Individual and community level factors associated with modern contraceptive utilization among women in Ethiopia: Multilevel modeling analysis.

来自 PUBMED

作者:

Gebrekidan HAlemayehu MDebelew GT

展开

摘要:

Modern contraceptive utilization is the most effective intervention to tackle unintended pregnancy and thereby reduce abortion and improve maternal, child, and newborn health. However, multilevel factors related to low modern contraceptive utilization and the robust analysis required for decision-making were scarce in Ethiopia. To investigate the individual and community-level predictors of modern contraceptive utilization among reproductive-age women in Ethiopia. We utilized data from a cross-sectional 2019 Performance Monitoring for Action Ethiopia survey. The survey employed a stratified two-stage cluster sampling method to select households for inclusion. In Stata version 16.0, the data underwent cleaning, aggregation, and survey weighting, following which a descriptive analysis was performed utilizing the "svy" command. Subsequently, the primary analysis was executed using R software version 4.1.3. We fitted a two-level mixed effects logistic regression model on 6,117 reproductive-age women nested within 265 enumeration areas (clusters). The fixed effect models were fitted. The measures of variation were explained by intra-cluster correlation, median odds ratio, and proportional change in variance. The shrinkage factor was calculated to estimate the effects of cluster variables using the Interval odds ratio and proportion opposed odds ratio. Finally, the independent variables with a significance level of (P<0.05) and their corresponding Adjusted Odds ratios and 95% confidence intervals were described for the explanatory factors in the final model. In Ethiopia, the prevalence of modern contraceptive utilization was only 37.% (34.3 to 39.8). Women who attained primary, secondary, and above secondary levels of education were more likely to report modern contraceptive utilization with AOR of 1.47, 1.73, and 1.58, respectively. Divorced/widowed women were less likely to report modern contraceptive utilization (AOR:0.18, 95% CI 0.13,0.23) compared to never-married women. Discussions between women and healthcare providers at the health facility about family planning were positively associated with modern contraceptive utilization (AOR:1.84, 95% CI: 1.52, 2.23). Community-level factors have a significant influence on modern contraceptive utilization, which is attributed to 21.9% of the total variance in the odds of using modern contraceptives (ICC = 0.219). Clusters with a higher proportion of agrarian (AOR: 2.27, 95% CI 1.5, 3.44), clusters with higher literacy (AOR: 1.46, 95% CI 1.09, 1.94), clusters with empowered women and girls about FP (AOR: 1.47, 95% CI 1.11, 1.93) and clusters with high supportive attitudes and norms toward FP (AOR: 1.37, 95% CI 1.04, 1.81) had better modern contraceptive utilization than their counterparts. In Ethiopia, understanding the factors related to modern contraceptive use among women of reproductive age requires consideration of both individual and community characteristics. Hence, to enhance family planning intervention programs, it is essential to focus on the empowerment of women and girls, foster supportive attitudes towards family planning within communities, collaborate with education authorities to enhance overall community literacy, pay special attention to pastoralist communities, and ensure that reproductive-age women as a whole are targeted rather than solely focusing on married women.

收起

展开

DOI:

10.1371/journal.pone.0303803

被引量:

0

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(283)

参考文献(42)

引证文献(0)

来源期刊

PLoS One

影响因子:3.748

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读