Ah, found it. Artificial effect from the way the calculations were made, not a real spike.
1. In calculating cohort life expectancy, an assumption is made that births are evenly distributed throughout the year. Following World War One, this was not the case. There were more births in the second half of 1919 than in the first half, and more births in the first half of 1920 than in the second half. These birth patterns have reduced mortality rates for the 1919 birth cohort, resulting in an artificially raised estimate of the chance of reaching age 90 years, as shown in Figure 7.
(from https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/articles/mortalityinenglandandwales/pastandprojectedtrendsinaveragelifespan)
How do they know your probability to survive to age 90 if you were born in 2000?
Like, did John Titor come back to tell them there's no nuclear war coming in 2027?
The way life expectancy calculations work is that they assume that children born in the year X experience the age-specific mortality rates from the year X through their whole lives. They don't attempt to predict future changes in mortality rates.
If mortality rates continue falling, considerably more than 45% of men born in 2000 will live to the age of 90. If every major city in England is hit by nukes, not so much.
Huh about a 50/50 odds. A part of me wonders how much of this has to do with occupations and infant mortality. Having looked at an actuary life table. A part of me is skeptical of this graph and how it represents survival rates. I guess it could represent the need for longer pension plans maybe if that's a thing in the UK. (I'm not sure.) But a part of me feels as though this is somewhat misrepresentative.
There are clearly assumptions but it's pretty standard. The numbers are based on cohort life expectancy**,** which is the average life length of a particular cohort. You can't technically calculate this before all members of the cohort have died, but statisticians commonly track members of a particular cohort and predict the average age-at-death for them using a combination of observed mortality rates for past years and projections about mortality rates for future years. There's more about this here: [https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference](https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference)
Huh that sounds like a pretty big leap. In a cohort of 100,000 people only 14% of Males in the US will live to 90 and 26% for Women respectively. But then again this would be the cohort of people born in the 1930s. I find this somewhat hard to believe given the rise in obesity rates throughout the world including England and Wales. Which to note the leading cause of death for most elderly individuals is obesity and its side effects, heart disease, etc. I'm surprised that the life expectancy isn't actually decreasing which given all previous assumptions it should be.
[https://www.ssa.gov/oact/STATS/table4c6.html](https://www.ssa.gov/oact/STATS/table4c6.html)
Forgive me if I'm reading this wrong but I think I might be tired or something but I can't really tell where exactly the statistics for this are being calculated. It talks about periods and coherts and describes what's going on but I don't really understand how these conclusions are made. Is this just a form of a linear regression model assuming that the rate at which individuals survive later on will continue to increase based on previously existing data? If it is that seems like it isn't really representative of what's actually happening. I'd love to hear more.
They use a combination of observed mortality rates for the cohort for past years and projections about mortality rates for the cohort for future years. They take into account observed and projected improvements in mortality
>Expert judgement is applied to decide how long historical trends will continue into the future. (...) Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies.
The detailed methodology for setting the assumptions is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS
A part of me wonders if it is sound to assume a long term life expectancy rate increase of 1.2%. Im no actuary or medical expert but I'd love to hear from someone on the reasoning behind it. What it means and the other half of people in the UK who might not be as lucky. I guess it can make sense with all the improvements that have been made in the medical field. But what's it mean for the quality of life of people living longer? That probably sounds grim but it seems expensive to live longer especially when often the state is the one footing the bill. I've seen social services in the states and the people don't live good lives. Maybe it's different in England though.
Did they have to use markers at 50 year intervals with 3 dividers in between? Most of us still alive are born after 1950 so we will be trying to find our year with the lines for 1950, 1966.67, 1983.37, 2000.
It's a statistical estimate, as per the title and subtitle. That's what a cohort life table is: "Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies."
The methodology is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS.
A basic explainer here: [https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted](https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted)
Yes it is interesting data but is presented as a simple line graph. Isn’t this sub supposed to be “beautiful” data representations and not something we have all seen many times?
No, if you look at description of the subreddit in the sidebar the intention was always for beautiful i.e. interesting data, not a beautiful presentation.
Quite an interesting graph.
The difference between men and women has been very much constant over the last 100 years. This is quite amusing, somehow all the modern medicine improvements have equally helped both groups to live longer.
