Coffee drinking linked to lower mortality risk, new study finds
nytimes.com
nytimes.com
And before someone asks "But what if it's .. instead?": Yes, they controlled for lots of things:
> lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors
The patient data is from UK Biobank, which has quite a bit about each participant. While they can't control for everything (like factors that aren't documented), they can control for a lot - probably including whatever possible confounder someone jumps to.
Although it's still subject to the limitations of an observational study, 171,616 people is a big cohort, mortality is clearly measurable, and the observed effect is really large. It's worth paying attention to.
> Scientists don’t know exactly what makes coffee so beneficial, Dr. Goldberg said, but the answer may lie in its antioxidant properties, which can prevent or delay cell damage. Coffee beans contain high amounts of antioxidants, said Beth Czerwony, a registered dietitian at the Cleveland Clinic’s Center for Human Nutrition in Ohio, which can help break down free radicals that cause damage to cells. Over time, a buildup of free radicals can increase inflammation in the body, which can cause plaque formation related to heart disease, she said, so dietitians recommend consuming foods and beverages that are rich in antioxidants.
> There’s also the possibility that coffee drinkers tend to make healthier choices in general. They might opt for a cold brew or a cup of drip coffee instead of a less healthy source of caffeine, like an energy drink or soda, Dr. Goldberg added. “If you’re pounding Mountain Dew or Coca-Cola or Red Bull or all these other drinks, they have tons more sugar, all the artificial stuff — versus coffee, which is a generally unprocessed food.”
(Side note: if someone else read this and started drinking coffee because of it, they'd probably be replacing an existing beverage choice as well. IOW, even if substitution effect was the cause or a contributing factor, people acting on the conclusions may still see the effect – and certainly would at public-health scale.)
Specifically:
> As result, in the data, sugar starts to look…a lot worse for you over time. In the earliest period of the data there is no observed correlation between the sugar measure and BMI (see below) but by the latest period, it’s hugely correlated. The “sugar-makes-you-fat” story only shows up in the last few years, coincidentally during the period when sugar is less consumed by individuals who exercise, do not smoke and are better educated.
None of this is conclusive to the point where no further study is necessary, but I’m guessing this study will make some institutions think/rethink their guidance on coffee consumption.
What makes you say that about this paper specifically? Certainly in general there are career incentives for authors to publish papers which are not very conclusive, and we know that relatively useless observational studies do get published.
The standard shouldn’t be “we did the best we can” for the sake of publishing. It should be “is what we’re doing useful”.
> I’m guessing this study will make some institutions think/rethink their guidance on coffee consumption.
This is the major issue with all these kinds of studies. The absolute last thing they should be doing is influencing public policy. Data that’s more or less garbage but you treat it like it’s solid because it’s “science” is harmful.
We need to have a way to figure out what to tell people to do, and we're doing that, whether you like it or not, with imperfect information.
Also not for nothing, this data is not "more or less garbage". This is about as good as we can do in science right now, and honestly your tone is pretty terrible. It sounds like you want religious levels of certainty and you feel you deserve that.
Science doesn't get much more certain than this (and this is far from very certain in any sense), there is no "better" way to do things that the researchers just lazily didn't follow here, and your suggesting that such is the case is ignorant and selfish. You should feel bad for what you've written here.
A well designed RCT isn’t much more certain than this?
Observational studies are hardly the peak for scientific knowledge.
Nearly all observational studies that you read draw their conclusions from regression analysis (or something, such as a ANOVA, which is a can be trivially implemented as regression analysis).
This just means that a linear model such as this is used:
outcome ~ b_coffee * drinks_coffee + b_income_level * income_level ....
Then, unlike in machine learning, researchers look at the value of the coefficients and most importantly the confidence in the coefficient value. In a simplified example:
years_of_life ~ b_coffee * drinks_coffee + b_intercept
Where b_intercept will represent the life expectancy in general. Then b_coffee (since drinks coffee is binary here) will represent whether or not coffee adds to your years of life. If it's negative it means drinking coffee reduces your life expectancy and if it's positive it means it increases it. In statistics we also look at how certain we are in b_coffee in terms of standard error and p-values. For example if b_coffee is say 5, meaning it adds 5 years to your life, but our standard error in this estimate is 4 (ie 95% chance that the real impact is between -3 and 13 years). In this case the p-value for this coefficient will be higher than necessary to conclude "statistical significance".
But suppose the standard error is very small, like 1 year, where we are virtually certain that coffee does improve life expectancy. To control for say, college education, we just add that coefficient to our model.
years_of_life ~ b_coffee * drinks_coffee + b_college + has_degree + b_intercept
The magic of regression analysis is that if, in fact, people that go to college life longer and people that go to college also drink more coffee, the our coefficient for b_coffee will change in this new model to reflect this. If for example it were to become negative now (with a low p-value) what we would conclude from this model is that coffee is in fact bad for you, and college is good for you and it just happens that a lot of people who go to college also drink coffee.
