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数据驱动的计划生育研究中连续摄取模式的发现。

Data-Driven Sequential Uptake Pattern Discovery for Family Planning Studies.

机构信息

IBM Research Africa, Nairobi, Kenya.

IBM T. J. Watson Research Center, Yorktown, NY, USA.

出版信息

AMIA Annu Symp Proc. 2022 Feb 21;2021:324-333. eCollection 2021.

Abstract

Family planning is a crucial component of sustainable global development and is essential for achieving universal health coverage. Specifically, contraceptive use improves the health of women and children in several ways, including reducing maternal mortality risks, increasing child survival rates through birth spacing, and improving the nutritional status of both mother and children. This paper presents a data-driven approach to study the dynamics of contraceptive use and discontinuation in Sub-Saharan African (SSA) countries. We aim to provide policymakers with discriminating contraceptive use patterns under different discontinuation reasons, contraceptive uptake distributions, and transition information across contraceptive types. We used Demographic Health Survey (DHS) Calendar data from five SSA countries. One recurrent pattern found was that continuous usage of injectables resulted in discontinuation due to health concerns in four out of five countries studied. This type of temporal analysis can aid intervention development to support sustainable development goals in Family Planning.

摘要

计划生育是可持续全球发展的关键组成部分,也是实现全民健康覆盖的必要条件。具体来说,避孕措施通过多种方式改善妇女和儿童的健康,包括降低产妇死亡率、通过生育间隔提高儿童存活率,以及改善母婴的营养状况。本文提出了一种数据驱动的方法来研究撒哈拉以南非洲(SSA)国家避孕措施的使用和停止动态。我们旨在为政策制定者提供不同停止原因下、不同避孕措施获取分布和不同避孕措施类型之间的过渡信息下的辨别避孕措施使用模式。我们使用了来自五个 SSA 国家的人口健康调查(DHS)日历数据。一个反复出现的模式是,在研究的五个国家中有四个国家,由于健康问题,连续使用注射剂会导致停止使用。这种时间分析可以帮助制定干预措施,以支持计划生育中的可持续发展目标。

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