Life expectancy is a statistical measure of the average time an organism is expected to live, based on the year of its birth, its current age and other demographic factors including gender. The most commonly used measure of life expectancy is at birth (LEB), which can be defined in two ways. Cohort LEB is the mean length of life of an actual birth cohort (all individuals born a given year) and can be computed only for cohorts born many decades ago, so that all their members have died. Period LEB is the mean length of life of a hypothetical cohort assumed to be exposed, from birth through death, to the mortality rates observed at a given year.
National LEB figures reported by statistical national agencies and international organizations are indeed estimates of period LEB. In the Bronze Age and the Iron Age, LEB was 26 years; the 2010 world LEB was 67.2 years. For recent years, LEB in Swaziland is about 49, while LEB in Japan is about 83. The combination of high infant mortality and deaths in young adulthood from accidents, epidemics, plagues, wars, and childbirth, particularly before modern medicine was widely available, significantly lowers LEB. For example, a society with a LEB of 40 may have few people dying at precisely 40: most will die before 30 or after 55. In populations with high infant mortality rates, LEB is highly sensitive to the rate of death in the first few years of life. Because of this sensitivity to infant mortality, LEB can be subjected to gross misinterpretation, leading one to believe that a population with a low LEB will necessarily have a small proportion of older people. Another measure, such as life expectancy at age 5 (e5), 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 5 would be another 65. Aggregate population measures, such as the proportion of the population in various age groups, should also be used along individual-based measures like formal life expectancy when analyzing population structure and dynamics. However, pre-modern societies still had universally higher mortality rates and universally lower life expectancies at every age for both genders, and this example was relatively rare. In societies with life expectancies of 30, for instance, a 40 year remaining timespan at age 5 may not be uncommon, but a 60 year one was.
Mathematically, life expectancy is the mean number of years of life remaining at a given age, assuming age-specific mortality rates remain at their most recently measured levels. It is denoted by ,[a] which means the mean number of subsequent years of life for someone now aged , according to a particular mortality experience. Longevity, maximum lifespan, and life expectancy are not synonyms. Life expectancy is defined statistically as the mean number of years remaining for an individual or a group of people at a given age. Longevity refers to the characteristics of the relatively long life span of some members of a population. Maximum lifespan is the age at death for the longest-lived individual of a species. Moreover, because life expectancy is an average, a particular person may die many years before or many years after the "expected" survival. The term "maximum life span" has a quite different meaning and is more related to longevity.
Life expectancy is also used in plant or animal ecology; life tables (also known as actuarial tables). The term life expectancy may also be used in the context of manufactured objects, but the related term shelf life is used for consumer products, and the terms "mean time to breakdown" (MTTB) and "mean time between failures" (MTBF) are used in engineering.
Records of human lifespan above age 100 are highly susceptible to errors. For example, the previous world-record holder for human lifespan, Carrie White, was uncovered as a simple typographic error after more than two decades. Therefore, the capacity for equivalent hidden errors make maximum lifespan records highly dubious. The oldest confirmed recorded age for any human is 122 years, reached by Jeanne Calment who lived between 1875 and 1997. 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. A theoretical study shows that the maximum life expectancy at birth is limited by the human life characteristic value δ, which is around 104 years. According to a study by biologists Bryan G. Hughes and Siegfried Hekimi, there is no evidence for limit on human lifespan.However, this view has been questioned on the basis of error patterns.
The following information is derived from the 1961 Encyclopædia Britannica and other sources, some with questionable accuracy. Unless otherwise stated, it represents estimates of the life expectancies of the world population as a whole. In many instances, life expectancy varied considerably according to class and gender.
