Regional population structures at a glance

July 20, 2018
By

(This article was first published on Ilya Kashnitsky, and kindly contributed to R-bloggers)

fig0

I am happy to announce that our paper is published today in The Lancet.

Kashnitsky, I., & Schöley, J. (2018). Regional population structures at a glance. The Lancet, 392(10143), 209–210. https://doi.org/10.1016/S0140-6736(18)31194-2

At a glance

Demographic history of a population is imprinted in its age structure. A meaningful representation of regional population age structures can tell numerous demographic stories – at a glance. To produce such a snapshot of regional populations, we use an innovative approach of ternary colour coding.

Here is the map:

fig1

We let the data speak colours

With ternary colour coding, each element of a three-dimensional array of compositional data is represented with a unique colour. The resulting colours show direction and magnitude of deviations from the centrepoint, which represents the average age of the European population, and is dark grey. The hue component of a colour encodes the direction of deviation: yellow indicates an elderly population (>65 years), cyan indicates people of working age (15–64 years), and magenta indicates children (0–14 years).

The method is very flexible, and one can easily produce these meaningful colours using our R package tricolore. Just explore the capabilities of the package in a built-in shiny app using the following lines of code:

install.packages("ticolore")
library(tricolore)
DemoTricolore()

Replication materials at github

Folow us on Twitter: @ikahhnitsky, @jschoeley.

SEE ALSO

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