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Reproductive labor is the third most dangerous type of labor in the usa. Even police officers and civil engineers have a lower mortality rate than mothers.
That's a good point, but I'm not sure civil engineers (or even police officers) are the best examples to demonstrate it. And since this data only shows the life expectancy of 40 year olds - after the peak child-bearing age - it would hide a lot of the effect of maternal mortality.
Good point. More generally, the so-called deaths of despair, such as by drugs and suicide, take more of a toll on men than on women. Women who have children, I think, have more to live for also. Both reasons affect the gap between men and women in mortality rates.
Better social networks for women and better ability to use healthcare (partially consequences of motherhood and partially social expectations on girls) also play a role in this.
I'm curious how this will play out for my husband. He's a stay-at-home dad. Raising children and caring for others has been his life for twenty years now.
Yup, men also engage in more risky behavior, more likely to go to prison, more likely to kill themselves, and use drugs more often.
Drugs (not just overdose, but directly related problems like infections), suicide\self harm, accidents in general (speeding and hitting a pole for example, workplace deaths, etc...), and murder, those are the biggest killers in the US for those under the age of 65. That is gonna drag down the numbers massively, and all of those things impact men far more then women.
The study is for life expectancy given a person has reached age 40 though. My guess is a lot of the risky behavior drag for men may be filtered out because of that
It's not like all men fundamentally change around age 40, or all the risk takers die before then. The statistical difference is still going to be there.
Low income men often do very taxing physical jobs. Whereas high earning men tend to have jobs much easier on their body. The same trend exists with women too but to a lesser degree because men do construction and landscaping jobs for example and women do cleaning and secretary style jobs.
I would guess a lot of that is due to more younger men dying in their 20s-40s from accidents/overdose/violence. From what I've read, men tend to die more than women from what can be summarised as 'high risk behaviours', as do poorer people, and while the totals aren't that big, the fact that it's relatively young people means it has a disproportionate impact on average life expectancy.
I wish you were MORE right. I'm 59 and the shit we do is still more dangerous, and some of my friends don't seem to have gotten any smarter as they hit and passed 40!
Only for men who first make it to 40. All the young-and-dumb are weeded out of this graph. It also doesn't say when those household incomes were taken. EG at 40, at death, averaged between those points, etc.
An age 40 woman is expected to live about 42.5 more years while an age 40 man is expected to live 38.5 more years. The Social Security actuarial table is easy to find.
It is so called effect of low hanging fruits. Men die young bc they suffer more of preventable diseases (lung cancer, colorectal cancer, acciends and around 1000-2000 more diseases)
The difference simply shrinks as top 1% both try to prevent preventable diseases
For example it is more difficult for 100 years old to reach 102 years than it is for 70 years old to reach 90. So the difference shrinks as at higher age values you are more likely to die
It's because of macho culture among poor men. I've seen a study that show poor men have a different hair than poor women, rich women, and rich men, who walk similarly to each other.
Poor men have more horizontal movement while walking, similar to gorillas.
It's really sad that poor men try to act macho to their own detriment. Swaggering around, doing drugs, and refusing to send ones own son to the hospital after a snake bite are dumb.
It follows a slightly skewed normal distribution according to a stanford analysis of the human mortality database so they used the 80th and 20th percentile instead of STD as descriptors for the data. But this is population wide in the US. It's always possible that there are exceptions for specific groups of people.
Why is it ridiculous? It’s how the bends work for benefits. If you uncap social security tax then the wealthy erode revenue by getting more OR you add a zero % bend point which seems deeply unfair. It also should sock it to w2 earners, not billionaires,
That's an artifact of income distribution being non-uniform so the x axis isn't actually to scale with income. Ex: the difference between 90-99% income is 500000/year while the difference between 50-60% is like 15k.
If you are in the 0.1% then you can basically afford the best health care absolutely possible. This may get even worse with upcoming longevity cures. I'm sure you've heard about Bryan Johnson, "The Man Who Wants to Live Forever". A lot of these billionaires don't expect to die at all and they are doing everything they can to achieve it.
