biological markers (Crimmins and Seeman, 2001) have demonstrated strong relationships between biological indicators and traditional demographic variables and health outcomes. In the following discussion, issues are considered regarding the incorporation of DNA collection into studies that were designed to address social science questions.
Incorporation of DNA collection into social science surveys has the potential to add considerable value to such studies. The utility of genetic information is based on the observation that there is variability in the allele form of individual genes that can be measured and that can contribute to variability in health-related outcomes. Potential uses include investigation of genes that have well-established influences, such as the Apolipoprotein E (ApoE) gene and its relationship to risk for Alzheimer disease and cardiovascular disease; identification of genes that had not been previously known to have relationships with the outcome variables; investigation of whether an individual’s genetic status contributes to variability in the way in which other factors influence outcome variables (gene-environment interaction or gene-gene interaction); investigation of correlations between genetic and environmental factors; and other, more novel uses, such as controlling for genetic status to obtain a more accurate picture of how nongenetic factors are related to the outcome variables. For example, by controlling for genetic status at the ApoE gene, a clearer picture could emerge of the effect of other factors, such as cognitive activity, on the development of dementia.
A central question is whether the complexity of the kinds of outcome variables that are considered in social science survey research is too great to be meaningfully considered in a genetic context. This argument might be considered to be valid if one is limited to the Mendelian perspective, which is the notion that genetic influences on a trait consist of the effect of a single major gene. Much early genetics research was concerned with determining the applicability of the Mendelian rules of transmission to an ever-broadening range of phenotypes. The phenotypes were typically dichotomous (presence or absence of a disease condition is a common type of Mendelian trait), and the principal concern was whether the relative numbers of organisms that were assignable to the different categories conformed to expectations derived from the Mendelian theory. Frequency