Reducing population stratification bias: stratum matching is better than exposure

Objective: Genetic studies of complex human diseases rely heavily on the epidemiologic association paradigm, particularly the population-based case-control designs. This study aims to compare the matching effectiveness in terms of bias reduction between exposure matching and stratum matching. Study Design and Setting: Formulas for population stratification bias were derived. An index of matching effectiveness was constructed to compare the two types of matching. Results: It was found that exposure matching can paradoxically increase the magnitude of population stratification bias sometimes, whereas stratum matching can guarantee to reduce it. Conclusion: The authors propose two simple rules for genetic association studies: (a) to match on anything that helps to delineate population strata such as race, ethnicity, nationality, ancestry, and birthplace and (b) to match on an exposure only when it is a strong predictor of the disease and is expected to have great variation in prevalence across population strata.