Multidimensional Analysis of Reproductive Health Indicators in Africa: A Clustering Approach for Identifying Disparities and Formulating Targeted Policies
DOI:
https://doi.org/10.29358/sceco.v0i42.599Keywords:
cluster analysis, reproductive health, infant mortality, maternal mortality, family planningAbstract
This research aims to interpret the key reproductive health indicators of African countries using cluster analysis. By classifying these countries based on their reproductive health indicators, this study highlights their strengths and weaknesses in achieving the Sustainable Development Goals, particularly those related to ensuring maternal and child health, access to healthcare, protection of reproductive rights, combating sexually transmitted diseases and harmful practices, and reducing maternal and child mortality rates. A combined descriptive-analytical approach was employed, enabling us to provide a comprehensive overview reflecting the reality of reproductive health in Africa. Additionally, advanced statistical methods were utilized through the implementation of two of the most significant clustering techniques. Furthermore, the TANAGRA 1.4.50 software, which encompasses a broad array of algorithms used in exploratory statistics, data analysis, and processing, was leveraged. The latest data on reproductive health indicators for African countries (42 countries), compiled from the United Nations Development Programme and the United Nations Population Fund in 2023, were also employed. The study revealed significant disparities in reproductive health indicators among African countries. These countries were classified into four main groups based on their priorities, the severity of their situation, and a set of demographic, social, and economic characteristics. Additionally, the study confirmed the existence of African countries categorized as being at risk, necessitating urgent interventions through the adoption of comprehensive strategic plans to strengthen families and support their reproductive health.
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