title: Measurement and explanation of socioeconomic inequality in catastrophic health care expenditure: evidence from the rural areas of Shaanxi Province.
abstract: BACKGROUND
  Policy interventions have been taken to protect households from facing unpredictable economic changes that may cause catastrophe in China. This study aims to estimate the change of overall proportion of households incurring catastrophic health care expenditure (CHE) and its income-related inequality in the rural areas of Shaanxi Province from 2008 to 2013.
  
  
  METHODS
  The data were drawn from the National Household Health Service Surveys of Shaanxi Province conducted in the years 2008 and 2013. In total, 3,217 households in 2008 and 13,085 households in 2013 were selected for analysis. A "Capacity to pay" approach was used to measure the incidence of CHE. The concentration index was employed to measure the extent of income-related inequality in CHE. A decomposition method, based on a logit model, was used to decompose the concentration index into its determining components.
  
  
  RESULTS
  From 2008 to 2013, the overall proportion of households incurring CHE dropped from 17.19 % to 15.83 %, while conversely, the inequality in facing CHE strongly increased. The majority of observed inequalities in CHE were explained by household economic status and household size in 2013. In addition, the absence of commercial health insurance and having elderly members were also important contributors to inequality in CHE.
  
  
  CONCLUSIONS
  Even though we used a conservative method to measure CHE, the overall proportion of households incurring CHE in Shaanxi Province is still considerably high in both years. Furthermore, there exists a strong pro-rich inequality of CHE in rural areas of Shaanxi Province. Our study suggests that narrowing the gap of household economic status, improving the anti-risk capability of small scale households, establishing prepayment mechanisms in health insurance, strengthening the depth of reimbursement and subsidising vulnerable households in Shaanxi Province are helpful for both reducing the probability of incurring CHE and the pro-rich inequality in CHE.
authors.affiliation: School of Public Health, Health Science Center, Xi'an Jiaotong University, P.O Box 86, No. 76 West Yanta Road, Xi'an, Shaanxi, 710061, China. xyjdyx@126.com.
authors.forename: Yongjian
authors.initials: Y
authors.lastname: Xu
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China. gaojm@mail.xjtu.edu.cn.
authors.forename: Jianmin
authors.initials: J
authors.lastname: Gao
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China. zzliang1981@163.com.
authors.forename: Zhongliang
authors.initials: Z
authors.lastname: Zhou
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China. qx-xue@mail.xjtu.edu.cn.
authors.forename: Qinxiang
authors.initials: Q
authors.lastname: Xue
authors.affiliation: School of Public Health, Health Science Center, Xi'an Jiaotong University, P.O Box 86, No. 76 West Yanta Road, Xi'an, Shaanxi, 710061, China. yangjinjuan@gmail.com.
authors.forename: Jinjuan
authors.initials: J
authors.lastname: Yang
authors.affiliation: School of Biological Sciences and Biotechnology, Murdoch University, Perth, Australia. luoli76@126.com.
authors.forename: Hao
authors.initials: H
authors.lastname: Luo
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China. 13589683885@163.com.
authors.forename: Yanli
authors.initials: Y
authors.lastname: Li
authors.affiliation: School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China. Shayanglala0217@163.com.
authors.forename: Sha
authors.initials: S
authors.lastname: Lai
authors.affiliation: School of Medicine, Flinders University, Adelaide, Australia. gang.chen@flinders.edu.au.
authors.forename: Gang
authors.initials: G
authors.lastname: Chen
mesh_terms: D000368:Aged; D002388:Catastrophic Illness / Q000191:economics*; D002681:China; D005191:Family Characteristics; D005260:Female; D005382:Financing, Personal; D019538:Health Care Surveys; D005102:Health Expenditures / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000191:economics; D006801:Humans; D007348:Insurance, Health / Q000191:economics; D007407:Interviews as Topic; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D012424:Rural Population; D012923:Social Class; D011795:Surveys and Questionnaires