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| {{About|the measure of remaining life|the Dean Koontz novel|Life Expectancy (novel)|life expectancy by country|List of countries by life expectancy}}
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| '''Life expectancy''' is the expected (in the statistical sense) number of years of life remaining at a given age.<ref>{{cite book
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| | last = Sullivan
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| | first = Arthur
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| | authorlink = Arthur O'Sullivan (economist)
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| | coauthors = Steven M. Sheffrin
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| | title = Economics: Principles in action
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| | publisher = Pearson Prentice Hall
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| | year = 2012
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| | location = Upper Saddle River, New Jersey 07458
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| | page = 473
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| | url = http://www.pearsonschool.com/index.cfm?locator=PSZu4y&PMDbSiteId=2781&PMDbSolutionId=6724&PMDbSubSolutionId=&PMDbCategoryId=815&PMDbSubCategoryId=&PMDbSubjectAreaId=&PMDbProgramId=5657&PMDbProductId=5475
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| | isbn = 0-13-063085-3}}</ref> It is denoted by <math>e_x</math>,{{ref|exsymbol|[a]}} which means the [[average]] number of subsequent years of life for someone now aged <math>x</math>, according to a particular [[wikt:mortality|mortality]] experience. Because life expectancy is an average, a particular person may well die many years before or many years after their "expected" survival. The term "[[maximum life span]]" has a quite different meaning. The "median life span" is also a different concept although fairly similar to life expectancy numerically in most developed countries.
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| The term that is known as life expectancy is most often used in the context of human populations, but is also used in plant or animal [[ecology]];<ref>{{cite journal|title=Life Histories of Mammals: An Analysis of Life Tables|author=John S. Millar and Richard M. Zammuto|journal=Ecology|volume=64|issue=4|year=1983|pages=631–635|doi=10.2307/1937181|publisher=Ecological Society of America|jstor=1937181}}</ref> it is calculated by the analysis of [[life table]]s (also known as [[actuary|actuarial tables]]). The term life expectancy may also be used in the context of manufactured objects<ref name=machine/> although the related term [[shelf life]] is used for consumer products and the terms "mean time to breakdown" (MTTB) and "[[Mean time between failures|mean time between failures]]" (MTBF) are used in engineering.
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| ==Interpretation of life expectancy==
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| It is important to note that life expectancy is an average value. In many cultures, particularly before modern medicine was widely available, the combination of high infant mortality and deaths in young adulthood from accidents, epidemics, plagues, wars, and childbirth, significantly lowers the overall life expectancy. But for someone who survived past these early hazards, living into their sixties or seventies would not be uncommon. For example, a society with a life expectancy of 40 may have very few people dying at age 40: most will die before 30 years of age or after 55.
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| In countries with high [[infant mortality]] rates, life expectancy at birth is highly sensitive to the rate of death in the first few years of life. Because of this sensitivity to infant mortality, simple life expectancy at age zero can be subjected to gross misinterpretation, leading one to believe that a population with a low overall life expectancy will necessarily have a small proportion of older people.<ref>http://scienceblogs.com/gregladen/2011/05/01/falsehood-if-this-was-the-ston/</ref> For example, in a hypothetical [[stationary population]] in which half the population dies before the age of five, but everybody else dies at exactly 70 years old, the life expectancy at age zero will be about 37 years, while about 25% of the population will be between the ages of 50 and 70. Another measure such as life expectancy at age 5 (e<sub>5</sub>) can be used to exclude the effect of infant mortality to provide a simple measure of overall mortality rates other than in early childhood—in the hypothetical population above, life expectancy at age 5 would be another 64 years. Aggregate population measures such as the proportion of the population in various age classes should also be used alongside individual-based measures like formal life expectancy when analyzing population structure and dynamics.
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| ==Human life expectancy patterns==
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| Human beings are expected to live on average 49.42 years in [[Swaziland]]<ref>url=https://www.cia.gov/library/publications/the-world-factbook/geos/wz.html</ref> and 82.6 years in [[Japan]], although Japan's recorded life expectancy may have been very slightly increased by counting many infant deaths as stillborn.<ref>{{cite journal|author=[[Ansley J. Coale]]|coauthors=Judith Banister|date=December 1996|title=Five decades of missing females in China|journal=Proceedings of the American Philosophical Society|volume=140|issue=4|pages=421–450|jstor=987286}}</ref> An analysis published in 2011 in ''[[The Lancet]]'' attributes Japanese life expectancy to [[equal opportunities]] and [[public health]] as well as diet.<ref name="guardian japan life expectancy">{{cite news | url=http://www.guardian.co.uk/world/2011/aug/30/japan-life-expectancy-factors | title=Japan's life expectancy 'down to equality and public health measures' | work=[[The Guardian]] | date=2011-08-30 | accessdate=August 31, 2011 | author=Boseley, Sarah | location=London | quote=Japan has the highest life expectancy in the world but the reasons says an analysis, are as much to do with equality and public health measures as diet. [...] According to a paper in a Lancet series on healthcare in Japan [...]}}</ref><ref name="lancet what has made the population of japan healthy">{{cite journal | url=http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(11)61055-6/abstract | title=What has made the population of Japan healthy? | author=Ikeda, Nayu | journal=[[The Lancet]] | year=2011 | month=08 | doi=10.1016/S0140-6736(11)61055-6 | quote=Reduction in health inequalities with improved average population health was partly attributable to equal educational opportunities and financial access to care. | coauthors=Saito, Eiko; Kondo, Naoki; Inoue, Manami; Ikeda, Shunya; Satoh, Toshihiko; Wada, Koji; Stickley, Andrew; Katanoda, Kota; Mizoue, Tetsuya; Noda, Mitsuhiko; Iso, Hiroyasu; Fujino, Yoshihisa; Sobue, Tomotaka; Tsugane, Shoichiro; Naghavi, Mohsen; Ezzati, Majid; Shibuya, Kenji | volume=378 | issue=9796 | pages=1094–105 | pmid=21885105}}</ref>
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| The oldest confirmed recorded age for any human is 122 years (see [[Jeanne Calment]]). This is referred to as the "[[maximum life span]]", which is the upper boundary of life, the maximum number of years any human is known to have lived.<ref name="Santrock">Santrock, John (2007). Life Expectancy. A Topical Approach to: Life-Span Development(pp. 128-132). New York, New York: The McGraw-Hill Companies, Inc.</ref> | |
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| ===Life expectancy variation over time===
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| The following information is derived from ''[[Encyclopædia Britannica]]'', 1961. and other sources, some with a questionable accuracy. Unless otherwise stated, it represents estimates of the life expectancies of the [[world population|population]] as a whole. In many instances life expectancy varied considerably according to class and gender.
