How big is big enough for epidemiology

W A /hen I was approached by the Editor to write this commentary, I had mixed feelings. On the one hand, grappling with the many complex issues that surround the role of "big" and "very big" studies in epidemiology (B/VBE) has increasingly become important given the number of national and international initiatives, both underway and proposed, to conduct such studies. On the other hand, the debate on these issues raises disquieting images reminiscent of both Tom Hanks' movie Big and Jonathan Swift's Gulliver's Travels. As you may recall from the movie Big, the protagonist-Josh, a 13-year-old boy-is transformed by a coin-operated fortune teller named Zoltar into a grown man. Innocent and inexperienced as he is, Josh finds that, although the experience of being grown-up does have some advantages, he longs to return to being a kid. From Swift we recall the perils and rewards of being too big in Lilliput and too small in Brobdingnag and hope that we will not become epidemiologic "Yahoos." Without the aid of Zoltar, the fortune teller, we have no way of predicting the consequences of epidemiology becoming "big," but Swift's satirical insight does forewarn us that one size definitely does not fit all and that size may impact our vision. Over the last few years, I have attended or participated in numerous conferences and symposia on the topic of "big epidemiology," have discussed the prospects and limitations of such studies with many colleagues, have participated in some of the planning for a "big" prospective national study, and have followed the considerations of groups such as the Secretary's Advisory Committee on Genetics, Health, and Society and its Task Force on Large Population Studies. Although I do not want to assert that I am an expert on the subject, I have developed considerable appreciation for all sides of the story and have become more and more skeptical about the need, feasibility, and desirability of such studies. I am also concerned that there may be potential for serious unintended conse quences of very large epidemiologic studies at this time. I will not try to address all of these issues in this commentary and I admit from the outset that simple answers'to complex issues are always somewhat suspect. Of immediate concern is what we mean by "big" or "very big" epidemiology. For the purposes of my comments, I am going to focus on studies with 100,000 plus participants. However, even that does not narrow the field enough, as we can imagine-and there already are examples of case-control studies, cohort studies, population-based registries, collections of biologic samples on a grand scale as in BIOBANK and deCode, and other "big" designs. Thus, one cannot really assess the promises and problems associated with "big" epidemiology without being very clear about what kinds of studies we are discussing. For much of what follows I mostly focus on "big" and "very big" longitudinal studies, because they present perhaps the biggest challenges. "Big" epidemiology should not be confused with interdisciplinarity or multidisci plinarity. Paralleling the trends in many other disciplines, many of us have found that problems of great epidemiologic and public health interest require the input and tools of multiple disciplines, regardless of study size.