Among subjects who have experienced a biological event, such as menarche, menopause or a delivery, one cannot distinguish the effects of time since the event from age at the event due to the linear dependency among these time variables and age at study ('current age'). This is a well-known problem that also exists in the determination of the short- and long-term influence of childbirth on subsequent disease risk, since one must take into account in the analysis both current age and age at delivery. We describe an approach to assess in case-control studies the effect of a full-term pregnancy on time-dependent disease risk by including nulliparous women in the analysis and considering current age as a modifier of the effect of age at delivery. One then uses current age-specific odds ratio estimates that compare uniparous to nulliparous women to examine whether the relative rate of disease varies over time after a delivery. Analytic options include stratified analysis and modelling with interaction terms for unconditional or conditional logistic regression analysis. As an example, we have applied this analysis to a large case-control study that utilized record linkage between the Cancer Registry and the Fertility Registry of Sweden and that documented a transient increase in breast cancer risk after a childbirth, followed by a long-term reduction in this risk.