EXPLORING SOME FACTORS AFFECTING AVERAGE LIFE EXPECTANCY OF WOMEN IN AFRICA COUNTRIES USING REGRESSION ANALYSIS

ABSTRACT Life expectancy is defined as the average number of years that a newborn could expect to live if he or she were to pass through life exposed to the sex and age-specific death rates prevailing at the time of his or her birth, for a specific year, in a given country, territory, or geographic area. The data used for this analysis was secondary data that was obtained from the website www.kaggle.com. The data contains Life expectancy of women (dependent variable) and 8 relevant influencing factors (independent variables) of 54 African countries which span from year 2015– 2022. The influencing factor (independent variables) are: HIV/AIDS, Total expenditure, Population, Adult mortality, Infant deaths, Alcohol, Hepatitis B, Body mass index (BMI). The statistical tools used for the study include Variance Inflation Factor (VIF), Breusch-pagan test, Durbin-Watson Statistic and Test for Normality of residual. All these test were carried out to check the assumptions of regression analysis. Since there is no violation of any of the assumptions of regression, Ordinary Least Squares (OLS) Estimation method is used to carry out the analysis. From the result of the analysis, the R-Squared of 0.955053 indicates that approximately 95.50% of the variation in the life expectancy of women is explained by the independent variables in the model. This suggests that the model has a relatively high explanatory power. It also shows that Adult mortality, Hepatitis B, BMI, and Total expenditure has a statistical significant effect on life expectancy of women and while others does not have a statistical significant on life expectancy also, the overall model is statistical significant. In conclusion, adult mortality, total expenditure and health related issues are factors affecting life expectancy of women in Africa. Population have negative relationship on life expectancy of women in Africa, which means as the population increases, life expectancy decreases. The recommendations are made for the government, policy makers and organizations to improve the life expectancy of women by addressing the health related issues, find out causes of adult mortality rates and optimizing healthcare expenditures.