Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis.
BACKGROUND:As one of its Millennium Development Goals (MDGs), China has achieved a dramatic reduction in the maternal mortality ratio (MMR), although a distinct spatial heterogeneity still persists. Evidence of the quantitative effects of determinants on MMR in China is limited. A better understandi...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2020-05-01
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| Series: | PLoS Medicine |
| Online Access: | https://doi.org/10.1371/journal.pmed.1003114 |
| _version_ | 1819021616353378304 |
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| author | Junming Li Juan Liang Jinfeng Wang Zhoupeng Ren Dian Yang Yanping Wang Yi Mu Xiaohong Li Mingrong Li Yuming Guo Jun Zhu |
| author_facet | Junming Li Juan Liang Jinfeng Wang Zhoupeng Ren Dian Yang Yanping Wang Yi Mu Xiaohong Li Mingrong Li Yuming Guo Jun Zhu |
| author_sort | Junming Li |
| collection | DOAJ |
| description | BACKGROUND:As one of its Millennium Development Goals (MDGs), China has achieved a dramatic reduction in the maternal mortality ratio (MMR), although a distinct spatial heterogeneity still persists. Evidence of the quantitative effects of determinants on MMR in China is limited. A better understanding of the spatiotemporal heterogeneity and quantifying determinants of the MMR would support evidence-based policymaking to sustainably reduce the MMR in China and other developing areas worldwide. METHODS AND FINDINGS:We used data on MMR collected by the National Maternal and Child Health Surveillance System (NMCHSS) at the county level in China from 2010 to 2013. We employed a Bayesian space-time model to investigate the spatiotemporal trends in the MMR from 2010 to 2013. We used Bayesian multivariable regression and GeoDetector models to address 3 main ecological determinants of the MMR, including per capita income (PCI), the proportion of pregnant women who delivered in hospitals (PPWDH), and the proportion of pregnant women who had at least 5 check-ups (PPWFC). Among the 2,205 counties, there were 925 (42.0%) hotspot counties, located mostly in China's western and southwestern regions, with a higher MMR, and 764 (34.6%) coldspot counties with a lower MMR than the national level. China's westernmost regions, including Tibet and western Xinjiang, experienced a weak downward trend over the study period. Nationwide, medical intervention was the major determinant of the change in MMR. The MMR decreased by 1.787 (95% confidence interval [CI]: 1.424-2.142, p < 0.001) per 100,000 live births when PPWDH increased by 1% and decreased by 0.623 (95% CI 0.436-0.798, p < 0.001) per 100,000 live births when PPWFC increased by 1%. The major determinants for the MMR in China's western and southwestern regions were PCI and PPWFC, while that in China's eastern and southern coastlands was PCI. The MMR in western and southwestern regions decreased nonsignificantly by 1.111 (95% CI -1.485-3.655, p = 0.20) per 100,000 live births when PCI in these regions increased by 1,000 Chinese Yuan and decreased by 1.686 (95% CI 1.275-2.090, p < 0.001) when PPWFC increased by 1%. Additionally, the western and southwestern regions showed the strongest interactive effects between different factors, in which the corresponding explanatory power of any 2 interacting factors reached up to greater than 80.0% (p < 0.001) for the MMR. Limitations of this study include a relatively short study period and lack of full coverage of eastern coastlands with especially low MMR. CONCLUSIONS:Although China has accomplished a 75% reduction in the MMR, spatial heterogeneity still exists. In this study, we have identified 925 (hotspot) high-risk counties, mostly located in western and southwestern regions, and among which 332 counties are experiencing a slower pace of decrease than the national downward trend. Nationally, medical intervention is the major determinant. The major determinants for the MMR in western and southwestern regions, which are developing areas, are PCI and PPWFC, while that in China's developed areas is PCI. The interactive influence of any two of the three factors, PCI, PPWDH, and PPWFC, in western and southwestern regions was up to and in excess of 80% (p < 0.001). |
| first_indexed | 2024-12-21T04:09:56Z |
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| institution | Directory Open Access Journal |
| issn | 1549-1277 1549-1676 |
| language | English |
| last_indexed | 2024-12-21T04:09:56Z |
| publishDate | 2020-05-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS Medicine |
