GOOD FOR YOU VS BAD FOR YOU and
TRUE OR FALSE VS CONCLUSION OR OBSERVATION
Example: a certain vitamin is said to be "good for you". This "conclusion" is based on evidence that a deficiency results in a disease state.
New research however shows that said vitamin does "its good" because our immune system perceives it as a threat and it is the immune system's adaptation that protects us from disease agents and not the vitamin itself. Taking a "poison" may kill us but taking a tiny bit of that poison can help us create antibodies that protect us not only from that poison but potentially other threats as well.
I used the vitamin example, because I believe the point I'm trying to make is especially relevant in highly complex instances where there are many variables, which, of course, is the case with the human body. (and reality in general)
Also, I would like to speak about "scientific evidence", "scientific proof", "anecdotal evidence" and "alternative medicine".
First off, let me acknowledge that proper studies using control groups in a double-blind fashion, with sufficient sample size is the gold standard for attempting to discern facts from speculation.
And of course that entails duplicating these studies in order to replicate original outcomes (or not).
I also wish to acknowledge that in the absence of such standards, the potential for abuse by unscrupulous individuals is enormous, and instances of this abound, however, I'm not prepared to concede that the scientific method is the only possible way for human beings to learn and to make distinctions. While the scientific method represents a quantum leap in the ability to make reliable distinctions in a fraction of the time, humans were able to make distinctions before the scientific method was even devised, albeit much more slowly.
Where I think we've gone wrong is to simply dismiss things altogether because they have not been held up to the scrutiny of the scientific method, rather than try to see whether there may be some basis to what may initially seem to be without foundation.
One of several challenges in utilizing the scientific method is ensuring that potential variables (which may be almost countless) remain consistent and are accounted for.
This can prove to be difficult and in some cases impossible.
For example, as pointed out in the book, "Good Calories, Bad Calories" in discussing the relative merits of various macronutrient ratios to human health, the author correctly points out that you can only decrease one macronutrient in a diet by simultaneously either increasing another macronutrient or reducing overall calories. That will leave you with no conclusion as to whether whatever result is produced was caused by the decrease of one macronutrient, the increase of another or the overall decrease in calories.
This doesn't even take into account that the underlying premise of categorizing all food into three groups is likely in my opinion to be a major oversimplification. There are many ways to subdivide these and depending on what was used to represent a macronutrient category (vegetable oil vs lard or soy protein vs grass fed beef etc) may yield very different outcomes.
I could go on and on:
-animal vs human studies
-difficulty of getting humans to comply strictly over sufficient time period
-maintaining double blind criteria
-selection bias (studies on exercise benefits almost always involve lifelong exercisers as it is very difficult to get them to stop in order to be part of control group or to get couch potatoes to exercise regularly over time, which than begs the question: does exercise make you fit or healthy or are fit and healthy people more likely to be active?)
So even the gold standard clearly has limitations in its applicability.
Most of our population is actually over fed and sleep deprived (misaligned with circadian rhythm), not to mention sedentary, spending hours of the day seated and also not getting much sunshine and fresh air.
In that population, macro nutrient ratios may have significance, but, in my opinion (okay, speculation) be far less relevant with above noted variables being more optimal.
I've sometimes speculated for example that a lot of research with sleep deprived subjects might well be invalidated if people just got enough sleep, sunshine and fresh air.
End of digression.
But adding to the turmoil is the fact that much of what passes for "science" is not actually based on above high standard scientific method.
Epidemiological studies look at patterns within large populations and identify relationships but do not establish whether those relationships are causal, however that fact is often not clearly stated.
Meta analysis looks at groups of studies, presumably to see if there is wide agreement, but the standards between studies, vary greatly.
For example many studies are conducted by university students rather than tenured scientists, and I'm told these are often very poorly designed however they are still often published and then repeated by mainstream media without any disclaimers.
I also am concerned by what I will call funding bias. While some will suggest that certain outcomes are more desirable if a researcher doesn't want to see funding dry up, I will stop short of implying that actual tampering or falsifying of results commonly takes place as I have no direct evidence of such. However my concern is that there will inevitably be more funding available to do certain types of research than others so some theories never actually get truly studied. Those theories are then left with largely only anecdotal evidence which of course isn't proof of anything and so that evidence is discarded due to "not having any scientific basis".
Good luck getting funding to research whether global warming is either not existent, not caused by humans or not detrimental if it does exist. Or to show that cholesterol lowering drugs may not be the best approach to fighting heart disease. (Or more specifically to test those theories, with no bias for either outcome).
(to be continued in part 3)
Purpose of this series:
It is my perception, that many people, including myself as well as many people whose reasoning minds I greatly respect , tend to make assumptions, sweeping generalizations and absolute statements in instances where I feel they are doing so prematurely. This blog entry post has two purposes:
-to challenge their thinking.
-to gather feedback as to errors of reasoning I may be making in this series of entries.