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Relatedly, there is evidence that certain types of "resistant starch" can help reduce visceral fat. This starch comes from green bananas, potatoes, legumes, etc. It has to be either raw (there are supplements for this) or cooked and cooled.

"Resistant starch intake facilitates weight loss in humans by reshaping the gut microbiota"

https://pmc.ncbi.nlm.nih.gov/articles/PMC10963277/

Edit: Ah, HN submission 2 years ago: https://news.ycombinator.com/item?id=39592367

sample size n=37 of which recruitment only happened in Shanghai without any real control for confounders, only evaluated over a period of two weeks with no longterm follow-ups, the dosage of 40g RS/d is very high (would take about 4-5 large potatoes daily for equivalency or ingesting likely expensive supplement), the crossover compares RS vs CS in the same participants with only a 4 week washout which is a weakness since fermentable fiber persists >4 weeks, also the supplement they used was industry-provided by a starch manufacturer which was weirdly not disclosed

this is a great study if you are an overweight/obese adult without overt metabolic disease, willing and able to consume 90 g/d of starch supplement within a controlled diet, and living in Shanghai with similar baseline fiber intakes endemic to that population. it is extremely not generalizeable to you or even me though I fit more of those characteristics than I care to admit

stay skeptical of small studies like this, friend

You can just go on a calorie deficit and it will reduce your visceral fat when you start getting lean enough.

But obviously, most people are a lot more interested in finding a magic food which does this rather than a proven calorie deficit, which is highly effective.

IMO my only concern is their dats shows they were actually able to maintain a pretty controlled diet for each participant, I wonder how selection was done. I also would've appreciated some bomb calorimetry of fecal samples, similar to [0] which is the widely cited paper that does link general fiber intake to a lower level of caloric/energy absorption.

Baer, David J., et al. "Dietary fiber decreases the metabolizable energy content and nutrient digestibility of mixed diets fed to humans." The Journal of nutrition 127.4 (1997): 579-586.

Mark Stache ( https://youtu.be/L-gNdQZorEE?si=nkwAhZOiAFtY2f44 ) just did a 90 day evaluation. The biggest problem at the level they mention is some intense flatulence. He is also in good shape and had mixed results compared to the study.
I feel like I've heard this story 1 million times before.
For non-invasive heart disease risk prediction nothing beat ECG, period.

Somehow American Heart Association and its European counterpart are in denial, and still pushing dinasour screening mechanism with very low accuracy for heart disease risk prediction.

The standard risk model for CVD based on PREVENT (US) and SCORE-2 (Europe) like parameters are very poor as reported in the recently published paper on the their accuracy performance by the Swedish team [1]. As all CVD risk stratification with cardiologist review (expert-in-the-loop), the most important accuracy metric is sensivity/recall (avoiding false negative that will escape review) of PREVENT and SCORE-2, 26% and 48%, respectively.

The paper alternative proposal increased the sensitivity to 58% by performing clustering instead of conventional regression models as practiced in the PREVENT and SCORE-2.

These type of models including the latest proposal performed very poorly as indicated by their otherwise excellent and intuitive display of graphical abstract results [1].

[1] Risk stratification for cardiovascular disease: a comparative analysis of cluster analysis and traditional prediction models:

https://academic.oup.com/eurjpc/advance-article/doi/10.1093/...

I'm not sure how ECG relates, how would ECG predict heart disease risk? I don't see any evidence of that, it's not even mentioned in the article you linked, which is odd considering the whole approach of clustering is gathering as many risk factors and relevant test results as are available.
There are lots of different types of heart disease. An ECG can be useful for diagnosing some of them but you're overstating the relative value. For many patients, a CT coronary calcium score or CT angiogram may be more valuable in terms of detecting the type of arterial plaques that might require medical management or major lifestyle modifications in order to prevent a heart attack. These are also non-invasive, although they do involve some radiation exposure.

https://www.mayoclinic.org/tests-procedures/heart-scan/about...

https://www.mayoclinic.org/tests-procedures/ct-coronary-angi...

How many ECGs can you sell vs how many other snake-oil products? :)

(Edit: This is intended to be sarcastic. I agree 100% with the comment)

(Edit 2: Added the smiley face)

This paper is.. not great. Their clusters and risk model were developed and validated on the same sample. There’s no train/test splitting, no cross-validation anywhere. As a result, all the performance metrics they report for their model are optimistically biased. The comparator models weren’t refit to this sample, either, so the comparison between their model and PREVENT et al. is really an internal validation versus an external validation, which isn’t apples-to-apples and disadvantages the existing models from the get-go.

You could say that it’s almost as if their model has a home-field advantage. Because of that fact alone, you can’t really conclude anything about the comparative performance of their models versus the existing ones from this paper.

Get as many scans you can under insurance. Data is king and Claude happens to chew it all pretty well. Apple Health data by itself and family history is enough to make a starter PDF for your cardiologist.