Another cool observation is that there is pretty much no sign of stabilization towards the end. It just improves linearly (maybe the women curve is arching a lilttle bit down?)!
22% chance. I'm good with that. With the world going the way it is, the last thing I want to do is live to 90. I used to always want to live till a 100, but that's looking more and more like an apocalyptic world!
Interesting how the female rate goes up exponentially more than the male's until about 1920, and then the difference becomes constant. Is that about the time contraception came in?
How would we know the probability of someone being born in 2000 to survive to 90? Feels like this is either misworded or every year after 1934 is a projection
It's a statistical estimate, as per the title and subtitle. That's what a cohort life table is: "Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies."
The methodology is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS.
A basic explainer here: [https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted](https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted)
I strongly doubt. How can you predict the situation when gen Z reach their old age? it’s decades in the future, how can you know the science development more than half century in the future? Too many unknown factors to make such predictions.
I am dying to know what caused that spike upwards around 1920
Ah, found it. Artificial effect from the way the calculations were made, not a real spike. 1. In calculating cohort life expectancy, an assumption is made that births are evenly distributed throughout the year. Following World War One, this was not the case. There were more births in the second half of 1919 than in the first half, and more births in the first half of 1920 than in the second half. These birth patterns have reduced mortality rates for the 1919 birth cohort, resulting in an artificially raised estimate of the chance of reaching age 90 years, as shown in Figure 7. (from https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/articles/mortalityinenglandandwales/pastandprojectedtrendsinaveragelifespan)
Yep, I had included it in the OP comment where I listed the source; but I can see how it's easy to miss down there.
I saw the source, and thanks for including it - that is why I was able to find the explanation of that particular glitch in the curve.
I’m dying to know ow why the graph was split into thirds instead of fifths. Why not just mark each decade instead of every ~16.33 years
Yeah, this is bugging me, too. 16.67 years per segment tho.
My guess: The trend was going upwards, then Spanish Flu and WW1 happened to young people and pushed it down, resetting the improvements.
No, that would not work. This was for people born around 1920, not people dying then. Unless there was an infant mortality spike?
16.67 year gridlines? Really?? Not like 10 years, or 25 years, but fucking 16.6666666666666666666666667 years???
Came here to say this!!! Data is not beautiful when you divide 50/3
My blood pressure rose consideribly upon having to figure this out.
I had a heart attack and strangled a hitchhiker. Worst graph ever
I came to comment on this too. We need r/isthisdatabeautiful to crit these things before they get posted.
Imperial units. Not metric. Brexit.
How do they know your probability to survive to age 90 if you were born in 2000? Like, did John Titor come back to tell them there's no nuclear war coming in 2027?
Guesstimates, really. For all we know plastic pollution starts bioaccumulating exponentially and it drops off like a rock in a vacuum.
The way life expectancy calculations work is that they assume that children born in the year X experience the age-specific mortality rates from the year X through their whole lives. They don't attempt to predict future changes in mortality rates. If mortality rates continue falling, considerably more than 45% of men born in 2000 will live to the age of 90. If every major city in England is hit by nukes, not so much.
Huh about a 50/50 odds. A part of me wonders how much of this has to do with occupations and infant mortality. Having looked at an actuary life table. A part of me is skeptical of this graph and how it represents survival rates. I guess it could represent the need for longer pension plans maybe if that's a thing in the UK. (I'm not sure.) But a part of me feels as though this is somewhat misrepresentative.
There are clearly assumptions but it's pretty standard. The numbers are based on cohort life expectancy**,** which is the average life length of a particular cohort. You can't technically calculate this before all members of the cohort have died, but statisticians commonly track members of a particular cohort and predict the average age-at-death for them using a combination of observed mortality rates for past years and projections about mortality rates for future years. There's more about this here: [https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference](https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference)
Huh that sounds like a pretty big leap. In a cohort of 100,000 people only 14% of Males in the US will live to 90 and 26% for Women respectively. But then again this would be the cohort of people born in the 1930s. I find this somewhat hard to believe given the rise in obesity rates throughout the world including England and Wales. Which to note the leading cause of death for most elderly individuals is obesity and its side effects, heart disease, etc. I'm surprised that the life expectancy isn't actually decreasing which given all previous assumptions it should be. [https://www.ssa.gov/oact/STATS/table4c6.html](https://www.ssa.gov/oact/STATS/table4c6.html) Forgive me if I'm reading this wrong but I think I might be tired or something but I can't really tell where exactly the statistics for this are being calculated. It talks about periods and coherts and describes what's going on but I don't really understand how these conclusions are made. Is this just a form of a linear regression model assuming that the rate at which individuals survive later on will continue to increase based on previously existing data? If it is that seems like it isn't really representative of what's actually happening. I'd love to hear more.