Just as even the most advanced AI is often just a lot of matrix multiplication with non-linear transforms, the vast majority of observational studies are drawing conclusion using linear models. In practice, as you add more variables to your model, you tend to get a lot of tricky to interpret results. Regression analysis is a remarkably powerful tool, but it is important to remember when you see publications this is what is really happening and there is a lot of room for subtlety when interpreting these models.
As a simple question, what about people who have weak stomachs or hearts? My mother doesn't drink coffee because it "makes her heart beat too hard". How, with no actual medical data for "coffee makes my heart beat hard", do you control for that? Is that something to control for?
This is the "caffeine and healthy pregnancy" problem. We know women who consume less than ~200mg of caffeine tend to have healthier pregnancies.. but if you can drink 5+ cups of coffee while pregnant and not get overtaken with nausea, that might indicate something is already wrong.
It seems to me that this problem is totally fatal for large-scale epidemiological studies with many factors, of which many are sure to have nonlinear effects.
That being said I agree with you entirely and we shouldn’t shy away from hard problems because of this.
Don't forget that the "fruit" for scientists is fame, not the truth. Anything that can get headlines and conference talks is a good thing, regardless of whether or not the methodology even makes sense.
This is a pretty shocking thing to say. It's not true whatsoever for the field of physics. Is there a particular field or a particular experience you're reacting to? I think I'm overreacting to how general your statement is.
https://sites.cs.ucsb.edu/~ravenben/cargocult.html
It's a 5 minute read. Arguably the 5 most intellectually productive minutes we can spend. (Well at least for me, anyway).
Now that ESP, paranormal, telekinesis research is thoroughly dead, (exposed by magicians like James Randi?), psychology still remains mired in it all. To the credit of a minority in that field they're having a go at getting it back to science and I wish them all the luck in the world. https://en.wikipedia.org/wiki/Replication_crisis
My understanding is that for vast amounts of "What food is healthy, what kills you." Research, epidemiological studies is all we have. They're obviously limited, easy to get wrong, easy to fool yourself (and you're the easiest person to fool!) The supply of identical twins, who are willing to commit to life long diet differences with rigor and make all the same choices outside of the study is, well, kinda low.
The statistics being used for these things is still under active development and being improved. Can it ever be done properly? Well I guess so. I think we're pretty clear on the smoking, cancer, heart disease, stroke link nowadays, right? And those studies have to have been similar.
It's interesting that scientists have to raise funding, publish or perish and so on to even have a career at all making them part P.T. Barnum. Fenymann, for all he didn't need to do that because of the different era, reflected "glory" from Los Alamos etc. really was capable of putting P.T. Barnum to shame while at the same time being the most devout adherent to and proselytiser of scientific principle & purity. So good and so lucky he could keep his hands clean?
Is there no academic misconduct in physics nowadays? None? I'd believe you if you told me so & why.
Perhaps I'm slow, but that was every bit of a 15 minute read for me.
its leading to junk science, and large swaths of people are losing faith in what we are labeling as science.
---
Right. IMO anyone criticizing observational studies on humans needs to overcome the idea that it's hard to do controlled studies on humans, and when it is possible (e.g. vaccine trials), the studies don't last very long, because you can't really control peoples lives that long and there tends to be significant attrition over time.
Theoretically, chimps would be the next best thing, but experimenting on chimps is ethically questionable as well, and they also live a long time. That's great for chimps, but not so great for biological studies where you want to observe the effects of an intervention over an entire lifecycle. Monkeys would be the next best thing after chimps, but experimenting on monkeys has the same issues as with chimps.
Among common experimental animals, that basically leaves dogs and rodents. Dogs are relatively large and hard to deal with compared to rodents, and their relatively long lives (compared to rodents) makes them difficult to selectively breed. Even if we modified the embryos using CRISPR or something to include genes that were of interest, a dog's gestation period is about 3 months whereas for rats and mice it's about 3 weeks. Likewise, Beagles (one of the more common experimentally used dogs due in part to their relatively small size and friendly disposition) live for about 12-15 years, whereas wild-derived mice and rats both live around 2-4 years in captivity. The general public is also much less concerned when rodents get euthanized as part of an experiment than when dogs do. Whether that should be the case or not is somewhat debatable, but, nonetheless it is. It's all a big trade off between fidelity and logistics, but shouldn't an audience like HN's consisting of a disproportionate number of software people compared to the general public actually appreciate that? ;)
So, rats and mice a really the only reasonable choice if you need to experiment on a live mammal in less time than it takes to actually get a PhD. But, then that triggers the chorus of "in mice" replies we see to pretty much every biomedical article on preclinical research here. And, there are undoubtedly interventions that would work on humans that don't work on mice, just as there are many interventions that work on mice but don't transfer to humans. We miss out on those, but the ones that do make it through rodent trials and into humans got there by a process that weeds out a lot of things that couldn't possibly work, which ultimately means humans benefit sooner by starting with mice than if we just used people in the first place.
Unhealthy people start drinking coffee in the hopes it's some kind of magic elixir that can erase their unhealthy choices.
Check again: "People who drink coffee don't live longer."
