The concept of causation is central to clinical research and practice. The health science literature on causality, largely contributed by epidemiologists, has examined the population-based question of whether an exposure can cause a given health outcome. Most of this literature has focused on criteria for assessing causality, rather than attempting to define it. Moreover, the population-based approach is rather distant from the individual persons in whom causes must act, which has led to different perspectives on causality among epidemiologists and health policy markers, on the one hand, and clinical practitioners and the lay public, on the other. We attempt to bridge the gap between these perspectives by defining three probabilistic causal propositions based on the locus (individual vs population) and time frame (past vs future outcome) to which they refer, beginning with the individual in whom a health outcome has already occurred ("retrodictive" causal propositions, i.e. It Did) and proceeding to "potential" causal propositions (It Can) for populations and "predictive" causal propositions (It Will) for individuals or populations. We conclude by showing how attention to these distinctions may help avoid common pitfalls that can impair clinical or public health decision-making.