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Monte Carlo simulation of body height in a spatial network
M Hermanussen1, C Aßmann2, K Staub3
1Aschauhof, Altenhof, Germany.
European Journal of Clinical Nutrition
|April 7, 2016
Summary
Spatial connectedness influences human height clustering. Even limited shared height data between connected districts can simulate natural height distributions, suggesting general network properties, not just geography, shape stature patterns.
Area of Science:
- Anthropometry
- Spatial network analysis
- Agent-based modeling
Background:
- Human body height exhibits spatial clustering.
- Investigating the impact of network connectedness on height distribution is crucial.
Observation:
- Swiss military conscript height data from three distinct historical periods (1884-1910 and 2004-2009) were analyzed.
- Height distributions were found to be overdispersed, with geographically connected districts showing similar heights.
- District mean height correlated with road connectivity and population size.
Findings:
- Agent-based modeling (Monte Carlo simulation) successfully replicated observed height distribution characteristics.
- As little as 5% of shared height information between connected districts was sufficient for simulation.
- Similar results in regular networks suggest these patterns are general spatial network features.
Implications:
- Spatial connectedness plays a significant role in human height clustering.
- These findings support the concept that interconnectedness influences human height regulation.
- The study highlights the generalizability of spatial network effects on anthropometric traits.
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