Life expectancy at birth takes account of infant mortality but not prenatal mortality.
|Era||Life expectancy at birth in years||Life expectancy at older age|
|Paleolithic||33||Based on Neolithic and Bronze Age data, the total life expectancy at 15 would not exceed 34 years. Based on the data from modern hunter-gatherer populations, it is estimated that at 15, life expectancy was an additional 39 years (total 54), with a 0.60 probability of reaching 15.|
|Neolithic||20 to 33||Based on Early Neolithic data, total life expectancy at 15 would be 28–33 years|
|Bronze Age and Iron Age||26||Based on Early and Middle Bronze Age data, total life expectancy at 15 would be 28–36 years|
|Classical Greece||25 to 28||Based on Athens Agora and Corinth data, total life expectancy at 15 would be 37–41 years|
|Classical Rome||20 to 30||Data is lacking, but computer models provide the estimate. If a person survived to age 20, they could expect to live around 30 years more. Life expectancy was probably slightly longer for women than men.|
|Medieval Islamic world||35+||Average lifespan of scholars was 59–84.3 years.|
|Pre-Columbian Southern United States||25–30|
|Late medieval English peerage||30||At age 21, life expectancy of an aristocrat was an additional 43 years (total age 64).|
|Early modern England||33–40||34 years for males in the 18th century.|
|Pre-Champlain Canadian Maritimes||60||Samuel de Champlain wrote that in his visits to Mi'kmaq and Huron communities, he met people over 100 years old. Daniel Paul attributes the incredible lifespan in the region to low stress and a healthy diet of lean meats, diverse vegetables and legumes.|
|18th-century Prussia||24.7||For males.|
|18th-century France||27.5–30||For males.|
|18th-century Qing China||39.6||For males.|
|18th-century Edo Japan||41.1||For males.|
|Early 19th-century England||40|
|1900 world average||31|
|1950 world average||48|
|2014 world average||71.5|
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 among 13th-century English nobles at 30. Having survived until the age of 21, a male member of the English aristocracy in this period could expect to live:
17th-century English life expectancy was only about 35 years, largely because infant and child mortality remained high. Life expectancy was under 25 years in the early Colony of Virginia, and in seventeenth-century New England, about 40 percent died before reaching adulthood. During the Industrial Revolution, the life expectancy of children increased dramatically. The under-5 mortality rate in London decreased from 745 in 1730–1749 to 318 in 1810–1829.
Public health measures are credited with much of the recent increase in life expectancy. During the 20th century, despite a brief drop due to the 1918 flu pandemic starting around that time 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.
Human beings are expected to live on average 30–40 years in Swaziland and 82.6 years in Japan, but the latter's recorded life expectancy may have been very slightly increased by counting many infant deaths as stillborn. An analysis published in 2011 in The Lancet attributes Japanese life expectancy to equal opportunities and public health as well as diet.
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 on life expectancy is particularly notable in many African countries. According to projections made by the United Nations (UN) in 2002, the life expectancy at birth for 2010–2015 (if HIV/AIDS did not exist) would have been:
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.
In the United States, African-American people have shorter life expectancies than their European-American counterparts. For example, white Americans born in 2010 are expected to live until age 78.9, but black Americans only until age 75.1. This 3.8-year gap, however, is the lowest it has been since 1975 at the latest. The greatest difference was 7.1 years in 1993. In contrast, Asian-American women live the longest of all ethnic groups in the United States, with a life expectancy of 85.8 years. The life expectancy of Hispanic Americans is 81.2 years. According to the new government reports in the USA, life expectancy in the country dropped again because of the rise in suicide and drug overdose rates. The Centers for Disease Control (CDC) found nearly 70,000 more Americans died in 2017 than 2016, with rising rates of death among 25- to 44-year-olds.
Cities also experience a wide range of life expectancy based on neighborhood breakdowns. This is largely due to economic clustering and poverty conditions that tend to associate based on geographic location. Multi-generational poverty found in struggling neighborhoods also contributes. In United States cities such as Cincinnati, the life expectancy gap between low income and high income neighborhoods touches 20 years.
Economic circumstances also affect life expectancy. For example, in the United Kingdom, life expectancy in the wealthiest and richest areas is several years higher 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. In Glasgow, the disparity is amongst the highest in the world: life expectancy for males in the heavily deprived Calton area stands at 54, which is 28 years less than in the affluent area of Lenzie, which is only 8 km away.
