Accurate population data is crucial for assessing exposure in disaster risk assessments. In recent years,there has been a signifcant increase in the development of spatially gridded population datasets.Despite these datasets often using similar input data to derive population fgures, notable diferencesarise when comparing them with direct ground-level observations. This study evaluates the precisionand accuracy of food exposure assessments using both known and generated gridded populationdatasets in Sweden. Specifcally focusing on WorldPop and GHSPop, we compare these datasetsagainst ofcial national statistics at a 100 m grid cell resolution to assess their reliability in foodexposure analyses. Our objectives include quantifying the reliability of these datasets and examiningthe impact of data aggregation on estimated food exposure across diferent administrative levels.The analysis reveals signifcant discrepancies in food exposure estimates, underscoring the challengesassociated with relying on generated gridded population data for precise food risk assessments.Our fndings emphasize the importance of careful dataset selection and highlight the potential foroverestimation in food risk analysis. This emphasises the critical need for validations against groundpopulation data to ensure accurate food risk management strategies.