埃塞俄比亚育龄妇女在家分娩的空间差异及相关因素,来自2019年埃塞俄比亚行动绩效监测调查的证据,空间和多层次logistic回归分析。

IF 2.3 Q2 OBSTETRICS & GYNECOLOGY
Frontiers in global women's health Pub Date : 2024-12-16 eCollection Date: 2024-01-01 DOI:10.3389/fgwh.2024.1474762
Ermias Bekele Enyew, Kokeb Ayele, Lakew Asmare, Fekade Demeke Bayou, Mastewal Arefaynie, Yawkal Tsega, Abel Endawkie, Shimelis Derso Kebede, Abiyu Abadi Tareke, Kaleab Mesfine Abera, Natnael Kebede, Mahider Shimelis Feyisa, Mengistu Mera Mihiretu
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引用次数: 0

摘要

简介:家庭分娩被描述为在没有熟练助产士在场的情况下在家中分娩。2017年,近29.5万名母亲死于各种与妊娠和分娩有关的问题,每天约有810名孕产妇死亡。因此,本研究旨在利用2019年行动绩效监测调查(PMAS)调查埃塞俄比亚家庭分娩的空间分布及其相关因素,以获取有助于采取基于地理的干预措施的信息,并可协助卫生规划者和政策制定者制定减少家庭分娩的具体措施。方法:在PMA-ET 2019中,于2019年9月至2019年12月在埃塞俄比亚与亚的斯亚贝巴大学、约翰霍普金斯大学和联邦卫生部合作开展了一项基于社区的横断面研究。采用多阶段整群抽样程序从分层的2019 PMAS样本中抽取。这项研究加权共纳入5796名女性。采用ArcGIS 10.7软件对空间分析进行可视化处理。此外,使用统计软件STATA版本14进行多水平分析,使用Kulldorff的SaTScan版本9.6软件应用Bernoulli模型来识别埃塞俄比亚家庭配送的重要纯空间集群。使用类内相关系数(ICC)、似然比(LR)检验、中位优势比(MOR)和偏差(-2LLR)值进行模型比较和适应度。具有95%置信区间(CI)和p值的调整优势比(AOR)结果:埃塞俄比亚家庭分娩的空间分布是非随机的。在索马里、阿法尔、西达马、南部民族和人民地区的大部分地区、阿姆哈拉的大部分地区、埃塞俄比亚西南部和奥罗米亚地区,发现了统计上显著的高送货热点。在多层逻辑回归模型中;来自最低财富五分之一的女性为1.68倍[AOR = 1.68;(95%可信区间:1.31,2.15)在家分娩的几率比其他女性高。在母亲受教育程度方面,未受教育、初等教育和中等教育的母亲在家分娩的几率分别是受过高等教育母亲的9.91倍[AOR = 9.91, 95% CI: 5.44, 18.04]、6.62倍[AOR = 6.62, 95% CI: 3.65, 12.00]和2.99倍[AOR = 2.99, 95% CI: 1.59, 5.63]。此外,社区水平因素与家庭分娩显著相关,社区高度贫困妇女的家庭分娩率为1.76倍[AOR = 1.76;(95% CI: 1.14, 2.72)与社区贫困程度较低的妇女相比,在家分娩的几率更高。结论:统计发现,在索马里、阿法尔、西达马、南部民族和人民地区大部分地区、阿姆哈拉大部分地区、埃塞俄比亚西南部和埃塞俄比亚奥罗米亚地区,送货上门是一个显著的高发热点。在埃塞俄比亚,与在家分娩相关的重要因素是妇女受教育程度较低、财富较差、生活在农村地区、社区贫困程度高、离婚或分居寡妇的婚姻状况以及母亲年龄较大。因此,卫生机构、卫生专业人员、国家和地区决策者、卫生规划人员、社区领导人和所有有关方面应优先考虑已确定的热点群集,以设计有效的干预方案,以减少在家分娩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial variation and associated factors of home delivery among reproductive age group women in Ethiopia, evidence from Performance Monitoring for Action Ethiopia Survey 2019, spatial and multilevel logistic regression analysis.

Introduction: Home birth is described as a delivery that takes place at home without the presence of a skilled birth attendant. In 2017, nearly 295,000 mothers died from various pregnancy and childbirth-related problems, accounting for approximately 810 maternal deaths per day. Therefore, this study aims to investigate the spatial distributions of home birth and associated factors in Ethiopia using the Performance Monitoring for Action Survey (PMAS) 2019) to get information that helps to take geographic-based interventions and can assist health planners and policymakers in developing particular measures to reduce home deliveries.

Method: In PMA-ET 2019, a community-based cross-sectional study was conducted in collaboration with Addis Ababa University, Johns Hopkins University, and the Federal Ministry of Health from September 2019 to December 2019, in Ethiopia. A multi-stage cluster sampling procedure was employed to draw from the stratified 2019 PMAS sample. A weighted total of 5,796 women were included in this study. ArcGIS version 10.7 software was used to visualize the spatial analysis. In addition, STATA version 14 of the statistical software was used for multilevel analysis The Bernoulli model was applied using Kulldorff's SaTScan version 9.6 software to identify significant purely spatial clusters for home delivery in Ethiopia. Intra-class Correlation Coefficient (ICC), Likelihood Ratio (LR) test, Median Odds Ratio (MOR), and deviance (-2LLR) values were used for model comparison and fitness. Adjusted Odds Ratios (AOR) with a 95% Confidence Interval (CI) and p-value <0.05 in the multilevel logistic model were used to declare significant factors associated with home delivery.

Result: The spatial distribution of home delivery was non-random in Ethiopia. Statistically significant high hotspots of home delivery were found in Somali, Afar, Sidama, most of South Nation Nationality and People Region (SNNP), most parts of Amhara, south west Ethiopia, and Oromia region. In the multilevel logistic regression model; Women from the lowest wealth quintile were 1.68 times [AOR = 1.68; 95% CI: 1.31, 2.15] higher odds of giving birth at home as compared to their counterparts. Regarding maternal educational status, mothers who had no education, primary education, and secondary education had 9.91 times [AOR = 9.91, 95% CI: 5.44, 18.04], 6.62 times [AOR = 6.62, 95% CI: 3.65, 12.00] and 2.99 times [AOR = 2.99, 95% CI: 1.59, 5.63] higher odds of giving birth at home compared to mothers who attained higher education, respectively. In addition, community-level factors were significantly associated with home delivery, women who had high community-level poverty were 1.76 times [AOR = 1.76; 95% CI: 1.14, 2.72] higher odds of home delivery compared to women who had low community-level poverty.

Conclusion: Home delivery was statistically found to be a significantly high hot spot in Somalia, Afar, Sidama, most of the South Nation Nationality and People area (SNNP), most of Amhara, southwest Ethiopia, and the Oromia region of Ethiopia. Significant factors associated with home delivery in Ethiopia were women with lower levels of education, poor wealth, living in rural areas, high levels of community poverty, divorced or separated widowed marital status, and older maternal ages. Therefore, health institutions, health professionals, National and regional policymakers health planners community leaders and all concerned should give priority to the identified hot spot clusters to design an effective intervention program to reduce home delivery.

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