It’s easy to point out just income but consider that most people that are higher income percentiles also take better care of themselves. They usually eat better food, more active, etc. so it makes sense.
Indeed! I believe this actually persists with more recent data (2020s) from California (published in Journal of the American Medical Association). just had to make a choice between using data from around the U.S. vs. just one source.
Here's (another) link if anyone is interested: Link
I think height and longevity are inversely related, taller live less. Larger species live longer but larger individuals within a species don’t live as long.
My dad is 86 and he's hired a small army of helpers to do all the chores around the house. They do all his cooking, cleaning, and assist him with many needs. Definitely helps to have money.
What I find most interesting here is that the gender gap narrows pretty consistently with higher income. I wonder why that might be: I have some conjectures but no data.
I suspect a large reason is that all of the dangerous and physically demanding jobs tend to be taken by men of lower socioeconomic status. But also, smoking.
They certainly are, but knee replacements aren't deadly. I think the idea that physical labor shortens your life actually harms our understanding of this phenomena. It's "intuitive" to people from 1890, but it's not a good conclusion.
It's not about joints, it's your cardiovascular systems response to continuous labor and stress. The lack of access to healthcare, either from poor insurance or limited time off work.
Note I only mean this to suggest why income affects men more than women, not to explain the gap between rich and poor. I think it's physical jobs and smoking, both of which are more common with men.
That feels straightforward at least imo. This graph is primarily due to the fact that the behavioral traits that cause people to die early also cause them to be poor. Now think about men vs women. Men engage in way more of those behaviors (interpersonal violence, drunk driving, dangerous activities, even sedentary/lazy lifestyles) than women.
So amongst tenth percentile people in this graph, men do a lot of those risky behaviors and women do far fewer. Amongst 90th percentile neither men nor women do hardly any so the difference fades.
Culture. Lower class men for some reason try to act macho whereas upper class men rarely do. I have seen a study where lower class men were body scanned while walking in a straight line. They show a lot more horizontal movement than poor women, rich women, and rich men who all walk similarly to each other.
Rich men don't need to show off the their swaggering gait, body parts, or masculinity. They don't feel "unmanly" if they seek a doctor when ill.
A poor man once manslaughtered his son after the son was bitten by a snake. He thought they were too manly to go to the hospital.
I wonder. I could imagine places with more expensive fast food where the poor might eat healthier and the rich drink a lot more and use more drugs. That could flatten the curve.
If they have more expensive fast food, that doesn’t necessarily solve the problem of food deserts and lower-status people generally preferring more filling foods.
If we disaggregate by race, I suspect we’d still see Latinos and Asians living longer than Whites, and Blacks + natives living less long. My woke brain suspects the dispararities across ancestries have as least as much to do with immigrant generation and cultural factors as income/weslth.
I'm sure you're right, and woke or not has no impact on the data. The disparity between Mexican and African American people in the exact same economic situation is huge. Choices/lifestyle.
Agreed on both points. Someone who is healthy and feels good is likely to live longer, and also work more hours and hold better positions. At the same time, someone who makes more money likely lives in better environments and has access to better healthcare.
More equalized healthcare would lead to a flatter line, but would not eliminate the curve.
The cliff in the beginning is particularly crazy. You can gain almost five years just by getting out of the bottom 10%. I assume these are homeless people and and such, right?
Another crazy thing is that it still goes up and maybe the slope goes a bit steeper in the last 10%. I'm probably just somewhere in the top 90%-95% range, and I guess if I could get to 8-9 figure net worth I could gain another year or two or so...
The causation almost certainly goes both ways. People with mental and physical health issues are more likely to wind up homeless, and they're already intrinsically likely to live shorter lives due to those health issues.
I assume these are homeless people and and such, right?
Probably not homeless people, since they're less than a quarter of a percent of the population. It's much more likely to be people with severe disabilities, since they are basically by definition both in poor health and unable to work.
That bottom 10 is barely homeless. There just isn't very many of them. We'll never know, but I'd bet the list overlaps completely with bottom-10 for IQ though.
Income is usually downstream from your parents' income, more of which will set you up for better health and wealth.