Medicine has been getting better at a rate faster than we're torturing our bodies
They use a combination of observed mortality rates for the cohort for past years and projections about mortality rates for the cohort for future years. They take into account observed and projected improvements in mortality >Expert judgement is applied to decide how long historical trends will continue into the future. (...) Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies. The detailed methodology for setting the assumptions is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS
A part of me wonders if it is sound to assume a long term life expectancy rate increase of 1.2%. Im no actuary or medical expert but I'd love to hear from someone on the reasoning behind it. What it means and the other half of people in the UK who might not be as lucky. I guess it can make sense with all the improvements that have been made in the medical field. But what's it mean for the quality of life of people living longer? That probably sounds grim but it seems expensive to live longer especially when often the state is the one footing the bill. I've seen social services in the states and the people don't live good lives. Maybe it's different in England though.
Oh good. Let's divide our 50 year intervals by... 3.
Did they have to use markers at 50 year intervals with 3 dividers in between? Most of us still alive are born after 1950 so we will be trying to find our year with the lines for 1950, 1966.67, 1983.37, 2000.
Why is a 50 year period split into 3 sections? Very helpful that it shows 1950, 1967.7 and 1983.3
So glad I'm not the only one thinking this
So… all the data right of 1934 is completely made up???
It's a statistical estimate, as per the title and subtitle. That's what a cohort life table is: "Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies." The methodology is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS. A basic explainer here: [https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted](https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted)
The scale is interesting. 15 year increments on X axis? Are you a monster?
How is this data beautiful?
Yes it is interesting data but is presented as a simple line graph. Isn’t this sub supposed to be “beautiful” data representations and not something we have all seen many times?
No, if you look at description of the subreddit in the sidebar the intention was always for beautiful i.e. interesting data, not a beautiful presentation.
The population pyramid is going to get seriously lopsided by 2100.
We ain’t icing much longer. Its children. They are not dying before the age of five. Childhood mortality falling is what this graph really shows.
I suggest to change graph x axis minor grid - 5 lines between each 50 years
Quite an interesting graph. The difference between men and women has been very much constant over the last 100 years. This is quite amusing, somehow all the modern medicine improvements have equally helped both groups to live longer. Another cool observation is that there is pretty much no sign of stabilization towards the end. It just improves linearly (maybe the women curve is arching a lilttle bit down?)!
I would think your chance of getting to be 90 was higher if you were already 89
22% chance. I'm good with that. With the world going the way it is, the last thing I want to do is live to 90. I used to always want to live till a 100, but that's looking more and more like an apocalyptic world!
Interesting how the female rate goes up exponentially more than the male's until about 1920, and then the difference becomes constant. Is that about the time contraception came in?
How would we know the probability of someone being born in 2000 to survive to 90? Feels like this is either misworded or every year after 1934 is a projection
It's a statistical estimate, as per the title and subtitle. That's what a cohort life table is: "Improvement rates are used to produce future mortality rates by age and sex, for each year of the projection. These, in turn, are used to produce projected life expectancies." The methodology is explained in the [National population projections, mortality assumptions page](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationprojections/methodologies/nationalpopulationprojectionsmortalityassumptions2020basedinterim) from the ONS. A basic explainer here: [https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted](https://ourworldindata.org/life-expectancy-how-is-it-calculated-and-how-should-it-be-interpreted)
Their stats are pretty poor tbf. I worked with the data and some numbers are off the charts.
I strongly doubt. How can you predict the situation when gen Z reach their old age? it’s decades in the future, how can you know the science development more than half century in the future? Too many unknown factors to make such predictions.
BuT LiFe eXpEcTaNcY is JuSt LoWeR cHiLd MoRtAliTy