I’d suggest a good book: “The Obesity Myth” by Paul Campo. It was disregarded by many people (such as Walter Willett, PhD) but as research comes out about fit vs. fat (and there is a lot of it) the thesis appears more potent. And it raises the question as to how much good many epidemiology studies on the subject actually provide. (And this is coming from someone with a masters degree in the area and feeling disenfranchised regarding my tuition dollars.)

Not too long ago I was teaching a “community exercise” educational seminar style class. The funds for this class were provided by a large govt. agency (not to be named) and things were going well. Our mission (and the millions of dollars being spent) were to go towards decreasing the amount of our populations overweight and obese prevalence. (Among some other things.)

About the third week, I woke up one morning and turned on the news. The headline was “Overweight people live longer than normal weight people.” Guess who the press release was given by…. yep, the national head of the govt. organization that was paying me to teach people to lose weight and fit into the “normal” category.

Guess what the first question was that night. Right.

That same organization puts out stats like:

“More than 1/3 of adults in the U.S. are overweight or obese according to the U.S. Centers for Disease Control and Prevention. Obesity is a risk factor for diabetes, cardiac disease and certain types of cancer”

oops. guess you know the organization. So the fact that they are saying that “overweight people live longer than normal weight people” makes that statement completely irrelevant. Even according to their own research analysis, long-term study designs and published press releases.

Now if they would say that “x” percentage of people are morbidly obese they could make a better stance within their own programs. But they like to use the 66% stat so they can march on (and justify more grant money for these programs.)

So how does an exercise physiologist interpret their data and programming? What do the statistics actually say about the “causal” factors associated with the data from things like NHANES, etc…

Well. That’s the issue with the interpretation of epidemiological analysis… it shows a relationship, but never a cause and effect. Though they like to suggest those assumptions all the time.

Fit vs. Fat. I say fit if you are concerned about your health. Thin if you concerned about societal pressure and judgment. A very sad, yet often true statement. God bless Richard Simmons!

Your reminder comes at a great time; I ate something like 5 cookies yesterday. Today its lentils, a long walk and yoga…and maybe zero cookies if I can control myself