Healthy quality has become a pressing issue for policymakers and researchers. The health indicators in Somalia are poor,
such as high mortality rates and low life expectancy. This study ascertains the impacts of environmental pollution, energy
consumption, economic growth, food production, and internal and external conflicts on the mortality rate in Somalia.
The study employs a machine learning method, specifically the Kernel regularized least squares (KRLS) technique, on
an annual unbalanced time series spanning 1985–2019. This method assesses the marginal effects of the sampled independent variables on mortality rate, unlike the traditional econometric methods that assume constant marginal effects.
The empirical results revealed that economic growth and food production reduce the mortality rate in Somalia, whereas
energy consumption and internal and external conflicts increase it. Environmental pollution does not have any significant effect on the mortality rate in Somalia. Based on the empirical findings, the study proposes shifting from fosil fuel
energy use to renewable energy, which is clean and favorable to the environment and health. Furthermore, deescalating
conflicts would help to reduce Somalia’s mortality rate.