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Morphometric distances among five ethnic groups and evaluation of the secular trend in historical Libya
Maria Enrica Danubio1, Domenico Martorella, Fabrizio Rufo
1Università de L'Aquila, Dipartimento di Scienze Ambientali, 67100 L'Aquila, Italy. marica.danubio@cc.univaq.it
Abstract:
This study analysed the variations, both in space and time, of 10 body dimensions and 2 anthropometric indexes of 745 adult males belonging to 5 ethnic groups of historical Lybia (el-Haràbi, el-Baraghìts, Marabtìn, Oases inhabitants and Tuareg). The data were collected in the years 1928 and 1932 by Puccioni and Cipriani, two Italian anthropologists. The aim was to reconstruct the biological history of Libya at the time, and thus contribute to the ongoing debate on the evolution of the biological standard of living in developing Countries. The subjects were analysed by ethnicity and by 10-year age groups, after adjusting for age. The results of ANCOVA and Tukey's post-hoc test show that among and between groups there are statistical significant differences overall for armspan, height, head breadth, bizygomatic breadth, biiliac breadth/height and head breadth/head length indexes. By means of the cluster analysis, the el-Haràbi, el-Baraghìts and Marabtìn groups cluster together, whereas the Tuareg and Oases inhabitants cluster separately one from the other and both from the other three ethnic groups. Within-group variations are not very marked in all ethnicities. In general, there is the tendency, not statistically significant, to the reduction and/or stasis of body dimensions from the older to the younger, and the differences are greater among the older than the younger age classes. In conclusion, it can be argued that these groups, all different culturally and geographically, were following the same tendency of stasis of the secular trend of the body dimensions considered in this study, and such stasis persisted since, at least, the last twenty years of the 19th century, when the older were born.
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The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
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