Although studying simultaneous effects of Age, Period, and Cohort (APC) in population and health has a long history, however, Identification Problem has been one of those main obstacles in detecting the three effects in Ordinary Regression Models. Introduction and application of Multilevel Models to address the Identification Problem in recent years, paved the way to precise investigation of APC effects without any need to impose some kinds of constraints into the model, the solution that mostly has been practiced in the APC literature. This paper tried to apply a Cross-Classified Multilevel APC Model to study APC variations in per capita consumption of edible oils in Iran. Investigating data from yearly cross-sections of Household Earning and Expenditure data set for 212035 Iranian households during 1984-2006, the study found that consumption of edible oils has been ever increasing since 1984, recording around 1,62 kg/month per capita in average in 2006-157% increase comparing to 0,620 kg/month of 1984's. Rural settlement, families with higher per capita income, and househead's age, are all positively related to higher levels of edible oil's consumption. A Strong period effect is evidenced on per capita consumption of edible oils during past two decades proceeding 2006, and cohort effect was not as strong as period's however. The methodology exploited in this paper could be applied for studying numerous demographic and any other outcome variables which are under the simultaneous effects of APC. Since Iran has been experiencing an ever-increasing trend in its edible oil consumption since 1984, possible health outcomes of this trend should be addressed by the policies, targeting the population health. Observed trend in oil consumption in Iran is much more similar to those of developing countries, experiencing demographic and nutrition transitions concurrently.