This project investigates which conditions have the greatest influence on life expectancy in the United States. With U.S. life expectancy declining, and billions spent each year on programs aimed at improving longevity, there is a pressing need for clear, actionable research that identifies which investments are most effective. The project develops a process to track these conditions across levels of administration and uses advanced data methods, including artificial intelligence (AI), to determine which combinations of factors are most strongly tied to longer lives. Findings from this work help identify where policies are falling short and offer a foundation for improving how public funds are allocated. In doing so, this research supports the broader goal of strengthening public resilience—an essential element of national well-being and security. This Mid-Career Advancement (MCA) project has three main goals. The first is to gather and standardize data on conditions that influence life expectancy, document how each is measured, and assess the strength of the evidence linking each measure to average life expectancy. Second, this project applies innovative modeling techniques, including use of AI, to assess how combinations of conditions and governments explain variation in life expectancy across populations. Third, building on the information gathered while achieving the first two goals, the project team creates a framework for a database designed to address the characteri