Here's what really struck me as funny. As a kind of last-ditch effort to say that we must exercise not just for fun, but for our health, Hutchinson tries to argue that there is bad fat as opposed to good fat, and exercise can focus on getting rid of the bad abdominal fat.
Szwarc has already dealt with this nonsense.
The health risk factors said to be associated with obesity — high blood sugars and insulin resistance, high blood lipids (cholesterol and triglycerides) — and said to lead to diabetes, heart disease and premature death — are all blamed on visceral fat. These health indices have been lumped together and called the metabolic syndrome. The entire metabolic syndrome theory — which is being used to support endless preventive health screening tests and surveillance, "healthy eating" plans, exercise programs and prescription drugs (that are costly for us, but make gobs of money for those who want to manage our health) — is held up by beliefs about visceral fat.
This theory is evidence of the failure to understand risk factors and of how a belief can be built and take on a life of its own by ignoring null studies — in this case, layers of null studies.
Null link: BMI; waist, hip, and arm circumference; waist-hip ratio; waist-height ratio; skinfold thickness; and body fat — and all causes of death
Among the many studies showing no link, the most recent null studies were two independent analyses of the most precise measurements of body size, measurements and body composition available on a large representative sample of the U.S. population conducted by the Third National Health and Nutrition Examination Survey (NHANES III, 1988–1994) of the Centers for Disease Control and Prevention (CDC). As senior scientists at the National Center for Health Statistics at the CDC and the National Cancer Institute reported, the data shows that no higher measurement of body shape or size — BMI; waist, hip or arm circumference; waist-hip ratio; waist-height ratio; skinfold thickness or body fat composition measured by bioelectrical impedance — is predictive of higher risks of dying from all causes.
Nor was there a net benefit of using BMI versus another measurement. The data also found that NONE of the 21 diseases popularly attributed to obesity — those “obesity-related” diseases, including: cardiovascular disease, cancers (colon cancer, breast cancer, esophageal cancer, uterine cancer, ovarian cancer, kidney cancer, or pancreatic cancer) and diabetes or kidney disease — are actually associated with excess deaths at any BMI category, including obese.
UPDATE August 18: Alex was kind enough to respond in detail when I e-mailed him this post, so I will give him more or less equal time:
I certainly didn’t suggest that exercise can focus on getting rid of the bad abdominal fat, anywhere in the article. I did, however, report that researchers believe visceral fat is a better indicator of the potential for health problems than subcutaneous fat. You link to Szwarc’s blog saying, basically, “That’s not true, because I say so.” That an easy game to play. Here’s a link to a study from the journal Obesity called “Visceral fat is an independent predictor of all-cause mortality in men”:
Are there conflicting studies dealing with this question? Of course. It’s a very complex question, and nobody really knows the answers at this point. That’s why you should be wary of anyone – on either side of the debate – who seems to be cocksure that they know that answers. That generally means that they’ve already decided what they believe, and see every study that agrees with their point of view as “confirmation,” and every study that disagrees as “flawed.” That’s what Szwarc accuses her foes of doing, but she certainly does the same thing herself.
You also note in your blog: “…for all I know he has that wrong somehow. (Sandy Szwarc says "the risks associated with the most ‘morbidly obese’ (BMIs 35+) — the uppermost 3% of this Canadian cohort— were statistically the same as those with ‘normal’ BMIs. [RR=1.09 (0.86-1.39, 95% CI) versus RR=1.0.]"”
That’s another great example of data-mining to support a point of view. The main conclusion of the paper, presented in Table 1, was that BMI of 35+ was associated with a 36% greater risk of dying. In Table 2, the authors present seven sub-analyses on factors like smoking, age, gender, and a correction factor related to problems with self-reported weights. Szwarc ignores the primary dataset in the paper (which she doesn’t agree with) and reports only the single sub-analysis that she agrees with, using the correction factor.
I’m certainly not trying to claim that I have all the answers here. I’m just pointing out that reflexively dismissing mainstream scientific opinion as “nonsense” without a thorough understanding of the complexities of the research is just as reductive as accepting that mainstream opinion without healthy skepticism.