Referent Selection Strategies in Case-Crossover Analyses of Air Pollution Exposure Data: Implications for Bias

The case-crossover design has been widely used to study the association between short term air pollution exposure and the risk of an acute adverse health event. The design uses cases only, and, for each individual, compares exposure just prior to the event with exposure at other control, or “referent” times. By making within-subject comparisons, time invariant confounders are controlled by design. Even more important in the air pollution setting is that, by matching referents to the index time, time varying confounders can also be controlled by design. Yet, the referent selection strategy is important for reasons other than control of confounding. The case-crossover design makes the implicit assumption that there is no trend in exposure across the referent times. In addition, the statistical method that is employed, conditional logistic regression, is only unbiased with certain referent strategies. This paper reviews the case-crossover literature in the air pollution context, focusing on key referent selection issues. It concludes with a set of recommendations for choosing a referent strategy with air pollution exposure data. We advocate the time stratified approach to referent selection because it ensures unbiased conditional logistic regression estimates, avoids bias due to time trend in the exposure series, and can be tailored to match on specific time-varying confounders.