In 1965, the epidemiologist, Austin Bradford Hill, who helped link smoking to lung cancer, gave a speech where he presented his viewpoints/criteria on how we can arrive at causation from correlation. This lecture was a bit of a game changer at the time given that the tobacco industry was employing statisticians, medical doctors, and even popular science writers to push the idea that the relationship between smoking and lung cancer was merely a correlation, not a causal one. Read More
Is Moderate Carbohydrate Intake the Best?
Recently, a giant paper on carbohydrate consumption and mortality was published in The Lancet. The paper discussed the findings of a prospective cohort study and a meta-analysis of several cohort studies. Studies like this are often the ones that generate the most hype, which is always bizarre to me given that higher quality randomized studies almost never receive any attention. As a result of all the noise (see below), I had to discuss the study in question. Read More
Vitamin E, Mortality, and the Bayesian Gloss
Bayesian data analysis is beginning to gain traction in several fields. Some of those reasons include that it allows individuals to represent uncertainty using probability distributions and it helps them avoid losing information that’s typically lost with point estimates and dichotomization. Bayesian inference also allows for relevant background information to be incorporated into a model using a more continuous approach rather than making binary decisions about what to include. Read More
Does Protein Increase the Risk of Heart Failure?
About three weeks ago, a cohort study was published in Circulation that claimed that protein consumption was associated with heart failure. The press reacted as I expected them to. If you read some of these articles, most of them seem to conclude that a high protein diet is probably not good for you and that Americans eat too much protein. Anyway, back to this study. Given the nature and limits of these types of studies (you can read more about that here) I was a bit skeptical, but also open to the idea that there might be a possible relationship between increased protein consumption and an increased rate of heart failure. Read More
Problems with the Number Needed to Treat
The number needed to treat (NNT) is a popular statistic used in medicine and its use is even encouraged by groups like Cochrane and CONSORT. Why is it so popular? Most believe that the NNT is more understandable than effect sizes like odds ratios or risk ratios or statistics like the absolute risk reduction. The NNT is also believed to convey more meaningful information. In this blog post, I am going to discuss: Read More
How Useful Is Nutritional Epidemiology?
Nutritional epidemiological findings are often the studies that generate the most buzz, but they’re also the ones that get harshly criticized. Some folks will even go out of their way to say that the entire field produces findings that are mostly useless. Here’s what one of the leading meta researchers has to say about nutritional epidemiology: “Nutritional Epidemiology is a scandal. It should just go to the waste bin. Read More
How Did We Figure Out Smoking Causes Lung Cancer?
Proving a cause and effect relationship isn’t easy. Causality is a complex subject, and there are thousands of texts on it, involving philosophical and mathematical arguments that are beyond my understanding. However, I do understand a bit of causality to discuss how we arrive at cause and effect relationships in the sciences. One of the first things often drilled into students in a research methods course is that correlation does not equal causation. Read More