Sigh. Sure, there is nothing wrong with eating those foods. But how about stopping the overconsumption of ultra-processed food instead?
I'm tired of all these articles that seem to promote the consumption of some magic bullet food as if eating more of that is the solution to all our dietary problems. No it isn't. Cut out all the garbage and just eat whole foods instead.
The two go together since you typically eat a fix amount of food per day, so more 'good' food also means less 'bad'. Quotes because the same applies to fad diets that promote aweful eating habits as well.
Totally agree. You and I get that, but a lot of other people won't. Take the whole olive oil thing as an example. You can switch your cooking oil, but if you're still eating (for example) loads of sugar and large quantities of processed food it's not going to make much of a difference is it?
Lastly, one unique aspect of the study is the focus on only protective foods, i.e. a dietary pattern score that highlights what is missing from the food supply, especially in poorer world regions, but this does not negate the importance of limiting the consumption of harmful foods such as highly processed foods.
For what it's worth they mention this at the section "strengths and limitations" near the end (bold is mine) and it's quite a long read.
We can't edit other people's titles and this is a good article, but I wanted to don my mod hat for a second to mention that this title is sensationalized, and we would appreciate it if you leave the original article title in tact in the future.
Thank you for actually caring about this. Many articles from /r/Science had the same issue and mods would simply delete my comments when I brought it up even though it's explicitly against the rules.
This link is the research paper which was reviewed by sciencedaily, my title is a blend of both sciencedaily and the paper titles. The research paper's title is super ambiguous and it seemed a blend of the two made more sense.
ScienceDaily Link: https://www.sciencedaily.com/releases/2023/07/230706231347.htm
Not sure how much I agree on the dairy part. Apart from the inherent ethical problems associated with it, dairy is an all around promoter of cardiovascular disease. My anecdote is that while I was vegetarian, I suffered from high BP and had to be put on meds. Once I went vegan, my BP dropped to the same levels as with meds before. I'm also prone to gout due to genetics. This change in lifestyle had to be the best step I took for my body.
Now, I see why this study had great results. Eating a varied diet, especially rich in whole foods is a good thing, dairy or no dairy. People just want cheese in their diet and that's a compromise a lot of studies do to reduce dropout rate and make people stick to a diet. It also makes dairy companies happy.
While most of this is interesting please take a look at the section "Water use of food products". Looks like cheese needs quite a lot of water.
I am neither vegetarian nor vegan, but I do tend to pick the foods I consume in sizeable quantities considering things like these.
I am not in any shape or form justifying cheese (over)consumption. Health isn't the only reason I advocate for a plant-based diet. The environmental impacts and carbon footprint of meat and dairy make a gas guzzling pickup truck pale in comparison. For me, cheese was the hardest thing to give up. That thing is addictive. But learning about the suffering that the animals endure, the environmental impact...I just could not go on like this.
While some foods are clearly more healthy and protective than others, people's bodies are so different that comparing individual experience is almost pointless. Some of the other comments here mention abstaining from X and having a great experience. There are just as many arguments to be made to the contrary. Also, human metabolism changes with age, so the habits that have sustained your health for the past decade may not continue to work in the future.
Also, human metabolism changes with age, so the habits that have sustained your health for the past decade may not continue to work in the future.
While this is certainly true, I feel the need to say here that the first time I looked at the contestants of an ultra-marathon event near me I was surprised to find that there were people well over their fifties participating. I mean, at least as far as this habit goes, their metabolism can't be very slow..
True, but it isn't just about fast or slow. Some things I used to be able to eat, I can't anymore. Stuff that used to make me feel crappy, might make me feel good now. I never used to be a breakfast person. Recently, I've become a breakfast person.
Yep, by definition metabolism is the sum of all chemical reactions in an organism! It's like the confusion with hypothesis and theory in media today, metabolism has basically been neutered the same way.
It's sad that they keep using flawed statistical methods in these studies...
Correction: as @Gaywallet@beehaw.org points out, they also use other statistical methods within the paper!
While taking issue with p-values is a valid stance, the paper uses confidence intervals and bayesian methods (cubic splines) in addition to p-values, both of the proposed alternatives in the ASA's statement that you mentioned below.
While p-values are listed, there's stats which fall in line with the recommendations in this very paper. If you take issue with either of these methods, could you help explain to me why you're upset? Or is it just the fact that p-values are stated rather than focusing on the CI and bayesian results? I personally think there's value to still showing a p-value because it makes it slightly more approachable to the non-scientific or statistical crowd, so long as it's not used to distract from poor fit of other models.
