产科医院的减少是否导致意外的院内分娩利用率下降?中国的因果多层次分析。

BMJ public health Pub Date : 2025-04-23 eCollection Date: 2025-01-01 DOI:10.1136/bmjph-2024-001683
Nan Chen, Peter C Coyte, Jay Pan
{"title":"产科医院的减少是否导致意外的院内分娩利用率下降?中国的因果多层次分析。","authors":"Nan Chen, Peter C Coyte, Jay Pan","doi":"10.1136/bmjph-2024-001683","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>China's progress towards achieving Sustainable Development Goals for maternal health is largely attributed to a reduction in maternal mortality rates, driven by increased in-hospital delivery services utilisation. However, recent reductions in the number of obstetric hospitals have raised concerns about compromised access to these services. This study investigates the impact of reduced obstetric hospitals on spatial accessibility and the utilisation of in-hospital delivery services.</p><p><strong>Methods: </strong>Data from 2016 to 2020 were collected from a densely populated province with approximately 83 million residents. Directed Acyclic Graph was applied to identify a minimally sufficient set of confounders, including residential characteristics and transportation-related factors. Multilevel regression models were employed to analyse the causal effects, with sensitivity analysis using fixed effect and quantile regression models.</p><p><strong>Results: </strong>Between 2017 and 2020, the number of obstetric hospitals decreased by 21.3% (from 1209 to 951), leading to a decline in the proportion of pregnant women covered within a 2-hour driving radius (from 97.4% to 97.1%) and an increase in the maximum of shortest driving time within county (from 117.2 to 121.0 min). Multilevel regression models, adjusted for confounders, showed that a 1 percentage point increase in the proportion of pregnant women covered within a 2-hour driving radius was associated with a 13 percentage point (95% CI: 11.4 to 14.7) increase in in-hospital delivery rates, especially in areas with lower coverage and in-hospital delivery rates.</p><p><strong>Conclusions: </strong>The reduction in obstetric hospitals increased travel distances, negatively impacting in-hospital delivery utilisation. Expanding the proportion of pregnant women covered within a 2-hour driving radius may be more effective than reducing the maximum of shortest travel distance within a county when optimising obstetric hospital locations. These findings provide insights for optimising obstetric facility locations in similar low- and middle-income countries. While improving spatial accessibility is important, the potential quality gains from centralising obstetric resources should also be considered.</p>","PeriodicalId":101362,"journal":{"name":"BMJ public health","volume":"3 1","pages":"e001683"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020756/pdf/","citationCount":"0","resultStr":"{\"title\":\"Does the reduction in obstetric hospitals result in an unintended decreased in-hospital delivery utilisation? A causal multilevel analysis in China.\",\"authors\":\"Nan Chen, Peter C Coyte, Jay Pan\",\"doi\":\"10.1136/bmjph-2024-001683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>China's progress towards achieving Sustainable Development Goals for maternal health is largely attributed to a reduction in maternal mortality rates, driven by increased in-hospital delivery services utilisation. However, recent reductions in the number of obstetric hospitals have raised concerns about compromised access to these services. This study investigates the impact of reduced obstetric hospitals on spatial accessibility and the utilisation of in-hospital delivery services.</p><p><strong>Methods: </strong>Data from 2016 to 2020 were collected from a densely populated province with approximately 83 million residents. Directed Acyclic Graph was applied to identify a minimally sufficient set of confounders, including residential characteristics and transportation-related factors. Multilevel regression models were employed to analyse the causal effects, with sensitivity analysis using fixed effect and quantile regression models.</p><p><strong>Results: </strong>Between 2017 and 2020, the number of obstetric hospitals decreased by 21.3% (from 1209 to 951), leading to a decline in the proportion of pregnant women covered within a 2-hour driving radius (from 97.4% to 97.1%) and an increase in the maximum of shortest driving time within county (from 117.2 to 121.0 min). Multilevel regression models, adjusted for confounders, showed that a 1 percentage point increase in the proportion of pregnant women covered within a 2-hour driving radius was associated with a 13 percentage point (95% CI: 11.4 to 14.7) increase in in-hospital delivery rates, especially in areas with lower coverage and in-hospital delivery rates.</p><p><strong>Conclusions: </strong>The reduction in obstetric hospitals increased travel distances, negatively impacting in-hospital delivery utilisation. Expanding the proportion of pregnant women covered within a 2-hour driving radius may be more effective than reducing the maximum of shortest travel distance within a county when optimising obstetric hospital locations. These findings provide insights for optimising obstetric facility locations in similar low- and middle-income countries. While improving spatial accessibility is important, the potential quality gains from centralising obstetric resources should also be considered.</p>\",\"PeriodicalId\":101362,\"journal\":{\"name\":\"BMJ public health\",\"volume\":\"3 1\",\"pages\":\"e001683\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020756/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ public health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjph-2024-001683\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ public health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjph-2024-001683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

