5 resultados para Mortality data

em National Center for Biotechnology Information - NCBI


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Geographic variation in cancer rates is thought to be the result of two major factors: environmental agents varying spatially and the attributes, genetic or cultural, of the populations inhabiting the areas studied. These attributes in turn result from the history of the populations in question. We had previously constructed an ethnohistorical database for Europe since 2200 B.C., permitting estimates of the ethnic composition of modern European populations. We were able to show that these estimates correlate with genetic distances. In this study, we wanted to see whether they also correlate with cancer rates. We employed two data sets of cancer mortalities from 42 types of cancer for the European Economic Community and for Central Europe. We subjected spatial differences in cancer mortalities, genetic, ethnohistorical, and geographic distances to matrix permutation tests to determine the magnitude and significance of their association. Our findings are that distances in cancer mortalities are correlated more with ethnohistorical distances than with genetic distances. Possibly the cancer rates may be affected by loci other than the genetic systems available to us, and/or by cultural factors mediated by the ethnohistorical differences. We find it remarkable that patterns of frequently ancient ethnic admixture are still reflected in modern cancer mortalities. Partial correlations with geography suggest that local environmental factors affect the mortalities as well.

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Most demographic data indicate a roughly exponential increase in adult mortality with age, a phenomenon that has been explained in terms of a decline in the force of natural selection acting on age-specific mortality. Scattered demographic findings suggest the existence of a late-life mortality plateau in both humans and dipteran insects, seemingly at odds with both prior data and evolutionary theory. Extensions to the evolutionary theory of aging are developed which indicate that such late-life mortality plateaus are to be expected when enough late-life data are collected. This expanded theory predicts late-life mortality plateaus, with both antagonistic pleiotropy and mutation accumulation as driving population genetic mechanisms.