The descriptive epidemiology of type 2 diabetes and findings from cohort studies suggest that this disorder originates in large part from a complex interaction between genetic and environmental factors. Determining the details of these interactions using the nested case-control design may be optimal, but is a long-term and expensive strategy. Quicker and cheaper results may be obtained by studying interaction on the quantitative traits that underlie diabetes; however, the power of such studies to detect interaction is highly dependent on the precision with which non-genetic exposures are measured. Unraveling these interactions will undoubtedly shed light on the etiology of diabetes and will, we hope, lead to opportunities for targeted prevention. Recent studies in high-risk groups such as people with impaired glucose tolerance suggest that the incidence of diabetes can be reduced by more than 50% by interventions aimed at changing dietary and physical activity behavior [39,40]; however, it may be that individuals with a particular genotype are particularly susceptible to the negative metabolic consequences of sedentary living, and that they conversely, therefore, would have most to gain from a targeted preventive intervention program. Understanding how to detect these individuals and which environmental factors a program should attempt to manipulate is a major goal of studies that attempt to unravel gene-environment interaction.