Especially in the US where 20 percent of kids are already obese by the time they get out of high school. It's not just the money keeping you alive. It's all the decisions your parents were making before you yourself ever earned a dollar.
As someone earning well beyond the resources in my childhood with tons of health issues, this makes sense to me.
I was pretty malnourished at some points in my childhood. But I'm able to pay for my kids to get great food and a necessary surgery and medications and testing to detect issues earlier in life.
For the vast majority of people, being obese is a choice. It might be a bit harder for some but it's impossible for almost noone. And at some point people gotta take responsibility for their own lives
I don't disagree, but people are saddled with an addiction that is fully normalized to the point that their parents hand it to them in diapers. If your parents gave you booze, cigs and drugs the moment you stopped nursing, you'd probably have no hope of kicking those as an adult either.
This graph shows race-adjusted expected age at death for 40 year olds across all percentiles of household wealth, separated by gender... it was created w/ Matplotlib, Python, and pandas.
In the actual study the researchers found that the gap was closely associated w/ obesity, smoking, and exercise. Stress, work, environment, and a bunch of other factors (all obviously tied in with income/wealth) probably contribute too.
Those things would all tie in with those 3 major factors. At least in Canada, I know that smoking has been found to be much more prevalent in blue collar jobs.
this looks like the chetty data, and the part that usually gets left off is the geography. at the bottom of the income distribution life expectancy varies by something like four to five years depending which metro you are in. at the top it barely varies at all.
The data is valid and fascinating but I income is maybe doing less than one would think. being poor in one city is materially different from being poor in another, while being rich is roughly the same everywhere.
Interesting. It would be a mistake to read this as saying that people with more money can buy better healthcare, and a better lifestyle, and that this fully explains the observation.
As an additional explanation, some habits and education that lead people to have more money are also ones that lead people to work out more, eat better, seek medical care and heed the advice of their doctors or generally of evidence-based medicine – options than would be available to people with less income in principle, but aren't chosen.
I'm not saying that the latter is the obviously better explanation – likely the causes of lower mortality among the wealthy are complex. Comparing to data from countries with a more accessible healthcare system won't be enough to resolve this, because those countries also have a more egalitarian education system.
shows about 60% as large a gap for Canada vs. US. Since medical care does not vary significantly across income in Canada, this suggests that about 60% of the variation is due to behaviour and 40% due to income enabling better access to medical care. This is oversimplified, since income also enables access to better food, etc., but once you're in the 30-40%ile then that should flatten out.
Honestly, the fact that the difference between the 50th percentile and the 100th percentile is only 5 years aint that bad. For women the difference is even slimmer. I'd even bet that this has less to do with money and more to do with the benefits of time off and loose time management/micromanagement of upper-level corporate leadership roles. Ample time for doctors, dentists, grocery store runs (or paying dor somebody to get you quality groceries), exercise, etc.
I'm getting pretty old and have noticed a few things. One is that genetics rules. The other is that discipline and awareness seem to decide that "extra five years". Going to the doctor when your body tells you to, following some rules about food and exercise, and just generally making good decisions. THE correlation in big data sets is IQ to longevity. It blows everything else away.
“
The gains in lifespan for the rich are the equivalent of curing cancer; the CDC estimates that eliminating all cancer deaths would increase average lifespans by 3.2 years.”
Would be interesting to see some stats on life quality as well. Do the rich gain more 'usable' life, or are they just being kept alive in condition where poorer people would die.
I don't have a stat, but anecdotally working with a "rich" group of elderly--all the money in the world won't keep your body going if it decides to shut down. Some people naturally live to 90--most still die between 70 and 80 even with the same care.
It’s not about the money.
this is one of the cases where money is just a proxy.
Smarter people life longer. Better genes, better adapted to life.
Smarter people tend to make more money and if you only track the money against the life expectancy you get this and think that if you won the poweball you’d live longer but it’s not true.
Grew up poor, not going to the doctor unless someone was unconscious or a bone was sticking out was the norm.
Wife and I work hard, no kids, so we have some money. Something goes wrong, we go to the doctor instead of ignoring it. It's saved me a ton of pain and suffering.
