Assessment of the factors responsible for premature deaths among men as compared to women in Uganda

Abstract

The overall objective was to assess the factors responsible for premature deaths among men as compared to women in Uganda using time series data of 1987-2019. It specifically found out the effect of Tobacco or marijuana Smoking, Prevalence of HIV, Education level and Alcohol use on premature mortality among men. Study findings indicated that on average, the number of Ugandan adult males dying between the ages of 15 and 60 per 1000 males (PMDi) was 500 males per 1000 adult males from 1987 to 2019.on average, 22.04% of Ugandan men aged 15 and above are currently smoking any tobacco product on a daily or non-daily basis (excluding smokeless tobacco use). Uganda‟s prevalence of HIV from 1987 to 2019 was highly skewed (skewness= 1.221632). Therefore Uganda‟s prevalence of HIV median was 1.2% in a range of [1.20 – 2.30]. On average, 62.33% of Ugandan adult males aged 15 and above can both read and write with understanding of a short simple statement about their everyday life. On average, each Ugandan male aged 15 and above was consuming 22.93 liters of pure alcohol yearly from 1987 to 2019 and the alcohol consumption was in a range of between 20.87 and 25.00 liters. Pairwise correlation results between tobacco smoking and premature deaths among men indicated a very strong positive relationship (R-value = 0.9844). Pairwise correlation results between prevalence of HIV and premature deaths among men indicated a chance positive relationship (R-value = 0.0379). Pairwise correlation results between education level (literacy rate among adult males) and premature deaths among men indicated a strong negative relationship (R-value = -0.8915). Pairwise correlation results between alcohol use and premature deaths among men indicated a chance positive relationship (R-value= 0.0062). Ordinary least square regression results indicated; a statistically significant (p-value<0.05) positive impact of tobacco smoking on premature deaths, a statistically insignificant (p-value > 0.05) positive impact of prevalence of HIV on premature deaths, a statistically insignificant (p- value > 0.05) negative impact of education level on premature deaths and a statistically significant (p-value< 0.05) positive impact of alcohol use on premature deaths among men in the long run at five percent level of significance. The R-squared value was found to be 0.9939 implying that the model is a best fit.