Comments and Key points
The authors made an assumption that I disagree with. They set their BMI cut-off values to maximize sensitivity for obesity, by saying:
"sensitivity is given more importance than specificity since a false positive is not considered as serious as a false negative."
Paraphrased, this means they think it is more acceptable to call some "normal" people as "overweight", rather than risk under-calling "overweight" people as "normal". This is opposite to how most people think. Most overweight people don’t mind being called normal, but normal people are angered if wrongly labelled as overweight.
They concluded that a BMI cutoff of 25.0 for men and 23.0 for women is optimal, to define "obesity" as a body fat percentage over 25% in men or over 33% in women. (Note, these body fat percentages are commonly used arbitrary values.) Lets restate that. They didn’t use science to test any variations other than 25% body fat in men and 33% in women. They just adopted those numbers because they are “known”. Then they did goal seeking with BMI cutoffs to see how many people would be normal or overweight, as they tried various cutoffs.
I think their terminology is confusing because most people would say these body fat percentages are "overweight" (not "obese").
This study’s data sample is weighted towards young adults, with average age of approximately 31 years.
I have gleaned from this article’s ROC curves, the following possible cut-off values. In my opinion, a Body Mass Index threshold should have about 90% specificity and at least 60% sensitivity, to gain popular acceptance.
This criteria is satisfied for women at a BMI of 25.0. For men, there is no perfect answer, but I would choose 27.0 for men.
Wait. This article is too short and had no references. Even if I could praise the CDC and NIH, nobody would care. Anyway, there’s something still valuable about this article. I like how I was able to figure out that BMI of 27 is probably a better overweight threshold for men, than 25.