This is a guest post by the computational epidemiologist Dr. John Ayers:
Most of us are aware of the “big data” revolution fueled by electronic information. It has been suggested that big data, along with hypothesis-free methods popularized by films such as Moneyball, will allow for an unprecedented growth of knowledge across disciplines, including epidemiology and preventive medicine. While I am a bit more circumspect in expectations (there is no substitute for survey data in many cases), I do believe that electronic data collected for a fraction of the cost of survey data can work hand-in-hand with research derived from more traditional sources.
While sugar-sweetened beverages (SSBs) have garnered much attention in the US given their associations with obesity and diabetes in the Nurses Health Study and a number of other assessments, a key question is whether this effect also translates to low- and middle-income countries where both domestic and imported beverages are becoming increasingly popular. In an article just published in the American Journal of Public Health, we looked at this question using the soft drink industry’s own statistics, merged with comparative survey data on weight status and diabetes across the globe.
In today’s edition of the journal PLoS One, we published an “open access” study on the relationship between sugars and type 2 diabetes. The study was an international analysis applying statistical techniques from the field of econometrics to public health data in order to understand the relationship between sugar availability and diabetes prevalence. It was peer-reviewed by five independent statisticians and diabetes experts. The study can be easily misinterpreted—for example, one doctor made the silly comment: “Well this is just like correlating the number of cups someone owns to their risk of diabetes, which is confounded by obesity”—which reflects that the doctor did not read the study or didn’t understand the statistical methods involved; obviously, as professors who teach statistics all day, we controlled for obesity and dealt with these kinds of issues up front. The study is not a typical simple “correlation study” that is far too common in the medical literature. There are, however, very important caveats to the findings, and some context that’s pretty critical to understand. So we wanted to re-iterate the very careful wording in the study and make sure that the actual study findings made it somewhere into the melodramatic discourse on this subject…