Life expectancy

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Life expectancy is a crude index of health. It is reasonably easy to estimate based on historical population data where there is accurate data as to births and deaths. Methods exist that are fairly accurate to estimate life expectancy by survey methods in populations, such as some third world countries where accurate national data does not exists. Such data is important for health care and economic planning. The insurance industry first utilised such data and indeed showed how useful such aggregate data could be. Studies suggest doctors as a group tend to veer to the optimistic side of estimating life expectancy, which perhaps reflects that most of life expectancy is able to be predicted by per capita income and social factors rather than individual healthcare interventions. The availability of such data can be very suggestive of the importance of inequalities in determining health.[1] Preston developed a graphical representation of this issue called a Preston curve.


Preston curves superimposed from 1960 to 2000


  • The gain in life expectancy from reducing early life mortality from malnutrition, infection (including poor water supply) and sewage disposal is marked but does require social cohesion (compare China's progress with India's).
  • The gain from social cohesion once health interventions are more directed at non infectious diseases still exists in the more mature economies that can afford such interventions. (compare Japan and the USA).

Each country is represented by a circle proportionate to its total population. Certain important and well known drops in life expectancy are shown. For example in Russia in 1990 with recovery and in South Africa (yet to recover). The advance of China up the third world (low income) portion of the graph is notable, as is India's. About a GNP of $3500 per person at 2000 prices there is a life expectancy transformation. The relatively flat progress in further gain in life expectancy in first world economies after this as represented by the USA. The big 3 European economies (UK, France and Germany) tend to cluster with the UK having slightly lower life expectancy (till 2000 at least). However like Japan they have better life expectancy than the USA. This is consistent with their societies having more social equity.

Expectancy at Age

The life expectancy of someone at a particular age may be useful.

Implications of life expectancy

It is possible to associate changes in life expectancy in populations with other metrics than GNP, as with Preston curves. Globally in developed economies there was a drop in life expectancy during 2014-15. A pausable association is with excess deaths due to the influenza strains that circulated that year as in most developed countries apart from the USA and UK. While the long term improvement in human life expectancy resumed in 2015-2016 in many developed nations, this did not happen in all. By 2018 in countries like England it was apparent that improvements in cardiovascular mortality were stalling with widening inequalities between affluent and deprived areas, and increasing deaths in the young from accidental poisoning[2]. Such trends were worse in the USA. In 2018 PHE and EuroMOMO reported substantial excess winter deaths, largely attributable to influenza in the very old as in 2015.[3] It is possible that social and health care policies adopted historically that affect social equality are interacting with disease to produce such trends.There is now good reason to believe that a factor in the effectively static life expectancy in the USA since 2010 is the opioid epidemic in that country. Other cultures have been more successful in controlling both legal and illegal access to opioids in the last decade. This is likely to be due to multiple factors, most with political overtones such as how income is distributed or redistributed, how access to opioids is controlled, how consumer and healthcare advertising is controlled, and the balance in criminal/social systems between punishment and support.


  1. Deaton A. Global patterns of income and health: facts and implications
  2. Deaton A. Global patterns of income and health