof-of-concept study using the nationally representative mortality data in China

机译:倾向得分加权可解决死亡率监测中报告不足的问题:使用中国具有全国代表性的死亡率数据进行的概念验证研究

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Background: National mortality data are obtained routinely by the Disease Surveillance Points system (DSPs) in China and under-reporting is a big challenge in mortality surveillance. Methods: We carried out an under-reporting field survey in all 161 DSP sites to collect death cases during 2009-2011, using a multi-stage stratified sampling. To identify under-reporting, death data were matched between field survey system and the routine online surveillance system by an automatic computer checking followed by a thorough manual verification. We used a propensity score (PS) weighting method based on a logistic regression to calculate the under-reporting rate in different groups classified by age, gender, urban/rural residency, geographic locations and other mortality related variables. For comparison purposes, we also calculated the under-reporting rate by using capture-mark-recapture (CMR) method. Results: There were no significant differences between the field survey system and routine online surveillance system in terms of age group, causes of death, highest level of diagnosis and diagnostic basis. The overall under-reporting rate in the DSPs was 12.9 % (95%CI 11.2 %, 14.6 %) based on PS. The under-reporting rate was higher in the west (18.8 %, 95%CI 16.5 %, 21.0 %) than the east (10.1 %, 95%CI 8.6 %, 11.3 %) and central regions (11.2 %, 95%CI 9.6 %, 12.7 %). Among all age groups, the under-reporting rate was highest in the 0-5 year group (23.7 %, 95%CI 16.1 %, 35.5 %) and lowest in the 65 years and above group (12.4 %, 95%CI 10.9 %, 13.6 %). The under-reporting rates in each group by PS were similar to the results calculated by the CMR methods. Conclusions: The mortality data from the DSP system in China needs to be adjusted. Compared to the commonly used CMR method in the estimation of under-reporting rate, the results of propensity score weighting method are similar but more flexible when calculating the under-reporting rates in different groups. Propensity score weighting is suitable to adjust DSP data and can be used to address under-reporting in mortality surveillance in China.
机译:背景:全国死亡率数据是通过中国疾病监测点系统(DSP)常规获取的,漏报是死亡率监测的一大挑战。方法:我们采用多阶段分层抽样方法,对2009年至2011年期间所有161个DSP站点进行了漏报调查,以收集死亡病例。为了识别报告不足的情况,通过自动计算机检查,然后进行彻底的手动验证,在现场调查系统和常规在线监视系统之间匹配死亡数据。我们使用基于Logistic回归的倾向得分(PS)加权方法来计算按年龄,性别,城市/农村居住地,地理位置和其他与死亡率相关的变量分类的不同组中的漏报率。为了进行比较,我们还使用捕获标记捕获(CMR)方法计算了漏报率。结果:现场调查系统与常规在线监测系统在年龄组,死亡原因,最高诊断水平和诊断依据方面无显着差异。基于PS,DSP中的总体漏报率是12.9%(95%CI 11.2%,14.6%)。西部(18.8%,95%CI 16.5%,21.0%)的漏报率高于东部(10.1%,95%CI 8.6%,11.3%)和中部地区(11.2%,95%CI 9.6) %,12.7%)。在所有年龄组中,漏报率最高的是0-5岁组(23.7%,95%CI 16.1%,35.5%),最低的是65岁及以上组(12.4%,95%CI 10.9%) ,13.6%)。 PS对每组的报告不足率与CMR方法计算的结果相似。结论:中国DSP系统的死亡率数据需要调整。与估计漏报率的常用CMR方法相比,倾向得分加权方法的结果相似,但在计算不同组的漏报率时更为灵活。倾向得分加权适用于调整DSP数据,可用于解决中国死亡率监测报告不足的问题。

著录项

相似文献

  • 外文文献
  • 中文文献
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号