A System Dynamics Framework for Analyzing and Ranking Factors Influencing Life Expectancy

Abstract

Life expectancy is a key measure of public health and development, but its determinants are complex and interdependent, making accurate prediction and policymaking challenging. This study adopts a system dynamics modeling approach to identify, rank, and simulate the factors influencing life expectancy, with a focus on healthcare clinics in Iran. Based on an extensive literature review and expert consultations, 25 indicators are selected and validated through a structured questionnaire, yielding a Cronbach’s alpha of 0.74, confirming acceptable internal consistency. Simulation experiments are carried out by Vensim software under baseline, inflationary, and deflationary conditions, and complemented by sensitivity analysis. The findings indicate that inflation has the most substantial negative impact, reducing life expectancy by more than four years under a 10% annual increase, while improvements in environmental quality, healthcare access, and nutrition exert positive and reinforcing effects. The study contributes by demonstrating the value of system dynamics in capturing feedback relationships often overlooked in conventional approaches, thereby providing policymakers with integrated insights to design effective strategies for improving life expectancy.