Skip to main content
Journal cover image

Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis.

Publication ,  Journal Article
Zhang, X; Ye, Y; Fu, C; Dou, G; Ying, X; Qian, M; Tang, S
Published in: BMC Public Health
May 24, 2020

BACKGROUND: The maternal mortality ratio (MMR) is an important indicator of maternal health and socioeconomic development. Although China has experienced a large decline in MMR, substantial disparities across regions are still apparent. This study aims to explore causes of socioeconomic related inequality in MMR at the province-level in China from 2004 to 2016. METHODS: We collected data from various issues of the China Health Statistics Yearbook, China Statistics Yearbook, and China Population and Employment Statistics Yearbook to construct a longitudinal sample of all provinces in China. We first examined determinants of the MMR using province fixed-effect models, accounted for socioeconomic condition, health resource allocation, and access to health care. We then used the concentration index (CI) to measure MMR inequality and employed the direct decomposition method to estimate the marginal impact of the determinants on the inequality index. Importance of the determinants were compared based on logworth values. RESULTS: During our study period, economically more deprived provinces experienced higher MMR than better-off ones. There was no evidence of improved socioeconomic related inequality in MMR. Illiteracy proportion was positively associated with the MMR (p < 0.01). In contrast, prenatal check-up rate (p = 0.05), hospital delivery rate (p < 0.01) and rate of delivery attended by professionals (p = 0.02) were negatively associated with the MMR. We also find that higher maternal health profile creation rate (p < 0.01) was associated with a pro-poor change of MMR inequality. CONCLUSION: Access to healthcare was the most important factor in explaining the persistent MMR inequality in China, followed by socioeconomic condition. We do not find evidence that health resource allocation was a contributing factor.

Duke Scholars

Published In

BMC Public Health

DOI

EISSN

1471-2458

Publication Date

May 24, 2020

Volume

20

Issue

1

Start / End Page

758

Location

England

Related Subject Headings

  • Socioeconomic Factors
  • Public Health
  • Pregnancy
  • Maternal Mortality
  • Maternal Health
  • Humans
  • Health Resources
  • Gross Domestic Product
  • Female
  • Databases, Factual
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhang, X., Ye, Y., Fu, C., Dou, G., Ying, X., Qian, M., & Tang, S. (2020). Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis. BMC Public Health, 20(1), 758. https://doi.org/10.1186/s12889-020-08830-2
Zhang, Xinyu, Yingfeng Ye, Chaowei Fu, Guanshen Dou, Xiaohua Ying, Mengcen Qian, and Shenglan Tang. “Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis.BMC Public Health 20, no. 1 (May 24, 2020): 758. https://doi.org/10.1186/s12889-020-08830-2.
Zhang X, Ye Y, Fu C, Dou G, Ying X, Qian M, et al. Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis. BMC Public Health. 2020 May 24;20(1):758.
Zhang, Xinyu, et al. “Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis.BMC Public Health, vol. 20, no. 1, May 2020, p. 758. Pubmed, doi:10.1186/s12889-020-08830-2.
Zhang X, Ye Y, Fu C, Dou G, Ying X, Qian M, Tang S. Anatomy of provincial level inequality in maternal mortality in China during 2004-2016: a new decomposition analysis. BMC Public Health. 2020 May 24;20(1):758.
Journal cover image

Published In

BMC Public Health

DOI

EISSN

1471-2458

Publication Date

May 24, 2020

Volume

20

Issue

1

Start / End Page

758

Location

England

Related Subject Headings

  • Socioeconomic Factors
  • Public Health
  • Pregnancy
  • Maternal Mortality
  • Maternal Health
  • Humans
  • Health Resources
  • Gross Domestic Product
  • Female
  • Databases, Factual