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| Life expectancy at birth takes account of [[infant mortality]] but not pre-natal mortality.
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| {| class="wikitable"
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| ! Era !! Life Expectancy at Birth<br>(years) !! Life Expectancy at Older Age
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| | [[Upper Paleolithic]] || style="text-align:center;"| 33 || Based on the data from the recent hunter-gatherer populations, it is estimated that at age 15, life expectancy was an additional 39 years (total age 54).<ref name=kaplanetal2000>{{Cite journal |year=2000 |author=Hillard Kaplan, Kim Hill, Jane Lancaster, and A. Magdalena Hurtado |title=A Theory of Human Life History Evolution: Diet, Intelligence and Longevity |journal=Evolutionary Anthropology |volume=9 |issue=4 |pages=156–185 |doi=10.1002/1520-6505(2000)9:4<156::AID-EVAN5>3.0.CO;2-7 |url=http://www.unm.edu/~hkaplan/KaplanHillLancasterHurtado_2000_LHEvolution.pdf |accessdate=12 September 2010 |postscript=.}}</ref>
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| | [[Neolithic]]<ref name=Galor&Moav2007>{{Cite web |year=2007 |author=Galor, Oded & Moav, Omer |url=http://www.brown.edu/Departments/Economics/Papers/2007/2007-14_paper.pdf |title=The Neolithic Revolution and Contemporary Variations in Life Expectancy |work=[[Brown University]] Working Paper |accessdate=12 September 2010 |postscript=.}}</ref> || style="text-align:center;"| 20 ||
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| | [[Bronze Age]] and [[Iron Age]]<ref name="sticerd.lse.ac.uk">{{cite web|url=http://sticerd.lse.ac.uk/seminarpapers/dg09102006.pdf |title=swp0000.dvi |format=PDF |date= |accessdate=2010-11-04}}</ref> || style="text-align:center;"| 26 ||
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| | [[Classical Greece]]<ref name="britannica">{{cite web|url=http://www.britannica.com/EBchecked/topic/393100/mortality |title=Mortality |publisher=Britannica.com |date= |accessdate=2010-11-04}}</ref> || style="text-align:center;"| 28 ||
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| | [[Classical Rome]]<ref>{{cite book |last=Frier |first=Bruce W. |chapter=More is worse: some observations on the population of the Roman empire |editor-last=Scheidel |editor-first=Walter |title=Debating Roman Demography |year=2001 |publisher=Brill |location=Leiden |isbn=9789004115255 |pages=144–145 |url=http://books.google.com/books?id=vh3pmAodawEC&pg=PA144}}</ref> || style="text-align:center;"| 20–30 || At age 10, life expectancy an additional 35 to 37 years (total age 45 to 47)
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| | [[Indigenous peoples of the Americas|Pre-Columbian North America]]<ref>{{cite web|url=http://www.encyclopediaofarkansas.net/encyclopedia/entry-detail.aspx?entryID=395 |title=Pre-European Exploration, Prehistory through 1540 |publisher=Encyclopediaofarkansas.net |date=2010-10-05 |accessdate=2010-11-04}}</ref> || style="text-align:center;"| 25–30 ||
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| | [[Caliphate|Medieval Islamic Caliphate]]<ref>{{Cite book|title=The Western Medical Tradition|first=Lawrence I.|last=Conrad|publisher=[[Cambridge University Press]]|year=2006|isbn=0-521-47564-3|page=137}}</ref> || style="text-align:center;"| 35+ ||
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| | [[England in the Middle Ages|Medieval Britain]]<ref>{{cite web|url=http://www.channel4.com/history/microsites/H/history/guide12/part06.html |title=Time traveller's guide to Medieval Britain |publisher=Channel4.com |accessdate=2010-11-04}}</ref><ref>{{cite news|url=http://news.bbc.co.uk/1/hi/health/241864.stm |title=A millennium of health improvement |publisher=BBC News |date=1998-12-27 |accessdate=2010-11-04}}</ref> || style="text-align:center;"| 30 || At age 21, life expectancy additional 43 years (total age 64).<ref name="Expectations of Life">[http://books.google.com/books?id=T4DLK7zLxYMC&lpg=PP1&pg=PA8 "Expectations of Life" by H.O. Lancaster] (page 8)</ref>
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| | [[Early Modern Britain]]<ref name="sticerd.lse.ac.uk"/> || style="text-align:center;"| 25–40||
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| | [[1900–1909|Early 20th Century]]<ref>{{cite web|url=http://www.who.int/global_health_histories/seminars/presentation07.pdf |title=PowerPoint Presentation |format=PDF |date= |accessdate=2010-11-04}}</ref><ref>[http://www.usaweekend.com/00_issues/001231/001231newyear.html Our Special Place in History]{{dead link|date=November 2010}}</ref> || style="text-align:center;"| 31 ||
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| | 2010 world average<ref>[https://www.cia.gov/library/publications/the-world-factbook/rankorder/2102rank.html CIA—The World Factbook—Rank Order—Life expectancy at birth]</ref><!-- ref>World Bank — http://www.worldbank.org/depweb/english/modules/social/life/index.html</ref --> || style="text-align:center;"| 67.2 ||
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| Life expectancy increases with age as the individual survives the higher mortality rates associated with childhood. For instance, the table above listed the life expectancy at birth in Medieval Britain at 30. Having survived until the age of 21, a male member of the English aristocracy in this period could expect to live:<ref name="Expectations of Life"/>
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| * 1200–1300: to age 64
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| * 1300–1400: to age 45 (due to the impact of the [[Black Death]])
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| * 1400–1500: to age 69
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| * 1500–1550: to age 71
