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April 20, 2005

Comments

Aric

I've always thought that the fundamental problem with BMI is that it's based on the *square* of your height -- human beings are three-dimensional creatures, so if you scale a linear dimension, the mass should increase or decrease with the *cube* of the scaling factor.

Has anyone ever looked into a BMI based on height^3 instead? Would that give more reasonable results?

Cecil Turner

That's funny, I always assumed they used a cubic scale, but a quick check of their calculator confirms it's square. Which sure doesn't seem to make much sense. I have a hard time believing they're really ignorant of the square-cube law. Is there some esoteric body mass function I'm unaware of?

ryan

I haven't seen the CDC's numbers or equations, but it seems to me that it'd be easy enough to solve the correlation problem between weight and sedentary lifestyle. Simply include a variable for "sedentary" in your regression and you'll have the effect of being overweight independant of being sedentary. (I have no idea if the CDC accounted for this, and since their numbers were so badly skewed before we certainly can't trust them without verifying.)

Cousin Dave

I can well believe that being slightly "overweight" according to the government charts is actually healthier for you, because it appears to me that the proscribed weight targets are actually underweight for most normal people of a given height and build. Weight targets have been revised downward in the last several years or so, creating (intentionally?) the perception of a hugely growing problem where, most likely, no significant problem exists.

ryan

Cousin Dave,

Regarding the perception of a hugely growing problem, the logic of bell curves suggests that any increase at all leads to apparent exponential growths in obesity rates. That is, if the weight of the average person increases even 1 pound every decade, a graph of obesity rates will show an apparently exploding obesity rates, leading to the conclusion that some massive change must be occurring.

Paul Zrimsek

I know of some 8,000-200,000 Iraqis who might agree with the bit about counting deaths not being an exact science.

dsquared

The real trouble here (and this is not a criticism of the study; just an observation that computing actuarial tables is *difficult*!) is that the death rates in this dataset are being driven by people who are old. People who are old and overweight are not likely to have been overweight their whole life. People who are, today, young and overweight, are likely to be overweight for their whole life. So the study leaves us slightly better informed, but perhaps not as much as we'd like, about what we might be doing to ourselves by being so fat. But as I say, this is not a criticism of the study - the issue is intrinsic to the problem of trying to make guesses about mortality rates from causes which have their effect a long time in the future. I suspect that people on this thread are correct to say that what this study shows is that BMI as calculated here, isn't really a good instrument for "overweightness".

btw, Ryan, in principle you could add a variable for "sedentary". However, there is no such variable in the database, so you would be looking at a wait of several years before you could do this even if you added it to the next major survey. And I'm also coming up short when I try to think of some objective criterion which might measure the extent to which someone was sedentary or not.

Victor

What is up with these obesity statistics?

I suspect that we have been and are being fundamentally misled. Simple enough. This is not unique to BMI.

The general approach is methodologically unsound. Just because we can calculate BMI doesn't mean that it is useful. And just because some people on the extremes ARE too obese and it will kill them doesn't mean that otherwise healthy people who resemble them are in danger. And just because some people do NOT resemble them (i.e., low obesity) doesn't mean that THEY are NOT in danger. Just because we can categorize doesn't mean that the categorizations are useful.

So, the number of deaths attributable to obesity is off by a factor of 14. No duh.

kim

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