5 ms·

Not to extract too much from the sample size of 1, but at the time this was filmed this farmer was 87 years old. He seems to be in really impressive health.

by syspec 5y ago

dredmorbius 5y ago
An alternative perspective on "high mortality" is "strong selection pressure". About half of all children born died before reaching the age of 20, and that mortality fell off tremendously with the 1st, 5th, and 10th years. This chart gives life expectancy by age (rather than mortality), but you can largely infer the latter. Range is 1700--2013, though for most ages data are from 1850 onwards. https://ourworldindata.org/uploads/2013/05/Life-expectancy-by-age-in-the-UK-1700-to-2013.png https://ourworldindata.org/uploads/2013/05/Life-expectancy-b...
- OJFord 5y ago
  Still seems problematic to use 'life expectancy' at all to me, since the at birth and early years lines are still affected. Wouldn't it be better to show something like 'probability of living another ten years' (at birth/each of x years old)? I'm no statistician.
  - dredmorbius 5y ago
    The age-adjusted concept is "life expectancy at year n". That is precisely equivalent to "additional years of survival at year n plus year n". The alternative notion I'd suggest is "anticipated mortality at year n for those born in year m". The latter would show a typical "bathtub" mortality curve, high initially, then lower, then climbing in late age. Note too that the image I'd posted is literally a representation of survivorship bias: the longer an individual has survived, the longer they're likely to continue to survive.
    - OJFord 5y ago
      > That is precisely equivalent to "additional years of survival at year n plus year n". But that's (minus n) not what I suggested; it's not equivalent to the probability of living another ten years (say). E.g. the life expectancy of five year olds (plus that they are five years old) is not sufficient information to determine how many of them (the probability one) will live to fifteen.
      - dredmorbius 5y ago
        Re-reading, sorry. So ... "probability of surviving another 10 years" is different from life-expectency. It's a variant on mortality, though expressed over a 10 year period rather than a 1 year period. For comparison, see the SSA's actuarial life tables. This gives 1-year mortality (both as percentage and as expected survivors per 100,000 lives) for each year of life from 0 to 119: https://www.ssa.gov/oact/STATS/table4c6.html https://www.ssa.gov/oact/STATS/table4c6.html I'm not aware of a compilation or chart showing changes in actuarial mortality by age over time. There's a good chart of anticipated deaths per year (separately for women and men) in the UK: https://understandinguncertainty.org/why-life-expectancy-misleading-summary-survival https://understandinguncertainty.org/why-life-expectancy-mis... What question are you trying to answer by looking at mortality probability?
        OJFord 5y ago
        > What question are you trying to answer by looking at mortality probability? Well, starting with the problem of 'life expectancy is biased by infant mortality', that it misleads people into thinking it was rare to live past 30 or whatever: stats like 'life expectancy at 20/30/etc.' are helpful. I was just saying that I don't think 'life expectancy at x' when x is small is helpful, since in the limit we're back to where we started, and until x > end of relatively high risk, it suffers the same bias. Looking at mortality probability would more directly show that early years are at risk, before it settles down and death is unlikely until old age. The old age curves (birth year is still the horizontal axis) would still show the truer change over time, but now so would the infant years. You could even (/might need to) refine it to P{living another year} - P{having died within last year (or before)} or something.
bumbada 5y ago
It does not surprise me at all. People did die very easily from infections, the people that survived were usually really strong. E.g My grandpa never caught a cold, he went to his 90s basically never getting ill. His immune system was so strong. I go to rural areas in Europe where 80 somethings climb the mountain faster than the city kids in their 20s. Some kids from the city have really no balance or physical skills at all, like they could not step over a stone without falling down.

Not to extract too much from the sample size of 1, but at the time this was filmed this farmer was 87 years old. He seems to be in really impressive health.

by syspec 5y ago

Not to extract too much from the sample size of 1, but at the time this was filmed this farmer was 87 years old. He seems to be in really impressive health.

dredmorbius 5y ago

An alternative perspective on "high mortality" is "strong selection pressure". About half of all children born died before reaching the age of 20, and that mortality fell off tremendously with the 1st, 5th, and 10th years. This chart gives life expectancy by age (rather than mortality), but you can largely infer the latter. Range is 1700--2013, though for most ages data are from 1850 onwards. https://ourworldindata.org/uploads/2013/05/Life-expectancy-by-age-in-the-UK-1700-to-2013.png https://ourworldindata.org/uploads/2013/05/Life-expectancy-b...

OJFord 5y ago
Still seems problematic to use 'life expectancy' at all to me, since the at birth and early years lines are still affected. Wouldn't it be better to show something like 'probability of living another ten years' (at birth/each of x years old)? I'm no statistician.
- dredmorbius 5y ago
  The age-adjusted concept is "life expectancy at year n". That is precisely equivalent to "additional years of survival at year n plus year n". The alternative notion I'd suggest is "anticipated mortality at year n for those born in year m". The latter would show a typical "bathtub" mortality curve, high initially, then lower, then climbing in late age. Note too that the image I'd posted is literally a representation of survivorship bias: the longer an individual has survived, the longer they're likely to continue to survive.
  - OJFord 5y ago
    > That is precisely equivalent to "additional years of survival at year n plus year n". But that's (minus n) not what I suggested; it's not equivalent to the probability of living another ten years (say). E.g. the life expectancy of five year olds (plus that they are five years old) is not sufficient information to determine how many of them (the probability one) will live to fifteen.
    - dredmorbius 5y ago
      Re-reading, sorry. So ... "probability of surviving another 10 years" is different from life-expectency. It's a variant on mortality, though expressed over a 10 year period rather than a 1 year period. For comparison, see the SSA's actuarial life tables. This gives 1-year mortality (both as percentage and as expected survivors per 100,000 lives) for each year of life from 0 to 119: https://www.ssa.gov/oact/STATS/table4c6.html https://www.ssa.gov/oact/STATS/table4c6.html I'm not aware of a compilation or chart showing changes in actuarial mortality by age over time. There's a good chart of anticipated deaths per year (separately for women and men) in the UK: https://understandinguncertainty.org/why-life-expectancy-misleading-summary-survival https://understandinguncertainty.org/why-life-expectancy-mis... What question are you trying to answer by looking at mortality probability?
      - OJFord 5y ago
        > What question are you trying to answer by looking at mortality probability? Well, starting with the problem of 'life expectancy is biased by infant mortality', that it misleads people into thinking it was rare to live past 30 or whatever: stats like 'life expectancy at 20/30/etc.' are helpful. I was just saying that I don't think 'life expectancy at x' when x is small is helpful, since in the limit we're back to where we started, and until x > end of relatively high risk, it suffers the same bias. Looking at mortality probability would more directly show that early years are at risk, before it settles down and death is unlikely until old age. The old age curves (birth year is still the horizontal axis) would still show the truer change over time, but now so would the infant years. You could even (/might need to) refine it to P{living another year} - P{having died within last year (or before)} or something.

bumbada 5y ago

It does not surprise me at all. People did die very easily from infections, the people that survived were usually really strong. E.g My grandpa never caught a cold, he went to his 90s basically never getting ill. His immune system was so strong. I go to rural areas in Europe where 80 somethings climb the mountain faster than the city kids in their 20s. Some kids from the city have really no balance or physical skills at all, like they could not step over a stone without falling down.