导言:中国在实现孕产妇健康可持续发展目标方面取得的进展,在很大程度上归功于住院分娩服务利用率提高所推动的孕产妇死亡率下降。然而,最近产科医院数量的减少引起了人们对这些服务难以获得的担忧。本研究调查了减少产科医院对空间可达性和院内分娩服务利用的影响。方法:2016 - 2020年的数据来自一个人口密集的省份,约有8300万人口。有向无环图被应用于识别一组最低限度的混杂因素,包括居住特征和交通相关因素。因果关系分析采用多水平回归模型,敏感性分析采用固定效应和分位数回归模型。结果:2017 - 2020年,产科医院数量减少了21.3%(从1209家减少到951家),导致2小时车程范围内孕产妇覆盖比例下降(从97.4%下降到97.1%),县内最大最短车程时间增加(从117.2 min增加到121.0 min)。根据混杂因素调整后的多水平回归模型显示,在2小时驾驶半径内覆盖的孕妇比例每增加1个百分点,住院分娩率就会增加13个百分点(95% CI: 11.4至14.7),特别是在覆盖率和住院分娩率较低的地区。结论:产科医院的减少增加了出行距离,对院内分娩的利用产生了负面影响。在优化产科医院位置时,扩大2小时车程范围内孕妇的覆盖比例可能比减少县内最短距离的最大值更有效。这些发现为在类似的低收入和中等收入国家优化产科设施地点提供了见解。虽然改善空间可达性很重要,但也应考虑集中产科资源可能带来的质量收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Does the reduction in obstetric hospitals result in an unintended decreased in-hospital delivery utilisation? A causal multilevel analysis in China.

Introduction: China's progress towards achieving Sustainable Development Goals for maternal health is largely attributed to a reduction in maternal mortality rates, driven by increased in-hospital delivery services utilisation. However, recent reductions in the number of obstetric hospitals have raised concerns about compromised access to these services. This study investigates the impact of reduced obstetric hospitals on spatial accessibility and the utilisation of in-hospital delivery services.

Methods: Data from 2016 to 2020 were collected from a densely populated province with approximately 83 million residents. Directed Acyclic Graph was applied to identify a minimally sufficient set of confounders, including residential characteristics and transportation-related factors. Multilevel regression models were employed to analyse the causal effects, with sensitivity analysis using fixed effect and quantile regression models.

Results: Between 2017 and 2020, the number of obstetric hospitals decreased by 21.3% (from 1209 to 951), leading to a decline in the proportion of pregnant women covered within a 2-hour driving radius (from 97.4% to 97.1%) and an increase in the maximum of shortest driving time within county (from 117.2 to 121.0 min). Multilevel regression models, adjusted for confounders, showed that a 1 percentage point increase in the proportion of pregnant women covered within a 2-hour driving radius was associated with a 13 percentage point (95% CI: 11.4 to 14.7) increase in in-hospital delivery rates, especially in areas with lower coverage and in-hospital delivery rates.

Conclusions: The reduction in obstetric hospitals increased travel distances, negatively impacting in-hospital delivery utilisation. Expanding the proportion of pregnant women covered within a 2-hour driving radius may be more effective than reducing the maximum of shortest travel distance within a county when optimising obstetric hospital locations. These findings provide insights for optimising obstetric facility locations in similar low- and middle-income countries. While improving spatial accessibility is important, the potential quality gains from centralising obstetric resources should also be considered.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信