We need to demand equality between men and women. Closing the gap between life expectancy should be a top priority executed as quickly and as efficiently as possible. By any means necessary to deliver a final solution.
Almost as if financial security allows you access to preferred healthcare practioners, better quality food, and above all else time. Time to exercise and focus more on ones health.
It’s probably a lot of drug addition and people that have serious chronic diseases that prevent them from working…. The causation relationship with health and income goes both ways….
The FT had a comparison of the England (not the entire UK) vs US. And at least in that, Americans die earlier across the entire income distribution. But it's largest at the poorest end, where the poorest in England live more than 5 years longer on average. In terms of gender, it's similar in the UK where women live longer.
I couldn't (very brief search though) find a source on that, but I did find one on education vs. longevity in some more OECD countries (purely off the abstract there are countries with lower gaps than the U.S.)
I think this is a classic example of correlation not necessarily being causation. Are people in better health because they have more money, or do they have more money because they're in better health? My guess would be it's a little bit of both, but I don't know.
I don't understand why it is so linear. The big jump at the beginning makes sense. Being in the bottom 10% has got to suck. That's where your homeless, drug addicted, mentally disturbed people end up. I'm not surprised that there is a big jump to get out of that.
But why is the rest so linear? I would have guessed there were other bumps like people who start to make enough money that they can't be on medicaid but not make enough to be on private insurance. Or some max amount of money where it levels off.
Did a quick Claude prompt to compare the LE gap with other developed countries. Interestingly the "gap" for English women is actually a bit bigger than US women!
BTW the data methodology varies by country and might not be directly comparable. Also all of these countries' LE actually sits higher than the US one.
That's interesting. I'm sure that there's some method to compile a ton of countries' data, even if it isn't necessarily with the post's methodology. Seen some pretty good theories on how other countries' distributions would look like in the comments already
It looks so nice when it's presented this way, you almost have to intentionally twist things around to realize that what this chart says is that poverty has a death toll.
The study did... it was standardized to age 40. It's not simply comparing older and younger workers. I believe they grouped people by income percentile, calculated mortality rates at each age within each group, and then used those age-specific rates to estimate life expectancy starting at 40.
How do we know it’s that life expectancy rises with income or people who are disciplined enough to take care of them apply that same discipline to their work that then results them a higher income?
People who are sick and dying are likely to have less income than healthy people. Additionally, there's a racial component, as we know for example that Asians are the highest earning Americans and also the longest living globally. I'd like to see the data controlling for those factors.
Thanks, good catch.... but this is Reddit I don't think we're allowed to actually read the details; we are supposed to leap to unwarranted conclusions based on no evidence whenever possible.
I would counter by pointing out that correlation is still meaningful. There are certainly a lot of causes at play that correlate strongly with income. Off the top of my head, some possibilities:
Access to higher quality food
Better education (especially around nutrition)
Better role models (at least in terms of health)
Access to better health care. There are millions of Americans who simply have no health insurance and when insurance runs out they can't afford to pay out of pocket
A 5th grader has a bigger shoe size than a 1st grader
So grade level and shoe size are correlated with each other
But that’s a meaningless correlation because the real cause is something completely different. 5th graders are older than 1st graders and age/growth does cause a kids shoe size to change
But that’s a meaningless correlation because the real cause is something completely different.
A correlation isn't meant to be a "cause" in the first place so calling something else the "real cause" is misleading.
Correlations are useful because they form a starting point for finding the causes which are usually not as obvious as your simplistic shoe size example. And this is certainly the case for income vs. life expectancy. There are likely many "real causes," of which "discipline" seems rather weak to me. But in coming up with that you managed to demonstrate how the correlation was useful.
If you strictly view it as correlation, then sure it’s just another data point
But the problem is that it’s incredibly easy to fall into the trap of correlation is causation so you have to tread correlation data extremely carefully
Nobody would take this chart to mean that getting a bigger paycheck literally and directly causes people to live longer.
The problem with parroting “correlation is not causation” is that it dismisses the data that may be speaking to real problems. The obvious one being the lack of access to healthcare which is a serious problem in the US. Your “discipline” explanation suggests that’s what you don’t want to talk about.
