More shallow science on obesity measures

For those who read the New York Times's stories denigrating BMI as an obesity metric, you have heard only a small part of the story. Their latest senasationalist coverage says that 18% of BMI-obese people are not really obese, with 12% labeled as "healthy obese" and 6% called "skinny fat".

This is a major missed opportunity by an important newspaper in promoting deeper thinking about scientific data.

The first question to ask when faced with those numbers is how is "true" obesity defined? A claim that 18% of BMI-obese people are misclassified is a claim by someone that they know the true state of "obesity". But how is obesity defined? You know what, there is no objective measure. BMI is based on height and weight. Other measures are based on waist size, body fat, and so on.

Those numbers make an assumption that body-fat percentage as measured by the DXA method is God's word on obesity. Someone is making a claim that the 12 percent of people who are obese under BMI but not obese under DXA is "healthy". The claim is not even that these people are "not obese"--they are "healthy". This isn't science.

Further, DXA requires a body scan on an expensive machine while BMI is a measure that can be computed and monitored by anyone at home. That alone makes using DXA as a measure impractical.

Further, there is a huge literature that establishes the correlation between BMI and a variety of health problems. There is very little research that shows DXA as correlated with health problems. (Much of this is because DXA is not readily measured.)

Further, the chart is a bit misleading because officially, BMI-obese is BMI over 30. Between 25 and 30 is called "overweight". Almost all of the "misclassifications" are BMI-overweight so those "healthy obese" are just under the BMI-obese definition. In any case, the worst that could happen to these 12% is that they are asked to exercise, eat healthy, etc. What is the cost of such misclassification? The "skinny fat" group is a bit more concerning but where is the proper scientific evidence proving that this group faces abnormal death risk from fat?

Chapter 2 of Numbersense (link) has the full story on this misguided argument about DXA vs BMI. The bottom line is: our obesity crisis will not be solved by changing how we measure obesity.

 

 

 

Comments

[Joshua]

BMI is a case of using the numbers you have simply because you have them, not because they are the right numbers. It is a prime example of what is wrong with a lot of the "Data speaks for itself" by prognostications around Big Data. Yes, BMI is easy to measure, but then again so are student test scores. Doesn't make either of them the best tool for evaluating a human's health risk or a teachers skill/performance.

As to the correlation, yes it exists, but their is no inherent reason why height/weight ratio should be predictive of health (which is what we are actually interested in). DXA, for its practical flaws, is more precise and accurate and prone to fewer "False Positives".

What the costs of misclassification you ask?
1. Well there is the tendency of many who are overweight to avoid going to the doctor so that they won't get nagged for not doing anything about it. False positives could keep those people from getting checked out as often for OTHER health problems.
2. Dr. OZ exemplifies what is wrong with the American approach to dieting. They are always looking for the Miracle cure that won't involve getting up and walking. How much money is wasted on treatments that don't work. If 18% of those identified as obese via BMI are not in-fact unhealthy, then it is probable that there is roughly 18% more money being wasted on these miracle cures than would otherwise be.
3. There are all sorts of programs out there to help people lose weight who need it, but the funding for these programs comes from somewhere. Having 18% fewer people attempting to take advantage of these programs would enable them to more aggressively target those who actually need them, or it could result in that money being more wisely spent somewhere else for another at-risk group.
4. Finally, we all carry insurance (or should) as result of the new health care laws. Premiums are tied to tables, and BMI is one of those metrics used to calculate your risk. If I'm one of those 18% for whom the BMI says I belong in a higher risk level, but DXA says I don't (which is the more direct measure of that which BMI is attempting to estimate) I'd rather use DXA and pocket the difference.

[Chris]

There is a simple correction to BMI used by the US Navy which addresses one of the concerns that 'big-boned' or very muscular people have higher BMI scores without fat.

For the Navy, only if you have a high BMI, do they do an additional measurement of neck and waist circumference. For women, its neck, waist and hips. Neck circumferences are subtracted from the others to create a score used with weight.

This simple extra measurement corrects one side of the errors.

However, the extra measurements are not universally collected, so cant be used for population health measures today.

[Kaiser]

Joshua: For 80 to 90 percent of the population, BMI and DXA come to the same conclusion. If we do not have effective remedies for the BMI-obese, we do not have remedies for the DXA-obese either. That is a much bigger problem facing us.

Chris: yes, BMI is a simple measure that works for almost everyone. Unusual cases can be teased out with secondary measures.

[Joshua]

@Kaiser, I'm not advocating tossing out BMI, but I don't think your repeated characterization of DXA as a solution in search of a problem is fair or accurate.

For those 10 to 20% of the population for where they disagree, there are real world consequences (financial, psychological, etc.) to that disagreement. As long as we are aware of the short comings, and using BMI primarily for science and indications when an intervention might be appropriate I have no objections. However, the wider the acceptance of BMI without acknowledging its limitations, the more likely we are to see it used inappropriately like as the primary driver of insurance premiums.

There is a lot of data showing that the poor are disproportionately likely to be obese. They are the segment of the population least capable of absorbing higher than necessary premiums due to false positive diagnosis as obese.

@Chris, My brother had to have those extra measurements done before the Naval Academy would accept him because he was so muscular for his height that he came up as obese. However, in his case they did not satisfy, so he ended up having to have a DXA (or it's predecessor) scan to determine his percent body fat before they would accept him. Those additional measurements may help, but they are not foolproof.