[01] Linali Pathirathne, Department of Statistics, University of Colombo, Colombo, Sri Lanka. [02] Roshini Sooriyarachchi, Department of Statistics, University of Colombo, Colombo, Sri Lanka.

The primary objective of this research is to examine the effect of economic, social and environmental indicators on life expectancy, using a cross-sectional comprehensive worldwide sample. The data corresponds to countries belonging to the United Nations (UN) and was taken from the World Statistics Pocketbook published by the UN (2005). Using this sample of data, the impact of country level variables on life expectancy (LE) at birth was analyzed. Multiple regression was used to model the LE. Principal Components (PCs) were used as explanatory variables for the model so as to avoid the problem of high correlation between explanatory variables (multi-collinearity). The model variants suggested that proxies for economic development, technology, nature conservation, education, healthcare, communication, population density and population growth rate all have a significant effect on average life expectancy. To increase the LE it is recommended to improve the economy, education level, health facilities, communication facilities and rural life style and to reduce industrialization, pollution, war and inflation. In addittion population growth should be encouraged but urbanization should be controlled so as to improve the LE. This analysis provides information required to governments, especially in the developing world as the LE at birth is predicted with high explanatory power by variables that can be influenced through public policy.

Life Expectancy, Principal Components, Regression, Proxy, Environmental, Socioeconomic

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