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I don't know what pile of straw you've found your "pro-CICO people" from, but in my experience, they are happy to point you directly to places where you can see the variability for yourself. I'll even preempt any digging in the straw you might do to claim that "pro-CICO people" simply reject the concept of metabolic adaptation, because they actually write entire articles about it, what it is, what it isn't, and what it practically means for people.
At the end of the day, they say things like that the Cunningham equation (or a few others) actually do a pretty good job of getting you to the right ballpark, but then you probably need direct observation if you want to really nail down where you are with precision. My wife and I proceeded with direct observation, and sure enough, the population-based equation estimates got us pretty darn close, but what was really incredible was that even though the data was insanely noisy (which was expected, and I have enough background in numerical analysis to know how awful that noise would be for estimating derivatives), the trend line over a couple years of tracking (through periods of cutting, periods of maintaining, and periods of gaining) was bang on at exactly 500cal/day = 1lb/wk... for both of us. The "pro-CICO people" that you strawman are actually doing things like putting direct observation into an app rather than making ridiculous claims like there being no variability whatsoever.
The thesis of CICO is that it's not just a useful guide, but literally an iron law of the universe. Ever heard of something called thermodynamics? So it's not obvious to me how a "metabolism" (whatever that is) can conjure up, or delete, energy or mass.
Personally I found CICO useful for losing weight and not useful for gaining weight. But, based on my own direct observation, you'll probably just call me a liar or say that I was tracking wrong. That is of course, what every CICO advocate does immediately. After all, CICO is (apparently) totally perfect and based on thermodynamics.
Perhaps you should read the link, discussing variability in the calories out portion. Saying that CICO is thermodynamics and that there is variability at least in CO is perfectly consistent. I'm not sure what windmill you think you've slain.
I will not call you a liar, but this is indicative of the mindset with which you are entering this conversation. You have tarred the people you hate with a scarlet letter and then simply closed your mind to any meaningful discussion. Very bad epistemic hygiene.
I don't hate CICO advocates, I just don't know if there's a constructive conversation to be had with people who consistently respond to everything with "you're lying" or "you must have missed something". This is also epistemic closure - anyone who struggles with CICO is always accused of lying.
As I've already said I did get some benefit from calorie tracking. I think it's useful even just to learn how many calories are in your food. So of course, I don't hate CICO, but of course this kind of defensiveness is also very typical of CICO advocates.
If the defense of CICO epicycles is that "uh, actually sometimes people just burn extra calories for no reason", that's not that compelling. Isn't the point of CICO that it should always give you predictable results, and that if your results are wrong, it's because you made a mistake or are lying?
The fact that CO is difficult to accurately assess in the real world - even moreso than CI, which is itself very difficult to accurately assess - isn't some epicycle of CICO, it's just a component of it. CICO does always give you predictable results, as long as your predictions are based on actual fact, i.e. the simple fact that you can't accurately assess CO in the real world.
In practice, the vast majority of CICO is directed at weight loss, which means simply making CI < CO. This can be accomplished consistently even without accurate measurements of either, by making them accurate enough such that the error bars don't overlap. That is, you can get a somewhat reasonable estimate for upper bound of CI by taking the nutrition label of every food you eat and then doubling it. And you can get a somewhat reasonable estimate for lower bound of CO by calculating your BMR and adding on half of what those caloric expenditure tables for exercise or your fitness band or smartwatch or your stationary bike says. Make the upper bound estimate of CI lower than the lower bound estimate of CO, then you can have fairly high confidence that you've gotten actual CI lower than CO.
For weight gain, the fact that the body has ways of physically refusing to take in more food or causing the food to pass through without nutrition being extracted makes things trickier, I believe, but that's an area that I've not had the privilege of needing to explore.
