Wednesday, March 14, 2012

The Latest "Red Meat Will Kill You" Scare

A great example of bad science:
"7) As I always consider conflict of interest, it would be remiss of me to end without noting that one of the authors (if not more) is known to be vegetarian and speaks at vegetarian conferences[ii] and the invited ‘peer’ review of the article has been done by none other than the man who claims the credit for having turned ex-President Clinton into a vegan – Dean Ornish.[iii]"

Here's another view:
"...Lastly, although the authors included controls for lifestyle factors I’m highly suspicious that people with so many unhealthy habits are at an increased risk of death primarily because of meat consumption...."
And here's the real nail in the coffin for this bit of propaganda:
“They found that the FFQ predicted true intake of some foods very well and true intake of other foods very poorly. True intake of coffee could explain 55 percent of the variation in answers on the FFQ, while true intake of beer could explain almost 70 percent. True intake of skim milk and butter both explained about 45 percent, while eggs followed closely behind at 41 percent.

"But the ability of the FFQ to predict true intake of meats was horrible. It was only 19 percent for bacon, 14 percent for skinless chicken, 12 percent for fish and meat, 11 percent for processed meats, 5 percent for chicken with skin, 4 percent for hot dogs, and 1.4 percent for hamburgers."

"If your jaw just dropped, let me assure you that you read that right and it is not a typo. The true intake of hamburgers explained only 1.4 percent of the variation in people’s claims on the FFQ about how often they ate hamburgers!”"
That's from Chris Masterjohn via J. Stanton, who comments:
"Stop for a moment and wrap your mind around this fact: the intake of meat reported by the hundreds of studies which use data mined from the Nurses’ Health Study is almost completely unrelated to how much meat the study participants actually ate."
(Emphasis in the original)

In short, the data's bogus, the study's vegan propaganda.

P.S. Gary Taubes takes out the bazooka:

"Back in 2007 when I first published Good Calories, Bad Calories I also wrote a cover story in the New York Times Magazine on the problems with observational epidemiology. The article was called “Do We Really Know What Makes Us Healthy?” and I made the argument that even the better epidemiologists in the world consider this stuff closer to a pseudoscience than a real science. I used as a case study the researchers from the Harvard School of Public Health, led by Walter Willett, who runs the Nurses’ Health Study. In doing so, I wanted to point out one of the main reasons why nutritionists and public health authorities have gone off the rails in their advice about what constitutes a healthy diet. The article itself pointed out that every time in the past that these researchers had claimed that an association observed in their observational trials was a causal relationship, and that causal relationship had then been tested in experiment, the experiment had failed to confirm the causal interpretation — i.e., the folks from Harvard got it wrong. Not most times, but every time. No exception. Their batting average circa 2007, at least, was .000.

Now it’s these very same Harvard researchers — Walter Willett and his colleagues — who have authored this new article claiming that red meat and processed meat consumption is deadly...
Read the whole thing. P.P.S. Ned Kock, the "Health Correlator" and a professional statistician, has a slightly different take on this:
"I am not a big fan of using arguments such as “food questionnaires are unreliable” and “observational studies are worthless” to completely dismiss a study. There are many reasons for this. One of them is that, when people misreport certain diet and lifestyle patterns, but do that consistently (i.e., everybody underreports food intake), the biasing effect on coefficients of association is minor. Measurement errors may remain for this or other reasons, but regression methods (linear and nonlinear) assume the existence of such errors, and are designed to yield robust coefficients in their presence. Besides, for me to use these types of arguments would be hypocritical, since I myself have done several analyses on the China Study data (1), and built what I think are valid arguments based on those analyses...."
However he concludes:
"...But its magnitude is apparently greater than the reported effects of red meat on mortality, which are not only minute but may well be statistical artifacts."
OK, so it sounds like the dismissal is not entirely unwarranted...