An investigation of the relation between life expectancy & socioeconomic variables using path analysis for Sustainable Development Goals (SDG) in Bangladesh.

Abstract

In today's world, the key variable for measuring population health is life expectancy (LE). The purpose of this research is to find out how life expectancy is related to other factors and develop a model to account for the predictors that contribute to LE. This study is also conducted to investigate and measure the effect of socioeconomic variables on LE in Bangladesh. In this study, the predictor variables are employment rate, gross national income (GNI), population growth rate, unemployment rate, and age dependency ratio. Path analysis disintegrated bivariate analysis and showed that employment rate, GNI, and age dependency ratio are significantly related to life expectancy, although bivariate analysis showed all variables are significantly related to LE. The maximum values of significant factors, GNI and employment rates, are $1930 and 21.32% happened in 2019, which is positively correlated with life expectancy. Also, the maximum value of the age dependency ratio (81.52%) happened in 1991, whereas the maximum value of the dependent variable LE (72.59 years) happened in 2019. It has been observed that LE, GNI, and employment rates all rise with one another. There exists an adverse relationship between LE and age dependency ratio. Based on comparisons with other highly developed nations, Bangladesh's GNI needs to grow faster than other significant factors to boost life expectancy. We have forecasted variables that were significantly related to LE until 2030 for the purpose of sustainable development goals, especially the 3rd goal.