A 2013 study found a pronounced relationship between economic inequality and life expectancy. 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. The authors suggest that when people are working extra hard during good economic times, they undergo more stress, exposure to pollution, and likelihood of injury among other longevity-limiting factors.
Life expectancy is also likely to be affected by exposure to high levels of highway air pollution or industrial air pollution. This is one way that occupation can have a major effect on life expectancy. Coal miners (and in prior generations, asbestos cutters) often have lower life expectancies than average. Other factors affecting an individual's life expectancy are genetic disorders, drug use, tobacco smoking, excessive alcohol consumption, obesity, access to health care, diet and exercise.
In the uterus, 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). 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. Also, data from the UK shows the gap in life expectancy between men and women decreasing in later life. This may be attributable to the effects of infant mortality and young adult death rates.
In the past, 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 despite females having higher morbidity rates, see Health Survival paradox. The reasons for this are not entirely certain. Traditional arguments tend to favor sociology-environmental factors: historically, men have generally consumed more tobacco, alcohol and drugs than women in most societies, and are more likely to die from many associated diseases such as lung cancer, tuberculosis and cirrhosis of the liver. Men are also more likely to die from injuries, whether unintentional (such as occupational, war or car accidents) or intentional (suicide). 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, prostate cancer, and coronary heart disease. These far outweigh the female mortality rate from breast cancer and cervical cancer.
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. This biological difference occurs because women have more resistance to infections and degenerative diseases.
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. Kalben's study, however, was restricted to data in Western Europe alone, where demographic transition occurred relatively early. In countries such as Hungary, Bulgaria, India and China, males continued to outlive females into the twentieth century. 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, males have higher mortality than females. Evidence suggests that the sex mortality differential in people is due to both biological/genetic and environmental/behavioral risk and protective factors.
There is a recent suggestion that mitochondrial 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; therefore such mitochondria are less likely to be passed on to the next generation. This thus suggests that females tend to live longer than males. The authors claim that this is a partial explanation.
In developed countries, starting around 1880, death rates decreased faster among women, leading to differences in mortality rates between males and females. Before 1880 death rates were the same. In people born after 1900, the death rate of 50- to 70-year-old men was double that of women of the same age. Cardiovascular disease was the main cause of the higher death rates among men. Men may be more vulnerable to cardiovascular disease than women, but this susceptibility was evident only after deaths from other causes, such as infections, started to decline. Most of the difference in life expectancy between the sexes is accounted for by differences in the rate of death by cardiovascular diseases among persons aged 50-70. 
In developed countries, the number of centenarians 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. 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.
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).
The greater mortality of people with mental disorders may be due to death from injury, from co-morbid conditions, or from medication side effects. Psychiatric medicines can increase the chance of developing diabetes. Psychiatric medicine can also cause agranulocytosis. Psychiatric medicines also affect the stomach, where the mentally ill have a four times risk of gastrointestinal disease.
The life expectancy of people with diabetes, which is 9.3% of the U.S. population, is reduced by roughly ten to twenty years. Other demographics that tend to have a lower life expectancy than average include transplant recipients, and the obese.
Education has a large role to play in life expectancy in a myriad of ways. For example it leads to higher income  which has been shown to lead to increased life expectancy.
Pre-school education also plays a large role in life expectancy. It was found that high-quality early stage childhood education had positive effects on health. Researchers discovered this by analyzing the results of the Carolina Abecedarian Project (ABC) finding that the disadvantaged children who were randomly assigned to treatment had lower instances of risk factors for cardiovascular and metabolic diseases in their mid-30s.
Various species of plants and animals, including humans, have different lifespans. Evolutionary theory states that organisms that, by virtue of their defenses or lifestyle, live for long periods and avoid accidents, disease, predation, etc. are likely to have genes that code for slow aging, which often translates to good cellular repair. One theory is that if predation or accidental deaths prevent most individuals from living to an old age, there will be less natural selection to increase the intrinsic life span. That finding was supported in a classic study of opossums by Austad; however, the opposite relationship was found in an equally prominent study of guppies by Reznick.
