In the United States, rural residents do not live as long as their urban counterparts. This disparity has been widening for decades. Around 1970, urban life expectancy was 70.9 years, compared with 70.5 in rural areas, but by 2005–2009, the difference was greater (78.8 versus 76.8 years). In our research recently published in the IJE, we found that the gap in life expectancy would be even wider today if declines in cardiovascular disease (CVD) mortality had not dramatically slowed around 2010.
In my earlier blog post, I introduced the concept first of thinking about demographic data like spatial data, and like spatial data producing ‘maps’ of the data’s demographic topography; and secondly, of reifying and rendering these statistical surfaces as three dimensional objects, either using computer generated imagery or 3D printers. This blog post will describe just one of these surfaces, a ‘statistical sculpture’ showing how the logarithm of mortality risk has changed for males in Finland from 1878 to 2012. Continue reading “Lexis Cubes 2 – Case-study: Log mortality for males in Finland, 1878 to 2012”→
Introduction A Lexis surface is a Cartesian mapping of three attributes to three dimensions:
year (or another measure of absolute time) to the x axis,
age (or another measure of relative time) to the y axis,
a third variable, which co-varies with year and age, to the z axis.
Put another way: a Lexis surface is a way of visualising temporal change as if it were spatial change, of thinking about time as if it were space: of absolute time as if it were latitude, relative time as if it were longitude, and a third variable as if it were a height above sea level. Continue reading “Lexis cubes 1: From maps of space to maps of time”→
This article originally appeared on the OUPblog on 19 September 2013: http://blog.oup.com/2013/09/demographic-landscape-bad-news/. It is reproduced here with updated figures and captions.
In the first part of this post, I showed how we used a classic mapping technique — contour plots — to explore the demographic landscape, examining the texture of the lives and deaths of billions of people from more than forty countries. Our maps showed how a third variable, mortality rates, varied against two others: age and time. Just as the coordinates of physical terrain are latitude and longitude, so the coordinates of mortality terrain are age and year, or age-time.
Previously, we saw how these contour maps highlighted the good news we found in demographic changes. Today we explore the bad news.
Period effects: The dinosaurs of the twentieth century
Our demography has been scarred by the two World Wars. In our maps these appear as two thin clusters of ovals, like onions that have been flattened then cut open. Topographically, these oval clusters show mortality risk jutting shard-like out of the lowlands of early adulthood like the kite-shaped plates of a stegosaurus. These are period effects, disruptions to the usual order. The bathtub-shaped age-specific mortality risks for the cohorts of men who had come of age by the onset of these wars had spikes in them. Women of the same age, though protected by patriarchal gender inequality from the front line, were still exposed to much of this additional risk, especially if they had the misfortune of having one’s home located in what turned into a battlefield. Continue reading “The demographic landscape, part II: The bad news”→
This article originally appeared on the OUPblog on 18 September 2013: http://blog.oup.com/2013/09/demographic-landscape-good-news/. It is reproduced here with some updated figures and captions.
If demography were a landscape, what would it look like? Every country has a different geographical shape and texture, visible at high relief, like an extra-terrestrial fingerprint. But what about the shape and texture revealed by the demographic records of the people who live and die on these tracts of land?
Maps show the fingerprints of the physical landscape on a human scale, letting us see the forests for the trees, the regions for the forests, and the countries for the regions. They are powerful visualisation techniques, knowledge tools for comprehending enormity.
This article originally appeared on the OUPblog on 14 April 2011: http://blog.oup.com/2011/04/life-expectancy/
Making a difference to the health of populations, however small, is what most people in public health hope they are doing. Epidemiologists are no exception. But often caught up in the minutiae of our day-to-day work, it is easy to lose sight of the bigger picture. Is health improving, mortality declining, are things moving in a positive direction? Getting out and taking in the view (metaphorically as well as literally) can have a salutary effect. It broadens our perspectives and challenges our assumptions. Looking at recent trends in European life expectancy is a case in point.
Since 1950 estimated life expectancy at birth of the world’s population has been increasing. Initially, this was accompanied by a convergence in mortality experience across the globe—with gains in all regions. However, in the final 15 years of the 20th century, convergence was replaced with divergence, in part due to declines in life expectancy in sub-Saharan Africa. However, this global divergence was also the result of declining life expectancy in Europe. Home to 1 in 10 of the world’s population, and mainly comprised of industrialized, high-income countries, Europe has over 50 states. These include Sweden and Iceland that have consistently been ranked among the countries with the highest life expectancies in the world. But while for the past 60 years all Western European countries have shown increases in life expectancy, the countries of Central and Eastern Europe (CEE), Russia and other parts of the former Soviet Union have had a very different, and altogether more negative experience. Continue reading “Trends in European life expectancy: a salutary view”→