Wednesday, May 31, 2017

Visualizing the concept of prospective aging with R

In two great papers published in Science and Nature, W. Sanderson and  S. Scherbov proposed a new way to understand population aging. Instead of focusing on the time people have lived, the authors take a prospective look at the number of years people are still expected to live.

This concept of "prospective aging" is nicely summarized by Ilya Kashnitsky in a blog post:
"The underlying idea is really simple – age is not static: a person aged 65 (the conventional border deliminating elderly population) today is in many aspects not the same as a person ages 65 half a century ago. Health and lifespan improved a lot in the last decades, meaning that today people generally have much more remaining years of life at the moment of being recognized as elderly by the conventional standards. Thus, Sanderson and Scherbov proposed to define elderly population based on the estimation of the expected remaining length of life rather than years lived. Such a refined view of population ageing disqualifies the alarmist claims of the approaching demographic collapse."
If you're interested in the topic, I would highly recommend reading the whole post (and the papers, of course). Ilya brings not only a nice summary of the concept, he also presents some R scripts to create animated population pyramids to visualize prospective aging.

 Ilya Kashnitsky writes a great blog and twitter about demographic research and R more broadly, and I would highly recommend following his work online.



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