I just did something sort of morbid.

Using the most recent life expectancy data published by the CDC, I ran the numbers for my current age and gender to find the distribution of my year of death if I lived 100 times.

This accounts for all of the currently reported causes of deaths, ranging from all types of cancer, to suicide, to assault, to lightning strikes and car accidents, to drowning, to kidney infections and a thousand other categories.

If there were 100 of me, all 36 years old (as I am right now), and you set them loose, one of me dies before I turn 40.

Another one of me dies before I turn 45.

Two more of me die before 50, another two before 55, and another two before 60.

Then things start to ramp up and five of me die before 65, six of me before 70, and nine of me before 75.

From the one hundred Busters that started at age 36, only 59 of me make it past my 80th birthday.

Sixteen of me die before 85, eighteen of me before 90, and fifteen of me before 95.

At my 100th birthday, seven of me got pretty close, but only two of me are left to blow out the candles.

Those two die within the next 5 years.

What were those last nine or ten Busters like? Were they the ones that, at age 36, were running every morning? Did they drink as much as I did last night? Or did they just get lucky? I want to know more. What happened to the Buster that died before age 40? Was it cancer, like my father (age 41)? Was it one of me that made a poor life choice and never course corrected? Or was he just hit by a bus?

My neighbor is 81 and is still in great health. I want to be one of me that is more like him when I’m 81… riding bikes, going on ski trips, gardening in the yard.

I turn 37 at the end of the month. And my average remaining life expectancy is 45.2 years. What if we celebrated our expected years left instead of our years already spent?

I’m going to run the script one more time, for a single Buster, and see what it turns up. [brb]

Hm. Not good. Its answer: “1 Buster dies before age 50”.

There’s nothing personal about this data. I have some time to fiddle with the odds, some natural advantages and disadvantages, etc. It would be interesting to look at likely causes of death, for example, and at forecasting outcomes for my wife and I together.

A more thorough experiment would be to take this baseline and apply some personal data (my current level of health, my current exposure to various risks) and play out another 100 Busters given different strategies (becoming vegan, running marathons, gaining 30 pounds, etc).

I’ll probably start playing around with this data a bit more. Let me know if you find it interesting.