MCA:improving U.S. Life expectancy

The National Science Foundation's Division of Social, Behavioral and Economic Science awarded a $372,000 Project Grant to The Ohio State University (awarded September 1, 2025, through August 31, 2028) to conduct research on improving U.S. life expectancy by identifying which health and social conditions most strongly influence longevity. The project delivers a comprehensive evidence synthesis and analytical framework through three primary products: (1) a standardized dataset documenting conditions that influence life expectancy, including assessment of measurement quality and evidence strength for each factor; (2) advanced statistical and artificial intelligence modeling analyses that determine how combinations of conditions and governmental factors explain variation in life expectancy across populations; and (3) a database framework designed to support evidence-based policy allocation decisions. The research team conducts systematic umbrella reviews of 1,164 studies examining life expectancy relationships, applies standardized weight-of-evidence protocols to assess measure strength, and harmonizes findings to support more effective public resource allocation in longevity-focused programs.

The project incorporates international subject matter expertise through sub-grants to the University of Bristol and the University of Sheffield. The University of Bristol sub-award funds 30 days of collaboration from Professor George Leckie to provide specialized methodological guidance and contribute to training materials on Multivariable Multilevel Mediation Analysis for Heterogeneous Effects (MAIHDA) methods. The University of Sheffield sub-award engages Dr. Andrew Bell, a leader in MAIHDA method development, to provide statistical and methodological expertise ensuring research robustness and enhancing the validity of project findings for academic and policy stakeholder audiences.

Abstract

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 characteristics most strongly associated with life expectancy. To accomplish these objectives, umbrella reviews (i.e., reviews of reviews) are conducted of 1,164 studies examining the relationship between life expectancy and conditions in the united states. Using standardized protocols for determining the ?weight of evidence,? Scores are assigned to each measure based on how strongly IT is linked to life expectancy. Analysis methods then are used to harmonize and integrate these measures with life expectancy data. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.