The percentage flow-mediated dilation index (FMD%) scales the increase in arterial diameter (Ddiff) as a constant proportion of baseline artery diameter (Dbase). We have demonstrated, albeit with small samples, that the scaling properties of FMD% can lead to biased inferences on endothelial dysfunction. Therefore, we aimed to investigate the underlying rationale and potential bias of FMD% using a selection of new examples from the large (n = 3499) and diverse Multi-Ethnic Study of Atherosclerosis (MESA). In this dataset, we found that smaller values of Ddiff are associated with larger values of Dbase, which contradicts the scaling properties of FMD%. Consequently, FMD% 'over-scales' and naturally generates an even stronger negative correlation between itself and Dbase. Using a data simulation, we show that this FMD%-Dbase correlation can be a statistical artefact due to inappropriate scaling. The new examples we present from MESA indicate that FMD% biases the differences in flow-mediated response between men and women, Framingham risk score categories, and diseased and healthy people. We demonstrate how FMD%, as an exposure for predicting cardiovascular disease, is confounded by its dependency on Dbase, which itself could be clinically important. This critical review, incorporating an allometric analysis of a large dataset, suggests that the FMD% index has a less-than-clear rationale, can itself generate the Dbase-dependency problem, provides biased estimates of differences in the flow-mediated response, complicates the interpretation of the flow-mediated protocol and clouds the causal pathway to vascular disease. These interpretative problems can be resolved by applying accepted allometric principles to the flow-mediated response.