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I’d rather write than talk. Nobody interrupts! Posting monthly or less now--see below. |
My original purpose for this blog, which I started in August of 2019, was to see if I could maintain consistency, to discover what I want to write about, and to find my writing voice. In January, I started a "niche-less" blog at Wordpress.com where I've published weekly. -- Kit’s Kontemplations  . -- I'm preparing to start a Catholic blog on Wordpress.com where I'll post weekly, and another site to put the rest of my writing. I also want to spend more time reading other blogs and offering thoughtful comments, both here on WDC and elsewhere. At most, I will publish once a month at no set time in this blog starting in September of 2020. Thank you to those who have read and rated any posts on this blog. I really appreciate it. I did NOT want to write “about” me on this blog. I wanted to share my interests, discoveries and maybe a few useful insights. If anything I've written helps even one person, whether or not they respond to the post, then this blog has been successful. |
| Shortly after World War II, the number of men dying of heart disease reached epidemic proportions. By the 1950s, medical researchers were focusing on finding the cause of cardiovascular disease. It was clear that the plaque thickening the arteries contained fats and cholesterol which were believed to have been deposited from the bloodstream. Researcher, Ancel Keys first believed that cholesterol in the diet led to cholesterol in the blood. When his research proved that to be false, he shifted the blame to saturated fats, providing no explanation as to how saturated fat raised blood cholesterol levels or how blood cholesterol levels caused plaque to develop in the arteries. A serious problem with nutritional claims is that they are based on associations between two or more factors. It is a logical fallacy that correlation is the same as causation. In other words, the existence of a statistical relationship between fat in the diet and fat in the bloodstream is not enough to establish that fat in the diet causes fat in the bloodstream, much less that it causes plaque to develop in the arteries. When you have two statistical variables, they can be associated or correlated. Association refers to any relationship between two variables and correlation refers to a linear relationship between associated variables. The terms “association” and “correlation” are usually used interchangeably. The relationship between two variables is usually shown in a scatter plot diagram. An association or even a strong correlation between two statistical variables often leads to the mistaken assumption that one caused the other. Here are a few examples of real “spurious” correlations that obviously have no causal relationship:  People who drowned after falling out of a fishing boat AND Marriage rate in Kentucky Per capita consumption of chicken AND Total US crude oil imports Suicides by hanging, strangulation and suffocation AND Number of lawyers in North CarolinaIf the sales of sunglasses and of ice-cream increase dramatically during the same week, it’s a logical fallacy to conclude either that eating ice-cream requires one to wear sunglasses or that wearing sunglasses induces a craving for ice-cream. The correct conclusion is that a third “lurking” variable, a series of hot sunny days caused people to need sunglasses and to buy ice-cream. We don’t know what the lurking variables are when it comes to heart disease but the answer won’t be discovered by researchers following Ancel Key’s example. Keys found the perfect diversion in the discipline of nutritional epidemiology, for which he required no special skills or training. Masquerading behind this covert scientific pretense, he promoted weak associational data from that freshly discovered academic discipline as if it were definitive proof for his — actually Gofman’s — hypotheses. Yet he was fully aware that associational data cannot prove causation except under a few exceptional circumstances, circumstances that Keys’ especially weak associational data could never establish. To prove causation, a scientific approach including a randomized control test must be used. For example, if you want to prove that a new cancer treatment is more effective than a current one, you need two groups of cancer patients who have as many characteristics in common as possible. These patients are randomly placed in either the control group who get the current treatment, or in the intervention group who get the new treatment. If it is to be a “blind” study, neither the experimenter nor the participants know which group they are in since the control group is given a placebo. The outcome for individuals in each group are carefully measured over a specific period of time. The Randomized Control Test (RCT) approach has a number of problems when it comes to nutrition research. With nutrition, no placebo exists for any given food or nutrient. It can’t be truly a blind study if the participant knows what they are supposed to eat, they can do research online and find out whether they