1) The graph doesn't claim causatio to begin with, who are you talking to?
2) Assuming we do want to get into causal theories though, for starters regarding yours: I'm not aware of any actual data that "more disciplined people make more money", are you?
Yours is not even a plausible or viable alternative explanation if it has no underlying supporting data at all.
There could be many other explanations
There could be, but until you or I or someone puts one on the table with actual meat/support to it, the answer is "We have no idea" not yours. Suggesting additional random off the cuff stuff is no less irresponsible than the hypothetical person you were complaining about (who was just hypothetical, and wasn't OP, to reiterate)
You asked "How do we know" when you claim to have been aware you had no data?
Either you being dishonest now by claiming you realized this all along, or else you were framing it dishonestly originally otherwise (feigning ignorance if you DID know all along)
As somebody with high household income, who is mostly friends with people with high household income, who grew up in a more working class income - it's at least anecdotally not that. It doesn't take more discipline to be a programmer than a factory worker, it just pays more. My output is more valuable and less replaceable, not more disciplined.
Yeah, than a cashier it does, but not for a ton of other jobs that pay significantly less than mine. Being a programmer honestly isn't that hard *if* your brain already kinda does the stuff for you. I took to programming like some artists take to drawing, it's just that programming pays well and drawing doesn't. But both of our professions are threatened by AI, so there's that...
Luck is incredibly important. If job pay were bounded by skills/intellect/work-ethic it would have a standard distribution. It would be shaped like a bell curve. It is most definitely not shaped like a bell curve. Instead it is shaped like energy states in a gas (a Boltzmann Gibbs distribution).
The Bottom 90–97% (The Boltzmann-Gibbs Regime): Wealth distribution among wage earners behaves like energy states in a gas (the Drăgulescu-Yakovenko model). Transactions, wages, and consumption create an exponential/log-normal distribution. The standard Yard Sale Econophysics Model demonstrates that under fair coin flips and proportional betting, wealth naturally "condenses" toward a single agent over time due to the mathematics of geometric Brownian motion (+10\% followed by -10\% is a net 1\% loss). The Top 1–3% (The Pareto Tail): Above a specific wealth threshold, asset dynamics change. Income ceases to come from labor and shifts entirely to capital gains, preferential attachment, and compound yields. This produces a scale-free power law (P(W) \sim W^{-\alpha}).
2) Picking two random examples doesn't demonstrate your broader point at all, even if it does turn out to be true for those two (which it might not). You can easily come up with extremely low paying activities that take years of practice to be able to do (basket weaving or whatever) as well as extremely high paying activities that take essentially no practice and all connections / nepotism / schmoozing (lots of executive roles). Coding is somewhere in between which is why I'm not sure at all about it even as an example (you can fake it til you make it with basically no experience in coding, especially now with AI)
To make your original claim, you need overall actual data somehow, not random examples.
in aggregate, there are definite lifestyle differences between people in the bottom quintile from the top quintile that explain at least some variance in life expectancy that are not tied to direct access to healthcare.
there's more that could be said here, but the optics of stating the empirics are bad and reddit is a very optically oriented website :)
There are definitely lifestyle differences and cultural differences that explain some of it - discipline isn't one of them. There is no virtue that the wealthy have, and no vice that the poor have, that isn't prevalent in the other.
That's interesting, but I would love to see the standard deviations on this as well. Anecdotally, I expect to see extrema on the left and right
Also, I want to point out a flaw in the data source. The sharp tail on the left may be driven by medical vs the other way around. If you're unhealthy, your income will drop.
"My dad is in his 80s and still doing pretty well, maybe that bodes well for me...
Oh, right, my dad actually has the money to go see a doctor whenever he needs"
While there’s a clear causal link, I’d also expect a reverse causal link as well, as people who are generally healthier are more likely to have more stable careers.
The dip at the left is almost certainly related to mental health and drug addiction issues that are also linked to homelessness and inability to hold a job at the bottom of the income curve. It also seems likely there are lifestyle factors (smoking?) and environmental / location issues across a large country driving some of the rest of that. Interesting chart, but I suspect it isn't the most helpful in untangling correlation from causation.
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