So, in answering my own question (after some consultation with colleagues), I'm thinking that evaluation of the logistic regression product-term p-value in isolation is not informative; as we know the hierarchical principle demands that product terms be interpreted in the context of their component variables. While indicative of a potential statistical interaction the product term itself evaluates only the variability of the exposure effect across levels of a covariate, but not whether the overall effects differ from the null. The latter is determined by evaluating the simple effects using contrasts, which incorporate the additional variability contributed by the product term component variables. 'Eye-balling' the simple effect contrasts generated using the regression equation that incorporated the product term is useful, but unless differences are huge at different levels of a potentially interacting variable statistical testing proves useful to evaluate the homogeneity of the simple effects and whether or not a statistical interaction truly exists. Further thoughts on this issue?