MPhil in Public Health
Intranet: https://Camtools.caret.cam.ac.uk (Raven login) Department of Public Health & Primary Care
Course Director: Dr John Powles email@example.com
Secretaries: Rosemarie Bell firstname.lastname@example.org
Francis Cater email@example.com
October 15, 2011
GAPMINDER: SOME THINGS TO EXPLORE
Double clink on the ‘Explore the world’ window and familiarise yourself with the layout.
The default screen should show income per person on the x axis (with a log scale selected) and
life expectancy at birth on the y axis (with a linear scale selected). There are no other summary
measures of health available. For the x axis there are a number of alternatives to income whose
associations with survival levels you may wish to explore; but income is probably the best one to
To see how it works, click on play on the left end of the time scale at the bottom.
You can enlarge or shrink the displayed area using the plus and minus magnifiers at the bottom
right of the screen. Eg to enlarge, click on the plus then click on the main screen. To shift the
position of the window, click on the white rectangle and move it within the small screen at the
Exploring life expectancy trends
You might like to start by exploring how different countries have performed through time in
improving their life expectancy.
You can select specific countries in the menu bar to the right.
Countries now in the high income goup
Countries that are now in the high income group tend to have the longest data series. You may
find it interesting to compare Australia, France, Japan, Sweden, United Kingdom, United States.
Note the effect of WW I and the 1918 influenza pandemic and WW II (the latter in Japan).
Many middle income countries in the Americas made dramatic gains through the middle of the
20th century. Look for example at Chile, Costa Rica, Cuba, Jamaica.
Switzerland has been a strong improver in the recent period.
Some of the resource rich higher income countries (such as South Africa and Gabon) have done
no better than Gambia which has doubled its life expectancy without increasing its income.
Countries such as Swaziland and South Africa show the devastating recent effects of the HIV
epidemic. Countries in north Africa such as Tunisia, Libya, Morocco have done rather better
over recent decades.
Start with the ‘2 giants – India and China – and add Sri Lanka and Hong Kong. Improvement in
India and China was spectacular in the 1950s and 60s but has tended to slow since the 1980s
when income has been increasing more. Sri Lanka performed spectacularly from the 1920s to the
1960s, in the absence of any appreciable increase in income. Note the sustained improvement in
Hong Kong through the second half of the 20th century – taking it to the top rank (along with
Japan). (Note that the effects of the catastrophic famine that followed the Great Leap Forward in
China, with around 20 million deaths between 1959 and 1961, do not appear to be registered in
Communist and post communist Europe
These show dramatically variable trends. Russia’s life expectancy falls to an estimated 12 years
in 1933 but then improves dramatically between the end of the second world war and around
1960. It then stagnates before plunging in the early 1990s and shows no improvement during the
period of rising incomes since 1998. Belarus has fared better since the 1980s. Albania shows
rapid life expectancy gains from the 1950s whilst incomes stay low. Slovenia follows a trajectory
not very different from that of many west European countries. Poland improves dramatically
from World War II to the mid 1960s, then stagnates, then improves dramatically following the
end of communism. Baltic states such as Estonia do much worse in the post communist period.
Exploring child survival trends
The y axis may be changed to ‘Mortality rate under 5’ (under ‘Births and deaths’).
Explore the extent to which trends in the levels of child mortality differ from those for life
January 8, 2009