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Life Expectancy
Measured in years, life expectancy can be calculated in a number of ways. Most usually it is taken to mean 'from birth' but can be from some other age e.g. 15, or 60. It may include 'healthy life expectancy.'
1) Which country has the highest life expectancy (use pop-ups) and which the lowest? (Zero values may mean data was not available.)
2) Describe the pattern shown in this map.
3) Would you expect to find a similar pattern in earlier years? Access this map to plot values for 1960-65.
This maps shows that life expectancy has increased between 1960-65 and 2010-15.
1) Which country in Europe has made the largest gain in life expectancy?
2) Which country in Africa has made the smallest gain?
3) Describe the pattern of increase in life expectancy as shown on the map. There are pop-ups to give you more information.
Natural Increase 1960-65
Natural increase is calculated by: Crude Birth Rate - Crude Death Rate.
The natural increase figure tells you how many babies are being born per 1000 population.
Natural Increase 2010-15
Moving on fifty years from Map 3, the world has changed. Natural increase has declined across large areas of the world, but one region still has high figures
1) Describe the differences between the two maps
Crude Birth Rates 2010-15
This figure, called 'crude' because it is only a snapshot - indeed the figures which make this map are UN Estimates. However there is a clear pattern. It is the number of births per 1000 population - often using the ‰ symbol to represent 1000.
Crude Death Rates 2010-15
1) What similarities and differences are there between the map for crude birth rates (Map 5) and this map of death rates?
Doubling time
Give the rate natural increase, it is possible to calculate the population doubling time using The Rule of 70.
This map shows that there are major population issues. Some countries' populations are not going to double (negative values) if births and deaths remain at their current levels. While it may be good that some countries' populations do not double, the problem of ageing and shrinking populations extends from the shores of the Atlantic to the Pacific.
Youthful Populations
The proportion (share) of the population aged under 15 is an interesting figure. It shows the likely level of demand for school places, family size and the need for jobs and also household formation in the coming years.
In some countries people under the age of 15 are not economically active - they are a financial burden (or liability) to their parents. However, in other countries children may enter the work force at a young age.
1) Where are the highest and lowest figures for the % under 15 population? Map pop-ups will help you.
Ageing Populations
The proportion (share) of the population aged over 65 is relatively high in high income countries. As with youthful populations, there are challenges from having a high percentage over the age of 65. While it is true that people do work beyond a notional retirement age, an ageing population may pose challenges because old age is often associated with poorer health
1) Where are the highest and lowest figures for the % over 65? Map pop-ups will help you.
Total Fertility Rate 1950-55
The Total fertility Rate (TFR) gives a more complex picture of births. The TFR is the number of children - on average - a woman has. A number around 2 means that women are replacing themselves and their partners (in fact the replacement level number is 2.1).
The deep pink colour shows countries where replacement level is being exceeded.
Total Fertility Rate 1970-75
Total Fertility Rate 2010-15
1) Taking maps 9, 10 and 11, describe what has happened to the pattern of countries with above (or below) replacement level values.
2) Draw a table with six rows and four columns.
Write country in the top left cell and then put 1950-55, 1970-75 and 2010-15 as the column headings.
Choose five countries from around the world and then fill in the TFR value (from the pop-ups).
Describe what has happened to the TFRs you have collected.
3) What does this information suggest is happening in the countries for which you have chosen TFR data?
Health care spending
Up to now all of the maps have been based on data from the United Nations. This map shows data from the OECD on healthcare spending and while it does not cover as much of the world as the UN data, it tells an interesting story.
The map pop-ups show the spend per head of population and the theoretical cost of one year's life in that country, given its life expectancy and the amount of money spent on healthcare. So, in the UK for example, healthcare spending is calculated as being U$3,971 and that works about at U$49 per year of life expectancy.
Examine the pattern shown on the map. You may want to go back and check out life expectancy information from Map 1. Use the pop-ups.
1) Which countries' populations appear to be getting best value for money?
2) Could some of the patterns you noted from Maps 1, 2, 6, 9 and 12 be partly explained by the information on this map? Give reasons for your answer (you answer will contain words like because, therefore...).
Net-Migration
The OECD defines this as the difference between immigration into and emigration from an area during the year (it is negative when the number of emigrants exceeds the number of immigrants).
So immigrants are people who come into a country. In the case of the UK, many immigrants are UK citizens returning to live in the UK. Country of birth is sometimes used to define immigrants, but many UK citizens were born overseas. Country of citizenship likewise can be used to define immigrant, but dual nationality is possible, just as it is possible to hold more than one passport.
The map, right, shows a patchwork or positive and negative net migration.
For countries with high rates of positive and negative net migration (fairly obvious from the map) try to find push and pull factors which may help explain their high figures.