If, on the other hand, you fall into the "I've been obese since childhood and if I got down to 'normal' weight according to this I will look like a stick, this is crazy talk," category, you may be mistaken. It's normal to have trouble picturing yourself at a very different weight than you're used to, particularly when you are surrounded by overweight and obese people. But BMI is more often than not pretty close to accurate.
cdjs77 wrote: »
I'll post what I posted somewhere else as the "it's meant for populations" statement is a misinterpretation of statistics that really irks me:
People usually misinterpret what is meant when we say a statistical measure is meant for "populations." All statistical measures are meant to determine something about a population, but that doesn't mean they can't or aren't designed to assess risks on an individual level. When statisticians say something is meant to assess risks in a population, what they mean is they have taken a sample from a certain population of people in order to estimate a parameter which can then be applied to assess some probability for other individuals or groups in that population. For example, if we take a sample of university students and estimate their score on a calculus test based on how much they study for it, we have a parameter we can use to predict test scores for the population of university students based on the amount of time they study. This has two important points:
1. Because the sample came only from university students, we can only accurately apply this statistic to the population of university students. We don't know how this applies to other people. Maybe university students already have some sort of knowledge which helps them on the test that the general population doesn't. So studying for one extra hour as a university student may increase your score by 10 percentage points, but only 2 percentage points for those with a lower education level.
2. Just because we say this can only be applied to the population known as university students, doesn't mean we can't use it to assess outcome likelihoods for individuals. We can use it to estimate individual scores with varying degrees of accuracy, but only if the people come from our select population known as university students. Let's say our confidence level is 99%. We can use this to say that, with 99% confidence, Student A who studied for 2 hours will score 10 percentage points higher than Student B who studied for one hour.
BMI works similarly. It estimates parameters for a "population" based on sample parameters, but that doesn't mean it was only meant to assess risks for a population as a whole. It is meant to serve as a easy way to estimate whether or not someone has a healthy body fat percentage based on certain criteria. It is accurate to within whatever confidence level is chosen when estimating these parameters and it applies to whatever individuals come from the population we estimated it from (in this case, adults of European descent). Obviously, there is an error rate, so some people will not fall into the correct categories, but error rates for scientific assessments such as these are usually no greater than 5% total (2.5% at each tail, meaning 2.5% will be classified as overfat when they are not, and 2.5% will be classified as underfat when they are not). The other thing to note is that this estimation was done at a different time, so it's very likely the estimate for a healthy BMI has changed over time, but given the fact that the western world has increased it's calorie consumption and become less active in the past few decades, it's unlikely that BMI overestimates the number of people with an unhealthy body fat percentage and more likely that it underestimates it.
In Short: BMI is a fairly accurate predictor for the average person, and can be applied to assess risk at an individual level. It is also possible that BMI today underestimates body fat percentage categories.
Saying it is a predictor meant for populations is a misinterpretation of how statistics works and can be applied. We use statistics derived for population assessments all the time to assess individual risk, that's how insurance rates are often calculated, and, since insurers do not regularly declare bankruptcy, it's a pretty good sign that these estimates are pretty accurate. If you're not someone who has been an athlete for a few years, BMI is very likely to be an accurate picture of your health risks, and possibly even an underestimation.
Overall, it's an accurate predictor for most people. There is a degree of error as with any statistical prediction. Smokers have a higher risk of lung cancer, but of course not all smokers will get lung cancer. The error rate is also not particularly high. It is also one statistic and, as with any one statistic, it cannot be used as the end all be all for determining health. However if your BMI says you are overweight or obese, it's fairly likely that you are. Whether or not you will face the health consequences associated with this depends on a number of other factors.
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