We post about this regularly, and it can be found almost every day in the popular science news and even in the scientific literature itself. GWAS are of course a very good example that we mention frequently.
These results are basically statistical ones resulting from various kinds of sampling. If they are consistent in anything, it's their inconsistency. And therein lies a serious challenge to observational science (including evolutionary biology).
An important part of the problem is that when effects are small (assuming they're real), there's a substantial probability that the excess risk they're responsible for won't be detected in a study sample. Study samples match cases and controls, or some similar kind of comparison, and a minor cause will be found about as often in both groups, and that means by chance may be found either more often in the controls or not sufficiently more often in cases to pass a test of statistical significance.A second problem is complexity and confounding. When many variables are responsible for a given outcome, the controls and cases may differ in ways not actually measured, so that the net effect of the risk factor under test may be swamped by these other factors.
Finally, the putative risk factor may have appeared on someone's radar by chance or by fluke or by a hyperactive imagination, a prejudicial bias, or a Freudian nightmare. We tend to see bad things all around us, and since we don't want anything bad at all of any kind ever, and we have a huge and hungry epidemiology industry, we're bound to test countless things. Puritanism may lead us inadvertently to assume that if it's fun it must be bad for you. Yet, negative findings aren't reported as often as positive ones, and that leads to biased reporting: the flukes that turn out positive get the ink.
We published a paper a while ago in which we listed a number of inconsistent findings. Ken has been told that the existence of this list has made its way into a book, and consequently he's gotten requests for the list. So, we thought we'd post it here. It's out of date now, and we could update it with a lot more examples, but we're sure you can think of plenty on your own.
Wishful thinking and legitimate hopes for knowledge lead us to tend to believe things that are far more tentative than they may appear on the surface. It's only natural--but it's not good science. It's a major problem that we face in relating science to society today.
| Table of irreproducible results? |
| Hormone replacement therapy and heart disease |
| Hormone replacement therapy and cancer |
| Stress and stomach ulcers |
| Annual physical checkups and disease prevention |
| Behavioural disorders and their cause |
| Diagnostic mammography and cancer prevention |
| Breast self-exam and cancer prevention |
| Echinacea and colds |
| Vitamin C and colds |
| Baby aspirin and heart disease prevention |
| Dietary salt and hypertension |
| Dietary fat and heart disease |
| Dietary calcium and bone strength |
| Obesity and disease |
| Dietary fibre and colon cancer |
| The food pyramid and nutrient RDAs |
| Cholesterol and heart disease |
| Homocysteine and heart disease |
| Inflammation and heart disease |
| Olive oil and breast cancer |
| Fidgeting and obesity |
| Sun and cancer |
| Mercury and autism |
| Obstetric practice and schizophrenia |
| Mothering patterns and schizophrenia |
| Anything else and schizophrenia |
| Red wine (but not white, and not grape juice) and heart disease |
| Syphilis and genes |
| Mothering patterns and autism |
| Breast feeding and asthma |
| Bottle feeding and asthma |
| Anything and asthma |
| Power transformers and leukaemia |
| Nuclear power plants and leukaemia |
| Cell phones and brain tumours |
| Vitamin antioxidants and cancer, aging |
| HMOs and reduced health care cost |
| HMOs and healthier Americans |
| Genes and you name it! |
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