Getting an ECG, EKG, TTE, CAC, carotid duplex US, lipid panel, CMP, TSH, 25-OH Vit D, B12 + folate were what my cardio recommended before appointment #2 on hypertension. Both of us are data guys.

I thought this was pretty well known already. Being “overfat” is the problem, not being overweight (though they’re often correlated). BMI is really easy to measure, and is mostly accurate, that’s why it’s so pervasive. However it remains a pretty rudimentary metric (and really should use the third power or your height instead of the second).
> BMI is really easy to measure, and is mostly accurate, that’s why it’s so pervasive.

BMI is easily misunderstood by people who know just enough to see that it’s imperfect, but not enough to understand why it’s still a valuable screening tool.

I’ve been in the “overweight” BMI range with low body fat before. It’s not too hard to get there if you’re lifting weights and paying attention to your diet consistently for years, but it takes a lot of work to get there. It doesn’t happen accidentally except for people who win some genetic lottery to build a lot of muscle and keep body fat low without trying.

Getting all the way to the obese BMI range while having healthy body fat is only happening for people with an extreme dedication to body building and diet (and let’s be honest, a lot of the people in this category are manipulating hormones too).

Yet whenever BMI comes up some people try to dismiss it as too flawed based on these possible edge cases. The edge cases for BMI exist, but that doesn’t mean it’s not useful. It’s a good general purpose screening tool with numbers that are available. If someone has more precise measurements available, those should be used instead. BMI is a really good first pass screener to determine if a closer look should happen.

Yes, it is a pretty high level metric with good correlation a bunch of diseases, but really many of these is because it is ALSO correlated to percent of fat, which is often the more relevant metric. But as you said BMI is so much simpler to measure.

Many active gym people have pretty high BMIs but fairly low fat (because muscle is dense), and unsurprisingly have better outcomes than the average person (if you ignore the share that uses/overuses anabolic steroids and co)

Another common misconception is that one is still healthy with high BMI that comes from having lots of muscle. It's not clear that lots of muscle is healthy.
How accurate is it, in practice, for a given individual? I'm not that out of the ordinary proportion wise. I have a slightly longer torso and arms versus my legs, a somewhat muscular-ish baseline and broad shoulders, but I accumulate fat almost exclusively abdominally. My teenage self, lifetime peak of my fitness, no visible body fat, hyperactive football player, qualified as solidly overweight. If I was to listen to it, I'd be called obese before I noticeably start to show body fat.

I often wonder far from the median I am in this regard. I was under the impression that it was pretty accurate for assessing populations, but fell apart very quickly at the individual level. How many "normal"/otherwise healthy people do fall outside BMI's numbers?

BMI is at best 66% accurate, so "mostly" is correct, but what is mostly good enough for?

BMI has known biases in gender, age, and race. It misclassified Asians, women, elderly w sarcopenia, and people with high body fat to lean tissue ratio.

A nitpick about the title: Not strictly abdominal fat, but visceral abdominal fat, which surrounds the organs. Not all abdominal fat is visceral; in fact, in many people the majority is not. The article mentions visceral early on, which is the subject.
This is known since decades. Male type fat, central obesity or belly fat, is much worse than female type, pear-like. Hormones play a role under the hood. I don't know if liposuction would play any preventive role.
So this study basically compares,

BMI

Waist circumference (WC)

Waist to hip ratio (WHR)

Subsequent risk of nine cardiovascular/mortality outcomes in >260,000 people followed for ~20 years

To make it even more useful they should have included DEXA scan bodyfat%.

Also, BMI becomes somewhat biased at height extremes because body mass doesn't scale exactly with height². Humans aren't geometrically scaled copies of one another and empirical scaling exponents are often somewhere between 2 and 3. Conventional BMI tends to read relatively high in very tall people and relatively low in very short people. But changing the exponent would only fix one relatively small limitation of BMI

For better height adjusted replacement for BMI itself, one option is Trefethen’s BMI

WHR and WC is positively correlated to bodyfat% but this may get distorted for strongmen or sumo wrestler who tend to have much higher than average lean mass, may also have higher WC and WHR but difference maybe waist to shoulder ratio, they tend to have much bigger and powerful shoulders.

what's interesting is, for sumo wrestlers specifically, WC still correlates strongly with BF% one study reported r ≈ 0.86

There is a category in fitness called "skinny fat" where you are at low bodyweight (so low BMI) but your fat mass is relatively higher when compared to lean mass, so higher bodyfat%

Many skinny fat people refuse to believe they carry higher bodyfat% because they think they've low bodyweight so they can't possibly carry higher fat, which is wrong.

If you are interested in knowing more about bodyfat, this may help you: https://aretecodex.pages.dev/knowledge/measure/bodyfat

The revenge of the six-pack. Now we have them as goal beyond aesthetics or vanity.
> Studies have shown that visceral fat, which is fat that surrounds the internal organs in the abdominal area, is associated with chronic diseases like heart disease and diabetes, while subcutaneous fat, which is located directly under the skin, is not as strongly associated.