Unhealthy people try to find some other magical cure from a new observational study, maybe of eggs, this time.
I don't really know anyone personally who doesn't know what they're doing bad to themselves. When I order a salad and my buddy orders a butter seared steak and fully loaded baked potato (after he ate a whole pack of sour patch kids at the movie), and I don't say anything, but he says "You've got to enjoy your life!" I know he knows. Because I've done that, and I knew. I'm no Sporty Spice but if more salad than steak, and more water/tea than soda/beer, means I don't have to go to a regular dialysis appointment I'd consider that a tick under "enjoying life," personally. But if I could eat the steak and potato and candy and just offset it with more coffee - by god, that's the ticket.
Not to nitpick what you're saying, anyone on HN who orders a salad is probably thinking about what's in it, but it's worth pointing out that the category is so broad that it can be deceptive for anyone who doesn't read the fine print. I read an article the other day complaining that a 324 cal Subway 6-inch didn't taste as good and wasn't as filling as a 685 cal Sweetgreen salad bowl.
I never thought about something like that being considered salad... but maybe I'm the weird one? Also, whoever orders that knows that this is not healthy right?
I'm going to copy a comment I made regarding Type 1 Diabetes on another post about a year ago. It's relevant because what you're saying, though very true, comes down to immediate effort versus delayed impact. I think people who fail to control their diabetes largely do so for the same reason people fail to control their diets...
> I am going to make a weird, but IMHO apt, comparison to Type 1 Diabetes. T1D is an attritional disease caused by the pancreas's inability to produce enough/any insulin and the list of complications is long and deadly. As someone who has lived with the disease for decades what makes the disease particularly insidious is immediate effort versus delayed impact. The disease affects everything...every single part of every single day. Eating, sleeping, exercising, traveling, finances...everything. And to be on top of everything is extremely effortful. However the impact of not taking enough insulin, of not checking blood sugars frequently enough, or living with high blood sugars, is delayed. Today's transgressions may not be punished for decades. It is no shock to read about poor therapy adherence when the effort is immediate (and constant) and the effect is delayed (and therefore hypothetical). I see the same issue - immediate and constant effort coupled with long term hypothetical effect - with protecting one's privacy. Obviously one should do the right thing. But many won't.
Coffee is a strange one though. I think I've only seen 'coffee is good' in recent years, but I'm wary because I don't expect 'coffee is bad' studies to get the same sort of publicity.
Just avoid processed foods and exercise more.
But pop science news interprets it as a causation.
...helpful...
On Reddit's /r/science board, there's a base rule that "criticism of published work should assume basic competence of the researchers and reviewers".
I think it would benefit HN if we all made the same assumption.
Since most studies/publications cant be replicated, I'd say basic competence is not warranted.
Put another way, just because Cosmo publishes an article doesn't mean it's true - but Cosmo does also publish true articles.
Plenty of studies are great and move our understanding forward. More studies answer a very narrow - but important - question. Some studies are just inconclusive, but have value too.
You should read studies. You should evaluate the quality of studies as part of integrating them and their conclusions. At the same time just because something was "a study" or got published doesn't make it true or good or useful, anymore than being written in blue ink makes something truthful.
The value of science is that it does not require faith.
If someone were advocating making policy decisions based on astrological charts, I would read and comment in such threads despite not trusting astrology on a fundamental level.
I personally would go quite as far as to say that purely observational studies have as much predictive value as astrology, but "observational studies are as reliable as astrology" is a better first-order approximation of my opinions than "observational studies are as reliable as large-n randomized controlled trials".
With N different control variables to either include or ignore, that's 2^N possible sets of control variables. Odds are decent at least one of those regressions has a large effect size for coffee.
I would trust this sort of research more if instead of publishing a particular set of control variables obtained by an unspecified method, the researchers chose 100 of those 2^N possible sets of control variables at random, then published the average effect size from the 100 resulting regressions. Ideally they would make the code to reproduce this average effect size publicly available, so anyone could easily replicate using another 100 randomly generated regressions.
Honestly - I do. Basic competence in creating a study would definitely include identifying confounding factors that are directly relevant to the study being conducted. It's a basic part of the scientific method - both in creating the hypothesis and creating a test against that hypothesis.
That said, if you are going to criticize something based on the idea "this result doesn't agree with my preconcieved notions so I'm going to say that their sample size was too small, the effect size was too small, or they made some sort of incorrect calculation, and conclude the paper can't be trusted", you owe it to yourself to read the paper carefully enough that you can make the determination they made a major error.
Unlike most people, I read the conclusion, then the methods section. For most papers I can't get enough from the methods section to conclude that I trust the authors to make their claim, because most methods sections are missing major details on how the corrections/controls were made.
I believe the latter, and the rule I mentioned also leads to that assumption. Otherwise, why read the studies at all? But that's not what people here do.
> missing major details on how the corrections/controls were made
I also make an assumption that some corrections/controls are so obvious within their field of study that they aren't worth documenting - that it's only "average joe" readers who assume they aren't being done.
It is, in a way, akin to asking why programmers didn't document how their JWT is secured.