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| In general, the available data indicate that longer lifespans became more common recently in human evolution.<ref name=Casparie&Lee2004>{{Cite journal |date=July 27, 2004 |author=Caspari, Rachel & Lee, Sang-Hee |title=Older age becomes common late in human evolution |journal=[[Proceedings of the National Academy of Sciences]] |volume=101 |pmid=15252198 |issue=20 |pmc=503716 |pages=10895–10900 |url=http://www.pnas.org/content/101/30/10895.long |doi=10.1073/pnas.0402857101 |accessdate=12 September 2010 |postscript=.}}</ref><ref name="encylopediahumanevolution">{{Cite journal |title=The Cambridge Encyclopedia of Human Evolution | editors=Steve Jones, Robert Martin & David Pilbeam | year=1994 | publisher= Cambridge University Press | place= Cambridge |isbn= 0-521-32370-3 | page=242 |postscript=.}} Also ISBN 0-521-46786-1 (paperback)</ref> This increased longevity is attributed by some writers to cultural adaptations rather than genetic evolution,<ref name=Caspari&Lee2006>{{Cite journal |year=2006 |pages=512–517 |author=Caspari, R., & Lee, S-l |issue=4 |title=Is Human Longevity a Consequence of Cultural Change or Modern Biology? |pmid=16342259 |journal=[[American Journal of Physical Anthropology]] |volume=129 |doi=10.1002/ajpa.20360 |url=http://www.faculty.ucr.edu/~shlee/Publications/06%20OY%20W%20As%20(AJPA).pdf |accessdate=12 September 2010 |postscript=.}}</ref> although some research indicates that during the [[Neolithic Revolution]] natural selection favored increased longevity.<ref name=Galor&Moav2007/> Nevertheless, all researchers acknowledge the effect of cultural adaptations upon life expectancy.<ref name="encylopediahumanevolution"/>
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| During the early 1600s in [[England]], life expectancy was only about 35 years, largely because two-thirds of all children died before the age of four.<ref>W. J. Rorabaugh, Donald T. Critchlow, Paula C. Baker (2004). "''[http://books.google.com/books?id=VL_6X5zWOokC&pg=PA47&dq&hl=en#v=onepage&q=&f=false America's promise: a concise history of the United States]''". Rowman & Littlefield. p.47. ISBN 0-7425-1189-8</ref> The average life expectancy in [[Colonial America]] was under 25 years in the Virginia colony,<ref>"[http://www.stratfordhall.org/learn/teacher/medicine.php Medicine & Health]", Stratfordhall.org.</ref> and in New England about 40% of children failed to reach adulthood.<ref>"[http://www.digitalhistory.uh.edu/historyonline/usdeath.cfm Death in Early America]". Digital History.</ref> During the [[Industrial Revolution]], the life expectancy of children increased dramatically.<ref>"[http://www.britannica.com/EBchecked/topic/387301/modernization/12022/Population-change Modernization - Population Change]". ''Encyclopædia Britannica''.</ref> The percentage of children born in [[London]] who died before the age of five decreased from 74.5% in 1730–1749 to 31.8% in 1810–1829.<ref>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</ref><ref>[http://www.bbc.co.uk/history/british/victorians/foundling_01.shtml BBC—History—The Foundling Hospital]. Published: 2001-05-01.</ref>
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| [[Public health]] measures are credited with much of the recent increase in life expectancy. During the 20th century, the average lifespan in the United States increased by more than 30 years, of which 25 years can be attributed to advances in public health.<ref>{{cite journal |author=CDC |title= Ten great public health achievements—United States, 1900–1999 |journal= MMWR Morb Mortal Wkly Rep |volume=48 |issue=12 |pages=241–3 |year=1999 |pmid=10220250 |url=http://cdc.gov/mmwr/preview/mmwrhtml/00056796.htm}} [http://jama.ama-assn.org/cgi/content/full/281/16/1481 Reprinted] in: {{cite journal |journal=JAMA |volume=281 |issue=16 |page=1481 |year=1999 |doi=10.1001/jama.281.16.1481 |pmid=10227303 |title=From the Centers for Disease Control and Prevention. Ten great public health achievements—United States, 1900–1999}}</ref>
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| In order to assess the quality of these additional years of life, 'healthy life expectancies' have been calculated for the last 30 years. Since 2001, the World Health Organization publishes statistics called Healthy life expectancy (HALE), defined as the average number of years that a person can expect to live in "full health", excluding the years lived in less than full health due to disease and/or injury. Since 2004, [[Eurostat]] publishes annual statistics called [[Healthy Life Years]] (HLY) based on reported activity limitations. The United States of America uses similar indicators in the framework of their nationwide health promotion and disease prevention plan "[[Healthy People 2010]]". An increasing number of countries are using health expectancy indicators to monitor the health of their population.
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| {{further2|[[Longevity]]}}
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| ===Regional variations===
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| {{further2|[[List of countries by life expectancy]]}}
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| [[File:Esperanza de vida.PNG|thumb|400px|
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| {| width=100%
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| {{legend|#0000CD|>80}}
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| {{legend|#4169E1|77.5 to 80}}
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| {{legend|#00BFFF|75 to 77.5}}
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| {{legend|#3CB371|72.5 to 75}}
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| {{legend|#32CD32|70 to 72.5}}
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| {{legend|#ADFF2F|67.5 to 70}}
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| {{legend|#FFFF00|65 to 67.5}}
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| {{legend|#FFD700|60 to 65}}
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| {{legend|#FF8C00|55 to 60}}
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| {{legend|#FF4500|50 to 55}}
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| {{legend|#FF0000|45 to 50}}
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| {{legend|#800000|40 to 45}}
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| |}]]
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| [[File:LifeExpectancy GDPperCapita.png|thumb|Plot of life expectancy vs. [[GDP per capita]] in 2009. This particular phenomenon is known as the [[Preston curve]].]]
