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The analysis of correlations among distance matrices can aid in assessing common patterns of biological and demographic variation. Distance measures were computed among 12 towns in rural western Ireland using geographic distance, male and female anthropometric distances, and male and female isonymy distances. For anthropometries, several distances were computed using data sets with different degrees of migration. Spearman’s rank-order correlations were computed among nine distance matrices and subjected to principal components analysis with both orthogonal and oblique rotation. The correlations between oblique components were used in a higher-order principal components analysis. The results indicate a hierarchy in the structure of the correlation matrix among distance measures, where anthropometric and isonymy distances tend to form independent axes of variation followed by a male-female difference for both. In all analyses, geographic distance did not emerge as an independent component, but was associated with female anthropometric distances.