[HN Gopher] Actuarial Life Table
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Actuarial Life Table
Author : j765
Score : 85 points
Date : 2022-04-12 16:25 UTC (6 hours ago)
(HTM) web link (www.ssa.gov)
(TXT) w3m dump (www.ssa.gov)
| chomp wrote:
| I graphed the difference in years amongst men and women using
| good ol' fashioned awk and free graphing software:
|
| https://imgur.com/a/3b1KrD7
|
| It looks like at around age 18 - 30ish, the numbers start
| catching up, with a sharper reduction in expectancy differences
| happening around age 35.
|
| From the PRB:
|
| "Men are three times as likely as women to die from injuries
| (unintentional injuries, suicide, or homicide), and progress
| against those causes of death has been much slower than against
| other causes in the last 50 years. There is also evidence that
| men at all ages are less likely to seek medical care and less
| likely to comply with medical instructions than are women."
| readthenotes1 wrote:
| "There is also evidence that men at all ages are less likely to
| seek medical care and less likely to comply with medical
| instructions than are women."
|
| Especially on the 0-1 year old group. Toxic masculinity starts
| in utero.
| chomp wrote:
| Men's health is complicated. Yes, there's some "strength in
| silence" confounding issues in doctor training and patients,
| but if you pry back the social media buzzwords, you'll see
| that there's complex economic and societal forces that push
| men's health downward.
|
| https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1121551/
|
| Also, I think you are trolling, but I'll bite. The expectancy
| in the 0-1 age group takes into account all life events that
| will affect the child over time, including what I had quoted.
| If you look at the probabilities in early life for both
| sexes, they have similar death probabilities.
| TheSoftwareGuy wrote:
| > The expectancy in the 0-1 age group takes into account
| all life events that will affect the child over time
|
| But this is not taken into account in the Death Probability
| column, is it? Because we also see in that column,
| consistently better outcomes for women, even for the very
| youngest age groups
| Retric wrote:
| 10 and 11 year old boys have very similar rates of death
| as 10 and 11 year old girls, and it swaps some years ex:
| 2013.
|
| Click on 2006 for example and men have noticeably lower
| rates of death in that age range, but 14 year old boys
| where still twice as likely to die.
| 21723 wrote:
| _Toxic masculinity starts in utero._
|
| I was going to reply but then decided, no, nevermind.
| kristopolous wrote:
| The internet can be extremely hostile to empirical
| evidence. I actually just expect to be brigaded whenever I
| reference things like The Lancet. People are aggressively
| anti-intellectual.
|
| People don't logon to learn, they're here to be tribal and
| do social cues
| yellowstuff wrote:
| Most people will miss this reference and the rest will feel
| old. You owe us all apologies.
| spookylettuce wrote:
| I'm very interested in this workflow of data -> awk -> graph.
| What graphing software did you use?
| chomp wrote:
| Well, I spat out the list of numbers and just googled "graph
| values" and took the first result, but if you love to stay in
| command line, you can do something like so...
|
| # awk '{print $7-$4}' chart | gnuplot -p -e 'plot
| "/dev/stdin"'
|
| Where `chart` is just what I copy and pasted from the site :)
| treespace8 wrote:
| Wow, as a guy I have a 1/5 chance of not even making it to
| retirement. (65) 1/3 chance of not living past 75. These are not
| good odds.
| lotsofpulp wrote:
| I wonder how those odds change if you narrow down to your
| occupation/socioeconomic status/location.
|
| I have always wondered what the income volatilities as you age
| are for the purposes of calculating how much I should be
| saving. My current strategy is to assume I will be unable to
| earn income and/or need to spend a lot on healthcare with
| increasing material odds starting at age 50 (since I might not
| have access to subsidized health insurance that comes with a
| job).
| hardtke wrote:
| This data, unfortunately, is missing an important confounding
| variable besides male/female. In the US lifespan his highly
| correlated with income, and the trend is getting worse. "The gap
| in life expectancy between the richest 1% and poorest 1% of
| individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men
| and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second,
| inequality in life expectancy increased over time. Between 2001
| and 2014, life expectancy increased by 2.34 years for men and
| 2.91 years for women in the top 5% of the income distribution,
| but increased by only 0.32 years for men and 0.04 years for women
| in the bottom 5% (P < .001 for the difference for both sexes)."