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| [[File:Comparison subsaharan life expectancy.svg|thumb|upright|Graphs of life expectancy at birth for some sub-Saharan countries showing the fall in the 1990s primarily due to the AIDS pandemic.<ref>[http://data.worldbank.org/indicator/SP.DYN.LE00.IN/countries/1W The World Bank - Life expectancy at birth, total (years)]</ref>]]
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| There are great variations in life expectancy between different parts of the world, mostly caused by differences in [[public health]], medical care, and diet. The impact of AIDS is particularly notable on life expectancy in many African countries. According to predictions made by the United Nations (UN) in 2002,<ref>[http://www.un.org/esa/population/publications/wpp2002/WPP2002-HIGHLIGHTSrev1.PDFUN "World Population Prospects — The 2002 Revision", 2003, page 24]</ref> the life expectancy at birth for 2010–2015 (if HIV/AIDS did not exist) would have been:
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| * 70.7 years instead of 31.6 in [[Botswana]]
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| * 69.9 years instead of 41.5 in [[South Africa]]
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| * 70.5 years instead of 31.8 in [[Zimbabwe]]
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| The UN's predictions were too pessimistic. Actual life expectancy in Botswana declined from 65 in 1990 to 49 in 2000 before increasing to 66 in 2011. In South Africa, life expectancy was 63 in 1990, 57 in 2000, and 58 in 2011. And in Zimbabwe, life expectancy was 60 in 1990, 43 in 2000, and 54 in 2011.<ref>[http://apps.who.int/gho/data/node.main.688?lang=en Life expectancy by country, Global Health Observatory Data Repository, World Health Organization]</ref>
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| Countries in Africa over the last 200 years have generally not had the same improvements in mortality rates that have been enjoyed by countries in Asia, Latin America, and Europe.{{Citation needed|date=June 2013}}
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| In the United States, African people have shorter life expectancies than their European counterparts. For example, white Americans born in 2010 are expected to live until age 78.9 but African Americans only until age 75.1. This 3.8-year gap, however, is the lowest it has been since at least 1975. The greatest difference was 7.1 years in 1993.<ref name="Final 2010 data">[http://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_04.pdf "Deaths: Final Data for 2010", ''National Vital Statistics Reports'', authored by Sherry L. Murphy, Jiaquan Xu, and Kenneth D. Kochanek, volume 61, number 4, page 12, 8 May 2013]</ref> In contrast, Asian-American women live the longest of all ethnic groups in the United States, with a life expectancy of 85.8 years.<ref>United States Department of Health and Human Services, Office of Minority Health - [http://minorityhealth.hhs.gov/templates/browse.aspx?lvl=2&lvlID=53 Asian American/Pacific Islander Profile]. Retrieved 2013-10-01</ref> The life expectancy of Hispanic Americans is 81.2 years.<ref name="Final 2010 data"/>
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| ===Economic circumstances===
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| Economic circumstances also affect life expectancy. For example, in the United Kingdom, life expectancy in the wealthiest areas is several years longer than in the poorest areas. This may reflect factors such as diet and lifestyle as well as access to medical care. It may also reflect a selective effect: people with chronic life-threatening illnesses are less likely to become wealthy or to reside in affluent areas.<ref>Department of Health -[http://www.dh.gov.uk/PublicationsAndStatistics/Publications/PublicationsPolicyAndGuidance/PublicationsPolicyAndGuidanceArticle/fs/en?CONTENT_ID=4117696&chk=OXFbWI Tackling health inequalities]: Status report on the Programme for Action</ref> In [[Glasgow]] the disparity is among the highest in the world with life expectancy for males in the heavily deprived [[Calton, Glasgow|Calton]] standing at 54 – 28 years less than in the affluent area of [[Lenzie]], which is only eight kilometres away.<ref>{{cite news|url=http://news.bbc.co.uk/1/hi/health/7584056.stm#Life%20expectancy|title=Social factors key to ill health|date=2008-08-28|publisher=BBC News|accessdate=2008-08-28}}</ref><ref name="WHO">{{cite news|url=http://news.bbc.co.uk/1/hi/scotland/glasgow_and_west/7584450.stm|title=GP explains life expectancy gap|date=2008-08-28|publisher=BBC News|accessdate=2008-08-28}}</ref>
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| A 2013 study found a pronounced relationship between [[economic inequality]] and life expectancy.<ref name=WaPoLifespan>{{cite news|last=Fletcher|first=Michael A.|title=Research ties economic inequality to gap in life expectancy|url=http://www.washingtonpost.com/business/economy/research-ties-economic-inequality-to-gap-in-life-expectancy/2013/03/10/c7a323c4-7094-11e2-8b8d-e0b59a1b8e2a_story.html|accessdate=23 March 2013|newspaper=Washington Post|date=March 10, 2013}}</ref> However, a study by José A. Tapia Granados and Ana Diez Roux at the [[University of Michigan]] found that life expectancy actually increased during the [[Great Depression]], and during recessions and depressions in general.<ref>{{cite web|url=http://www.sciencedaily.com/releases/2009/09/090928172530.htm|title=Did The Great Depression Have A Silver Lining? Life Expectancy Increased By 6.2 Years|date=2009-09-29|accessdate=2011-04-03}}</ref> The authors suggest that when people are working extra hard during good economic times, they undergo more [[stress (biology)|stress]], exposure to [[pollution]], and likelihood of injury among other longevity-limiting factors.
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| Life expectancy is also likely to be affected by exposure to high levels of [[roadway air dispersion model|highway air pollution]] or industrial [[air pollution]].{{Citation needed|date=February 2007}} This is one way that occupation can have a major effect on life expectancy. Coal miners (and in prior generations, asbestos cutters) often have shorter than average life expectancies. Other factors affecting an individual's life expectancy are genetic disorders, obesity, access to health care, diet, exercise, [[tobacco smoking]], drug use and excessive alcohol use.