BTW I've definitely gone into code reviews assuming the programmer lacks basic competence and been right. Other times, I've had to rollback other people's code (or stop a rollout) because an ostensibly genius programmer who made a change (and got a review from a starry-eyed junior) wasn't using their basic competence or testing their change at all.
The former is perfectly fine and encouraged. The latter is incredibly rude and derails discussions.
Relatedly, you took the rule incredibly literally just so you could critize a strawman...
> Unlike most people, I...
Yes, yes, you a very smart and everyone else, in particular me, is an idiot...
On the one hand I get what they're saying about their own study design, on the other hand, it might be good to get more info about lifestyle vs lifestyle.
I'm no experiment designer but I fail to see how you can control for variables when the field of the experiment is "life". There are an unlimited number of variables, wouldn't you find tonnes of meaningless correlations ?
The set of variables is unlimited and the focus of the study is so precise that I have a real hard time to understand how meaningful these results can be.
> there may be other lifestyle factors contributing to that lower mortality risk among people who drink coffee, like a healthy diet or a consistent exercise routine.
Yeah no shit. Or like getting 8+ hours of sleep, or winning the genetic lottery, or working at a desk instead of on a construction zone, &c.
If it's all self reported it's kind of garbage to begin with, I know people who think they eat healthy diets, they don't
Now if you'll excuse me I need to go drink my coffee and glass of red wine while doing yoga/meditation, then eating Mediterranean meals during my intermittent fasting period while making more that $75K per year, sleeping 8 hours a day and living in a "blue zone".
Well, I guess you're more of the live fast die young crowd and shouldn't expect to be here much longer, not without copious amounts of carrot juice, chili peppers and olive oil.
This should be a criteria for posting studies in general - large cohort, controls for every known factor, clearly measurable outcome like all-cause mortality, and large observed effect.
"..self-reported..."
which always raises questions.
Also, was this an actual study. Or simply a statistical pattern detected in UK Biobank members?
Note: Not trolling, just looking for full context.
If it's an observational study, they didn't control for anything; they adjusted for things.
Having said that, coffee is great.
While it’s closer to speculation than science, past discussion of health benefits from coffee focused on antioxidants. Coffee, green and black tea, and cocoa have relatively high antioxidant content[1], particularly after adjusting for quantity consumed.
I haven’t seen any breakdowns of how the average person ingests antioxidants, but it’s not like everyone eats 3 oz of blueberries a day :-) Beverages might be a major source.
Again, this is pretty close to speculation, but it’s not nothing.
[1]: https://pubmed.ncbi.nlm.nih.gov/11453788/ (a quick citation - IANA expert)
One paper, there are many:
I tend to think along the lines of `rsync: https://news.ycombinator.com/item?id=31595857
But these people were mostly healthy.
I'm sure that coffee doesn't work better compared to medicine if you are diseased,
Even more impressive result, exercise reduces all cause mortality by 40%:
> Using a large nationally representative sample of US adults, we found that those who engaged in both aerobic and muscle strengthening activities consistent with the recommended 2018 physical activity guidelines for Americans showed a reduced risk of all cause mortality (40% reduction).
https://www.bmj.com/content/370/bmj.m2031
> instantly prolong human lifespan dramatically
But that doesn't follow. It's conditional. More accurate follow would be "instantly prolong human lifespan dramatically AS LONG AS YOU DON'T GET DISEASED"
Example: having a fire extinguisher in your house decreases risk of losing your house in a fire by 30% before a fire. But if your house is on fire I bet it's much much lower. There are two different populations, two different distributions.
> Your estimate will be wrong for a silly, almost tautological reason: if you can only detect large effects, then any effect you detect will be large. If you keep looking for an effect, over and over again, until finally one study gets lucky and sees it, that study will almost necessarily give a wild overestimate of the effect size.
[1]: https://jaydaigle.net/blog/replication-crisis-math/, https://news.ycombinator.com/item?id=30181696
As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
Seems to me that a likely reason for a large effect size is both a causal effect of drinking coffee and confounding, added together.
As an analogy, suppose you and I are talking about a Hollywood star who has made a lot of money. I say: "The star is probably a good actor." You say: "I would just encourage people to think about this wealth level and ask whether it's plausible. The star is probably just physically attractive." Of course, the wealthiest Hollywood stars tend to be both good actors and physically attractive.
Why is a large effect size more plausible for some unspecified confounder than it is for coffee? I think some research suggests coffee induces benefits akin to caloric restriction (autophagy) among other good things: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111762/ Should we really have a prior that an unspecified confounder can have such a large effect size? How common is that?
BTW, this appears to be the money quote from the paper https://www.acpjournals.org/doi/epdf/10.7326/M21-2977
>Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors, with respective hazard ratios of 0.79 (95% CI, 0.70 to 0.90), 0.84 (CI, 0.74 to 0.95), 0.71 (CI, 0.62 to 0.82), 0.71 (CI, 0.60 to 0.84), and 0.77 (CI, 0.65 to 0.91); the respective estimates for consumption of sugar-sweetened coffee were 0.91 (CI, 0.78 to 1.07), 0.69 (CI, 0.57 to 0.84), 0.72 (CI, 0.57 to 0.91), 0.79 (CI, 0.60 to 1.06), and 1.05 (CI, 0.82 to 1.36). The association between artificially sweetened coffee and mortality was less consistent. The association of coffee drinking with mortality from cancer and CVD was largely consistent with that with all-cause mortality. U-shaped associations were also observed for instant, ground, and decaffeinated coffee.
