Due to their feasibility and cost-effectiveness, food frequency questionnaires (FFQs) have traditionally been used to capture dietary intake data in large epidemiological cohort studies. However, data from FFQs are prone to measurement errors, including misreporting of energy intake (EI). The revised Goldberg and predicted total energy expenditure methods have been proposed for identifying misreporters (under- or over-reporters) of EI in order to inform the analyses and interpretation of dietary data. Drawing upon data from Alberta’s Tomorrow Project (n=9,847 men, 16,241 women), we applied the two methods to FFQ data collected using the past-year Canadian Diet History Questionnaire I. Specifically, we examined the proportion of individuals identified as EI misreporters, as well as sociodemographic characteristics and health behaviours associated with EI misreporting. We also compared dietary patterns derived by K-means clustering estimated with and without EI misreporters included.