One prominent and very popular theory states that lifespan can be lengthened by a tight budget for food energy called caloric restriction. Caloric restriction observed in many animals (most notably mice and rats) shows a near doubling of life span from a very limited calorific intake. Support for the theory has been bolstered by several new studies linking lower basal metabolic rate to increased life expectancy. That is the key to why animals like giant tortoises can live so long. Studies of humans with life spans of at least 100 have shown a link to decreased thyroid activity, resulting in their lowered metabolic rate.
In a broad survey of zoo animals, no relationship was found between the fertility of the animal and its life span.
The starting point for calculating life expectancy is the age-specific death rates of the population members. If a large number of data is available, a statistical population can be created that allow the age-specific death rates to be simply taken as the mortality rates actually experienced at each age (the number of deaths divided by the number of years "exposed to risk" in each data cell). However, it is customary to apply smoothing to iron out, as much as possible, the random statistical fluctuations from one year of age to the next. In the past, a very simple model used for this purpose was the Gompertz function, but more sophisticated methods are now used.
These are the most common methods now used for that purpose:
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. 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: in aircraft, methods like accelerated aging are used to model the life expectancy of a component.
The age-specific death rates are calculated separately for separate groups of data that are believed to have different mortality rates (such as males and females, and perhaps smokers and non-smokers if data are 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 to age is denoted and the probability of dying during age (between ages and ) is denoted . For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, the age-specific death probability at 90 would be 10%. That is a probability, not a mortality rate.
The expected future lifetime of a life age in whole years (the curtate expected lifetime of (x)) is denoted by the symbol .[a] It is the conditional expected future lifetime (in whole years), assuming survival to age . If denotes the curtate future lifetime at ,
Substituting in the sum and simplifying gives the equivalent formula: If the assumption is made that on average, people live a half year in the year of death, the complete expectation of future lifetime at age is .
Life expectancy is by definition an arithmetic mean. It can also be calculated by integrating the survival curve from 0 to positive infinity (or equivalently to the maximum lifespan, sometimes called 'omega'). For an extinct or completed cohort (all people born in year 1850, for example), it can of course simply be calculated by averaging the ages at death. For cohorts with some survivors, it is estimated by using mortality experience in recent years. The estimates are called period cohort life expectancies.
It is important to note that the 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.
However, for some purposes, such as pensions calculations, it is usual to adjust the life table used by assuming that age-specific death rates will continue to decrease over the years, as they have usually done in the past. That is often done by simply extrapolating past trends; but some models exist to account for the evolution of mortality like the Lee–Carter model.
As discussed above, on an individual basis, a number of factors 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.
In order to assess the quality of these additional years of life, 'healthy life expectancy' has been calculated for the last 30 years. Since 2001, the World Health Organization has published 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 uses similar indicators in the framework of the national health promotion and disease prevention plan "Healthy People 2010". More and more countries are using health expectancy indicators to monitor the health of their population.
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 since the cash flow in these systems depends on the number of recipients who are still living (along with the rate of return on the investments or the tax rate in pay-as-you-go systems). With longer life expectancies, the systems see increased cash outflow; if the systems underestimate increases in life-expectancies, they will be unprepared for the large payments that will occur, as humans live longer and longer.
Life expectancy forecasting is usually based on two different approaches:
Life expectancy is also used in describing the physical quality of life of an area or, for an individual when the value of a life settlement is determined a life insurance policy sold for a cash asset.
Disparities in life expectancy are often cited as demonstrating the need for better medical care or increased social support. A strongly associated indirect measure is income inequality. For the top 21 industrialized countries, if each person is counted equally, life expectancy is lower in more unequal countries (r = −0.907). There is a similar relationship among states in the US (r = −0.620).
