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Category: Health

Taubes on the Weakness of Observational Studies, and a Methodological Rant

One caveat is observational studies, where you identify a large cohort of people – say 80,000 people like in the Nurse’s Health Study – and you ask them what they eat. You give them diet and food frequency questionnaires that are almost impossible to fill out and you follow them for 20 years. If you look and see who is healthier, you’ll find out that people who were mostly vegetarians tend to live longer and have less cancer and diabetes than people who get most of their fat and protein from animal products. The assumption by the researchers is that this is causal – that the only difference between mostly vegetarians and mostly meat-eaters is how many vegetables and how much meat they eat.

I’ve argued that this assumption is naïve almost beyond belief. In this case, vegetarians or mostly vegetarian people are more health conscious. That’s why they’ve chosen to eat like this. They’re better educated than the mostly meat-eaters, they’re in a higher socioeconomic bracket, they have better doctors, they have better medical advice, they engage in other health conscious activities like walking, they smoke less. There’s a whole slew of things that goes with vegetarianism and leaning towards a vegetarian diet. You can’t use these observational studies to imply cause and effect. To me, it’s one of the most extreme examples of bad science in the nutrition field.

That’s Gary Taubes in a FiveBooks interview over at The Browser. Taubes is better known for his book Good Calories, Bad Calories, in which he argues that a diet rich in carbohydrates is what makes us fat and, eventually, sick, and in which he argues in favor of an alternative diet rich in fats.

I really don’t know what kind of diet is best for weight loss, but I do want to stress Taubes’ point about the weakness of observational studies, even longitudinal ones. It is not uncommon for social science researchers to say “Well, we’ve been following these people over time, so we can use fixed effects to control for unobserved heterogeneity.” That is, they control for what remains constant for each unit of observation over time, which is made possible because they have more than one observation for each unit of observation. I have certainly been guilty of that.

Assessing the Impacts of Telemedicine

My Sanford School colleague Manoj Mohanan talks about one of his current research projects, which aims about assessing the impacts of telemedicine in India:

 

Agricultural Policy and Malaria in the United States

From a recent working paper by Barreca et al.:

The Agricultural Adjustment Act (AAA) caused a population shift in the United States in the 1930s. Evaluating the effects of the AAA on the incidence of malaria can therefore offer important lessons regarding the broader consequences of demographic changes. Using a quasi-first difference model and a robust set of controls, we find a negative association between AAA expenditures and malaria death rates at the county level. Further, we find the AAA caused relatively low-income groups to migrate from counties with high-risk malaria ecologies. These results suggest that the AAA-induced migration played an important role in the reduction of malaria.

If you want to know more about the AAA, here is the Wikipedia page for it.