Life expectancy

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This article is about the measure of remaining life. For the Dean Koontz novel, see Life Expectancy (novel).
 It has been suggested that Life Expectancy Index be merged into this article or section. (Discuss)

Life expectancy is the average number of years of life remaining at a given age. It is the average expected lifespan of an individual. [1] Life expectancy is heavily dependent on the criteria used to select the group. In countries with high infant mortality rates, the life expectancy at birth is highly sensitive to the rate of death in the first few years of life. In these cases, another measure such as life expectancy at age 5 (e5) can be used to exclude the effects of infant mortality to reveal the effects of causes of death other than early childhood causes.

Contents

[edit] Humans

[edit] Variation over time

Humans live on average 31.99 years in Swaziland and on average 82 years in Japan (2008 est.). The oldest confirmed recorded age for any human is 122 years, though some people are reported to have lived longer. Although there are several longevity myths, mostly in different stories that were spread in some cultures, there is no scientific evidence of a human living for hundreds of years. The following information is derived from the Encyclopaedia Britannica, 1961, as well as other sources:

Humans by Era Average Lifespan at Birth
(years)		 Comment
Upper Paleolithic 33 At age 15: 39 (to age 54)[2][3]
Neolithic 20  
Bronze Age[4] 18  
Classical Greece[5] 20-30  
Classical Rome[6][7] 20-30  
Pre-Columbian North America[8] 25-35  
Medieval Islamic Caliphate[9] 35+ The average lifespans of the scholarly class were 59–84.3 years in the Middle East[10][11] and 69–75 in Islamic Spain.[12]
Medieval Britain[13][14] 20-30  
Early 20th Century[15][16] 30-40  
Current world average[17][18] 66.12 (2008 est.)

These represent estimates of the life expectancies of the population as a whole. In many instances life expectancy varied considerably according to class and gender. Life expectancy rises sharply in all cases for those who reach puberty. All statistics include infant mortality, but not miscarriage or abortion. This table also rejects certain beliefs based on myths that the ancient humans had life expectancy of hundreds of years. The sharp drop in life expectancy with the advent of the Neolithic mirrors the evidence[citation needed] that the advent of agriculture actually marked a sharp drop in life expectancy that humans are only recovering from in more recent times, mainly in affluent nations.

During the Industrial Revolution, the life expectancy of children increased dramatically. The percentage of the children born in London who died before the age of five decreased from 74.5% in 1730-1749 to 31.8% in 1810-1829.[19]

Public health measures are credited with much of the recent increase in life expectancy. During 20th century, the average lifespan in the United States increased by more than 30 years; 25 years of which can be attributed to advances in public health.[20]

[edit] Variation in the world today

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There are great variations in life expectancy worldwide, mostly caused by differences in public health, medical care and diet from country to country. Climate may also have an effect, and the way data is collected may also be an important influence. According to the U.S. Census Bureau, Andorra has the world's longest life expectancy of 83.5 years.

There are also variations between groups within single countries. Significant differences still remain in life expectancy between men and women in France and other developed countries, with women outliving men by five years or more. These gender differences have been lessening in recent years, with men's life expectancy improving at a faster rate than women's.[citation needed] Poverty, in particular, has a very substantial effect on life expectancy. In the United Kingdom life expectancy in the wealthiest areas is on average ten years longer than the poorest areas and the gap appears to be increasing as life expectancy for the prosperous continues to increase while in more deprived communities there is little increase.[21] However, in Glasgow the disparity is among the highest in the world with life expectancy for males in the heavily deprived Calton standing at fifty-four — twenty-eight years less than in the affluent area of Lenzie, which is only eight kilometres away.[22][23]

Life expectancy may also be reduced for people exposed to high levels of highway air pollution[citation needed] or industrial air pollution. Occupation may also have a major effect on life expectancy. Well-educated professionals working in offices have a high life expectancy, while coal miners (and in prior generations, asbestos cutters) do not. Other factors affecting an individual's life expectancy are genetic disorders, obesity, access to health care, diet, exercise, tobacco smoking, and excessive drug and alcohol use.

As pointed out above, AIDS has recently had a negative effect on life expectancy, especially in Sub-Saharan Africa.