Positive health effects from drinking sugar-sweetened coffee make me think it's not just confounding, since I wouldn't expect health-conscious people to drink sugar-sweetened coffee. But I'm suspicious regarding the "less consistent" association for artificially sweetened coffee. That makes me think that there is just too much noise in the data to know for sure, or perhaps artificial sweeteners are actually bad for you?
Edit: I wrote some more skeptical thoughts here https://news.ycombinator.com/item?id=31602472
If you apply this thought process to alcohol (given what we know now), what would you conclude about this approach to updating your priors based on implausible observational data?
With causal interpretability? Yes (Mendelian randomization).
For instance, I would expect people to not drink coffee if they have chronic stomach illness or are under a pretty strict diet, or heavily medicated. This could heavily skew results of how long heavy coffee drinkers tend to live.
Yes, the researchers did an admirable job trying to control for confounders. Doesn't matter. Confounding factors for health are impossible to adjust for, whether it's healthy user bias or nutritional choices or a million other possible factors. There's just no way to take this sort of causality seriously when humans are living infinitely complex lives. Stop wasting money and do an RCT.
Also, traditional media is still embarrassingly bad at communicating correlation vs causation. How does this get past a science editorial board.
What you can do is mendelian randomization studies. There are genes which influence bitter taste which seem like obvious candidates: If coffee tastes like pure quinine to you, you're probably drinking less of it than you otherwise would.
A quick search shows that there have been M.R. studies on coffee, and they do suggest the relationships between coffee drinking and various good health outcomes aren't causal, just like the ones on alcohol. At this point, we should be suspicious of any "U-shaped" effect curves of extremely common and popular habits.
It sounds like we need a study comparing people who rarely drink anything but water vs coffee drinking vs energy drink/soda drinking.
But I'll have a C4 once in a blue moon, if I plan to hit the gym very soon after.
> Coffee suppresses your appetite because it contains chlorogenic acids which are a type of phytochemical compounds that help control hunger pangs and suppress your appetite. Because of this, you don’t need to drink caffeinated coffee to integrate it into your weight loss program; decaffeinated coffee will do just fine.
Source for the quote: https://energeticlifestyle.com/how-to-use-coffee-as-an-appet...
Pubmed source which corroborates coffee as an appetite suppressant: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683100/
And since they already have heart issues - ding ding ding. Correlation. It's not that coffee is making people healthier, it's just a substance that is addictive that people that don't have heart issues drink.
- Is sweetened coffee also adding creamer? I don't know of many people who take coffee with sugar but no cream. They usually go together.
- Were coffee preparation methods at all considered? I don't know if everyone in the trial was being served the same coffee or if respondents prepared coffee in whatever manner they liked and just reported how much coffee/how sweet they made it. Different methods may require more or less sweetner, so the guy who takes it black might be e.g. doing a Chemex/pourover, while the guy doing cream and sugar might be going through a standard drip. A third might be doing a French Press. The extractions from those methods will be wildly different.
2nd one black - pure or with one drop of la perruche sugar cube - depending on the mood.
https://www.npr.org/sections/thetwo-way/2016/09/13/493739074...
It was not a controlled trial, it's an observational study. They had a few hundred thousand people fill in a questionaire (up to 5 times in different seasons) about their diet (sweetened/unsweetened/type of coffee consumption were only a few of the many questions). They registered the answers and compareed a few years later how many died, with statistical controlls for different observed characteristics between drinkers and non-drinkers.
Full details: https://roar-assets-auto.rbl.ms/documents/16093/Sweetened%20...
I'm a regular coffee drinker (and not caffeine sensitive), and I do get a placebo boost from decaf, but without any noticeable effects from actual caffeine.
This data is from the UK where coffee is still significantly less popular than tea. Would be interesting to see the mortality risk of coffee vs tea drinkers though.
Also how many people load it up with sugar and cream rather than just the brew itself.
Like they're just covering up the bad taste.
You have to pay like 20$ a bag to get something that isn't bitter in North America. Here if you want bad coffee at a low price I guess you can buy instant?
I don't think green tea drinkers are putting many additives in there.
I feel like the potential health risks of doing this every day might be worse than the health risks of cancer caused by exposure to hot liquids, even if it's something as small as a bit of increased weight gain. (Especially since you can just wait for it to cool down a bit.)
Even better on a hot day is iced coffee! Something about letting it end up at room temperature for a while alters the taste but if it just goes straight on ice it's kinda sweet on its own.
