A new protocol for evaluating putative causes for multiple variables in a spatial setting, illustrated by its application to European cancer rates
- 16 December 2003
- journal article
- research article
- Published by Wiley in American Journal of Human Biology
- Vol. 16 (1) , 1-16
- https://doi.org/10.1002/ajhb.10231
Abstract
We introduce a statistical protocol for analyzing spatially varying data, including putative explanatory variables. The procedures comprise preliminary spatial autocorrelation analysis (from an earlier study), path analysis, clustering of the resulting set of path diagrams, ordination of these diagrams, and confirmatory tests against extrinsic information. To illustrate the application of these methods, we present incidence and mortality rates of 31 organ‐ and sex‐specific cancers in Europe; these rates vary markedly with geography and type of cancer. Additionally, we investigated three factors (ethnohistory, genetics, and geography) putatively affecting these rates. The five variables were correlated separately for the 31 cancers over European reporting stations. We analyzed the correlations by path analysis, k‐means clustering, and nonmetric multidimensional scaling; coefficients of the 31 path diagrams modeling the correlations vary substantially. To simplify interpretation, we grouped the diagrams into five clusters, for which we describe the differential effects of the three putative causes on incidence and mortality. When scaled, the path coefficients intergrade without marked gaps between clusters. Ethnic differences make for differences in cancer rates, even when the populations tested are ancient and complex mixtures. Path analysis usefully decomposes a structural model involving effects and putative causes, and estimates the magnitude of the model's components. Smooth intergradation of the path coefficients suggests the putative causes are the results of multiple forces. Despite this continuity of the path diagrams of the 31 cancers, clustering offers a useful segmentation of the continuum. Etiological and other extrinsic information on the cancers map significantly into the five clusters, demonstrating their epidemiological relevance. Am. J. Hum. Biol. 16:1–16, 2004.Keywords
This publication has 19 references indexed in Scilit:
- Refugia, differentiation and postglacial migration in arctic‐alpine Eurasia, exemplified by the mountain avens (Dryas octopetala L.)Molecular Ecology, 2006
- ENVIRONMENTAL CORRELATES OF POPULATION DIFFERENTIATION IN ATLANTIC HERRINGEvolution, 2005
- The Mantel Test versus Pearson's Correlation Analysis: Assessment of the Differences for Biological and Environmental StudiesJournal of Agricultural, Biological and Environmental Statistics, 2000
- Testing for Regional Differences in Means: Distinguishing Inherent from Spurious Spatial Autocorrelation by Restricted RandomizationGeographical Analysis, 1993
- Genetic diversity, mating systems, and interpopulation gene flow in neotropical Hemionitis palmata L. (Adiantaceae)Heredity, 1992
- Study of spatial components of forest cover using partial Mantel tests and path analysisJournal of Vegetation Science, 1992
- Ecology of Ectomycorrhizal‐Basidiomycete Communities on a Local Vegetation GradientEcology, 1992
- Matrix correlation analysis in anthropology and geneticsAmerican Journal of Physical Anthropology, 1992
- Spatial patterns of human gene frequencies in EuropeAmerican Journal of Physical Anthropology, 1989
- Distances between populations ofDrosophila subobscura, based on chromosome arrangement frequenciesTheoretical and Applied Genetics, 1975