Further information: List of countries by life expectancy

[edit] Gender differences

Women tend to have a lower mortality rate at every age. In the womb, male fetuses have a higher mortality rate (males are conceived at a ratio of about 124 males/100 females, but by birth, the ratio is only 105 males/100 females). Among the smallest premature babies (those under 2 pounds), females have a higher survival rate. At age 110, about 90 percent of the[clarification needed] population is female, and this increases still higher to about 92 percent by age 112.[citation needed]

If one does not consider the many women who die while giving birth or in pregnancy, or infanticide, the female human life expectancy is considerably higher than those of men. The reasons for this are not entirely certain. Traditional arguments tend to favor socio-environmental factors: men, on average, consume more tobacco, alcohol and drugs than females in most societies,[citation needed] and are more likely to die from some associated diseases such as lung cancer, tuberculosis and cirrhosis of the liver.[24] Men are more likely to die from injuries, whether unintentional (automotive accidents, etc.), or intentional (suicide, violence, war).[24]

However, such arguments are not entirely satisfactory, even if the statistics are corrected for known socio-environmental effects on mortality, females still have longer life expectancy. Interestingly, the age of equalization (about 13) tends to be close to the age of menarche, suggesting a potential reproductive-equilibrium explanation. Women, whose reproductive cycle tends to result in regular blood loss, are better-able to cope with blood loss and trauma.[dubious – discuss]

Some argue that shorter male life expectancy is merely another manifestation of the general rule, seen in all mammal species, that larger individuals tend on average to have shorter lives.[25][26] If small body size is a result of poor nutrition and not of genetics, then the rule is the other way around: better nourished people are taller and live longer. [27]

[edit] Lower life expectancy in people with serious mental illness

Persons with serious Mental illness die, on average, 25 years earlier than the general public.

Mental illnesses such as schizophrenia, bipolar disorder and major depression. Three out of five mentally ill die from mostly preventable physical diseases. Diseases such as Heart/Cardiovascular disease, Diabetes, Dyslipidaemia, Respiratory ailments, Pneumonia, Influenza.

[edit] Evolution and aging rate

The differing lifespans within various species of plants and animals, including humans, raises the question of why such lifespans are observed.

The evolutionary theory states that organisms that are able by virtue of their defenses or lifestyle to live for long periods whilst avoiding accidents, disease, predation etc. are likely to have genes that code for slow aging - good repair.

This is so because if a random genetic trait found in the organism increases its survivability, it is more likely to pass on its genes to the next generation. Thus, a member of the population with genes that lend to increased survivability will tend to reproduce more and have more successors. This gene which increases survivability will thus be increasingly spread throughout the species, increasing the survivability of the species as a whole.

Conversely a change to the environment that means that organisms die younger from a common disease or a new threat from a predator will mean that organisms that have genes that code for putting more energy into reproduction than repair will do better.

The support for this theory includes the fact that better defended animals, for example small birds that can fly away from danger live for a decade or more whereas mice which cannot, die of old age in a year or two. Tortoises and turtles are very well defended indeed and can live for over a hundred years. A classic study comparing opossums on a protected island with unprotected opossums also supports this theory.[citation needed]

But there are also counterexamples, suggesting that there is more to the story. Guppies in predator-free habitats evolve shorter life spans than nearby populations of guppies where predators exact a large toll. A broad survey of mammals indicates many more exceptions. The theory of evolution of aging may be in flux.

Another main counterexample is that the evolutionary traits best for short term survival may be detrimental to long term survival. For example, a hummingbird's extremely fast wings allow it to escape from predators and to find mates, assuring that the genetic trait for fast wings is passed on, explained by natural selection. However, these fast wings can be detrimental to the hummingbird's long term health, as the wings consume vast amounts of Adenosine triphosphate (cellular energy molecules) and cause the hummingbird's heart to deteriorate with permanent and long-term wear. This allows for hummingbirds to effectively survive and reproduce; as a result, however, hummingbirds usually die shortly after reproducing.

Natural selection tends to favor short-term survival traits. Human technology driven artificial selection, however, now appears to have prioritized long-term survival traits' having previously improved short-term survival rates through global food-chain dominance.

[edit] Calculating life expectancies

The starting point for calculating life expectancies is the age-specific death rates of the population members. For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, then the age-specific death rate at age 90 would be 10%.

These values are then used to calculate a life table, from which one can calculate the probability of surviving to each age. In actuarial notation the probability of surviving from age x to age x+n is denoted \,_np_x\! and the probability of dying during age x (i.e. between ages x and x+1) is denoted q_x\!.

The life expectancy at age x, denoted \,e_x\!, is then calculated by adding up the probabilities to survive to every age. This is the expected number of complete years lived (one may think of it as the number of birthdays they celebrate).

e_x =\sum_{t=1}^{\infty}\,_tp_x = \sum_{t=0}^{\infty}t \,_tp_x q_{x+t}

Because age is rounded down to the last birthday, on average people live half a year beyond their final birthday, so half a year is added to the life expectancy to calculate the full life expectancy.

An average age for death expectancy is very close life expectancy (and exactly same for the exponential growth of death rate with increasing age).

e_x = \frac{\sum_{t=x}^{\infty}\,tq_tl_t}{\sum_{t=x}^{\infty}\,q_tl_t},

Life expectancy is by definition an arithmetic mean. It can be calculated also by integrating the survival curve from ages 0 to positive infinity (the maximum lifespan, sometimes called 'omega'). For an extinct cohort (all people born in year 1850, for example), of course, it can simply be calculated by averaging the ages at death. For cohorts with some survivors it is estimated by using mortality experience in recent years.