| spelling | doaj.art-43035cd0cbe3422dbb497d19292994952022-12-21T19:16:29ZengPublic Library of Science (PLoS)PLoS Medicine1549-12771549-16762020-05-01175e100311410.1371/journal.pmed.1003114Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis.Junming LiJuan LiangJinfeng WangZhoupeng RenDian YangYanping WangYi MuXiaohong LiMingrong LiYuming GuoJun ZhuBACKGROUND:As one of its Millennium Development Goals (MDGs), China has achieved a dramatic reduction in the maternal mortality ratio (MMR), although a distinct spatial heterogeneity still persists. Evidence of the quantitative effects of determinants on MMR in China is limited. A better understanding of the spatiotemporal heterogeneity and quantifying determinants of the MMR would support evidence-based policymaking to sustainably reduce the MMR in China and other developing areas worldwide. METHODS AND FINDINGS:We used data on MMR collected by the National Maternal and Child Health Surveillance System (NMCHSS) at the county level in China from 2010 to 2013. We employed a Bayesian space-time model to investigate the spatiotemporal trends in the MMR from 2010 to 2013. We used Bayesian multivariable regression and GeoDetector models to address 3 main ecological determinants of the MMR, including per capita income (PCI), the proportion of pregnant women who delivered in hospitals (PPWDH), and the proportion of pregnant women who had at least 5 check-ups (PPWFC). Among the 2,205 counties, there were 925 (42.0%) hotspot counties, located mostly in China's western and southwestern regions, with a higher MMR, and 764 (34.6%) coldspot counties with a lower MMR than the national level. China's westernmost regions, including Tibet and western Xinjiang, experienced a weak downward trend over the study period. Nationwide, medical intervention was the major determinant of the change in MMR. The MMR decreased by 1.787 (95% confidence interval [CI]: 1.424-2.142, p < 0.001) per 100,000 live births when PPWDH increased by 1% and decreased by 0.623 (95% CI 0.436-0.798, p < 0.001) per 100,000 live births when PPWFC increased by 1%. The major determinants for the MMR in China's western and southwestern regions were PCI and PPWFC, while that in China's eastern and southern coastlands was PCI. The MMR in western and southwestern regions decreased nonsignificantly by 1.111 (95% CI -1.485-3.655, p = 0.20) per 100,000 live births when PCI in these regions increased by 1,000 Chinese Yuan and decreased by 1.686 (95% CI 1.275-2.090, p < 0.001) when PPWFC increased by 1%. Additionally, the western and southwestern regions showed the strongest interactive effects between different factors, in which the corresponding explanatory power of any 2 interacting factors reached up to greater than 80.0% (p < 0.001) for the MMR. Limitations of this study include a relatively short study period and lack of full coverage of eastern coastlands with especially low MMR. CONCLUSIONS:Although China has accomplished a 75% reduction in the MMR, spatial heterogeneity still exists. In this study, we have identified 925 (hotspot) high-risk counties, mostly located in western and southwestern regions, and among which 332 counties are experiencing a slower pace of decrease than the national downward trend. Nationally, medical intervention is the major determinant. The major determinants for the MMR in western and southwestern regions, which are developing areas, are PCI and PPWFC, while that in China's developed areas is PCI. The interactive influence of any two of the three factors, PCI, PPWDH, and PPWFC, in western and southwestern regions was up to and in excess of 80% (p < 0.001).https://doi.org/10.1371/journal.pmed.1003114 |
| spellingShingle | Junming Li Juan Liang Jinfeng Wang Zhoupeng Ren Dian Yang Yanping Wang Yi Mu Xiaohong Li Mingrong Li Yuming Guo Jun Zhu Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. PLoS Medicine |
| title | Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. |
| title_full | Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. |
| title_fullStr | Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. |
| title_full_unstemmed | Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. |
| title_short | Spatiotemporal trends and ecological determinants in maternal mortality ratios in 2,205 Chinese counties, 2010-2013: A Bayesian modelling analysis. |
| title_sort | spatiotemporal trends and ecological determinants in maternal mortality ratios in 2 205 chinese counties 2010 2013 a bayesian modelling analysis |
| url | https://doi.org/10.1371/journal.pmed.1003114 |
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