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You're mashing up two different things which should be clearly distinct at this point in the conversation. There is no epicycle that there is variability in CO. There is just variability in CO, given the things we are generally able to control for. That's just the data and the labels we have to go with it. I've seen some attempts to quantify things like calories consumed by individual organs and how that correlates to their sizes and such, but on a population scale, we're basically never going to have measurements like that to control for, nor is an individual likely to go to the effort of taking precise measurements that could, in theory, more precisely predict individualized CO. So, absent that, we take a few factors that are easily measurable, fit the curves, see that they work pretty well, with some variability. Before, you had been claiming that this population-level variability was flatly denied by your enemies. Now, you think it's an epicycle. These are both Obvious Nonsense claims. This is just data and empirics.
Now, what you're stuck on is the second part, given that the population-level curves aren't able to precisely control for everything, how do these curves and the variability they contain provide predictable results for individuals? Well, you need individualized observational data to figure out where you are within that variability. The population-level curves get you close, but if you want precision, you need good individualized observational data. My experience with tracking for my wife and I is that the data is extremely noisy and must be handled with care. But after that care, the trend line is, indeed, 500cal/day = 1lb/wk, only with very noisy measurements. I don't think either of our maintenance levels from the trend line were precisely what the population-level data predicted, but they were both pretty close, and our tracking decisions were probably suitable to explain the minor deviation. It's this part, after you've already gotten a lot of individual observational data to avoid the population-level variability problem, where the vast majority of people (and all tightly-controlled lab experiments) get predictable results. The population-level variability doesn't magically jump into this part as an epicycle.
My actual experience of CICO was exactly the opposite. It worked initially but when I tried to bulk, I found it predicted weight gain very poorly. Since CICO is of course, perfect and never wrong, it must have been a mistake I was making, and since I couldn't find my mistake, I decided to spare myself the stress and anxiety and stopped tracking.
I am sorry you had that experience. Unfortunately, it is probably unlikely that I will be able to figure out whatever was going on in your individual case through comments. But I'm not sure what is supposed to change about my understanding of the published literature from your example.
FYI, my personal experience included periods of gaining, and my trend line from the noisy data was bang on at 500cal/day = 1lb/wk on that side, too (and my wife's). But I'm not sure how you might/might not want to update your understanding of the published literature based on my example, either.
I have a similar understanding of the published literature to you, I think - but knowing that planes crash when their altitude decreases is not enough to avoid crashing a plane. The published literature tells us, for example, that calories out should probably exceed calories in by about 500 and then you'll lose weight. But as I've heard in this thread there is no reliable way to measure either, calories out has been shown to change in response to calories in, so you are in effect chasing a constantly moving target.
What useful information are we left with? Pretty much, eat more or less until you get the desired change in weight, and that "more or less" refers specifically to calorie content. Which is a reasonable start.
But all this amounts to is a fine motte. The actual bailey of CICO is that everyone who follows a calorie tracker and gets an incorrect result is lying or denying science, that it's physically impossible to fail to lose weight on 1800 calories or to fail to gain weight on 4000 calories, and that hormones don't affect weight.
Good news! The CICO folks that you dislike have entire articles on how this works, what the ranges are, how to understand it, etc. To steal a little bit of the plane analogy from below (not adopting it entirely), when a plane uses fuel, its dynamics change, too. That doesn't mean that physics don't work or that we can't understand how to use the system effectively.
Much more than that. Once you dial in where you are within the population-level variance, you get remarkably good predictions for how the noisy process works. I have a lot of background in stochastic systems, too, and I think this part trips a lot of people up. It's not easy to filter noisy data appropriately or to even understand the right timescales to pick for your filters. That's why the CICO people don't jump to an imaginary bailey and instead do things like creating an app that has a lot of filtering built-in.
Even though my degrees are actually in aerospace, I'm not sure the plane analogy is the best one for this part. Instead, maybe let's push things to a bit of an extreme with an analogy to semiconductor fabrication. In this case, someone could have some familiarity with the published literature in semiconductor physics, could go through a variety of published patents, but then when they try to make their own semiconductors, they fail. One response could be to claim that everyone in semiconductor physics is lying to them or just blaming them for doing it wrong; that those baddies are claiming that semiconductor physics "just works and must be perfect" or whatever. Another response could be that there are parts of the process that do require some specialized background knowledge to do precisely, perhaps some experience with tuning certain processes along the way that aren't always shouted to the rooftops in the public domain.