Life expectancy is commonly confused with the average age an adult could expect to live. This confusion may create the expectation that an adult would be unlikely to exceed an average life expectancy, even though, with all statistical probability, an adult, who has already avoided many statistical causes of adolescent mortality, should be expected to outlive the average life expectancy calculated from birth. One must compare life expectancy of the period after childhood, to estimate the life expectancy of an adult. Life expectancy can change dramatically after childhood, even in preindustrial times as is demonstrated by the Roman Life Expectancy table, which estimates life expectancy to be 25 years at birth, but 53 years upon reaching age 25. Studies like Plymouth Plantation; "Dead at Forty" and Life Expectancy by Age, 1850–2004 similarly show a dramatic increase in life expectancy once adulthood was reached.
Life expectancy differs from maximum life span. Life expectancy is an average for all people in the population — including those who die shortly after birth, those who die in early adulthood (e.g. childbirth, war), and those who live unimpeded until old age. Maximum lifespan is an individual-specific concept — maximum lifespan is therefore an upper bound rather than an average. Science author Christopher Wanjek said "has the human race increased its life span? Not at all. This is one of the biggest misconceptions about old age." The maximum life span, or oldest age a human can live, may be constant. Further, there are many examples of people living significantly longer than the average life expectancy of their time period, such as Socrates, Saint Anthony, Michelangelo, and Benjamin Franklin.
However, anthropologist John D. Hawks criticizes the popular conflation of life span (life expectancy) and maximum life span when popular science writers falsely imply that the average adult human does not live significantly longer than their ancestors. He writes, "[a]ge-specific mortality rates have declined across the adult lifespan. A smaller fraction of adults die at 20, at 30, at 40, at 50, and so on across the lifespan. As a result, we live longer on average... In every way we can measure, human lifespans are longer today than in the immediate past, and longer today than they were 2000 years ago... age-specific mortality rates in adults really have reduced substantially."
a. ^ ^ In standard actuarial notation, ex refers to the expected future lifetime of (x) in whole years, while ex with a circle above the e denotes the complete expected future lifetime of (x), including the fraction.
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....
Reduction in health inequalities with improved average population health was partly attributable to equal educational opportunities and financial access to care.
To date, reliable information on the lifespans of domestic cats is varied and relatively scant. Nevertheless, a number of studies have investigated the matter and have come up with noteworthy estimates. Estimates of mean lifespan in these studies range between 13 and 17 years, with a single value in the neighborhood of 15 years. At least one study found a median lifespan value of 14 years and a corresponding interquartile range of 9 to 17 years. Maximum lifespan has been estimated at values ranging from 22 to 30 years although there have been claims of cats dying at ages greater than 30 years.. According to the 2010 edition of the Guinness World Records, the oldest cat ever recorded was Creme Puff, who died in 2005, aged 38 years, 3 days. Female cats have been evidenced to outlive male cats, while neutered cats and crossbred cats have been evidenced to outlive entire and purebred cats, respectively. It has also been found that the greater a cat's weight, the lower its life expectancy on average.The life expectancy of a cat that is living indoors is typically 15.1 years. In one study of cat mortality, the most frequent causes were trauma (12.2%), renal disorder (12.1%), non-specific illness (11.2%), neoplasia (10.8%) and mass lesion disorders (10.2%).Aging in dogs
Aging in dogs (Canis lupus familiaris) varies from breed to breed, and affects the dog's health, physical ability and life expectancy.
As with humans, advanced years often bring changes in a dog's ability to hear, see and move about easily. Skin condition, appetite and energy levels often degrade with geriatric age, and medical conditions such as cancer, renal failure, arthritis, dementia, and joint conditions, and other signs of old age may appear.
The changes in care often required by an older dog may lead a non-experienced owner to release the animal to a shelter or rescue organization. Non-profit groups have sprung up in response to the growing need for senior dog rescue.
