The AddHealth survey currently includes measures of social, behavioral, and genetic characteristics (Udry, 2003). In the recently funded Wave IV data collection, biomarkers (e.g., glycosylated hemoglobin, C-reactive protein levels, blood pressue, lipids, etc.) will be collected, and DNA will also be collected from all 17,000+ participants. These new data, added to the rich longitudinal social environment data already available from adolescence on this sample that is now aged 25-31 will make the AddHealth dataset a valuable resource for transdisciplinary research in the coming years. Care should be taken to ensure that this uniquely valuable dataset is sustained and made available to researchers. The inclusion of parents and the oversampling of twins and siblings make this an especially valuable dataset. Of course, the focus on adolescents restricts the types of health questions that can be addressed, but each dataset has its own strengths and weaknesses. In this case, the strengths are exceptional, and a high priority should be placed on continuing the study and the excellent access that is available to it.
With the increased use of existing datasets comes the challenges that are associated with data sharing, privacy, confidentiality, and the scope of informed consent. Chapter 10 examines these issues. However, it is worth a brief discussion here. The sharing of data is a powerful tool for ensuring that the benefits of large investments in complex datasets are realized and that such datasets are not unduly restricted to a small number of researchers. Careful consideration must be given to the understanding that participants have about who will have access to their information, under what circumstances, and perhaps for what purposes. However, it is difficult—if not impossible—to envision all of the specific ways in which the data could be used. Researchers and funding agencies should give careful attention to how participants are informed of the potential sharing of their information (i.e., data and/or biological samples), the protections in place to guard their privacy, and the uses to which these data might be put. Although there is movement toward greater sharing of data, the need still exists to be attentive to and involved in this fast-moving field.
Another valuable NIH role could be the development of a guide that includes measures of key concepts in data collection about the impact of interactions among social, behavioral, and genetic factors on health. This is not a new idea, but it is one that has proved useful in other fields (NIH, 2005b) and is one that also could help introduce researchers in disparate fields to the methods used by their colleagues. It is not uncommon for researchers to realize the need for measures from another field and, therefore, to add data elements that are either not state-of-the-art or not appropriate for the specific circumstances. To the extent that such a guide includes a discussion of the underlying concepts being measured or the