I think that careful filtering of CICO data also requires some mathematical experience if you want mathematical precision. I haven't actually used the particular app that I linked, nor am I privy to the tuning/filtering decisions they've made, but I'm familiar with the work of the guys who made it, so I have a reasonable amount of trust that they're doing a pretty good job at tuning it in a way that will work pretty well for most users. But the good news is that most people don't need mathematical precision here (unlike in semiconductor fabrication). I think @07mk goes a bit overboard in how wide of an error bar is needed, but for most people, you really can just hand-tune a bit with a little fudge factor, not needing to be super precise on your filtering, and see the results. But at the same time, if you do get into the details of tuning filters well (or offload that work to something like that app that probably does that ok enough for you), then you probably do get pretty precise predictions.
A lot of this comes down to error analysis and ranges for estimation. One group of CICO-haters say that it's just flatly impossible to filter in a way that gets you even remotely close to usable data without metabolic ward precision. Another group of CICO-haters say that any quantity of error violates their strawman that "CICO is perfect in every way". Most of the time, they don't put numbers to their error ranges. They don't put any numerical analysis tools to the question of how much data must be collected to achieve some O(epsilon) error or how different filtering schemes affect this. Frankly, many do fall into a small number of common 'traps', just like how undergrads in a numerical analysis course often fall into a small number of common 'traps'. I am lucky in that I have the toolset to get a lot more mathematical precision than most people, so I don't have to learn all of that from scratch or trust somebody else's filter. And when I did those things for an n=2 experiment, knowing all of the caveats about how noisy things are and how difficult the numerics is, my technical assessment was that I was shocked by how precise it turned out to be.
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Dictating the food that one eats and the calories one expends is nowhere near as complex as piloting a plane. There's a reason why there are very few plane pilots, most of whom had to train a long time even before ever flying a real plane, while basically everyone, even many children, choose what to eat and how much to move.
And it absolutely is possible to get reliable enough measurements of both in order to accomplish certain goals, specifically weight loss. It's not that common for packaged foods to have multiple times the calories as their label indicates, and so one can pretty accurately place an upper bound in CI by adding up all the calories in those labels and then applying some multiplier >1. I like to use 2. It's also not that common for one's real caloric expenditure to be lower than their calculated BMR, especially if they do things like stand or walk during the day, so one can pretty accurately place a lower bound in CO by just calculating BMR. Get the upper bound of CI lower than CO, and you can be quite confident that true CI is lower than true CO. For weight gain, it's more tricky, because of the physical ability of the body to reject food, as well as its ability to involuntarily expend energy through heat, but generally CICO isn't talked about when it comes to weight gain; people looking to gain weight are rarely just concerned with weight, but rather specifically gaining muscle more than fat (or even not gaining fat at all or even even losing fat, which, despite some myths, are possible simultaneously while gaining muscle), and the composition goals tend to take precedence over just pure mass goals, which tack on a whole host of other requirements. The mirror is also true, of course, in that people looking to lose weight tend to want to lose fat while maintaining muscle, but due to how weight affects joint stress, simply losing the mass is often beneficial in itself even if it's muscle, and general everyday life often tends to provide enough exercise to maintain enough muscle (still, a lot of the advice around weight loss does push people towards doing resistance training to better help to maintain that muscle while losing weight).
Are there any specific comments on this forum that are in this bailey? Without specific references to such, this just seems like, at best, weakmanning, and likely strawmanning, based on what I've observed from people talking about CICO.
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Well, yes. The problem is that CO is not directly measurable outside of a metabolic ward. That's why successful CICO approaches dial in CI (which is measurable) to hit a certain rate of weight change (also measurable).
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