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| ===Gender differences===
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| [[Image:Comparison gender life expectancy CIA factbook.svg|thumb|right|300px|Comparison of male and female life expectancy at birth for countries and territories as defined in the 2011 CIA Factbook, with selected bubbles labelled. The dotted line corresponds to equal female and male life expectancy. The apparent 3D volumes of the bubbles are linearly proportional to their population.<ref>[https://www.cia.gov/library/publications/the-world-factbook/fields/2102.html]</ref><ref>[https://www.cia.gov/library/publications/the-world-factbook/fields/2119.html]</ref>]]
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| Women tend to have a lower mortality rate at every age. In the womb, male fetuses have a higher mortality rate (babies are conceived in a ratio estimated to be from 107 to 170 males to 100 females, but the ratio at birth in the United States is only 105 males to 100 females).<ref>Kalben, Barbara Blatt. "Why Men Die Younger: Causes of Mortality Differences by Sex". Society of Actuaries", 2002, p. 17.http://www.soa.org/library/monographs/life/why-men-die-younger-causes-of-mortality-differences-by-sex/2001/january/m-li01-1-05.pdf</ref> Among the smallest premature babies (those under 2 pounds or 900 g) females again have a higher survival rate. At the other extreme, about 90% of individuals aged 110 are female. The difference in life expectancy between men and women in the United States dropped from 7.8 years in 1979 to 5.3 years in 2005, with women expected to live to age 80.1 in 2005.<ref>{{cite web | last = Hitti | first = Miranda | title = U.S. Life Expectancy Best Ever, Says CDC| work = eMedicine | publisher = [[WebMD]] | date = February 28, 2005 | url = http://www.webmd.com/healthy-aging/news/20050228/us-life-expectancy-best-ever-says-cdc | accessdate = 2011-01-18 }}</ref>
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| In the past, [[maternal death|mortality rates for females in child-bearing age groups]] were higher than for males at the same age. This is no longer the case, and female human life expectancy is considerably higher than that of males. The reasons for this are not entirely certain. Traditional arguments tend to favor socio-environmental factors: historically, men have generally consumed more [[tobacco]], [[alcoholic beverage|alcohol]] and [[drug]]s than women in most societies, and are more likely to die from many associated diseases such as [[lung cancer]], [[tuberculosis]] and [[Cirrhosis|cirrhosis of the liver]].<ref name=worldhealth/> Men are also more likely to die from injuries, whether unintentional (such as occupational or [[war]] or [[car accident]]s) or intentional ([[suicide]]).<ref name=worldhealth>{{cite web | author=World Health Organization | year= 2004 | work = The world health report 2004 - changing history | title = Annex Table 2: Deaths by cause, sex and mortality stratum in WHO regions, estimates for 2002 | url = http://www.who.int/entity/whr/2004/annex/topic/en/annex_2_en.pdf | format=PDF | accessdate = 2008-11-01}}</ref> Men are also more likely to die from most of the leading causes of death (some already stated above) than women. Some of these in the United States include: cancer of the respiratory system, motor vehicle accidents, suicide, cirrhosis of the liver, emphysema, and coronary heart disease.<ref name="Santrock" /> These far outweigh the female mortality rate from breast cancer and cervical cancer.
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| Some argue that shorter male life expectancy is merely another manifestation of the general rule, seen in all mammal species, that larger (size) individuals (within a species) tend on average to have shorter lives.<ref>{{cite web|url=http://jerrymondo.tripod.com/lgev/id1.html |title=Telemores, sexual size dimorphism and gender gap in life expectancy |publisher=Jerrymondo.tripod.com |date= |accessdate=2010-11-04}}</ref><ref>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</ref> This biological difference occurs because women have more resistance to infections and degenerative diseases.<ref name="Santrock" />
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| In her extensive review of the existing literature, Kalben concluded that the fact that women live longer than men was observed at least as far back as 1750 and that, with relatively equal treatment, today males in all parts of the world experience greater mortality than females. Of 72 selected causes of death, only 6 yielded greater female than male age-adjusted death rates in 1998 in the United States. With the exception of birds, for almost all of the animal species studied, the males have higher mortality than the females. Evidence suggests that the sex mortality differential in people is due to both biological/genetic and environmental/behavioral risk and protective factors.<ref>Kalben, Barbara Blatt. "Why Men Die Younger: Causes of Mortality Differences by Sex". Society of Actuaries", 2002.http://www.soa.org/news-and-publications/publications/other-publications/monographs/m-li01-1-toc.aspx</ref>
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| There is a recent suggestion that [[mitochondria]]l mutations that shorten lifespan continue to be expressed in males (but less so in females) because mitochondria are inherited only through the mother. By contrast [[natural selection]] weeds out mitochondria that reduce female survival as such mitochondria are less likely to be passed on to the next generation. Therefore it is suggested human females and female animals tend to live longer than males. The authors claim this is a partial explanation.<ref>[http://www.bbc.co.uk/news/health-19093442 Fruit flies offer DNA clue to why women live longer]</ref><ref>[[Evolutionary biology|Evolutionary biologist]], [[PZ Myers]] agrees. [http://scienceblogs.com/pharyngula/2013/02/06/mothers-curse/ Mother’s Curse]</ref>
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| ===Centenarians===
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| In developed countries, the number of [[centenarian]]s is increasing at approximately 5.5% per year, which means doubling the centenarian population every 13 years, pushing it from some 455,000 in 2009 to 4.1 million in 2050.<ref>United Nations [http://www.un.org/esa/population/publications/WPA2009/WPA2009-report.pdf "World Population Ageing 2009"]; ST/ESA/SER.A/295, Population Division, Department of Economic and Social Affairs, United Nations, New York, Oct. 2010, liv + 73 pp.</ref> Japan is the country with the highest ratio of centenarians (347 for every 1 million inhabitants in September 2010). [[Shimane prefecture]] had an estimated 743 centenarians per million inhabitants.<ref>Japan Times [http://search.japantimes.co.jp/cgi-bin/nn20100915a8.html "Centenarians to Hit Record 44,000"]. The Japan Times, Sept. 15, 2010. [[Okinawa Prefecture|Okinawa]] (667 centenarians per 1 million inhabitants in September 2010, had been for a long time the Japanese prefecture with the largest ratio of centenarians, partly because it also had the largest loss of young and middle-aged population during the [[Pacific War]].</ref>