How does one determine if one has an excess of visceral fat?

This is new? I thought they have been saying this for years
> Those with obesity and low WC [waist circumference] were not found to be associated with a significantly different risk of outcomes compared with those who had normal weight and low WC, except for all-cause mortality, for which risk was significantly lower.

If I'm reading that right, it sounds like obesity (and therefore BMI) is still a better predictor for all-cause mortality. Perhaps waist circumference is better at predicting cardiovascular risk but BMI is still useful.

You can control your CVD risk.

Cutting saturated fat to under 15g per day and increasing intake of viscose fibre (e.g. beans) will reduce your LDL particle count in a few weeks, which reduces your CVD hazard ratio. You can measure your LDL and look up the papers yourself. Statins will reduce it a lot too (potentially with side effects). Replace solid fats like butter with liquid fats like olive oil.

Literally any amount of regular exercise, including walking, will decrease CVD HR. The more the better (up until quite a large amount e.g. professional athlete). The more your heart is steadily pumping during exercise the better. Every bit helps reduce CVD risk. Movement is medicine.

For the love of God do not smoke. Literally one of the surest ways to die a horrible death. Stopping smoking reduces CVD risk by a large amount.

Do not give yourself diabetes by eating vast amounts of sugar. If you are doing this, stop. Not having diabetes decreases CVD risk.

Other factors you probably can't change so focus on these.

Doctors, if I got anything wrong please correct me.

A summary:

Thirty years after we learned that abdominal fat distribution matters, large-scale longitudinal evidence shows that waist measurements meaningfully reclassify cardiovascular risk beyond BMI alone.

BMI isn’t a good metric, this has been known for a long time.

For example, I’m 45yo/178cm/93kg and am obese by BMI measurement. However, my body fat is 20% (Dexa), VO2 of 50 (lab) & have the aerobic fitness to run a half marathon after work and not care.

I’m not surprised that you need other metrics like hip/waist ratio, measured body fat, visceral fat, etc to better understand the composition of someone’s body and how it might relate to health outcomes like heart disease.

Well any fat % predicts heart disease better than BMI. So the question is whether Abdominal fat predicts better than overall fat.
But LDL-cholesterol is already better than both at predicting heart disease. Why waste money on this "research"?
take a look at myticker.com

(previously at https://news.ycombinator.com/item?id=45857053)

Very interesting, now if only you could measure abdominal fat without need expensive specialists.
For two people that are the same height, one could have X lbs of pure muscle, and one could have X lbs of pure fat, and they would have the same BMI. Color me shocked that it is not always a good predictor of disease.
Well, BMI doesn't count fat, just mass, that includes muscles, so yeah nothing unexpected here
I am not sure if this is adjusted appropriately for different groups who are much more or less pre-disposed to heart disease.
Yeah because it has an actual correlation, whereas BMI is a ridiculously oversimplified measurement designed for population statistics based on what data is easily available, not individual assessment.
It doesn’t matter how fat you are or how much cholesterol you have in your blood. What matters is the oxidative stress that oxidizes the lipids.

They need to figure out a way to reliably Measure OXLDL.

The 2000's called. We've known this for decades because we did a LOT of studies back in the day when you could still get government funding.
No shit.
how does it compare to cholestrol ?

just got statin at 44 :(

i am not fat and workout ( although diet can use some improvment)

Sugar is a drug and this whole discussion beats around the bush.
The irony of BMI is that people with plenty of muscle mass are more likely to have a high BMI as well as lowered risk for heart disease.

BMI was never meant to be used as a diagnostic measure. BMI is just a rough filter for large data sets, and entirely dependent on the average height and habits of that population.

Anyone taller than about 6'3" could tell you the recommended weight according to their BMI has always been absurdly low. If it's a printed chart on the wall, they might not even be on it.

BMI is an objectively terrible individual health metric, it's is literally just weight / height². It measures neither body fat nor visceral fat, cannot distinguish muscle from adipose tissue, says nothing about fat distribution, fitness, metabolic health, or organ function, and its interpretation varies with age, sex, ethnicity and body composition.

And these aren't merely hypothetical bodybuilder edge cases. A systematic review found BMI had only ~50% sensitivity for detecting obesity when compared with body-fat reference methods—i.e. it missed roughly half the people classified as obese by adiposity.

More importantly, the 2025 Lancet Commission on clinical obesity explicitly recommended that BMI be used only as a population-level risk surrogate or screening tool, not as an individual measure of health. For individual assessment they recommend actually confirming excess adiposity with waist measurements or direct body-fat measurement.

Which is basically what this study is demonstrating again: where the fat is contains substantially more useful cardiovascular information than the number you get from dividing someone's mass by the square of their height.