Real Science?
“When scientists die, their published papers live on—even if they’re based on lies. Downloaded in seconds from anywhere in the world, fake results continue to steal other scientists’ time, influencing their choice of which research avenues to follow and which trials to design and seek ethical approval for.” (here)
When I wrote my blog last week Taking Apart Bad Science, I had not yet read the article from which I took the quote above. Coincidentally that article and my blog published on the same day.
What Bad Science Is & What It Does
Good scientific findings make the news much less often than headlines based on bad science. Unfortunately, the science you hear on TV or read about in newspapers is more likely to be bad science than real science. What do I mean by bad science? Bad science can be bad for two reasons:
- A research or theory that cannot be replicated or the data collected is used incorrectly by the wrong statistical analysis due to lack of enough academic knowledge or sheer ignorance.
- A research or theory that manipulates the data and/or the statistical analysis to find support for whatever theory or agenda the researchers originally had in mind, regardless of what the data shows
While both types of bad science are harmful, the second type is obviously worse, not just because the data are manipulated deliberately and thus fake information is presented, but also because it is done intentionally and therefore the authors of such papers would never voluntarily admit to wrongdoing. Society is led astray with the wrong information.
Bad science is demonstrated well in the article about Yoshihiro Sato (see above) and by a spoof paper that was accepted by over 100 academic journals, even though the paper had no meaning.
The Ripple-Effect
While on the surface some of this may seem humorous, such bad science has a ripple-effect through every single area that science touches, including funding of future research on connected subjects, the scientists livelihood in the field of that subject, the inability to publish against the spoof article by followers of real science. Crucially in the case of health care, as in the low carbs diets’ deadly effects paper I reported on August 17, 2018, it can hurt millions of sick people whose healthcare will be the wrong type.
From the Sato article, I am showing here an excellent image that demonstrates the ripple-effect of bad science on institutions, funding, etc.
The Ripple Effects of Bad Science
As you can see, the ripple-effect extends to thousands of scientists in the future, basing their hypotheses on the original bad science, and so the bad outcome can be several magnitudes higher than that of the original bad research paper.
This is very similar to the most famous American example of such bad science that was created by Ancel Keys 7-Country Study, in which he cherry picked data from those countries that fit his hypothesis, which was that saturated fat and cholesterol cause heart disease. Ancel Keys’ bad science started off a ripple-effect that still blocks science from advancing further today. Few scientists are funded to go after research that opposes Ancel Keys’ theories and the USDA food guidelines have been based on Ancel Key’s bad data findings. Nearly 50 years after his bad science, researchers whose hypotheses are based on this bad science are still funded and produce more and more bad research papers in many academic journals.
The outcome of the bad science from Ancel Keys’ research has so far managed to create a metabolic disease crisis in most countries of the world, with obesity and chronic insulin resistance skyrocketing, as do health-care related costs for both government and individuals.
The Sham Science of Today
An example of such sham science was published on August 16, 2018 in The Lancet Public Health, announcing that low carbohydrate diets reduce lifespan, thereby starting a new ripple that will change the meaning of all nutrition-researchers past work and future research and livelihood, based on bad science. This article, which is completely faulty from data collection to analysis and with data and statistical analysis manipulations (clearly readable in the paper hiding in plain sight), is exacerbated by media titles, akin to “low carbs diet causes death”.
The ripple-effects of this paper will stop research funds for scientists who have been working for decades showing that low carbohydrate diets reverse type 2 diabetes (here and here), obesity, heart conditions, and much success has already been reported in cancer research, Alzheimer’s disease, and it is also used for seizure control.
It now will prevent doctors and nutritionists from helping their patients reverse their health conditions, who will instead be placed on seriously debilitating medications for life–a life that will be shortened by their disease.
Unfortunately, as the Sato example shows us above, even post-mortem, bad science still may be the basis of science. He may not be alive and his articles may already be retracted, yet his bad science lives on. My suspicion is that even if The Lancet Public Health retracts the article “Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis“, unless it is done really fast, the bad data will be disseminated for years to come, misleading hundreds, perhaps thousands, of scientists, and millions of people’s lives will be at stake.
Your opinions are welcome and are moderated for appropriateness,
Angela
Clueless Doctors & Scientists 
Pingback: Reflections on a Carbage Article | Clueless Doctors fail to keep up with the latest science.
Hi Angela,
Thanks for sharing this post. Do you have any book recommendations for teaching oneself to analyze the details of medical and public health studies and assess their validity?
