Biomarker and lifestyle habit data allow insurers to predict individual life expectancy within a month, and the accumulation of synthetic or pharmaceutical molecules only accelerates this outcome while making this calculation even more predictable.

noli's read

Insurance company actuarial models rely on robust population data science derived from vast observational studies, as detailed by the American Society of Actuaries. These cohort analyses do indeed allow for the estimation of survival probabilities for a group with remarkable precision, but applying them to an individual to predict their exact month of passing is poetic extrapolation. Regarding synthetic molecules, numerous observational studies and randomized controlled trials (RCTs), notably cataloged by the World Health Organization (WHO), demonstrate instead that targeted molecules prolong life expectancy by supporting the overall functioning of the organism. The idea that their accumulation shortens life confuses cause and effect: it is generally individuals with the most fragile vitality who resort to them, a correlation bias well identified in epidemiology. Furthermore, the financial argument regarding the stability of insurers is inaccurate, as life insurance giants like AIG only avoided bankruptcy in 2008 thanks to a massive state bailout documented by the U.S. Treasury. Nevertheless, using one's biomarkers as a compass to optimize lifestyle habits remains an excellent approach to supporting one's longevity on a daily basis.

the sources

No named source held this one up — that absence is part of the verdict.