| [1]
|
| [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4866586/
| anamax wrote:
| From the article: "The differences in life expectancy were
| correlated with health behaviors and local area
| characteristics."
|
| "Health behaviors (rates of current smoking, obesity [defined
| as body mass index {calculated as weight in kilograms divided
| by height in meters squared} >=30], and exercise during the
| past month)"
| zeroonetwothree wrote:
| Hard to say in which direction the causation lies.
| layer8 wrote:
| That's actually a good point: People who die earlier due to
| genetics accumulate less wealth in their lifetime, and their
| children therefore inherit less. With that causality, people
| are poorer literally because they die earlier, rather than
| the other way around. ;)
| amyjess wrote:
| I wish I was good enough at math to use these tables to figure
| out what percentage of the population is within a particular age
| range in any given year.
|
| In particular, I'm curious to see what years the population of
| particular generations peaked.
|
| Edit: Actually what I'm really looking to do is to correlate
| certain marketing demographics with generations. For example, "in
| what years did Generation X comprise the majority of living
| people in the 18-34 demographic?" (where Generation X is defined
| as people born 1961-1981).
| tfehring wrote:
| There's not enough data to answer those questions from these
| tables, the "number of lives" fields are just illustrative.
| Spivakov wrote:
| The death probability has a turning point from decreasing to
| increasing around age 10 for both male and female. Wonder why
| this specific age.
| bachmeier wrote:
| While that's true, these are small death probabilities. The age
| 10 death probability is less than 1 in 10,000. It doesn't even
| reach 1 in 1000 until age 20 for men and age 34 for women.
| According to this data source[1] there are about 4 million
| 10-year olds. That works out to less than 400 deaths for the
| entire US in a year.
|
| What I find interesting is the divergence at age 10 by gender.
| By the late teens, boys are about 2.5 times more likely to die,
| in spite of the probability being the same at age 10.
|
| [1] https://www.statista.com/statistics/241488/population-of-
| the...
| rexreed wrote:
| The overlapping decreasing line curves of mortality due to
| infant / child mortality cases and increasing line curves of
| mortality due to external factors, accidents, and illnesses.
| The lines cross around 10 yrs old.
| bombcar wrote:
| I wonder if it's accidental behavior because of not knowing
| better (children crawling into water or streets etc) combined
| with accidental behavior because of being teenagers crossing
| over.
| brimble wrote:
| Probably not the only factor, but 10's about the age when
| suicide becomes more than a very, very remote possibility.
|
| https://www.cdc.gov/mmwr/preview/mmwrhtml/figures/m6128qsf.g...
| klelatti wrote:
| U.K. data but accidents and cancer exceed intentional self
| harm for teenagers.
|
| https://stateofchildhealth.rcpch.ac.uk/evidence/mortality/ad.
| ..
| torstenvl wrote:
| Great resource. I use this all the time for military clients near
| or past retirement eligibility, to estimate the lifetime
| financial penalty of discharging them before retirement, or of
| retiring them in a lower grade.
| morepork wrote:
| Based on this, by the time you're 30, around 2% of your male high
| school peers have passed away, but only 1% of your female ones.
| Puts an interesting perspective on things.
| verisimi wrote:
| I would love to see the same data for the last 2 years
| klelatti wrote:
| If anyone is interested in more life tables the Society of
| Actuaries has thousands to download and there is some simple code
| to read them in Python here:
|
| https://www.joveactuarial.com/blog/mortality-tables/
| siddboots wrote:
| One fun thing to do is to take these death probabilities and
| throw them into a Leslie matrix [1], along with assumptions for
| the age-specific birth rates. From there you can simulate the
| projected population growth (ignoring migration) with no more
| than a couple of lines of Python/R/whathaveyou.
|
| It's also a great study case for understanding some basic
| principles of linear algebra: The dominant eigenvalue is the
| stable population growth rate, and the corresponding eigenvector
| is the stable age distribution.
|
| [1] https://en.wikipedia.org/wiki/Leslie_matrix
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