self-description 23, although the extent to which this can avoid stratification depends on the population under study and the differences in disease prevalences and allele frequencies across populations 24-27. Further matching on sex can reduce population stratification in situations where there are gender differences in disease prevalence (since many other traits may be gender-related and may in turn be associated with polymorphisms across the genome). Whether or not further matching on other COVARIATES is necessary and actually reduces the potential of population stratification is a question for debate and will depend on the disease in question. Various epidemiological matching schemes were developed for studies of environmental factors, in which environmental confounding is a problem. Although environmental confounding is not generally considered to be a problem for genetic association studies, theoretically, it could still be an issue in GWA studies of very large sample sizes. One could imagine a scenario where controls were matched to cases on ethnicity and sex, but were very disimilar in terms of e.g. socioeconomic background, smoking patterns etc, resulting in phenotypic differences between cases and controls unrelated to the disease in question, but related to the environmental exposure patterns. These effects could possibly show up in
