Study: Lots of red meat increases mortality risk March 24, 2009 ![]() One big problem: "lots of red meat increases mortality risk" - suggests that cause-and-effect has been established when this kind of observational study simply CAN NOT establish causation and risk. Our Review Summary
This story covers a big study that reports a statistical association between a diet high in red meat and a higher death rate. The report does a number of things well:
The report has two significant shortcomings.
We know we hold the bar high with this expectation that stories explain the quality of the evidence. But it is not simply splitting hairs; it is inaccurate to use language that does not fit the evidence. Journalists and should consumers should review the excellent guest column by Mark Zweig and Emily DeVoto, entitled "Does Your Language Fit the Evidence?" One of our medical editors wrote to me about this topic: "I can tell you, the average practicing physician (one of the presumed target audiences for the medical literature) has a less than firm grasp of this difference! I have been teaching evidence-based medicine for years, and it seems that our residents finally get this by the end, but I don't think it's a skill that was routinely taught in medical training before the past decade or two, nor one that sticks with most docs."None of this denigrates the importance of the study or the quality of the work. But all studies have limitations and news about research should explain those limitations.
Click on Criteria for definitions. ![]() Establish the availability of the treatment/test/product/procedure? - NOT APPLICABLE
This is a study of subjects' voluntary diets, so no "treatment" is involved. ![]() Discuss costs? - NOT APPLICABLE
Again, no treatment is involved. Speculation about the relative costs of high red meat vs. high white meat diets would not be productive. ![]() Avoid "disease-mongering"? - NOT SATISFACTORY
Because the story confuses association with causation, it indeed does commit disease-mongering repeatedly. It may frighten readers into thinking that cause-and-effect has been established when, in fact, only a statistical association has been established. For example, the story says:
It's a common pitfall of such stories. Association does not equal causation. It's not journalists who get it wrong. Scientists and physicians commonly express this incorrectly. But that doesn't make it acceptable. Most stories we saw on this study stated this incorrectly. ![]() Evaluate the quality of evidence? - SATISFACTORY
The report is based on results of a large, prospective epidemiological dietary study. The reporter mentions the important caveats: that the study group may be healthier than the general adult population, and the data is based on self-reports of eating habits, which can be unreliable. We've already commented on the "association does not equal causation" issue, so we won't rule this criterion unsatisfactory for that flaw. ![]() Quantify the potential harms? - SATISFACTORY
The story focuses plainly on the death risks of the diets studied. However, risks are stated only in relative terms, not in absolute terms. We won't penalize the story for that here, but we do under "quantification of benefits." The story makes no claims for the novelty of this kind of research or this general finding. In the second paragraph the report states that these findings "bolster[s] prior evidence" about the risks of diets high in red meat. ![]() Quantify the potential benefits? - NOT SATISFACTORY
The reporter does a fair job describing the study and the findings. The article includes such details as size of the study population, the duration of the study and the method of data collection. But, as already discussed, this kind of study can't establish cause-and-effect or risk. Just statistical associations. However, once it started describing risk, it did that incompletely as well. It compaes the relative risk of death by heart disease and cancer in the highest- vs. lowest-red meat consumption groups for both men and women. But the story suffers because it describes the findings only in terms of relative risk--men who ate the most red meat had a 27 percent higher risk of dying from heart disease compared to those who ate the least, for instance. But the story fails to put these percentages into context. In the example above, about 1.2 percent of the men who ate the most red meat died of heart disease during the 10-year study, compared to .06 percent of those who ate the least red meat Looking at male deaths by all causes, about 4 percent of the red meat group died, compared to about 2 percent of the least-red-meat group. Overall, about 13 percent of study participants died during the 10-year study. This is not to suggest the findings are insignificant. But reporters should always include absolute data to help readers understand the size of the risk an individual faces. (But , as already stated, risk language was risky in this story to begin with.) ![]() Appear to rely solely or largely on a news release? - SATISFACTORY
Given the number of sources cited, the story does not appear to rely on the Archives of Internal Medicine press release or any other news release. ![]() Use independent sources and identify conflicts of interest? - SATISFACTORY
The reporter does an excellent job sourcing the story. Sources include
The reporter gets extra points for including two industry sources. While their thoughts appear very late in the story, including them both makes the story seem--and actually be--more credible. There are no financial conflicts to report. ![]() Compare the new approach with existing alternatives? - SATISFACTORY
In several places, the article appropiately indicates that limiting red meat in the diet may improve health. The reporter carefully avoids implications that more extreme options, such as a meatless diet, would cut death risk more. Total Score: 6 of 8 Satisfactory The U.S. Preventive Services Task Force is considered the gold standard of preventive health recommendations - including on screening tests. It's a good source for journalists and consumers.
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Stories on new technologies like Cyberknife, DaVinci robotic surgery systems, and proton beam cancer therapy often fail to scrutinize the evidence and/or to discuss the costs involved.
Rather than suggesting that everyone should be screened for everything, news stories could explain: "All screening tests cause harm; some may do good."
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Both TIME magazine and BusinessWeek have published terrific stories explaining the importance of the Number Needed to Treat - or NNT.
Knowing relative risk reduction is like knowing you have a 50% off coupon but not knowing whether it's for a Lexus or a lollipop. Absolute risk reduction tells you what the "coupon" is worth. Read more.
The website NoFreeLunch.org posts "a database of health care professionals who have pledged to accept no gifts from industry and to rely on non-promotional sources of information."
To help journalists cover stories responsibly, we post a list of independent experts who state that they do not have financial ties to drug or medical device manufacturers.
We apply the same ten standardized criteria to the review of every story.
We have about 30 story reviewers. Each story is reviewed by 3 different people.
Gary Schwitzer's seven words you shouldn't use in medical news: cure, miracle, breakthrough, promising, dramatic, hope, victim. Read why.
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