Insights into Gender-Equity in Healthcare Accessibility in Northern Nigeria
Domain:
healthcaresocioeconomicRecord type:
paper
Creator:
OlaYinAkiTre
Editor:
Ola
Publisher:
Cod
Host:
This work considered regions in Northern Nigeria and carried out analyses on data on healthcare
accessibility, while taking individual characteristics (gender inclusive), socio-economic status, and
healthcare equity into consideration. Descriptive analysis (using Pearson’s and Spearman’s correlation
coefficients) and predictive analysis (using CATBoost, Random Forest, and Support Vector Machine
models) were done on the data. The descriptive analysis revealed that women with lower income and
education levels, and the elderly have a higher chance of accessing healthcare services compared to male
and non-binary gender, while the predictive analysis revealed that, using machine learning models, it is
possible to predict an individual’s accessibility to healthcare services with up to 81% accuracy.
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