Why the truth about bacon can be very refreshing

Figures, percentages and calculations, the media loves to use such data that contain (simple) messages that can be used to create newsworthy stories. News organisations and their audiences are very interested in statistics, especially when they seem to be related to our daily lives (Wormer, 2007). But with the use of statistical data for news comes a risk as well, and that is telling the wrong story. Of course you can discuss the severity of wrong interpretations in statistical data, but the fact remains that one may be misinformed about serious topics. This phenomenon has recently appeared in various news media.


Why bacon seemed to be dangerous
In october this year, the World Health Organisation (2015) announced that processed meat, such as sausages or bacon, can cause cancer. The International Agency for Research on Cancer (IARC) has surveyed over 800 studies on the issue and listed processed meat in the same category as smoking, alcohol, uranium, and exposure to solar radiation (Stats, 2015). The IARC also found that red meat was probable carcinogenic to humans. After these announcements from the WHO, many news organisations started to report about the findings of the study from the IARC: The NOS, the NBC, the AD, the FD, the NRC, the Telegraaf and many more reported about the carcinogenic risks of processed meat. Although this story went “viral” in the news, it appears that not many media sources understood the real implications of the study.

Screenshot 2015-11-27 at 10.32.45

The increase of absolute risk or the risk we already had… Who cares!?
In some of the articles that were published in the news, the media reported about the increased risks of getting cancer by eating processed or red meat. For instance the NOS, Nu.nl, and the Telegraaf reported that people who eat 50 grams or more on a daily basis, would have an increased risk of 18% to get colorectal cancer compared to people who eat less meat.

Now this reasoning was not exactly correct, because this was not what the IARC meant with their publications. When the IARC argued that ‘each 50 gram portion of processed meat eaten daily increases the risk of colorectal cancer by 18%’, they actually meant an increase in risk that we already had (which is less than 18%). To illustrate this, if for instance the risk to get cancer is 10%, an increase of 18% in a 10% risk results in an increase of 1.8%. This means our absolute risk would increase from 10% to 11.8% (Stats, 2015), which is less than the some news organisations reported. The problem is that these findings are less dramatic than the 18% which was eventually mentioned. But there were new organizations that went even further.

Screenshot 2015-11-27 at 10.37.32

Some media, as for instance the Metro and the Daily Mail, reported that the consumption of processed meat was just as carcinogenic as smoking cigarettes. But an infographic from Cancer Research UK (2015) shows that this is absolutely not the case. Although significant results were found that both processed meat and smoking cigarettes causes cancer, does not mean the risk and damage are the same. There is a far greater risk of getting cancer through smoking cigarettes, and the number of cases could be much more reduced by quit smoking than by stop eating meat.

Screenshot 2015-11-26 at 12.54.08

So what does this mean for (data) journalism?
Now this is may seem just one example of a recent misinterpreted breaking news story, but this happens more often than we think. Not only in the news, but also in science there is an attitude of the most dramatic findings are also the most likely to get published (Lehrer, 2010). In science, opportunistic biases or invalid findings has negatively affected the way that the public regards research and scientists. People tend to doubt about the validity of research findings because researchers are suspected to be motivated by political, economic or social agendas (DeCoster, Sparks, Sparks, Sparks & Sparks, 2015). I believe the same thing can happen for journalists and news organisations. However, with the emerge of big data and data journalism, more and more people have accessibility to data sets, and therefore more and more people can act as a journalist. This leads to greater importance of statistics and statistical reasoning in journalism, because the availability of data will give people the opportunity to check everything they read in the news (Nguyen & Lugo-Ocando, 2015). There is a risk that people will increasingly mistrust journalism and the media, if it turns out that the stories they publish are not always based on truth. And with the continued growth of data and analytical tools, we may be close at a point in the future we can reveal how often news organisations tell us the truth or lie about breaking stories.




5 thoughts on “Why the truth about bacon can be very refreshing

  1. I like your approach in explaining the topic human errors in statistic. I was really surprised how many mistakes are made in statistics. In addition the publication bias enhances the publication of dramatic findings. You used great infographic and supporting pictures in your story. Furthermore, your presentation was very clear.

    Liked by 1 persoon

  2. Perfect example of misinforming the readers about very serious topics. Your topic is a bit related to my first blog which stated that drinking a glass of fresh orange is as bad as drinking Coke. In reality it was that drinking too many glasses of orange juice is not as good as you might think. But the journalists brought it very differently. I can see this back in your bacon story and the risk of cancer. How can we avoid these phenomenon in the future? People should be informed correctly and researcher should be honest about their findings and need creating their ideal ‘results’. A possible solution could be to sharpen all rules and regulations regarding misbehavior of researchers. Should it be allowed to penalize researchers when they report the incorrect results?

    Liked by 1 persoon

  3. Really interesting your example about bacon, that makes your whole point more clear than when you tell it in an abstract way. I must say, if I read that there is an increase risk of 18%, I would think the same as the journalists, so in my opinion it is the fault of the scientist. He should have described it in a better way. You can say it’s a grey practise, because he wants people to think that what he has found is really big, but it is actually not. This has everything to do with the publication bias, but I don’t think that this bias can be solved or do you have an idea to solve this bias?

    p.s. I liked your presentation! 🙂

    Liked by 1 persoon

  4. You’ve written a really clear and fun to read post and just like your presentation I liked it a lot. Regarding your statement, I couldn’t agree more. It should be taken seriously that journalists report the truth. I also think that is it just not okay to report results of a study without thoroughly, so knowing that all info in news articles can be better verified in the future is a nice thought.

    Looking forward to your next post!

    Liked by 1 persoon

  5. It comes down to the fact that science has reachd a sad point of reality. It is not about the given that ‘numbers don’t lie’, but about the gact that scientists and journalists are getting more and more ‘creative’ with numbers, so that the story will be more interesting. This shifts to the stories based on selective and results that are extracted while being very quiet about other variables. Initially, science should be ment to decrease the questioning of reality and gain knowledge based on empirical evidence. But maybe we should explore how many studies are biases or based on a desired outcome, and check whether this result is ‘significant’.

    Liked by 1 persoon

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