Catastrophic health expenditure and rural household impoverishment in China: what role does the new cooperative health insurance scheme play?

PLoS One. 2014 Apr 8;9(4):e93253. doi: 10.1371/journal.pone.0093253. eCollection 2014.


Objective: To determine whether the New Cooperative Medical Insurance Scheme (NCMS) is associated with decreased levels of catastrophic health expenditure and reduced impoverishment due to medical expenses in rural households of China.

Methods: An analysis of a national representative sample of 38,945 rural households (129,635 people) from the 2008 National Health Service Survey was performed. Logistic regression models used binary indicator of catastrophic health expenditure as dependent variable, with household consumption, demographic characteristics, health insurance schemes, and chronic illness as independent variables.

Results: Higher percentage of households experiencing catastrophic health expenditure and medical impoverishment correlates to increased health care need. While the higher socio-economic status households had similar levels of catastrophic health expenditure as compared with the lowest. Households covered by the NCMS had similar levels of catastrophic health expenditure and medical impoverishment as those without health insurance.

Conclusion: Despite over 95% of coverage, the NCMS has failed to prevent catastrophic health expenditure and medical impoverishment. An upgrade of benefit packages is needed, and effective cost control mechanisms on the provider side needs to be considered.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Catastrophic Illness / economics
  • China
  • Family Characteristics
  • Health Expenditures* / statistics & numerical data
  • Humans
  • Insurance, Major Medical* / economics
  • Insurance, Major Medical* / statistics & numerical data
  • Models, Statistical
  • Poverty / economics
  • Poverty / statistics & numerical data
  • Rural Health Services* / economics
  • Rural Health Services* / statistics & numerical data
  • Rural Population / statistics & numerical data

Grants and funding

This work was supported by National Natural Science Fund (key grant :71333003, and general grant 71073044, 71203049). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.