It's the same as with repeatedly touching hot things with your hands: The nerves deaden and eventually very hot stuff doesn't feel as hot anymore. For your mouth, this is not so handy I feel. I occasionally make mistakes that burn me quite badly, but I can't really tell when it's happening because my memory of a bad burn feels way worse than the reality currently does.
Edit: Actually it's not so handy on your hands either.
Also, if you have issues with caffeine and have never drank coffee before, why ever start? It seems like a thing you could just never do and be fine with.
Not to mention, what if the problem isn't with the caffeine, but something else in the coffee. Decaf doesn't fix that.
I can’t drink coffee because my heart will go crazy. Does that make me more at risk according to this study?
With confidence intervals on those, about the same even if the number of cups is different, but odd that 1.5-2.5 cups per day unsweetened comes out worse than sweetened.
So there is that. So much for "a glass of wine a day is good for your heart".
> Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors, with respective hazard ratios of 0.79 (95% CI, 0.70 to 0.90), 0.84 (CI, 0.74 to 0.95), 0.71 (CI, 0.62 to 0.82), 0.71 (CI, 0.60 to 0.84), and 0.77 (CI, 0.65 to 0.91); the respective estimates for consumption of sugar-sweetened coffee were 0.91 (CI, 0.78 to 1.07), 0.69 (CI, 0.57 to 0.84), 0.72 (CI, 0.57 to 0.91), 0.79 (CI, 0.60 to 1.06), and 1.05 (CI, 0.82 to 1.36).
It explicitly says that the all-cause mortality for unsweetened coffee was lower, that's pretty clear. But then it just gives (Confidence Interval?) numbers for "the respective estimates for consumption of sugar-sweetened coffee" but doesn't say if it lowers all-cause mortality, is that implied as well? Or are those numbers just confidence intervals without giving an assessment?
Reading scientific papers is hard. They are dense and packed with numbers. Nobody is "good" at it, it takes effort to unpack them and digest them.
Now also imagine that the self-same Bash script is written in the tersest style possible without any consideration to how accessible it might be for the reader. That's most science papers.
Once you understand how a paper is to be read, and different papers, e.g. medical, or observational (like this study) or computer science, will have differing common styles between them.
So you're not bad at reading science papers. It is simply that nobody bothered to show you the techniques yet.
Eh? So having sugar in the coffee was better than no sugar? am I reading this wrong?
I also wonder if it's just increased consumption of water via coffee that is helpful here. They're saying it's not the caffeine so would it then just be the residue from the beans soaking in the water?
How do you adjust for that in the analysis?
I find that caffeine made me anxious, so much that all the energy wasn't even worth it anymore, as I couldn't focus on anything from anxiety. After stopping, my anxiety has went down so much that I feel I'm able to do much more work then before, even if I'm doing it slower, because I can just relax and focus on what I need to do, without being distracted by every single intrusive thought I have and without the crash that inevitably comes every day after caffeine wears off.
I don't care about "health benefits" of coffee, to be honest. Caffeine is a crappy drug (for me), so nowdays I only save it for situations where I have to stay awake for longer than I usually can.
I've always had issues with focus, and first year of college was overwhelming. I cut out all unnecessary time sinks, and I've found that I lack enough "focus" in a day - at some point I'd just read, but be unable to engage with any words I'm reading.
Caffeine pills helped me study for longer, however, the tolerance made me take more and more until at some point I was taking up to 2000mg of caffeine a day. I was barely functioning from anxiety, but I managed to be amongst better students on my year.
At work we have an espresso machine, so it's very easy to just "grab a cup" when I feel tired while working on an important task. It wasn't strange for me to drink 5-6 cups per day.
Nowdays, I'm only drinking coffee if it's a social event, and I keep a hard limit of one cup per day.
I've been caffeine free since the start of January and no more tinnitus, anxiety, shaking hands or waking up during the night.
Downside is I'm eating more food, it's harder to focus and gaining weight.
For example, are coffee drinkers less likely to die in a crash commuting to work in the morning?
Or less likely to die from stroke?
There seems to be an unhealthy neurosis/anxiety built up around staving off death as long as possible - the number of articles on HN, companies started around longevity by people who are, to put it bluntly, scared shitless of dying, is disturbing. You can't lower your risk of dying. If enjoy a cup of coffee, then enjoy a damn cup of coffee regardless of what studies say.
Of course you can. Moderate exercise unambiguously makes this risk lower. Of course, even with much lower risk today you will eventually die. Perhaps this is what you meant.
I wish coffee studies would report results in ounces (or better, ml) instead of ambiguous "cups"
The Coffee industry uses 6 ounce cups, the USA standard "cup" is 8 ounces, and the imperial cup is 10 ounces (the study was based on UK data).
I drink around 12 oz of coffee a day and I drink it out of a single large coffee cup, is that 1 cup, 2 cups, 1.5 cups, or 1.2 cups?
“People who can afford to buy lots of coffee can also afford other lifestyle ingredients that lead to longer life, relatively.” ?
Latter Day Saints and Adventists don”t drink coffee, and yet they get to brag about better than average longevity too. But that too could just be a canary for economic indicators.
What's the reason not to drink coffee for them?