The aging profile of dogs varies according to their adult size (often determined by their breed): smaller dogs often live over 15–16 years, medium and large size dogs typically 10 to 13 years, and some giant dog breeds such as mastiffs, often only 7 to 8 years. The latter reach maturity at a slightly older age than smaller breeds—giant breeds becoming adult around two years old compared to the norm of around 12–15 months for other breeds.Demographics of Yemen
This article is about the demographic features of the population of Yemen, including population density, ethnicity, education level, health of the populace, economic status, religious affiliations and other aspects of the population.Demography of Australia
The demography of Australia covers basic statistics, most populous cities, ethnicity and religion. The population of Australia is estimated to be 25,292,200 as of 17 March 2019. Australia is the 52nd most populous country in the world and the most populous Oceanian country. Its population is concentrated mainly in urban areas and is expected to exceed 28 million by 2030.Australia's population has grown from an estimated population of between 300,000 and 1,000,000 at the time of British settlement in 1788 due to numerous waves of immigration during the period since. Also due to immigration from other continents, the European component's share of the population is declining as a percentage.
Australia has an average population density of 3.3 persons per square kilometre of total land area, which makes it is one of the most sparsely populated countries in the world. This is generally attributed to the semi-arid and desert geography of much of the interior of the country. Another factor is urbanisation, with 89% of its population living in a handful of urban areas, Australia is one of the world's most urbanised countries. The life expectancy of Australia in 1999–2001 was 79.7 years, among the highest in the world.
Australia generally doesn't collect data on race and ethnicity, with the exception of Australian Aboriginals and Torres Strait Islanders.Eagle County, Colorado
Eagle County is one of the 64 counties of the U.S. state of Colorado. As of the 2010 census, the population was 52,197. The county seat is the Town of Eagle. The county is named for the Eagle River.
Eagle County comprises the Edwards, CO Micropolitan Statistical Area.Five-year survival rate
The five-year survival rate is a type of survival rate for estimating the prognosis of a particular disease, normally calculated from the point of diagnosis. Lead time bias from earlier diagnosis can affect interpretation of the five-year survival rate.There are absolute and relative survival rates, but the latter are more useful and commonly used.Football player
A football player or footballer is a sport person who plays one of the different types of football. The main types of football are association football, American football, Canadian football, Australian rules football, Gaelic football, rugby league and rugby union.
It has been estimated that there are 250 million association football players in the world, and many play the other forms of football.Health in Hungary
Although death rates have decreased in Hungary since 1985, life expectancy remains low by European standards, particularly among Romani people. Almost half the deaths are caused by cardiovascular disease. A tax on some high-sugar foods, introduced in 2011, has encountered opposition from the confectionery trade. Drinking remains a major health problem, while smoking prevalence has greatly decreased. Health in general is poorer in southern and eastern parts of the country.Health in Sri Lanka
Sri Lanka scores higher than the regional average in healthcare having a high Life expectancy and a lower maternal and infant death rate than its neighbors. In 2018 life expectancy was 72.1 for men and 78.5 for women ranking the country 70th in the world.Health in the United Kingdom
Health in the United Kingdom refers to the overall health of the population of the United Kingdom. Smoking, alcohol consumption and obesity in the United Kingdom are all above the OECD average.Human Development Index
The Human Development Index (HDI) is a statistic composite index of life expectancy, education, and per capita income indicators, which are used to rank countries into four tiers of human development. A country scores a higher HDI when the lifespan is higher, the education level is higher, and the GNI (PPP) per capita is higher. It was developed by Pakistani economist Mahbub ul Haq, with help from Gustav Ranis of Yale University and Lord Meghnad Desai of the London School of Economics, and was further used to measure a country's development by the United Nations Development Program (UNDP)'s Human Development Report Office.The 2010 Human Development Report introduced an Inequality-adjusted Human Development Index (IHDI). While the simple HDI remains useful, it stated that "the IHDI is the actual level of human development (accounting for inequality)", and "the HDI can be viewed as an index of 'potential' human development (or the maximum IHDI that could be achieved if there were no inequality)". The index does not take into account several factors, such as the net wealth per capita or the relative quality of goods in a country. This situation tends to lower the ranking for some of the most advanced countries, such as the G7 members and others.The index is based on the human development approach, developed by ul Haq, often framed in terms of whether people are able to "be" and "do" desirable things in life. Examples include—Being: well fed, sheltered, healthy; Doings: work, education, voting, participating in community life. The freedom of choice is central—someone choosing to be hungry (as during a religious fast) is quite different from someone who is hungry because they cannot afford to buy food, or because the country is in a famine.List of Indian states by life expectancy at birth
