We are always warned that a statistical correlation should not be used to infer causation because either the causal relationship can go either way or both effects may be due to a third cause. The only way to truly determine the direction of causality is to design experiments that are specifically meant to tease it out. But sometimes we can be fooled by multiple, seemingly independent correlations that strongly suggest causality. A recent study of vitamin D deficiency and health illustrates this danger.
Researchers had earlier found that lower levels of vitamin D correlated with a wide variety of non-skeletal disorders such as heart disease, weight gain, mood disorders, multiple sclerosis, and metabolic disorders. This seemed to strongly suggested correlation and that supplementing with vitamin D might stave off those ill effects.
But a report on a new study by Philippe Autier and others that was published in the journal The Lancet Diabetes & Endocrinology finds that rather than lower levels of vitamin D causing these problems, people who had these conditions had lower vitamin D levels. Autier says that “The absence of an effect of vitamin D supplementation on disease occurrence, severity, and clinical course leads to the hypothesis that variations [in vitamin D levels] would essentially be a result, and not a cause, of ill health.”
Another study found that supplementing diets with vitamin D did not help and may even have negative effects, such as increasing the risk of hip fractures. It added to studies that showed that it made no difference in preventing osteoporosis in most healthy adults.
This is important since many older people are told by their doctors to take vitamin D supplements. I too was also told this many years ago but ignored it because in general I am wary of taking medications as a preventative measure.