Big data and systematic reviews in nutritional epidemiology

Nutritional epidemiology today is characterized by “big data.” The last 50 years have seen an accumulation of numerous large-scale prospective studies as well as countless smaller epidemiologic studies of varying quality, providing us with a wealth of information on the dietary underpinnings of a wide range of health outcomes, particularly chronic diseases. Such a profusion of data creates a need to summarize findings into a cohesive body of evidence. Systematic reviews, carried out by following a predefined, systematic, reproducible methodology, constitute the preferred method of summarizing literature in nutritional epidemiology. These are usually divided into two categories on the basis of how data from the individual studies are summarized. If the review provides a qualitative summary of evidence, it is simply called a systematic review. If, on the other hand, a review quantitatively summarizes individual study results into one effect estimate, it is called a meta-analysis. Several such summaries of evidence have shown that diets characterized by high intakes of plant-source foods (e.g., whole grains, fruits, vegetables, nuts, tea, and coffee) or high intakes of fish and low-fat dairy, in addition to low intakes of certain animal-source foods (e.g., red and processed meats), sugar-sweetened beverages, and refined grains, are associated with a reduced risk of several chronic diseases, including cardiovascular disease, diabetes, obesity, and certain cancers.1–4 Although the concept of systematically reviewing and summarizing scientific evidence dates back to the early 20th century, its introduction into the field of epidemiology has been relatively recent.5 Despite this, developments in this methodology within the field of epidemiology have advanced rapidly, with the number of systematic reviews and meta-analyses published increasing at an astronomical rate. A PubMed search with the search strategy [“meta-analysis” or “systematic reviews”] results in 12,403 citations in 2013 alone, compared with just 1 citation in …