article · Statistical Journal of the IAOS
This study investigated the spatial distribution and determinants of fertility rates across 53 African countries. Using Ordinary Least Squares (OLS) regression to identify key factors, the research then applied Geographically Weighted Regression (GWR) for a more nuanced spatial analysis. Findings revealed that Total Fertility Rate (TFR) is significantly influenced by adolescent fertility rates, contraceptive prevalence rates, and gross domestic product per capita. The GWR model proved superior to OLS in fitting African TFR data. High TFRs were particularly noted in Middle to Western African nations, including Burundi, Democratic Republic of the Congo, Central African Republic, Chad, Nigeria, Niger, Benin, Burkina Faso, and Mali, contributing to the continent's overall positive TFR spatial autocorrelation.
Understanding the spatial patterns and drivers of fertility rates in Africa is crucial for effective population planning and development strategies. This research provides detailed insights into where and why fertility remains high, offering a basis for targeted interventions to address associated socio-economic challenges.
The abstract suggests that the findings could inform targeted interventions to manage factors affecting Total Fertility Rate in specific African regions. This research is early-stage, providing analytical tools and insights for policy development and public health programmes, rather than indicating a direct commercial product or service.
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Studies have shown that fertility rate in Africa is still among the highest in the world. However, there are few spatial investigations into the variation of fertility rate and its determinant in Africa. This study aimed to examine the spatial distribution of fertility rate as well as highlight its significant determinants. Ordinary Least Squares (OLS) regression was carried out on dataset for 53 African countries on Total Fertility Rate (TFR) and eleven determinant factors to obtain a best model, which was then used for Geographically Weighted Regression (GWR). The study showed that TFR was significantly influenced by adolescent fertility rates, contraceptive prevalence rates and gross domestic product per capita. GWR model diagnostics of Akaike Information Criterion and adjusted R-squared showed that GWR fitted TFR in Africa better than OLS model. Also, countries around Middle to Western Africa comprising Burundi, Democratic Republic of the Congo, Central African Republic, Chad, Nigeria, Niger, Benin, Burkina Faso and Mali, were regions with high TFRs that impacted Africa’s positive TFR spatial autocorrelation. More intense works could therefore be carried out in these countries to manage the identified significant factors affecting TFR to address the negative consequences of high TFR in Africa.
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DOI: 10.3233/sji-200717
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