There’s not a lot of chatter about coffee being healthy or unhealthy. The only unhealthy thing that people tend to want to avoid is being unable to sleep due to drinking too much of it or too late.
Another cultural thing is to joke about the first cup of joe being mandatory if you want to wake up properly (at the office). In that light it makes sense to not really consider whether it is healthy or unhealthy; it’s as if your body needs it anyway so you either gotta get it or sleepwalk through the day.
Also, I looked up the acronym PAWS, you used, and Wikipedia says it is not a medically recognized term by major medical associations.
These are all anecdotes - I don't believe there is actual evidence for this being the case. With such reports, it is frequently the case that there are other factors that influence this as well (for example, getting off of multiple drugs at once or an external factor that influences quitting, but that also makes you sad). I'm not saying it absolutely can't take a while to feel normal again, but you should take this frankly histrionic type of reporting with a grain of salt.
Given no other type of input, you should expect to be average. On average, it takes a week or two to get over coffee and you may miss it for a while.
A comment of mine got flagged because I think I hit a nerve.
Here's CNN saying coffee is good for you as if it's a new idea since 2010 on one page of search results alone,
https://duckduckgo.com/?q=site%3Acnn.com+coffee+good+for+you
Here's Fox News saying the same thing:
https://duckduckgo.com/?q=site%253Afoxnews.com+coffee+good+f...
> National Natural Science Foundation of China
China's scientific credibility went out with the window when they lied about spreading a weaponized virus a few years back.
Like how children medicine is sweetened to increase compliance.
One aspect I notice from my caffeine intake is that it helps me deal with stuff in general--nothing stresses me out. The downside is that I also feel positive things less as well, so I try to limit it to morning/mid-afternoon of weekdays. I can certainly see in my case living a life with less stress promoting longevity but with less richness of experience.
I don't think they do. Which is much better than correcting for variables and doing it badly.
Anecdotally, I am the only healthy person I know of in my group who voluntarily uses artificial sweetener. It seems to me that the use of artificial sweetener is strongly associated with health problems such as morbid obesity and diabetes: people who don't have to don't use them.
Regarding artificial sweetener itself being causal there is very little reliable data to support that. There does seem to be a link between Aspartame and (bladder) cancer but it has so far only been shown in animal models.
Yeah. Cause and effect seems to be reversed here. I started using sweeteners because of my coffee consumption and watching the effect it was having on teeth. Later on cut the sweeteners completely, just because they don't taste as good as actual sugar, so why bother.
I don't think most are as bad as some people believe. A lot of it has probably to do with the notion that they are 'artificial'.
Well, no more so than pure sugar. Go chew on some sugar cane if you want something more "natural" :) Even that must be done in moderation.
For those of you that have quit completely - does the roller coaster stop? By that I mean... you have caffeine, feel productive, caffeine wears off, you feel unproductive, rinse and repeat.
Are you over all more productive or do the peaks and valleys just average out into nothing?
tl;dr: Overall more productive. It's also more pleasurable.
Very interesting! I've seen this conclusion many times in the past decade+ but have yet for someone to call out the aspect of caffeine. I wouldn't suspect caffeine to result in lower mortality risk, but you never know
> The association between artificially sweetened coffee and mortality was less consistent.
Also, is unsweetened coffee black coffee, or could it be coffee + some type of creamer? I’m assuming it must be the latter because if they meant black coffee they would have said that.
>I’m assuming it must be the latter because if they meant black coffee they would have said that.
The authors seem to have Chinese names, a country with extremely low dairy consumption, so I wouldn't assume that. I'm from south america and never seen a coffee with creamer, had to look up what that means.
I didn’t know what else to call it. It’s typically dairy or a dairy substitute but I’m also thinking of things like steamed milk in a latte, flat white, or cappuccino (those are global, no?).
Edit: doesn't explain that the effect also worked with decaf. Maybe coffee contains other compounds and secondary metabolites which have health benefits
> there may be other lifestyle factors contributing to that lower mortality risk among people who drink coffee, like a healthy diet or a consistent exercise routine
Instead, coffee consumption is so pervasive that coffee drinkers are “normal” and many people that don’t consume coffee do so because it’s actually hurtful or uncomfortable … and that likely correlates to other weaknesses.
The same interpretation should be considered for all of those moderate drinking studies… I am quite certain nobody is getting a health benefit from alcohol.
The effect where moderate alcohol use is beneficial have disappeared after better studies. It didn't prevent it from becoming "common wisdom".
Not saying I agree, but thats my interpretation.
It also says they don't make the same conclusion about artificially sweetened coffee (the study says it's "less consistent"—seems I need to pass the paywall to see the numbers on that). One wonders if they believe that the artificial sweeteners are killing people, or that they interfere with the benefits of coffee, or if they'd say this reveals that selection effects are strong here.
> the data cannot conclusively prove that coffee itself lowers the risk of dying; there may be other lifestyle factors contributing to that lower mortality risk among people who drink coffee, like a healthy diet or a consistent exercise routine
...and controlled for in the study
> lifestyle, sociodemographic, and clinical factors
Folks who drink alcohol should consider taking safer and more powerful drugs.