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| In the United States, the number of centenarians grew from 32,194 in 1980 to 71,944 in November 2010 (232 centenarians per million inhabitants).<ref>[http://www.census.gov/popest/national/asrh/2009-nat-res.html "Resident Population. National Population Estimates for the 2000s. Monthly Postcensal Resident Population, by single year of age, sex, race, and Hispanic Origin"], Bureau of the Census (updated monthly). Different figures, based on earlier assumptions (104,754 centenarians on Nov.1, 2009) are provided in [http://www.census.gov/newsroom/releases/pdf/cb10-ff06.pdf "Older Americans Month: May 2010"], Bureau of the Census, Facts for Features, March 2, 2010, 5 pp.</ref>
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| ==Evolution and aging rate==
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| Various species of plants and animals, including humans, have different lifespans. There is an evolutionary theory of [[aging]], and general consensus in the academic community of evolutionary theorists; however the theory doesn't work well in practice, and there are many unexplained exceptions.{{Citation needed|date=July 2013}} Evolutionary theory states that organisms that, by virtue of their defenses or lifestyle, live for long periods whilst avoiding accidents, disease, predation, etc., are likely to have genes that code for slow aging — which often translates to good cellular repair. This is theorized to be true because if predation or accidental deaths prevent most individuals from living to an old age, then there will be less natural selection to increase intrinsic life span.<ref>{{cite journal |author=Williams G |title=Pleiotropy, natural selection, and the evolution of senescence |journal=Evolution |volume=11 |pages=398–411 |year=1957 |doi=10.2307/2406060 |issue=4 |publisher=Society for the Study of Evolution |jstor=2406060 }}</ref> The finding was supported in a classic study of opossums by Austad,<ref>{{cite journal |author=Austad SN |title=Retarded senescence in an insular population of Virginia opossums |journal=J. Zool. London |volume=229 |issue=4 |pages=695–708 |year=1993 |doi=10.1111/j.1469-7998.1993.tb02665.x }}</ref> however the opposite relationship was found in an equally prominent study of guppies by Reznick.<ref>{{cite journal |author=Reznick DN, Bryant MJ, Roff D, Ghalambor CK, Ghalambor DE |title=Effect of extrinsic mortality on the evolution of senescence in guppies |journal=Nature |volume=431 |issue=7012 |pages=1095–1099 |year=2004 |doi=10.1038/nature02936 |pmid=15510147 }}</ref><ref>{{cite journal |author=Mitteldorf J, Pepper J |title=How can evolutionary theory accommodate recent empirical results on organismal senescence? |journal=Theory in Biosciences |volume=126 |issue=1 |pages=3–8 |year=2007 |doi=10.1007/s12064-007-0001-0 |pmid=18087751 }}</ref>
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| One prominent and very popular theory attributes aging to a tight budget for food energy called [[caloric restriction]].<ref>{{cite journal |author=Kirkwood TE |title=Evolution of aging |journal=Nature |volume=270 |pages=301–304 |year=1977 |doi=10.1038/270301a0 |pmid=593350 |issue=5635 }}</ref> Caloric restriction observed in many animals (most notably mice and rats), shows a near doubling of life span due to a very limited calorific intake. Support for this theory has been bolstered by several new studies linking lower [[basal metabolic rate]] to increased life expectancy.<ref>http://physrev.physiology.org/content/87/4/1175.full</ref><ref>http://www.discoverymedicine.com/S-J-Olshansky/2009/07/25/what-determines-longevity-metabolic-rate-or-stability</ref><ref>http://genesdev.cshlp.org/content/19/20/2399.full</ref> This is the key to why animals like [[giant tortoise]]s can live so long.<ref>http://www.immortalhumans.com/the-longevity-secret-for-tortoises-is-held-in-their-low-metabolism-rate/</ref> Studies of humans with 100+ year life spans have shown a link to decreased thyroid activity, resulting in their lowered metabolic rate.
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| In a broad survey of zoo animals, no relationship was found between the fertility of the animal and its life span.<ref>{{cite journal |author=Ricklefs RE, Cadena CD |title=Lifespan is unrelated to investment in reproduction in populations of mammals and birds in captivity |journal=Ecol. Lett. |volume=10 |issue=10 |pages=867–872 |year=2007 |doi=10.1111/j.1461-0248.2007.01085.x |pmid=17845285 }}</ref>
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| ==Calculating life expectancies==
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| [[File:Survivaltree.png|thumb|A survival tree to explain the calculations of life-expectancy. Red numbers indicate chance of survival at a specific age, and blue ones indicate age-specific death rates.]]
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| The starting point for calculating life expectancies is the [[age-specific death rate]]s of the population members. In the past, a very simple model of age-specific mortality used the [[Gompertz function]], although these days more sophisticated methods are used.<ref>Anderson, Robert N. (1999) Method for constructing complete annual U.S. life tables. Vital and health statistics. Series 2, Data evaluation and methods research ; no. 129 (DHHS publication ; no. (PHS) 99-1329) [http://www.cdc.gov/nchs/data/series/sr_02/sr02_129.pdf PDF]</ref>
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| In cases where the amount of data is relatively small, the most common methods are to fit a mathematical formula, such as an extension of the Gompertz function, to the data, or to look at an established [[mortality table]] previously derived for a larger population and make a simple adjustment to it (e.g. multiply by a constant factor) to fit the data.
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| With a large amount of data, one looks at the mortality rates actually experienced at each age, and applies smoothing (e.g. by [[cubic splines]]) to iron out any apparently random statistical fluctuations from one year of age to the next.
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| While the data required are easily identified in the case of humans, the computation of life expectancy of industrial products and wild animals involves more indirect techniques. The life expectancy and demography of wild animals are often estimated by capturing, marking and recapturing them.<ref>Linda J Young; Jerry H Young (1998) Statistical ecology : a population perspective. Kluwer Academic Publishers. p. 310</ref> The life of a product, more often termed [[shelf life]] is also computed using similar methods. In the case of long-lived components such as those used in critical applications, such as in aircraft methods such as [[accelerated aging]] are used to model the life expectancy of a component.<ref name=machine>Eliahu Zahavi,Vladimir Torbilo & Solomon Press (1996) Fatigue Design: Life Expectancy of Machine Parts. CRC Press. ISBN 0-8493-8970-4</ref>
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| The age-specific death rates are calculated separately for separate groups of data which are believed to have different mortality rates (e.g. males and females, and perhaps smokers and non-smokers if data is available separately for those groups) and 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 <math>x</math> to age <math>x+n</math> is denoted <math>\,_np_x\!</math> and the probability of dying during age <math>x</math> (i.e. between ages <math>x</math> and <math>x+1</math>) is denoted <math>q_x\!</math>. For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, then the age-specific death probability at age 90 would be 10%. Note that this is a probability rather than a mortality rate.