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Hi Max,
Great question and I wish it were that easy. It takes years of statistics to see some of the problems without hitting analysis from scratch. You may want to get some SAT review on statistics to help you to some point but it will still not make much sense without learning the many applications and tricks of the trade. Unfortunately there is no easy way–that is probably why you see so many papers being published with terrible statistical and conceptual errors passing over reviewers heads. However, there are some simple (relatively simple) tricks one can discover by observing the study. To help you see some of the easier points that you can pick up by simply reading the paper, here are a few to help you:
In this paper, for example, they refer to the age group of the participants at start: 45-69 and the study lasted for 25 years, which means at the end everyone, by definition, is 70-89. From this point on it takes common logic to know that cause of death for this age group can be from:
1) old age
2) infections–such a pneumonia, something very common for old people
3) cancer
4) car accidents
5) heart disease (this would actually be connected to eating high carbs diet)
6) people smoked–that is a huge factor of death that they ignored
7) the survey ignored alcohol–alcohol is a huge factor of death
8) the survey excluded medicines–medication overdose for the elderly in particular, or taking the wrong medication, is a serious cause of death
So immediately one must ask: how on earth did they come to the conclusion that it is the low carbs that reduced their life span? Might there be something missing here that has no explanation?
Another is if you look at the data in the paper, the carbohydrate groups ranges were changed in the middle. First the ranges changed by 10 points, such as from 40-50% and all of a sudden it went to 50-55%… to 10% change to 5% change… why? This is a clear sign that something is not right. In statistics, the population groups to be compared, the cut-off range-size needs to be the same–so 40-50% and 50-60% (so 10 points difference between each). So with such artificial cut off, some groups (the low carbs) had only like 400 people in it whereas the 50-55% and the 55-65% each had several thousands. In statistics, this is a deliberate trick to do because the smaller groups increase in their importance with fewer people in it. This is a trademark of data manipulation. This, I suppose, requires some education in statistics.
Another point that, I think, is common sense: this study was conducted for 25 years but they only visited the people 6 times during the 25 years and they were to recall what they ate the year before with only 66 choices to pick from. This is an impossible task and is bound to give all kinds of errors. Heck, try to remember how many “pats of butter” you ate last year and what is the definition of “a pat”? So food survey questions from memory and the questions, in general, are extremely inaccurate and quite useless.
And the most striking common sense, I think, is that of the 6 data collection, they used only 2 and predicted the rest. One must immediately ask why they didn’t use the data they had—why predict? Something is stinky right there as well. If one has the data: use it!
Another problem, which is more of a statistical issue is that they picked 2 data-points to predict 25 years: connecting 2 points can only be done one way—straight line. So that is not statistics and certainly is not analysis.
So much of what you see in my writing is a mix of my heavy statistics/mathematics background and by no means are my findings evident and easy to most scientists. The kind of analysis I gave here is heavily influenced by my many years of studies in math and statistics. But there are plenty of common logic kind of things one can attack without any education.
I hope it is not disappointing for you to know how much mathematics and statistics studying it takes to see through an article like this upon first reading. I encourage you to read review articles, commentaries and responses, things that analyze articles so you can sort of grow an eye for it.
Good luck applying your common sense too! I would start with that one first.
Best wishes,
Angela
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Hi Angela,
Thanks a lot, that’s great. It gives me some ideas what to start looking for, and beyond that it seems worthwhile to spent quite some time learning statistics in depth.
Best wishes,
Max
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Awesome Max. 🙂 It really is worthwhile but quite a challenge!!! Good luck!
Anegla
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Great analysis Angela. It looks like more bad science has just been published dissing cannabis for pain relief in Oz – again via Lancet Public Health.
Comment: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30143-9/fulltext
Full paper: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30118-X/fulltext
Given it’s right in your sphere of pain management – would be great to see your analysis. Best, Rob
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Thanks Rob. Wow, for being a new journal, they sure are mocking everything they can all at once is short order! I am getting the feeling that they are after sensationalism to catch high ratings. I will read it tomorrow as in my time zone it is actually almost 2 am [[[acting surprised as if time could stand still]]]. Lol… sleep should not be forgotten over this.
Best,
Angela
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Meandered a bit through both urls 👀, but couldn’t find anything about, “dissing cannabis for pain relief in Oz”. 🙈
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me neither… I think he meant to link to a different article. He is a scientist friend in a group I belong so this was accidental I am sure.
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So sorry Angela – I had a previous URL in my clipboard! I was referring to the Lancet Public Health study here: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30110-5/fulltext. There is a linked editorial too at: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30117-8/fulltext. This is what a lot of mainstream docs will see and hear! Apologies for the wrong link! Best, Rob
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No problem Rob. I figured it was a misplaced link. 🙂 We have been talking about a lot of papers of late so no wonder! Thanks for the update of the links. I think this new journal is trying to catch points to grow up; trying to catch up to its parent journal but it is not doing it the right way. Reminds me of bullies.
Have a great day,
Angela
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Checked the right urls now. A lot of talk about cannabis use. To me that’s way to general. What kind of cannabis are they talking about? You know how many strains there are? And was there CBD in it? THC? A combination of the two? Also, the benefits of “cannabis” depend for a great part on the individual using it. Some people get high from a little bit of THC, others not at all, feel loopy, or get extremely anxious. And then there’s the way a person uses it, e.g. smoking, eating, ointment, capsules, “under the tongue”.
