Permit me to make a grand statement: science is not about revealing the truth, it’s about learning. And permit me to say something heretical: just because a scientist, as a scientist says something doesn’t make it the truth or even a particularly good conclusion based on the evidence.

One of the news items from last week that prompted these grand thoughts was about research that identified an association between body fat and artery stiffness in teenagers. In fact, the study found the association between artery stiffness and metabolic syndrome generally. The study and the news item picked up on the current hew and cry over obesity in children. The news item concludes by extolling the benefits of weight loss. But as I discuss in latest issue of the Progressive Health Observer, it’s a big leap from associating body fat with illness and making it the cause of illness.

Why isn’t this study about something (say stress, nutrient deficiencies, or pollution) causing artery stiffness AND weight gain? And why exactly is artery stiffness an illness? Isn’t it the body responding to something, say trying to bring circulation back into some kind of balance?

Early in the modern era, I’m talking about 500 years ago, promoters of science like Francis Bacon believed that if you experiment and pay attention and collect enough data, the secrets of nature will reveal themselves. I think we now understand that it doesn’t work that way; that scientists bring a load of assumption to their work. Those assumptions find there way into how scientists design experiments and the conclusions they draw from what they find.

For example, in today’s news there was a report out of the misbegotten Women’s Health Initiative on how estrogen does nothing to improve the quality of life for post-menopausal women. The study was designed using synthetic estrogen unopposed by progesterone on women of an age 10 years past menopause. In addition to the poor design, why isn’t the conclusion that unopposed synthetic estrogen is ineffective?

Allow me answer that question. Studies show that the use scientists make of the literature in their fields is too often narrow and biased. Typically, a small set of studies becomes accepted as the paradigm in their design and conclusions, become stuck, almost literally and become the principal guides to research. That’s what a paradigm is: a really good example of how to do something. In other words, scientists too often tend not to evaluate evidence far removed from what is already accepted. So “estrogen” is made to mean synthetic estrogen and not bio-identical estrogen.

Here’s some good news: science is self-correcting, although not perfectly so. The issues of climate change and global warming are a good example as is the increasing acceptance of Robert Atkins.

This process of what scientists bring to their work isn’t just happening somewhere else, in some lab funded by the NIH or pharmaceutical company. It’s happening when you make health decisions. You evaluate evidence from a perspective. You have your own set of paradigms, of really good examples. Like, what’s a healthy diet? Or what’s a good body weight? Being a good scientist means making sure you’re operating from good paradigms. It doesn’t mean you question everything always. It means you pay attention, stay honest, and don’t look for the truth, look for what you can learn.