@article{GomulaKozielGrothetal.2017, author = {Gomula, Aleksandra and Koziel, Slawomir and Groth, Detlef and Bielicki, Tadeusz}, title = {The effect of neighboring districts on body height of Polish conscripts}, series = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, volume = {74}, journal = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, number = {1}, publisher = {Schweizerbart}, address = {Stuttgart}, issn = {0003-5548}, doi = {10.1127/anthranz/2017/0701}, pages = {71 -- 76}, year = {2017}, abstract = {The aim of the study was to investigate the correlation of heights of conscripts living in neighboring districts in Poland. The study used 10\% of a nationally representative sample of 26,178 males 18.5-19.5 years old examined during the National survey of Polish conscripts conducted in 2001. The sample represented all regions and social strata of the country and included 354 different districts within 16 voivodships (provinces). Analyses were performed with the R statistical software. A small but significant correlation (0.24, p < 0.0001) was observed for height between 1st order neighboring districts. Correlations decreased with increased distances between neighboring districts, but remained significant for 7th node neighbors (0.18, p < 0.0001). Regarding voivodships (provinces), average height showed a geographical trend from the northwest (relatively tall) to the southeast (relatively short), and the correlation was stronger for first order neighboring provinces (0.796, p < 0.001). This study revealed clusters of tall people and short people, providing a support for hypothesis of the community effect in height. Small correlations between 1st order neighbors than in another country (Switzerland) may be associated with differences in geography, since in Poland there are no natural barriers (e.g., mountains) and road infrastructure is well-developed.}, language = {en} } @article{BentsRybakGroth2017, author = {Bents, Dominik and Rybak, Alexander and Groth, Detlef}, title = {Spatial conscript body height correlation of Norwegian districts in the 19th century}, series = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, volume = {74}, journal = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, number = {1}, publisher = {Schweizerbart}, address = {Stuttgart}, issn = {0003-5548}, doi = {10.1127/anthranz/2017/0700}, pages = {65 -- 69}, year = {2017}, abstract = {Background: We investigated height of Norwegian conscripts in view of the hypothesis of a "community effect on height" using autocorrelation analysis of district heights within a time-span of 20 years at the end of the 19th century and correlations between neighboring districts at this time. Material and methods: After digitalizing available body height data of Norwegian draftees in 1877-1878, 1880 (averaged as 1878), and 1895-1897 (averaged as 1896) we calculated the magnitude of autocorrelation of body height within the same municipality at different time points. Furthermore, we generated three different neighborhood networks, (1) based on Euclidean distances, (2) a minimum spanning tree build on those distances, (3) a network founded on real world road connections. The networks were used to determine the correlation between body height of neighboring districts depending on the number of edges required to connect two municipalities. Results: The autocorrelation value for body heights was around r = 0.5 (for all p < 0.001) in the years 1878 and 1896. The correlation between neighboring districts varied in the Euclidean distance based network between 0.47 and 0.27 approximately for both years in a sorted order, descending from nearest (0-50 km) to farthest (150-200 km, for all p < 0.001). First order neighbors in the minimum spanning tree network correlation was 0.36 in 1878 and 0.42 in 1896 (for all p < 0.001). The values of neighbor correlation in the road connection based network ranged in 1878 from 0.42 (first order neighbors) to 0.17 (forth order neighbors, for all p < 0.01) and in 1896 from 0.46 (first order neighbors) to 0.12 (forth order neighbors, for all p < 0.05). Conclusion: This initial study of Norwegian conscript height data from the 19th century showed significant medium sized effects for the within district autocorrelation between 1878 and 1896 as well as medium neighborhood correlation, slightly lower in comparison to a recent study regarding Swiss conscripts. Digitalizing more data from other years in this and later time spans as well as using older road and ship connections instead of the actual road data might stabilize and improve those findings.}, language = {en} } @article{Groth2017, author = {Groth, Detlef}, title = {Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network}, series = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, volume = {74}, journal = {Anthropologischer Anzeiger : journal of biological and clinical anthropology ; Mitteilungsorgan der Gesellschaft f{\"u}r Anthropologie}, number = {1}, publisher = {Schweizerbart}, address = {Stuttgart}, issn = {0003-5548}, doi = {10.1127/anthranz/2017/0703}, pages = {81 -- 88}, year = {2017}, abstract = {Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later, of the whole network increased by up to 0.1 cm per iteration depending on the network model. The general increase in height within the network depended on connectedness and on the amount of height information that was exchanged between neighboring districts. If higher amounts of neighborhood height information were exchanged, the general increase in height within the network was large (strong secular trend). The trend in the homogeneous fishnet like network was lowest, the trend in the random network was highest. Yet, some network properties, such as the heteroscedasticity and autocorrelations of the migration simulation models differed greatly from the natural features observed in Swiss military conscript networks. Autocorrelations of district heights for instance, were much higher in the migration models. Conclusion: This study confirmed that secular height trends can be modeled by preferred migration of tall individuals into network hubs. However, basic network properties of the migration simulation models differed greatly from the natural features observed in Swiss military conscripts. Similar network-based data from other countries should be explored to better investigate height trends with Monte Carlo migration approach.}, language = {en} }