Causal inference lies at the center of epidemiologic research. In social epidemiology, two separate approaches to framing cause-effect relations have been considered: the counterfactual (or potential outcomes) framework and the theory of fundamental causes. The relations between these two frameworks have not yet been articulated. In this paper, I review the counterfactual and fundamental cause frameworks, and show how they capture different notions of cause-effect relations. Additionally, I show how the counterfactual and fundamental cause frameworks can be integrated to provide a more rigorous treatment of causality in social epidemiology. In particular, I show how counterfactual quantities can be used to evaluate predictions that follow from fundamental cause theory, assess the relations between and roles of various social resources in a given health disparity, and generate evidence on the potential interventions to mitigate health disparities.