Yes, this is strong. Worth noting the limitations though:
> Randomization generated groups with comparable percentage of unfavorable risk factors as there was no significant difference in subjects with at least one risk factor, except for high blood pressure and diabetes mellitus, known risk factors for unfavorable disease progression [2], which were more frequent in patients not treated with calcifediol.
These are HUGE risk factors. Also:
> This pilot study has several limitations as it is not double-blind placebo controlled. On the other hand, in the first studies evaluating risk factors for severe disease and/or death from COVID-19, the possible role of obesity was not considered. Therefore, given the isolation characteristics of the patients, we did not collect the BMI, which would have allowed us to add obesity as a risk factor for severe evolution of COVID-19 [37] It is striking to consider that obesity shares with aging and black or asian ethnicity a surprising overlap as risk factors for severe COVID-19 and vitamin D deficiency.
Yeah, BMI would've been nice too.
Still, check out table 2. Even with these limitations, seems powerful.
The group receiving Calcifediol had more "no bad risk" patients:
"At least one prognostic bad risk factor(@)
Group receiving Calcifediol: 48%
Group without Calcifediol: 61.54%"
"@) Patients with at least one of the following risk factors (age >60, previous lung disease, chronic kidney disease, diabetes mellitus, hypertension, cardiovascular disease or Immunosuppressed and transplanted patients)."
That's what can be concluded from "at least one": (52% had no bad risk in D group, but only 38.46% had no bad risk in the other group). But it is also not clear where there were more patients with "multiple" factors! Or if they were those who had more problems at the end.
The whole paper contains neither raw data nor any graphs and only means and standard deviations, as far as I see? I would personally really like to see the graphs of distributions or to use raw data to check myself.
The critical question is how good the randomization was done.
Randomization doesn't ensure perfectly balanced groups-- it just ensures that the imbalances of variables you don't measure (including things that change after randomization not related to your intervention, with blinding) are drawn from a distribution that you can apply rigorous statistical reasoning about.
Yes, we can see some things are a little unbalanced. But the effect is so massive: we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely; instead, we see 1/50 of the rate.
> we might see 4/5 of the control's rate of ICU admissions if the "one prognostic bad risk factor" determined outcome entirely
But we still don't know if the persons with multiple bad risk factors were those who ended with bad outcomes? As far as I understand, if it was like that or not can't be seen from the paper at all, and I can imagine that it could have happened. I would really prefer the more raw data to the tables with the selected means and deviations given.
You have to get very, very unlucky on the dice rolls to get samples that are so tilted-- to pick 26 people out of 76, and somehow come up with 13/14 of those requiring ICU in the smaller group, if vitamin D has no effect. Outside of deliberate rigging... (it might even be difficult to deliberately sort and get this much of an imbalance).
Indeed, checking that the two groups look similar after randomization is completely optional. This study does an OK job of doing so.
There's both known and unknown reasons why someone might be predisposed to have a bad outcome. The reason we randomize, rather than try and make "balanced" groups, is that it addresses both unknown and known factors.
Yes, you can, by chance, get more people who are going to have a bad outcome in one group; about 5% of the time you'll get a p<0.05 finding this way. :P
It’s actually pretty decent. It can make errors in the case of people with extreme muscle mass, or very low muscle mass for their size, or the very short, or the very tall.
But for most people, if you’re over 25 bmi you probably could lose some weight. And at a population levels the errors above average out, even in a smaller group.
People make a big deal over the exceptions to it while ignoring that it is broadly accurate and that exceptions are not as common.
Perhaps, but we don't have reliable data on that. The population of people with high muscle mass is small to begin with and thus hard to study. And the use of anabolic steroids and other PEDs is common in that group, which may be a larger factor in heart disease risk than muscle mass by itself.
At 6'1" BMI seems to say I should be between 140lbs and 185 lbs. I'm currently 165 lbs and feel pretty skinny -- I can't imagine being healthy at 140 lbs! The 185 seems about right -- I've been close to 180 lbs and felt like I could lose a few.
I guess people are downvoting because it’s not super relevant to the discussion, but I have a similar opinion that the BMI normal weight range is unreasonable for me.
I’ve been in these two modes:
1) genuinely overweight with too much fat and not enough muscle
2) nearly overweight according to BMI while very fit, with low fat and high muscle. got here from the other state by exercising a lot, losing fat and gaining muscle.
I think I would have to become totally sedentary again to get rid of my muscle
mass and actually reach the lower end of “normal weight” according to BMI, while starving myself and feeling feeble.
> nearly overweight according to BMI while very fit, with low fat and high muscle
Not knowing you personally, it seems statistically more likely to me that your idea of "fit, low fat, high muscle" is what's at fault here (as opposed to BMI). Sure, you could be an exception. But all things being equal, you probably aren't. (Also maybe I misunderstand - if you mean that BMI was saying you were at the high end of normal then ... isn't that just saying that you're fine?)
(Of course if a medical professional or academic specializing in such matters also thought BMI was inaccurate in your case then I would tend to view things differently.)
(Not OP)
I’m not an athlete anymore, but I used to be. It would be physically impossible for me to maintain my muscle mass and have a BMI considered normal, whilst also having a body fat percentage >5%. I know many other (pretty much exclusively taller men) people in the same situation.