That is not exclusive to alcohol though. I am not extremely drug-savvy, but I do believe this is true for psilocybin mushrooms and a few other hallucinogenic plants/fungi.
> Folks who drink alcohol should consider taking safer and more powerful drugs.
This is often an issue with legality and sourcing for many, not to mention the cultural acceptance of alcohol by many cultures.
I don't think alcohol is somehow better than anything else, but I don't think it's that harmful either until you get well beyond the 14d / wk max recommendation.
There are plenty of other factors like meat consumption and exercise habits that have a bigger effect. I'm not giving up one harmless vice for an infinitesimal benefit. We're all going to die of something.
I do wonder about some of those error bars and controls though. For example artificially sweetened coffee decaffinated at 1.5-2.5 cups per day seems to have a higher rate of death (1.11) - but artifically sweetened decaffinated at 3.5-4.5 cups has half the rate of death (0.52). By contrast black decaf at 3.5-4.5 per day does worse than that (0.66).
Anyway, if there's any significance to this, you're right that caffeine does not seem to play into it much in their stats.
Yes, if you are having sleep problems they might tell you to cut back on coffee and other caffeine sources. Some people are particularly sensitive to caffeine and get jitters and have trouble sleeping. Most people do not have this problem and as long as they don’t drink coffee late in the day, it does not cause sleep problems.
I've found most sleep problems disappear if I stop drinking coffee before 3pm. YMMV.
In college, I could drink coffee at 9pm with a bowl of icecream and it didn't hurt my sleep at all. lol
Edit: by "these studies", I mean caffeine, cigarettes/smoking, alcohol, coffee and generally any food or "health" study. If you don't know the exact make up of the test group, then I just assume it's rigged to get a certain result.
While I can't debate "These studies" without knowing what you're referring to, this specific study provides a clear explanation of the study cohort and there's no sign that anyone was excluded or otherwise cherry-picked.
I've found that digging deeper into studies in the past that they would leave out people with heart conditions (specifically with caffeine studies) and not state that _anywhere_ in documentation. And this only came out from investigations.
I have a friend who does statistical analysis for a living, and we have a game where he points out the flaws that are only obvious to those that know statistics and research well, and us laymen are oblivious.
A medical doctor once told me "coffee must be good for you because I drink it!". It seems common that people just want science to agree with them, and they don't care how or why.
I can't prove my point on this article (not enough time/energy/will) but I have watched health articles for years and you can go back to news sites and find this same exact study done over and over, reported in news organizations as if it's new every time.
One stupid example, articles from just CNN going back to 2010 just on one page of search results:
https://duckduckgo.com/?t=ffsb&q=site%3Acnn.com+coffee+good+...
Does Starbucks add sugar to the coffee? Or what do you mean. The ice coffee?
They serve coffee also.
If you google 'starbucks unhealthiest drinks', you'll find references to stuff like 'cinnamon roll frappucino blended coffee' which apparently had 85 grams of sugar in its largest size and 510 calories. If you're familiar with the 'packets' of sugar people sometimes sweeten coffee or tea with, 85 grams is like 20 packets. The 'sweetened cup of coffee' referenced in the study referred to a coffee with about 5 grams of sugar added.
The control was not drinking coffee, and far lower all-cause mortality was observed in both black coffee and coffee with a tiny bit of sugar.
Or: Yes, adding a ton of sugar to anything is unhealthy, but this study provides far more information than that. Although it's observational, the observed effect is huge. From the study:
"Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors," [then repeats for lightly sugar-sweetened coffee, but not artificially-sweetened coffee].
This study seems to confirm that fake sugar is harmful. I have family who drink fake-sugar cola products - these don't help their weight. I've seen one person fall apart 'mentally' within 1/2 hour of drinking an electrolyte beverage made with sucralose and other fake sugar.
Ideally glucose is consumed with potassium, to avoid insulin release: milk, orange juice, potatoes, etc... Fructose does not stimulate the release of insulin.
I mean, so does running, swimming, watching an exciting movie..
> This study seems to confirm that fake sugar is harmful.
This study confirms no such thing.
> have family who drink fake-sugar cola products - these don't help their weight.
Yes but (probably) not because the fake sugar but because their palette is too sweet focused. You need dietary change to lose weight.
> I've seen one person fall apart 'mentally' within 1/2 hour of drinking an electrolyte beverage made with sucralose and other fake sugar.
I've seen someone have a heart attack after crossing paths with a black cat.
I don't think it was the cats fault.
Also, I've been taking caffeine pills for the better part of a decade, often on an empty stomach. There's no crash from the absence of sugar, the only sort of crash I get occurs a few days after each time I try to quit the stuff.
Probably dehydrated and whatever hydration they did get wasn't sufficient.
It does, but less so than glucose. That may help on the insulin response curve but will only help weight if you keep calories down. Energy is energy.
It's not a panacea either. Can be harmful. Eg.
https://www.genengnews.com/topics/omics/fructose-is-harder-t...