This is a list of Indian states by Life expectancy at birth. The figures come from the Human Development Index Report, published in 2011, by United Nations Development Programme (UNDP) India and Sample Registration Survey (SRS) based life table 2010-14.The report provides life expectancy at birth for years 2002-06 and 2010-14. In 2002-6, Punjab had the second highest life expectancy. Kerala had the highest life expectancy among the states in India, while Assam had the lowest. The figures for North-Eastern States were unavailable.List of U.S. states and territories by life expectancy
This article presents a list of United States states and territories sorted by their life expectancy at birth and by race/ethnicity in every state where the population of that racial or ethnic group is sufficiently large for robust estimates. The data is taken from the Measure of America's third national human development report, The Measure of America 2013–2014, and from the CIA World Factbook for the territories. Overall, life expectancy at birth in Hawaii, Minnesota and Puerto Rico are among the longest in the nation, while life expectancy at birth in Mississippi and American Samoa are among the shortest in the nation.List of countries by life expectancy
This is a collection of lists of countries by average life expectancy at birth.Longevity
The word "longevity" is sometimes used as a synonym for "life expectancy" in demography. However, the term longevity is sometimes meant to refer only to especially long-lived members of a population, whereas life expectancy is always defined statistically as the average number of years remaining at a given age. For example, a population's life expectancy at birth is the same as the average age at death for all people born in the same year (in the case of cohorts). Longevity is best thought of as a term for general audiences meaning 'typical length of life' and specific statistical definitions should be clarified when necessary.
Reflections on longevity have usually gone beyond acknowledging the brevity of human life and have included thinking about methods to extend life. Longevity has been a topic not only for the scientific community but also for writers of travel, science fiction, and utopian novels.
There are many difficulties in authenticating the longest human life span ever by modern verification standards, owing to inaccurate or incomplete birth statistics. Fiction, legend, and folklore have proposed or claimed life spans in the past or future vastly longer than those verified by modern standards, and longevity narratives and unverified longevity claims frequently speak of their existence in the present.
A life annuity is a form of longevity insurance.Longevity escape velocity
Longevity escape velocity (sometimes referred to as Actuarial escape velocity) is a term used in the life extension movement. It is a hypothetical situation in which life expectancy is being extended longer than the time that is passing. For example, in a given year in which longevity escape velocity would be maintained, technological advances would increase life expectancy more than the year that just went by.
Life expectancy increases slightly every year as treatment strategies and technologies improve. At present, more than one year of research is required for each additional year of expected life. Longevity escape velocity occurs when this ratio reverses, so that life expectancy increases faster than one year per one year of research, as long as that rate of advance is sustainable.The concept was first publicly proposed by David Gobel, co-founder of the Methuselah Foundation (MF). The idea has been championed by biogerontologist Aubrey de Grey (the other co-founder of the MF),
and futurist Ray Kurzweil, who named one of his books, Fantastic Voyage: Live Long Enough to Live Forever, after the concept. These two claim that by putting further pressure on science and medicine to focus research on increasing limits of aging, rather than continuing along at its current pace, more lives will be saved in the future, even if the benefit is not immediately apparent.Pitkin County, Colorado
Pitkin County is one of the 64 counties in the U.S. state of Colorado. As of the 2010 census, the population was 17,148. The county seat is Aspen. The county is named in honor of the late Colorado Governor Frederick Walker Pitkin. Pitkin County has the seventh-highest per capita income of any county in the United States.Pitkin County is included in the Glenwood Springs, CO Micropolitan Statistical Area, which is also included in the Edwards-Glenwood Springs, CO Combined Statistical Area.Summit County, Colorado
Summit County is one of the 64 counties in the U.S. state of Colorado. As of the 2010 census, the population was 27,994. The county seat is Breckenridge.Summit County comprises the Breckenridge, CO Micropolitan Statistical Area.
(over age 100)
(over age 110)