AN ALTERNATIVE APPROACH TO ESTIMATING MAXIMUM LIFE EXPECTANCY BASED ON SIMULATING AN OPTIMALLY HEALTHY POPULATION

    Purpose: Little is known about the maximum achievable life expectancy given a population's unique characteristics, which is important for estimating actionable population health metrics. Our objective is to address the question: Given the current state of health science and technology, what is the difference in the potential life expectancy gain that could be achieved in the United States and Norway in the idealized scenario where modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect.

   Method(s): We developed a Monte Carlo microsimulation model of 19 conditions representing the top causes of mortality in each age decile and the 28 risk factors associated with their onset that had consistent directions of effect as well as clinical and statistical significance. Each month individuals can develop new risk factors and/or new conditions, have existing risk factors or conditions resolve (e.g. through treatment), or die. We simulated a birth cohort of one million patients with characteristics resembling the population of the United States and Norway. We then compared current health with an idealized scenario where all modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect.

   Result(s): We estimated that the maximum life expectancy in the United States would be 84.7 years (a potential increase of 5.9 years) in the idealized scenario. The life expectancy for Norway would be 85.4 years (a potential increase of 3.9 years). Limitations include only capturing mortality through mortality causing conditions and therefore missing mortality acting through alternative pathways.

   Conclusion(s): With a highest achievable life expectancy of 84.7 years, an increase of 5.9 years above current life expectancy (78.8 years), the United States has a greater potential for improvement than Norway, which has a highest achievable life expectancy of 85.4 years, an increase of 3.9 years above current life expectancy (81.5 years). The use of mathematical simulations can estimate the maximum achievable life expectancy in a population and compare the differences in the potential of health improvement between populations in order to better inform efforts to improve population health. Through statistically-, rather than projection-based life expectancy predictions, the use of mathematical modelling holds the potential to improve the validity of health measures frequently used in health policy decision making.