No, that's my bad, thank you for correcting me! I only read the abstract, and they don't mention Bayesian methods there. Confidence intervals suffer from similar flaws as p-values and statistical significance.
It's great that they do analyses with other methods too indeed. Not, from my point of view, because they're more approachable – quite the opposite: people think in terms of probabilities-of-the-hypotheses, and p-values are not that (that's one source of their misuse). But because it helps the transition to other methods. It'd been nice if they had stated the results from all methods in the abstract. But that'll be for next time maybe!
Cool thanks for clarifying! While I am a data scientist I am not a stats expert so always looking to understand proper critiques from those more knowledge than me 😄
Thank you for the correction. Don't trust me, though: check out the proofs and discussions in the references here, see for yourself :)
The statistical method is not flawed. Many scientific communities are misinterpreting or abusing it - thats the problem.
P-values-based methods and statistical significance are flawed: even when used correctly (e.g.: stopping rule decided beforehand, various "corrections" of all kinds for number of datapoints, non-gaussianity, and so on), one can get results that are "statistically non-significant" but clearly significant in all common-sense meanings of this word; and vice-versa. There's a constant literature – with mathematical and logical proofs – dating back from the 1940s pointing out the in-principle flaws of "statistical significance" and null-hypothesis testing. The editorial from the American Statistical Association gives an extensive list.
I'd like to add: I'm saying this not because I read it somewhere (I don't like unscientific "my football team is better than yours"-like discussions), but because I personally sat down and patiently went through the proofs and counterexamples, and the (almost non-existing) counter-proofs. That's what made me change methodology. This is something that many researchers using "statistical significance" have not done.
This is interesting and something I've not heard of - can you recommend a starter link for someone with a basic stats background? I had some in undergrad, but this sounds like a topic that could get very tinfoil-hat-y if not searched correctly and with good context.
There's still a lot of debate around this topic. It's obviously difficult for people who have used these methods for the past 60 years to simply say "I've been using a flawed method for 60 years" – although in the end that's how science works. The problem moreover is double: the method has built-in flaws, and on top of that it's often misused.
Some starters:
The official statement by the American Statistical Association
Signatories for the dismissal of the method
Many papers explaining the built-in flaws, from this old 1935 paper and this old 1965 discussion, to more recent ones; for example this, or this, or this, or this, or this tutorial
This paper gives a good summary
Journals that don't accept "statistical significance" methods anymore: this or this
Several books, for example this one. I agree with the factual content of this book, but I don't like the authors's braggart way of writing. In their defence, though: it's the same braggart way of writing that R. A. Fisher, the father of "statistical significance", often had.
What's sad is that these discussions easily end in political or "football-team"-like debates. But the mathematical and logical proofs are there, for those who care to go and read them.
Thanks, I appreciate it - looks like I've got some bedtime reading for awhile :)
My pleasure!
Ah, I thought you were talking about p-values - which is just a simple metric and gets a bad rep from being used for statistical significance. Statistical significance certainly is trash.
Yes I'm talking about p-values. Statistical "significance" is based on p-values.
I totally agree with the first five, but not sure about the last one, whole fat dairy. Eg cheese contains saturated fat which isn't healthy. I had assumed that lower fat milk would be better for eg the calcium.
Turns out that saturated fat isn't the big awful thing that has been peddled for decades. What turns out to be better for you is shorter chain saturated fats produced by a health gut microbiome, and that feeding your microbiome is essential to better health. Also, not all calories are equal. It turns out items higher in resistant starch feeds a healthy microbiome and in turn those bacteria convert the food calories into short chain saturated fats which feed you. See this recent Nature Comm paper.
Thanks for sharing. I had a scan of that paper but I don't see any mention of saturated fats? Not saying I don't agree, it is just contrary to what my GP has been telling me. I have slightly elevated cholesterol and it runs through the family, so I'm watching intake of saturated fats.
Lipids are one of the four macromolecules found in life. Moderation of lipids is the key part here. LDL (bad cholesterol) is needed for digestion, cell signaling, and immune cells require it for certain functions. It's the goldilocks principle, too much or too little is an issue.
I had to look it up, but reducing milk by 2% fat increases the calcium ~6mg/cup. A little calcium goes a long way for human cell functions, so it's a decent increase for sure.
I definitely don't need more reasons to eat more cheese.
Fish and dairy definitely aren't needed
Basically my usual diet, nice. Well, minus the dairy.
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