Modeling determinants of time-to-premarital cohabitation among Ethiopian women using parametric shared frailty models

利用参数共享脆弱性模型对埃塞俄比亚女性婚前同居时间的决定因素进行建模

阅读:1

Abstract

BACKGROUND: Premarital cohabitation is rampant and currently practiced worldwide, particularly in sub-Saharan Africa. It is a known cause of marital instability and divorce. It is also associated with intimate partner violence and harms the psychology of children in later life. However, in Ethiopia, there has been limited attention given to premarital cohabitation. OBJECTIVE: The main goal of this study was to identify the determinants of time-to-premarital cohabitation among Ethiopian women. METHODS: The 2016 EDHS data was used to achieve the study's goal. The survival information of 15683 women was analyzed based on their age at premarital cohabitation. The regional states of the women were used as a clustering effect in the models. Exponential, Weibull, and Log-logistic baseline models were used to identify factors associated with age at premarital cohabitation utilizing socioeconomic and demographic characteristics. RESULTS: The median age of premarital cohabitation was found to be 18 years. Surprisingly, 72.7% of participants were cohabitated in the study area. According to the Log-logistic-Gamma shared frailty model, place of residence, occupation, educational status, and being pregnant were found to be factors determining the time to premarital cohabitation. CONCLUSION: Premarital cohabitation among Ethiopian women was higher compared to women in the sub-Saharan Africa and East Africa. Place of residence, occupation, educational status, and being pregnant were found to be factors determining the time for premarital cohabitation. Therefore, we recommend the concerned bodies set out strategies to educate women about the influencing factors and dangers of premarital cohabitation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。