Interpretation of trends in disease rates using conventional age-period-cohort analyses is made difficult by the lack of a unique set of parameters specifying any given model. Because of difficulties inherent in age-period-cohort models, neither the magnitude nor the direction of a linear trend in birth cohort effects or calendar period effects can be determined unambiguously. This leads to considerable uncertainty in making inferences regarding disease etiology based on birth cohort or calendar period trends. In this paper, the authors demonstrate that changes in the direction or magnitude of long term trends can be identified unequivocally in age-period-cohort analyses, and they provide parametric methods for evaluating such changes in trend within the usual Poisson regression framework. Such changes can have important implications for disease etiology. This is demonstrated in applications of the proposed methods to the investigation of birth cohort trends in female breast cancer mortality rates obtained from the National Center for Health Statistics for the United States (1970-1989) and from the World Health Organization for Japan (1955-1979).