Life-course epidemiology seeks to better understand the mechanisms that lead to the development of chronic diseases. An example is the mechanism leading from body size to coronary heart disease (CHD); one way to acquire a better understanding of this mechanism is to investigate to what extent it works through other risk factors. In this paper, the dynamic path analysis model is presented as a tool to analyze these dynamic mechanisms in life-course epidemiology. A key feature of dynamic path analysis is its ability to decompose the total effect of a risk factor into a direct effect (not mediated by other variables) and indirect effects (mediated through other variables). This is illustrated by examining the associations between repeated measurements of body mass index (BMI) and systolic blood pressure (SBP) and the risk of CHD in a sample of Danish men between 1976 and 2006. The effect of baseline BMI on the risk of CHD is decomposed into a direct effect and indirect effects going through later BMI, concurrent SBP, or later SBP. In conclusion, dynamic path analysis is a flexible tool that by the decomposition of effects can be used to increase the understanding of mechanisms that underlie the etiology of chronic disease.