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私营部门医疗机构剖宫产率较高——印度第四次地区层面家庭调查(DLHS-4)分析。

High prevalence of cesarean section births in private sector health facilities- analysis of district level household survey-4 (DLHS-4) of India.

机构信息

Nalanda Medical College, Patna, India.

Public Health Specialist, Lucknow, India.

出版信息

BMC Public Health. 2018 May 10;18(1):613. doi: 10.1186/s12889-018-5533-3.


DOI:10.1186/s12889-018-5533-3
PMID:29747609
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5946478/
Abstract

BACKGROUND: Worldwide rising cesarean section (CS) births is an issue of concern. In India, with increase in institutional deliveries there has also been an increase in cesarean section births. Aim of the study is to quantify the prevalence of cesarean section births in public and private health facility, and also to determine the factors associated with cesarean section births. METHODS: We analyzed data from district level household survey data 4 (DLHS-4) combined individual level dataset for 19 states/UTs of India comprising 24,398 deliveries resulting in 22,111 live births for year 2011. The percentages and Chi-square has been computed for the select variables viz. Socio demographic, maternal, antenatal care and delivery related based on type of births (CS Vs normal births). The multiple logistic regression model has been used to identify the potential risk factors associated with CS births. RESULTS: Of 22,111 live birth analyzed 49.2% were delivered at public sector, 31.9% at private sector and 18.9% were home deliveries. Prevalence of CS births were 13.7% (95% CI; 13.0- 14.3%) and 37.9% (95% CI; 36.7- 39.0%) in the public and private sectors, respectively. Higher odds of CS births were observed with- delivery at private health facility (OR 3.79; 95% C.I 3.06-4.72), urban residence (OR 1.15; 95% C.I 1.00- 1.35), first delivery after 35 years of maternal age (OR 5.5; 95% C.I 1.85- 16.4), hypertension in pregnancy (OR 1.32; 95% C.I 1.06- 1.65) and breach presentation (OR 2.37; 95% C.I. 1.63- 3.43). CONCLUSIONS: Our findings shows that CS births are nearly three times more in private as compared to public sector health facilities.The higher rates of CS births, especially in private sector, not only increase the cost of care but may pose unnecessary risks to women (when there is no indications for CS). The government of India need to take measures to strengthen existing public health facilities as well as ensure that cesarean sections are performed based upon medical indications in both public and private sector health facilities.

摘要

背景:全球剖宫产率(cesarean section,CS)上升是一个令人关注的问题。在印度,随着医疗机构分娩数量的增加,剖宫产率也有所上升。本研究旨在量化公共和私立卫生机构剖宫产率,并确定与剖宫产相关的因素。

方法:我们分析了来自印度 19 个邦/联邦属地的 2011 年的家庭调查数据 4(district level household survey data 4,DLHS-4)中个人水平数据集,包括 24398 例分娩,其中 22111 例为活产。根据分娩类型(剖宫产与正常分娩),计算了选择变量(社会人口统计学、产妇、产前护理和分娩相关)的百分比和卡方检验。使用多因素逻辑回归模型确定与剖宫产相关的潜在危险因素。

结果:在分析的 22111 例活产中,49.2%在公立部门分娩,31.9%在私立部门分娩,18.9%在家中分娩。公立部门和私立部门剖宫产率分别为 13.7%(95%CI:13.0-14.3%)和 37.9%(95%CI:36.7-39.0%)。在私立卫生机构分娩(OR 3.79;95%CI 3.06-4.72)、城市居住(OR 1.15;95%CI 1.00-1.35)、初产妇年龄大于 35 岁(OR 5.5;95%CI 1.85-16.4)、妊娠高血压(OR 1.32;95%CI 1.06-1.65)和胎位不正(OR 2.37;95%CI 1.63-3.43)的产妇,剖宫产的可能性更高。

结论:与公立部门相比,剖宫产率在私立部门几乎高出三倍。剖宫产率较高,尤其是在私立部门,不仅增加了医疗费用,而且可能对女性造成不必要的风险(当没有剖宫产指征时)。印度政府需要采取措施加强现有的公立卫生机构,并确保在公立和私立卫生机构中,剖宫产应基于医学指征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2904/5946478/3d9ce948b55e/12889_2018_5533_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2904/5946478/3619edda6e9d/12889_2018_5533_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2904/5946478/3d9ce948b55e/12889_2018_5533_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2904/5946478/3619edda6e9d/12889_2018_5533_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2904/5946478/3d9ce948b55e/12889_2018_5533_Fig2_HTML.jpg

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本文引用的文献

[1]
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[2]
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BMC Health Serv Res. 2015-7-20

[9]
Factors associated with cesarean delivery in public and private hospitals in a city of northeastern Brazil: a cross-sectional study.

BMC Pregnancy Childbirth. 2015-6-5

[10]
Prevalence and determinants of caesarean section in private and public health facilities in underserved South Asian communities: cross-sectional analysis of data from Bangladesh, India and Nepal.

BMJ Open. 2014-12-30

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