are in the control or the intervention group. Adherence is also a problem which grows over time. If participants “cheat” on what they eat much of the time and don’t disclose this, what effect will that have on the results? RCTs are rare in nutrition for a variety of reasons. Only a randomized controlled trial (RCT) can come close to establishing that an exposure to something causes a particular outcome. But RCTs — where researchers deliberately expose people to something and compare them to a group of people who were not exposed — are rare in nutrition. They're too expensive, and it's too difficult to study people over a long period of time in real-life eating situations. It's also unethical to expose people to something if the hypothesis suggests it will cause harm. The epidemiology tools that work in other areas do not work for nutrition. There are too many factors including, but not limited to: stress, income and education levels, and sleep rhythms. There are 250,000 different foods consumed in endless combinations. The sheer complexity prevents researchers from making clear links between diet and health outcomes. The usual method of nutritional research often involves poorly designed studies. The October 9th edition of the Los Angeles Times featured an Op-Ed article by Nina Teicholz describing the “crash and burn” of Brian Wansink, a Cornell University professor and prominent scientist. He served as executive director of the U.S. government’s Dietary Guidelines, which set the standard for healthy eating for the nation. She focuses, not on Wansink, but on the type of science he represents which has provided mistaken dietary advice since the 1980s. She quotes John Ioannidis, a Stanford University professor and evidence-based medicine expert who wrote this about the state of nutritional research: ... given all of the problems with this kind of nutrition research, “Reform has long been due.” The claims of this weak science, when tested properly by rigorous clinical trials, have been shown in two analyses to be correct only 0% to 20% of the time. This means that 80% to100% of the time, they’re wrong. If the problem of confusing correlation with causation wasn’t a big enough problem with the nutritional research method, the major data source are food questionnaires where the participant is required to report quantities and types of foods consumed. I might remember what I ate yesterday but I’d have no accurate idea of the quantity. If I ate three candy bars this afternoon, what do you think the chances are that I’d report that on the questionnaire? Worse, the associational data in nutrition studies are particularly unreliable because the studies depend upon self-reported answers on dietary questionnaires with such queries as: How many cups of pasta did you consume weekly for the last six months? Or, how much did you enjoy that last slice of pizza? Studies have long shown that people misrepresent what they eat — or they simply can’t remember. Obviously nutrition research can’t accurately prescribe what we should eat. So why do we still listen to them? For centuries, people ate based on instinct and common sense. They were much healthier than we are now. Shouldn’t that tell us something? When it comes to information and truth, it doesn’t take much to destroy my trust. One contradiction is all it takes. For me, it was the flip-flop on eating eggs. I’ve always avoided any food plan that severely restricted any food group. It makes sense to eat more “whole” foods that have not been processed and to eat moderately from every food group. One serious problem with the dietary guidelines is the power they have over what is available to us in the supermarket. If we don’t believe the myth that fat is bad and want dairy products with higher fat, good luck finding it! Reflection: How much attention do you pay to what health care practitioners tell you to eat or to avoid? What’s the first nutritional advice you questioned the truth of? Do you give much thought to what you eat or do you just go for what is quick, convenient and tasty? If you’ve chosen a particular diet, how did you find out about it and what promises were attached to it? If you consented to participate in a nutrition study, what aspect of it would you find to be the most challenging?Sources The Diet-Heart Hypothesis, Part 1 Ancel Keys' Cholesterol Con, Part 1 Spurious Correlations Op-Ed: Sloppy science bears substantial blame for Americans’ bad eating habits Randomized trials are no panacea for what ails nutrition research Brainwashed — The Mainstreaming of Nutritional Mythology {x-link:https://www.diagnosisdiet.com/full-article/epidemiological-studies}The Problem with Epidemiological StudiesMonique from Ottawa, Canada No matter what, WRITE! |
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Yes, I know some people do that but I'm a creative writer not a journalist. Poetry sells ... but it's a money-maker for only a few. I write A LOT. Almost 180 pieces since Spring equinox. My goal is 300-400 per year. One year I went over 1,000. I need to do more editing, polishing, sharing, submitting. Writer's block? Who has time for that? I don't.