使用2005年和2016年EDHS的埃塞俄比亚意外怀孕变化的决定因素:非线性多变量分解分析

Abiyu Abadi Tareke, Ermias Bekele Enyew, Abiy Tasew Dubale, Aynadis Worku Shimie, Mulugeta Desalegn Kasaye, Habitu Birhan Eshetu
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引用次数: 0

摘要

背景:意外怀孕是指不合时宜或不想要的怀孕。意外怀孕的主要后果是人工流产。在埃塞俄比亚,超过一半的意外怀孕以堕胎告终。目的:本研究旨在测量2005年至2016年调查期间育龄妇女意外怀孕的变化,并确定对这一变化最重要的社会人口因素。方法:分析最近两次埃塞俄比亚人口与健康调查(EDHS)的数据。我们量化了社会人口因素对意外怀孕变化的贡献,通过应用STATA命令“mvdcmp”,使用非线性回归模型的Oaxaca-Blinder分解。结果:埃塞俄比亚的意外怀孕率从2005年的37%下降到2016年的27%。人口特征和系数的变化是观察到的意外怀孕变化的贡献因素。在人口特征因素中,2005年至2016年期间,索马里地区的部分决策者和贫民窟分别对意外怀孕的变化贡献了10%和14%。在系数因素中,现代计划生育知识、作为部分决策者、媒体接触、卫生设施距离和卫生设施访问次数分别对变化贡献了93%、43%、17%和10%。结论:2005 - 2016年调查中意外妊娠的变化主要是由于系数的差异(85%)。改变意外怀孕的主要因素是计划生育知识、决策、媒体接触和保健设施访问。因此,如果专注于更大的促成因素,干预计划将是有效的,更好的,更有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determinants of change in unintended pregnancy in Ethiopia using the 2005 and 2016 EDHS: non-linear multivariable decomposition analysis.

Background: Unintended pregnancy is a pregnancy either mistimed or unwanted. The main consequence of unintended pregnancy is inducing abortion. In Ethiopia, more than half of unintended pregnancies end up in abortion.

Objective: This study aims to measure the change in unintended pregnancy among women of reproductive age between survey years 2005 and 2016 and to identify the socio-demographic factors that most significantly contributed to the change.

Methods: Data from the two most recent Ethiopian Demographic and Health Surveys (EDHS) were analyzed. We quantified the contribution of socio-demographic factors in the change of unintended pregnancy, using Oaxaca-Blinder decomposition for non-linear regression models by applying the STATA command 'mvdcmp'.

Result: Unintended pregnancy decreased from 37% in 2005 to 27% in 2016 in Ethiopia. Both changes in population characteristics and coefficient were the contributing elements to the observed change in unintended pregnancy. Among population characteristics factors, being a partial decision-maker and being a slum in the Somali region contributed 10 and 14% to the change of unintended pregnancy between the 2005 and 2016. Of the coefficient factors, knowledge of modern family planning, being a partial decision-maker, media exposure, distance to health facilities, and health facility visits contributed to the change by 93, 43, 17, and 10% respectively.

Conclusion: The majority of the change in unintended pregnancy from 2005 to 2016 survey was due to differences in coefficients (85%). The principal contributing factors to the change of unintended pregnancy were FP knowledge, decision making, media exposure and health facility visits. Therefore, an interventional plan will be efficient, better, and more effective if focused on the larger contributing factors.

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