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The demographic history of a population is a major evolutionary force that shapes the patterns of genetic and, consequently, phenotypic variation. Therefore, integrating knowledge of population history into genetic mapping projects can improve the design of genetic epidemiology studies and help contextualize their findings. Over the past ten years, I have illustrated the power of such an integrative approach in European populations with unique histories, such as those in Sardinia and Finland, and have applied this approach to the study of childhood cancer in Latinos. In this talk, I will describe our recent work integrating population genetics insights with non-genetic information, such as dietary patterns, into genetic epidemiology studies for Native Hawaiians. This work helps us understand why certain populations may have elevated susceptibilities to cancer and metabolic diseases with a genetic component. Furthermore, I will outline our recent efforts to develop methods that utilize the rich information from inferred genome-wide genealogies to better reveal the structure within a population sample. I will also show that this genealogy-based analytical framework can enhance future study designs in both population genetics and genetic epidemiology.