how to map an estimated risk ratio of 0.76 to increased life expectancy Andrew Gelman's blog contains the following question:

John Ioannidis writes: Assuming the meta-analyzed evidence from cohort
  studies represents life span–long causal associations, for a baseline
  life expectancy of 80 years, eating 12 hazelnuts daily (1 oz) would
  prolong life by 12 years (ie, 1 year per hazelnut)
...With increasing intake (for each daily serving) of ... nuts (RR: 0.76; 95% CI: 0.69,
  0.84)... the risk of all-cause mortality decreased . . .
...I assume that hazelnuts count as nuts for this serving size.
The next question is how to map an estimated risk ratio of 0.76 to
  increased life expectancy. There’s gotta be some standard formula for
  this

So I'm curious: what is the standard formula for this?
https://statmodeling.stat.columbia.edu/2019/01/26/article-portrays-things-accurately-nutrition-literature-even-worse-shape-thought/#respond
 A: The following answer was posted on Gelman's blog (the source of the original question), and seems to provide a good rough approximation:
Joshua R Goldstein says:
January 29, 2019 at 11:35 am
There’s a nice literature on life table “entropy” that has analytic expressions on how to convert a uniform change in mortality by age into a change in life expectancy at birth.
The basic result is that the proportional change in life expectancy is currently equal to about .1 to .2 times the change in mortality rates. So if some treatment causes mortality to drop by 10% at all ages, life expectancy at birth will increase by 1-2%.
For those interested, here is our paper that reviews this classic result with some extensions to slowing the rate of aging: Goldstein, Joshua R., and Thomas Cassidy. “How slowing senescence translates into longer life expectancy.” Population studies 66.1 (2012): 29-37.
https://statmodeling.stat.columbia.edu/2019/01/26/article-portrays-things-accurately-nutrition-literature-even-worse-shape-thought/#comments 
