title: Propensity score weighting for addressing under-reporting in mortality surveillance: a proof-of-concept study using the nationally representative mortality data in China.
abstract: 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.
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China ; Department of Medical Statistics, West China School of Public Health, Sichuan University, Chengdu, China.
authors.forename: Kang
authors.initials: K
authors.lastname: Guo
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Yin
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Lijun
authors.initials: L
authors.lastname: Wang
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Yibing
authors.initials: Y
authors.lastname: Ji
authors.affiliation: School of Public Health, Johns Hopkins University, Baltimore, USA.
authors.forename: Qingfeng
authors.initials: Q
authors.lastname: Li
authors.affiliation: School of Public Health, Johns Hopkins University, Baltimore, USA.
authors.forename: David
authors.initials: D
authors.lastname: Bishai
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Shiwei
authors.initials: S
authors.lastname: Liu
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Yunning
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Science and Health, University of Western Sydney, Sydney, Australia ; School of Geography and Geosciences, University of St Andrews, St Andrews, UK.
authors.forename: Thomas
authors.initials: T
authors.lastname: Astell-Burt
authors.affiliation: Centre for Health Research, School of Medicine, University of Western Sydney, Sydney, Australia.
authors.forename: Xiaoqi
authors.initials: X
authors.lastname: Feng
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Jinling
authors.initials: J
authors.lastname: You
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Jiangmei
authors.initials: J
authors.lastname: Liu
authors.affiliation: National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, 100050 Beijing, China.
authors.forename: Maigeng
authors.initials: M
authors.lastname: Zhou
keywords: Mortality; Propensity scores; Surveillance; Under-reporting