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| The expected future lifetime of a life age <math>x</math> in whole years (the ''curtate expected lifetime'' of ''(x)'') is denoted by the symbol <math>\,e_x\!</math>.{{ref|exsymbol2|[a]}} It is the conditional expected future lifetime (in whole years), assuming survival to age <math>x</math>. If <math>K(x)</math> denotes the curtate future lifetime at <math>x</math>, then
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| :<math>e_x = E[K(x)] = \sum_{k=0}^\infty k\, Pr(K(x)=k) = \sum_{k=0}^{\infty}k\, \,_kp_x \,\, q_{x+k}.</math>
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| Substituting <math>{}_kp_x \, q_{x+k} = {}_k p_x - {}_{k+1}p_x</math> in the sum and simplifying, we get the equivalent formula<ref>{{cite book|title= Models for Quantifying Risk| edition=Third| author=R. Cunningham, T. Herzog, and R. London| publisher=Actex| year=2008|isbn=978-1-56698-676-2}} page 92.</ref>
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| :<math>e_x = \sum_{k=1}^\infty {}_k p_x.</math>
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| If we make the assumption that on average people live a half year in the year of death, then the complete expectation of future lifetime at age <math>x</math> is <math> e_x + 1/2</math>.
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| Life expectancy is by definition an [[arithmetic mean]]. It can also be calculated by integrating the survival curve from ages 0 to positive infinity (or equivalently to the maximum lifespan, sometimes called 'omega'). For an extinct or completed [[Cohort (statistics)|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. These estimates are called period cohort life expectancies.
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| It is important to note that this statistic is usually based on past mortality experience, and assumes that the same age-specific mortality rates will continue into the future. Thus such life expectancy figures need to be adjusted for temporal trends before calculating how long a currently living individual of a particular age is expected to live. Period life expectancy remains a commonly used statistic to summarize the current health status of a population.
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| However for some purposes, such as pensions calculations, it is usual to adjust the life table used, thus assuming that age-specific death rates will continue to decrease over the years, as they have done in the past. This is often done by simply extrapolating past trends; however some models do exist to account for the evolution of mortality (e.g., the [[Lee–Carter model]]<ref>Ronald D. Lee and Lawrence Carter. 1992. "Modeling and Forecasting the Time Series of U.S. Mortality," ''Journal of the American Statistical Association'' 87
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| (September): 659-671.</ref>).
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| As discussed above, on an individual basis, there are a number of factors that have been shown to correlate with a longer life. Factors that are associated with variations in life expectancy include family history, marital status, economic status, physique, exercise, diet, drug use including smoking and alcohol consumption, disposition, education, environment, sleep, climate, and health care.<ref name="Santrock" />
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| ==Life expectancy forecasting==
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| Forecasting life expectancy and mortality forms an important subdivision of [[demography]]. Future trends in life expectancy have huge implications for old-age support programs like [[U.S. Social Security]] and [[pension]] systems, because the cash flow in these systems depends on the number of recipients still living (along with the rate of return on the investments or the tax rate in [[PAYGO]] systems). With longer life expectancies, these systems see increased cash outflow; if these systems underestimate increases in life-expectancies, they won't be prepared for the large payments that will inevitably occur as humans live longer and longer.
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| Life expectancy forecasting usually is based on two different approaches:
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| * Forecasting the life expectancy directly, generally using [[ARIMA]] or other time series extrapolation procedures: This approach has the advantage of simplicity, but it cannot account for changes in mortality at specific ages, and the forecasted number cannot be used to derive other [[life table]] results. Analyses and forecasts using this approach can be done with any common statistical/ mathematical software package, like [[EViews]], [[R (programming language)|R]], [[SAS (software)|SAS]], [[Stata]], [[Matlab]], or [[SPSS]].
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| * Forecasting age specific [[death rates]] and computing the life expectancy from the results with life table methods: This approach is usually more complex than simply forecasting life expectancy because the analyst must deal with correlated age specific mortality rates, but it seems to be more robust than simple one dimensional time series approaches. This approach also yields a set of age specific rates that may be used to derive other measures, like survival curves or life expectancies at different ages. The most important approach within this group is the [[Lee-Carter Model|Lee-Carter model]],<ref>http://www.soa.org/library/journals/north-american-actuarial-journal/2000/january/naaj0001_5.pdf</ref> which uses the [[singular value decomposition]] on a set of transformed age-specific mortality rates to reduce their dimensionality to a single time series, forecasts that time series, and then recovers a full set of age-specific mortality rates from that forecasted value. Software for this approach include Professor [[Rob J. Hyndman]]'s [http://robjhyndman.com/software/demography/ R package called `demography`] and [http://lcfit.demog.berkeley.edu/ UC Berkeley's LCFIT system].
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| ==Policy uses of life expectancy==
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| {{Expand section|date=July 2011}}
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| Life expectancy is one of the factors in measuring the [[Human Development Index]] (HDI) of each nation, along with adult literacy, education, and standard of living.<ref>{{cite web|url=http://hdrstats.undp.org/indicators/6.html |title=International Human Development Indicators — UNDP |publisher=Hdrstats.undp.org |date= |accessdate=2010-11-04}}</ref>
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| Life expectancy is also used in describing the [[Physical quality-of-life index|physical quality of life]] of an area.
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| Disparities in life expectancy are often cited as demonstrating the need for better medical care or increased social support.
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| Life expectancies are also used when determining the value of a life settlement, a life insurance policy sold for a cash asset.