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I didn’t read it yet to be honest so cannot comment. However, in the US in some states cannabis can be legally sold and in other states it is illegal. Federally it is illegal everywhere but states managed to pull a few loopholes, as usual. I am quite neutral in this since I don’t know enough about it. One of these days I will have the time to read these two papers. I have soooooooooo much on my plate to do that’s unreal. Long weekend, spending it al on the PC working. 😦
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During my 35 years in Mental health I have observed many Doctors, who are not adequate diagnostitions and, (IMO) use the medication of choice promoted by drug representatives from the pharmaceutical industries as their TX of choice. In many instances certain diagnostic categories also become more popular, maybe to justify the current popular medication. Could it be the drug industry is promoting catagories in Mental health in order to promote a cycle of misdirected (motive) ie.,their Financial goals as reflected in the organizational mission and vision statements. On a more positive note, many medications have been helpful for many patients. Question: do hospital Directors provide Doctors the time necessary to conduct a thorough Diagnostic Assessment?
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Michael I agree to your thinking that financial goals direct many mental (and other) health categories. I am not too familiar with mental disease (other than starting to understand that getting my PhD IS a mental disease lol) but it is certainly true in metabolic diseases. let me give you a couple of examples.
1)A type 2 diabetes (T2D) sufferer is told to eat 3 main meals a day plus 2-3 snack, each filled with carbs. In fact, in some countries/states, T2D are recommended 2 candies or desserts a day. Yet we know that T2D is caused by unresponsive insulin to sugar so does it make sense to feed the T2D more sugar? Great financial planning for big pharma, since this kind of behavior guarantees a long-term patient on all kinds of medicines, insulin, eventually amputations of limbs, etc. Great for the bottom line for all agencies involved: included in this doctors, nurses, hospitals, medical secretaries, pharmacies, even the buses that drive the disabled, not just big pharma. T2D is 100% preventable and reversible (or at least put to remission) by a change of diet. No meds are needed at all. Zero meds. A disease created for meds by meds.
2) MI (heart attack) of an oil-free vegan. Hmmmm… We are always hit in the face by vegans that being vegan is so healthy. Yep. Being vegan is paid for the US subsidies for farmers, processed food makers, etc. The MI of this one person is just an isolated incidence but in my migraine group I have several vegans/vegetarians. Every single one of them had prediabetes/chronic insulin resistance/diabetes (they are all the same things only different depth of the condition). The particular MI patient had a stent put in, placed on a slew of drugs. Then he met me. I sent him to get a CAC (Coronary Artery calcium) scan–a 5-minute CT scan with a couple of heart markers to “freeze” the heart beat on an image so we can see the arteries leading into the heart. his score is insignificant for his age–score 55, which is nothing (mine is 0 by the way and eat a carnivore diet). So what caused his heart attack? Homocysteine. Not one doctor checked his homocysteine.
Why is that important? Because vegans don;t get any B vitamins in their food and oil-free vegans also don’t get essential fats and amino acids. homocysteine is an amino acid buildup that requires B9 (folic acid) to clear it from the blood. Since no one ever checked him and since he never realized he needed to supplement B vitamins, nor did he ever have a genetic testing that would have identified an MTHFR variant for his inability to methylate folic acid into folate, he ended up with a heart attack with a stent if (for no reason).
Did his doctor make a lot of money off of him? You bet! So did big pharma, the hospital, and the drugstore–before he met me! Since he met me and we found out the real reason for his heart condition, we reversed his homocysteine, stabilizing his condition with the proper B vitamin supplements. He is also on the carnivore diet now–forget veggies. He is now biking 40-70 miles a day.. did I say he was 70? Now I do. Is he takign statins now? Nope. Aspirin? Nope. Any medicines? Nope.
So you can see that drugs create illness and disease from nothing.
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Ripple-effects? Among other things, ADHD comes to mind.
Remember celebrity doctor Daniel Amen and his SPECT (single photon emission computed tomography)? Some believe he’s the best there is. Others call him a snake, a fraud, etc. And there you have the problem for the general public. Who to believe? What is true and what is not? How can lay people find out about it? How to separate wheat from chaff?
As long as people are taught they should listen to, trust, and do as their so called experts (leaders, scientists, doctors)) tell them to do, they won’t learn, even resist, to put what is told to them to the test.
Um…….the DSM (all versions) tells us about all kinds of so called disorders, but I couldn’t find one defining/describing cheating scientists 😈
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Yep, and I cannot tell you how many people fight with me about ADD/ADHD to this day–it is not in the DSM now I believe. In terms of Daniel Amen vs nutrition: the public has the upper hand. Heck if I stop eating grains and 90% of my illnesses that I used medication for vanish and I can quit my medication, and one bite of grains gets me into pain, I have proof. It is easier to not led astray the public with nutrition–assuming people dare.
Then there is that famous herd mentality in which the leader takes the whole herd of buffalo to the ditch….
So we have two types of people: leaders who are easily discovered and can be pulled into the dirt, and followers, who will follow anyone into the dirt.
The DSM doesn’t include very many specific mental conditions… lol… being a scientist, like me, is crazy enough. It should be in there. 😉 It should state with warnings and capital letters that GETTING A PHD IS A MENTAL DISEASE–OR WILL BE EVENTUALLY!
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