Maps of morbidity or mortality rates, whether considered individually or as a layer in a geographic information system application, invite multiple comparisons of area rates. However, comparisons of rates across different populations require standardization of the age-specific rates to account for differences in population age structures. The indirect standardization method, or equivalently the standardized mortality ratio (SMR), has been recommended for small areas where age-specific rates can be quite variable. Although theoretically equivalent to directly adjusted rates under the assumption of independent age and area effects, indirect summary measures are not comparable across areas when this assumption is violated. We tested the validity of this assumption for the 10 most common causes of death in the United States during 1980-84 and examined the geographic clustering apparent when categorized death rates, adjusted by different methods, are presented as thematic maps. Although overall agreement between the methods was good (rank correlation coefficient > 82 per cent for each cause), when the adjusted rates were classified into quintiles 18 per cent of the states fell into different categories depending on the method of adjustment. Using an internal standard for the indirect method reduced this discrepancy to 4.9 per cent. However, both traditional chi-square tests and a generalized logistic spline model identified significant interactions between age and area for each cause of death, a violation of the assumption required for equivalence of the methods. Potential variation in geographic inferences is illustrated by maps of direct and indirect rates and an empirical Bayes posterior mean, which is a function of these traditionally adjusted rates. Based on these results, we recommend the direct age-adjustment method for rate maps.