1/23 We haven't had a lot to celebrate during this pandemic. But achieving the milestone of offering vaccine to the over 70s, health and care workers and the most clinically vulnerable just before target date is a huge cause for celebration, given the scale of the achievement.
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I applaud the #EUCancerPlan *BUT* caution: putting #meat 🥩 (a nourishing, evolutionary food) in the same box as 🚬 to solve a contemporary health challenge, would be basing policy on assumptions rather than robust data.
#FollowTheScience yes, but not just part of it!
THREAD👇
1/ Granted, some studies have pointed to ASSOCIATIONS of HIGH intake of red & processed meats with (slightly!) increased colorectal cancer incidence. Also, @WHO/IARC is often mentioned in support (usually hyperbolically so).
But, let’s have a closer look at all this! 🔍
2/ First, meat being “associated” with cancer is very different from stating that meat CAUSES cancer.
Unwarranted use of causal language is widespread in nutritional sciences, posing a systemic problem & undermining credibility.
3/ That’s because observational data are CONFOUNDED (even after statistical adjustment).
Healthy user bias is a major problem. Healthy middle classes are TOLD to eat less red meat (due to historical rather than rational reasons, cf link). So, they
4/ What’s captured here is sociology, not physiology.
Health-focused Westerners eat less red meat, whereas those who don’t adhere to dietary advice tend to have unhealthier lifestyles.
That tells us very little about meat AS SUCH being responsible for disease.
#FollowTheScience yes, but not just part of it!
THREAD👇
\U0001f534LIVE \U0001f4c5Today \u23f012:00 CET
— EU_HEALTH - #EUCancerPlan (@EU_Health) February 3, 2021
We are presenting today the #EUCancerPlan as part of a strong \U0001f1ea\U0001f1fa#HealthUnion
Follow the presentation live here: https://t.co/Cr8ATvzNkg#WorldCancerDay pic.twitter.com/zdByuklWV6
1/ Granted, some studies have pointed to ASSOCIATIONS of HIGH intake of red & processed meats with (slightly!) increased colorectal cancer incidence. Also, @WHO/IARC is often mentioned in support (usually hyperbolically so).
But, let’s have a closer look at all this! 🔍
2/ First, meat being “associated” with cancer is very different from stating that meat CAUSES cancer.
Unwarranted use of causal language is widespread in nutritional sciences, posing a systemic problem & undermining credibility.
3/ That’s because observational data are CONFOUNDED (even after statistical adjustment).
Healthy user bias is a major problem. Healthy middle classes are TOLD to eat less red meat (due to historical rather than rational reasons, cf link). So, they
4/ What’s captured here is sociology, not physiology.
Health-focused Westerners eat less red meat, whereas those who don’t adhere to dietary advice tend to have unhealthier lifestyles.
That tells us very little about meat AS SUCH being responsible for disease.
You gotta think about this one carefully!
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)
The test is 99% effective in detecting both sick and healthy people.
Your test comes back positive.
Are you really sick? Explain below 👇
The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through
Really doesn\u2019t fit well in a tweet. pic.twitter.com/xN0pAyniFS
— Dr. Lena Sugar \U0001f3f3\ufe0f\u200d\U0001f308\U0001f1ea\U0001f1fa\U0001f1ef\U0001f1f5 (@_jvs) February 18, 2021
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.
👇
Here is what we know:
- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative
Assuming 1 million people take the test (including you):
- 100 of them are sick
- 999,900 of them are healthy
👇
Let's now test both groups, starting with the 100 people sick:
▫️ 99 of them will be diagnosed (correctly) as sick (99%)
▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)
👇
