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Assessing Spatial Accessibility to Maternity Units in Shenzhen, China

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Listed:
  • Peige Song
  • Yajie Zhu
  • Xi Mao
  • Qi Li
  • Lin An

Abstract

Background: With the rapid development of urbanization, pregnant population is growing rapidly in Shenzhen, and it has been a difficulty to serve more and more pregnant women and reduce spatial access disparities to maternity units (MUs). Understanding of the current status of accessibility to MUs is valuable for supporting the rational allocation of MUs in the future. Methods: Based on pregnant population data and MUs data, this study uses a two-step floating catchment area (2SFCA) method based on Geographic Information System (GIS) to analyze the current spatial accessibility to MUs, and then make a comparison between that to public MUs and private MUs. Results: Our analysis of the accessibility to all MUs within a distance of 20 km shows that the accessibilities of the areas alongside the traditional border management line are acceptable, meanwhile highlights some critical areas, such as the west part of Nanshan district and the vast east part of Longgang district. The comparison between spatial accessibility to public MUs and private MUs shows statistically significant difference. Discussion: Results of this study suggest a great effort should be made to improve the equity of spatial accessibility to MUs in Shenzhen. For policy-making, strategy for the siting and allocation of future MUs, no matter public or private, should guarantee the greatest spatial accessibility for every pregnant woman.

Suggested Citation

  • Peige Song & Yajie Zhu & Xi Mao & Qi Li & Lin An, 2013. "Assessing Spatial Accessibility to Maternity Units in Shenzhen, China," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    • Handle: RePEc:plo:pone00:0070227
    DOI: 10.1371/journal.pone.0070227
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    References listed on IDEAS

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    Cited by:

    1. Lei Zhu & Shuang Zhong & Wei Tu & Jing Zheng & Shenjing He & Junzhe Bao & Cunrui Huang, 2019. "Assessing Spatial Accessibility to Medical Resources at the Community Level in Shenzhen, China," IJERPH, MDPI, vol. 16(2), pages 1-15, January.
    2. Xuechen Xiong & Chao Jin & Haile Chen & Li Luo, 2016. "Using the Fusion Proximal Area Method and Gravity Method to Identify Areas with Physician Shortages," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-17, October.
    3. Antonio Paez & Christopher D Higgins & Salvatore F Vivona, 2019. "Demand and level of service inflation in Floating Catchment Area (FCA) methods," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-38, June.

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