The population health impact of an exposure risk is described as the absolute or relative number of individuals who developed disease due to the exposure. Several risk measures have to be combined to obtain these estimates: The absolute risk in the unexposed population, the relative risk, the population size, and the exposure prevalence. Previous attempts to visualize these dimensions together have failed to consider the exposure prevalence. If the exposure prevalence is known, then the number of cases attributable to the exposure is determined using Levin’s formula. A 3-dimensional (3D) plot enables global visualization of the attributable cases in the exposed population together with the relative risk, along with the exposure prevalence. If, moreover, the uncertainty of the absolute and relative risks can be estimated from the literature, then the 3D plot is extended to a 3D ellipsoid, representing confidence volumes of the attributable cases. The 3D pictogram enables illustration of the different exposures/diseases in comparison and visualization of the health impact in terms of attributable cases. The 3D pictogram is produced using the R package “RGL” with Microsoft Excel to capture the data. The simultaneous visualization of population impact of different exposures/diseases allows for a comprehensive assessment of relevant risk dimensions. Thus, the 3D pictogram can be helpful for public health discussions and prioritization of health policies by supporting communication, comparison, and interpretation of different exposures and risks.