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| ==Life expectancy vs. life span==
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| Life expectancy is often confused with life span to the point that they are nearly synonyms; when people hear 'life expectancy was 35 years' they often interpret this as meaning that people of that time or place had short life spans.<ref>{{Cite book
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| | last = Wanjek
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| | first = Christopher
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| | title = Bad Medicine: Misconceptions and Misuses Revealed, from Distance Healing to Vitamin O
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| | publisher = Wiley
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| | year = 2002
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| | pages = 70–71
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| | isbn = 0-471-43499-X
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| | postscript = <!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> One such example can be seen in the ''In Search of...'' episode "The Man Who Would Not Die" (About [[Count of St. Germain]]) where it is stated "Evidence recently discovered in the British Museum indicates that St. Germain may have well been the long lost third son of [[Rákóczi]] born in Transylvania in 1694. If he died in Germany in 1784, he lived 90 years. The average life expectancy in the 18th century was 35 years. Fifty was a ripe old age. ''Ninety''... was forever."
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| This ignores the fact that the life expectancy generally quoted is the ''at birth'' number which is an ''average'' that includes all the babies that die before their first year of life as well as people that die from disease and war. The genetics of humans and rate of aging were no different in preindustrial societies than today, but people frequently died young because of untreatable diseases, accidents, and malnutrition. Many women did not survive childbirth, and individuals who reached old age were likely to succumb quickly to health problems.
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| It can be argued that it is better to compare life expectancies of the period after childhood to get a better handle on life span.<ref>{{Cite book
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| | last = Wanjek
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| | first = Christopher
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| | title = Bad Medicine: Misconceptions and Misuses Revealed, from Distance Healing to Vitamin O
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| | publisher = Wiley
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| | year = 2002
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| | page = 71
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| | isbn = 0-471-43499-X
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| | postscript = . {{inconsistent citations}}}}</ref> Life expectancy can change dramatically after childhood, as is demonstrated by the [http://www.richardcarrier.info/lifetbl.html Roman Life Expectancy table] where ''at birth'' the life expectancy was 25 but at the age of 5 it jumped to 48. Studies like [http://web.archive.org/web/20070713083310/http://www.plimoth.org/discover/myth/dead-at-40.php Plymouth Plantation; "Dead at Forty"] and [http://www.infoplease.com/ipa/A0005140.html Life Expectancy by Age, 1850–2004] similarly show a dramatic increase in life expectancy once adulthood was reached.
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| ==See also==
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| {{Div col|cols=3}}
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| * [[Depreciation]]
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| * [[Biodemography]]
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| * [[Calorie restriction]]
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| * [[Demography]]
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| * [[DNA damage theory of aging]]
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| * [[Glasgow effect]]
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| * [[Healthcare inequality]]
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| * [[Indefinite lifespan]]
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| * [[Life extension]]
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| * [[Life table]]
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| * [[List of countries by life expectancy]]
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| * [[List of long-living organisms]]
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| * [[Maximum life span]]
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| * [[Medieval demography]]
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| * [[Mitohormesis]]
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| * [[Mortality rate]]
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| * [[Population Pyramid]]
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| * [[Senescence]]
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| * [[Lindy Effect]]
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| {{Div col end}}
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| ===Increasing life expectancy===
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| {{Div col|cols=3}}
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| * [[Strategies for Engineered Negligible Senescence]] (SENS)
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| * [[John Sperling]]
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| * [[Life extension]]
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| * [[Longevity]]
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| * [[Rejuvenation (aging)|Rejuvenation]]
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| * [[Public health]]
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| * [[Infant mortality]]
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| {{Div col end}}
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| ==Notes==
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| a. {{note|exsymbol}}{{note|exsymbol2}}In standard actuarial notation, ''e<sub>x</sub>'' refers to the expected future lifetime of ''(x)'' in whole years, while ''e<sub>x</sub>'' with a circle above the ''e'' denotes the complete expected future lifetime of ''(x)'', including the fraction.
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| ==References==
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| <!--<nowiki>
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| to generate footnotes using the<ref> and </ref> tags, and the template below
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| {{Reflist|2}}
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| ==Further reading==
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| * [[Leonid A. Gavrilov]] & Natalia S. Gavrilova (1991), ''The Biology of Life Span: A Quantitative Approach''. New York: Harwood Academic Publisher, ISBN 3-7186-4983-7
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| * Kochanek, Kenneth D., Elizabeth Arias, and Robert N. Anderson (2013), ''[http://purl.fdlp.gov/GPO/gpo41789 How Did Cause of Death Contribute to Racial Differences in Life Expectancy in the United States in 2010?]''. Hyattsville, Md.: [[United States Department of Health and Human Services|U.S. Department of Health and Human Services]], [[Centers for Disease Control and Prevention]], [[National Center for Health Statistics]].
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| ==External links==
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| {{Commons category|Life expectancy}}
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| * [http://www.google.com/publicdata/explore?ds=wb-wdi&met=sp_dyn_le00_in&idim=country:CAN&dl=en&hl=en&q=average+life+expectancy+canada#met=sp_dyn_le00_in&idim=country:USA:CHN Charts for all countries]
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| * [http://www.helpage.org/global-agewatch/population-ageing-data/ Global Agewatch has the latest internationally comparable statistics on life expectancy from 195 countries.]
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| * [https://www.cia.gov/library/publications/the-world-factbook/rankorder/2102rank.html Rank Order - Life expectancy at birth] from the CIA's World Factbook.
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| * [http://www.cdc.gov/nchs/fastats/lifexpec.htm CDC year-by-year life expectancy figures for USA] from the USA Centers for Disease Controls and Prevention, National Center for Health Statistics.
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| * [http://www.utexas.edu/depts/classics/documents/Life.html Life expectancy in Roman times] from the University of Texas.
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| * Animal lifespans: [http://web.archive.org/web/20060427184844/http://www.tesarta.com/www/resources/library/lifespans.html Animal Lifespans] from Tesarta Online (Internet Archive); [http://www.sonic.net/~petdoc/lifespan.htm The Life Span of Animals] from Dr Bob's All Creatures Site.
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| {{Longevity}}
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| {{DEFAULTSORT:Life Expectancy}}
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| [[Category:Actuarial science]]
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| [[Category:Ageing]]
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| [[Category:Demography]]
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| [[Category:Population]]
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| [[Category:Gerontology]]
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| [[Category:Demographic economics]]
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| [[Category:Senescence]]
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| {{Link FA|uk}}
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| {{Link GA|uk}}
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