Note that no allowance has been made in this calculation for expected changes in life expectancy in the future. Usually when life expectancy figures are quoted, they have been calculated like this with no allowance for expected future changes. This means that quoted life expectancy figures are not generally appropriate for calculating how long any given individual of a particular age is expected to live, as they effectively assume that current death rates will be "frozen" and not change in the future. Instead, life expectancy figures can be thought of as a useful statistic to summarize the current health status of a population. Some models do exist to account for the evolution of mortality (e.g., the Lee-Carter model[28]).

[edit] See also

[edit] Increasing life expectancy

[edit] References

[edit] Notes

  1. ^ Sullivan, arthur; Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River, New Jersey 07458: Pearson Prentice Hall. pp. 473. ISBN 0-13-063085-3. http://www.pearsonschool.com/index.cfm?locator=PSZ3R9&PMDbSiteId=2781&PMDbSolutionId=6724&PMDbCategoryId=&PMDbProgramId=12881&level=4. 
  2. ^ Hillard Kaplan, ect. al, in "A Theory of Human Life History Evolution: Diet, Intelligence,weed knowledge and Longevity" (Evolutionary Anthropology, 2000, p. 156-185, - http://www.soc.upenn.edu/courses/2003/spring/soc621_iliana/readings/kapl00d.pdf
  3. ^ Caspari & Lee 'Older age becomes common late in human evolution' (Proceedings of the National Academy of Sciences, USA, 2004, p. 10895-10900
  4. ^ James Trefil, "Can We Live Forever?" 101 Things You Don't Know About Science and No One Else Does Either (1996)
  5. ^ Average Life Expectancy at Birth
  6. ^ Life expectancy (sociology)
  7. ^ University of Wyoming
  8. ^ Pre-European Exploration, Prehistory through 1540
  9. ^ Conrad, Lawrence I. (2006), The Western Medical Tradition, Cambridge University Press, p. 137, ISBN 0521475643 
  10. ^ Ahmad, Ahmad Atif (2007), "Authority, Conflict, and the Transmission of Diversity in Medieval Islamic Law by R. Kevin Jaques", Journal of Islamic Studies 18=issue=2: 246-248 [246], doi:10.1093/jis/etm005 
  11. ^ Bulliet, Richard W. (1983), "The Age Structure of Medieval Islamic Education", Studia Islamica 57: 105-117 [111] 
  12. ^ Shatzmiller, Maya (1994), Labour in the Medieval Islamic World, Brill Publishers, p. 66, ISBN 9004098968 
  13. ^ Time traveller's guide to Medieval Britain
  14. ^ A millennium of health improvement
  15. ^ World Health Organization
  16. ^ Our Special Place in History
  17. ^ CIA - The World Factbook -- Rank Order - Life expectancy at birth
  18. ^ World Bank - http://www.worldbank.org/depweb/english/modules/social/life/index.html
  19. ^ Mabel C. Buer, Health, Wealth and Population in the Early Days of the Industrial Revolution, London: George Routledge & Sons, 1926, page 30 ISBN 0-415-38218-1
  20. ^ CDC (1999). "Ten great public health achievements—United States, 1900–1999". MMWR Morb Mortal Wkly Rep 48 (12): 241–3. PMID 10220250. http://cdc.gov/mmwr/preview/mmwrhtml/00056796.htm.  Reprinted in: JAMA 281 (16): 1481. 1999. doi:10.1001/jama.281.16.1481. PMID 10227303. 
  21. ^ Department of Health -Tackling health inequalities: Status report on the Programme for Action
  22. ^ "Social factors key to ill health". BBC News. 2008-08-28. http://news.bbc.co.uk/1/hi/health/7584056.stm#Life%20expectancy. Retrieved on 2008-08-28. 
  23. ^ "GP explains life expectancy gap". BBC News. 2008-08-28. http://news.bbc.co.uk/1/hi/scotland/glasgow_and_west/7584450.stm. Retrieved on 2008-08-28. 
  24. ^ a b World Health Organization (2004). "Annex Table 2: Deaths by cause, sex and mortality stratum in WHO regions, estimates for 2002" (pdf). The world health report 2004 - changing history. http://www.who.int/entity/whr/2004/annex/topic/en/annex_2_en.pdf. Retrieved on 2008-11-01. 
  25. ^ http://jerrymondo.tripod.com/lgev/id1.html
  26. ^ Samaras, Thomas T. und Heigh, Gregory H.: How human size affects longevity and mortality from degenerative diseases. Townsend Letter for Doctors & Patients 159: 78-85, 133-139
  27. ^ http://www.oberlin.edu/alummag/oamcurrent/oam_may99/tall.html
  28. ^ Ronald D. Lee and Lawrence Carter. 1992. "Modeling and Forecasting the Time Series of U.S. Mortality," Journal of the American Statistical Association 87 (September): 659-671.

[edit] Further reading

[edit] External links

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