I guess it would be interesting to see how those numbers interacted graphically. Are the "bad" areas (ie high muscle mass at reasonable fat percentage) associated with health problems according to experts? Or should people with significantly above average muscle mass be using a different scale instead?
The claim is that BMI does not differentiate between body lean mass and body fat mass. Things like hydrostatic testing are more accurate for determining body fat mass.
I understand the desire to be contrarian, but BMI is widely regarded as totally obsolete with cheap and accurate ways to actually measure body fat percentages.
It’s well understood that BMI is totally wrong for athletes or anyone remotely muscular.
I assure you that's not my motivation at all. I'm not an expert in that field so I tend to trust the metrics used by the health professionals I encounter.
> BMI is widely regarded as totally obsolete
That is not my impression at all, but again I'm not a subject matter expert here. If you have reliable (ie academic or medical) sources I would be interested in learning more about any current preferred metrics.
> totally obsolete with cheap and accurate ways to actually measure body fat percentages
What do you have in mind? With a bit of searching I haven't found much that's cheap. (Obviously you can take some tape or caliper measurements to improve your numbers but that's neither new nor particularly accurate.)
And pretty terrible in my experience (tested two, one noname and one branded, unfortunately forgot the manufacturer/model number).
First, there is a fundamental constrain that it measures impedance only through legs and a little bit of belly, but no upper body (at least here in .cz, no consumer-grade scales have hand electrodes). I do road cycling as the only sport, and therefore get extremely skewed results as I have strong legs, but the rest of the body is much weaker.
Second, the measurements are almost non-repeatable. You get tens of percent difference across measurements, god forbid if you suddenly have moist feet etc. However, both scales used firmware cheating to mask this noise: once you set up a "profile", it will remember the initial value, and then change the following measurements only slightly. However, set up a second profile (preferably with a slightly modified age etc. to prevent advanced firmware cheating) and you get completely different results.
It isn't anywhere near obsolete, not as far as I've seen in both scientific and medical contexts. BMI remains heavily used in many nutritional and disease related studies and remains a common metric in healthcare and public heath.
It's imperfect, but generally correct. More importantly, it's easy to measure. Accurate except for outliers isn't as much of an issue as you think it is, especially as these are generally already accounted for by its users.
I can believe it. I’m curious what typical body types were like in the hunter/gather societies human evolved in, and whether those are ideal for longevity and quality of life in modern society.
The kind of hunt that humans are believed to have practiced early on was persistence hunting, which consists of chasing prey over long distances until they are exhausted (the gazelle can outrun any human on a scale of minutes, but not on a scale of hours).
> and whether those are ideal for longevity and quality of life in modern society
This seems like the real question to me; I assume pre-agrarian humans were biologically optimizing to survive famine. Not being an expert on the subject, I wonder what sort of tradeoffs are associated with intense exercise regimes (and how the balance ultimately comes out with respect to modern society).
Lacking in raw physical power by comparison, sure. But what health issues do we avoid? Do new health issues arise? Optimality in a complex environment is inevitably a nontrivial trade off; we aren't forced to hunt animals with primitive weapons or contend with widespread famine in the modern world.
Assuming you're male, 140 is the lower bound, so, you know, much lower than that might be considered anorexic, but in the 140s is not necessarily unhealthy per se. That's why it's the lower bound.
I am your height and when I was in my 20s, I think I was in the 140s, later I was a little over 200, and now I am just about 185. So the range makes sense to me, but I've never been far from completely sedentary. I know a pro sports player at ~200 would be very skinny. I think Mariano Rivera was an example.
I understand the objections to BMI comparisons at an individual level (though I believe people think themselves a bit too exceptional too often), but as part of a larger study, I would think it'd make a good additional data point, no?
But then you couldn't easily extrapolate to the population. Well, you could, but you'd require the population to have an understanding of their body fat percentages. BMI isn't ideal, but it's quick and dirty, easy to collect and it should be relatively reliable for the population.
I'm 6' and 84kg (185lbs), I recently had a full health checkup. I do cardio and calaesthebics 90 mins a day during weekdays. I'm lean, not bulky. The top finding of the report. Overweight, consider a healthier diet and more exercise.
It's actually not bad, but it's even better if you couple it with a simple waist circumference measurement (adjusted for sex, and for ethnic background in some circumstances).
> Randomization generated groups with comparable percentage of unfavorable risk factors as there was no significant difference in subjects with at least one risk factor, except for high blood pressure and diabetes mellitus, known risk factors for unfavorable disease progression [2], which were more frequent in patients not treated with calcifediol.
These are HUGE risk factors. Also:
> This pilot study has several limitations as it is not double-blind placebo controlled. On the other hand, in the first studies evaluating risk factors for severe disease and/or death from COVID-19, the possible role of obesity was not considered. Therefore, given the isolation characteristics of the patients, we did not collect the BMI, which would have allowed us to add obesity as a risk factor for severe evolution of COVID-19 [37] It is striking to consider that obesity shares with aging and black or asian ethnicity a surprising overlap as risk factors for severe COVID-19 and vitamin D deficiency.
Yeah, BMI would've been nice too.
Still, check out table 2. Even with these limitations, seems powerful.