ABSTRACT
Most common human diseases have a multifactorial etiology involving a complex interplay
among genetic susceptibilities and environmental exposures. Studying the “interaction” of
multiple factors on the risk of a complex disease can improve the statistical power to detect
the underlying causative factors of the disease, give insight into their biologic effects, and
lead to public health strategies for prevention. The purpose of this chapter is to describe some
classical andmodern statistical approaches to investigation of interaction in population-based
epidemiologic studies.
