Life Expectancy is a statistical measure of the time the average organism is expected to live, by year of birth, current age and other demographic factors including sex. The most commonly used life expectancy is birth (LEB), which can be defined in two ways. Cohort LEB is the average length of life of the actual birth cohort (all individuals born in a given year) and can be counted only for groups born many decades ago, so that all of their members have died. Period LEB is the average length of life of hypothetical groups assumed to be exposed, from birth to death, to the level of mortality observed in a given year.
National LEB figures reported by national statistics agencies and international organizations are indeed estimates of the LEB period. In the Bronze Age and Iron Age, the LEB was 26 years old; LEB world 2010 is 67.2 years. For the last years, in Swaziland LEB is about 49, and in Japan, it is about 83. The combination of high infant mortality and deaths in young adulthood from accidents, epidemics, calamities, wars, and births, especially before modern medicine widely available, significantly lowered LEB. But for those who survived the initial danger, life expectancy of 60 or 70 will not be rare. For example, people with LEB 40 may have fewer people who die at exactly 40: most will die before 30 or after 55 years. In populations with high infant mortality, LEB is very sensitive to mortality rates in the first few years of life. Because of this sensitivity to infant mortality, LEB can be a dirty misinterpretation, leading people to believe that populations with low LEBs will have a smaller proportion of older people. For example, in a hypothetical stationary population in which half the population dies before the age of five but others die right at the age of 70 years, LEB will be around 36, but about 25% of the population will be between the ages of 50 and 70. Another measure, such as life expectancy at age 5 (e 5 ), can be used to rule out the effects of infant mortality to provide a modest measure of overall mortality rate than in early childhood; in the hypothetical population above, life expectancy at 5 would be 65 again. The size of the aggregate population, such as the proportion of people in different age groups, should also be used with individual-based measures such as formal life expectancy when analyzing population structure and dynamics..
Mathematically, life expectancy is the average number of years of living left over at a certain age, assuming age-specific mortality rates remain at the last level measured. This is denoted by , [a] which means the average number of years next life for someone is now age , according to a certain mortality experience. Long life, maximum age, and life expectancy are not the same. Life expectancy is statistically defined as the average number of years left for individuals or groups of people at a certain age. Longevity refers to the characteristics of a relatively long life span of several members of the population. Maximum age is the age of death for the longest-lived individual of a species. In addition, because life expectancy is average, certain people may die many years earlier or years after "expected" survival. The term "maximum life span" has a very different meaning and is more closely related to longevity.
Life expectancy is also used in plant or animal ecology; the life table (also known as actuarial tables). Long life expectancy can also be used in the context of produced objects, but the term shelf-life is used for consumer products, and the term "mean time for damage" (MTTB) and "mean time between failures" (MTBF) are used in engineering.
Video Life expectancy
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Humans are expected to live on average 30-40 years in Swaziland and 82.6 years in Japan, but the last recorded life expectancy may have been slightly increased by counting the many deaths of infants as stillbirths. An analysis published in 2011 at The Lancet attributes Japan's life expectancy to equal opportunities and public health as well as diet.
The oldest age confirmed for human age is 122 years, achieved by Jeanne Calment who lived between 1875-1997. This is called the "maximum life span", which is the upper limit of life, the maximum number of years known to every human being to live. Theoretical studies show that the maximum life expectancy at birth is limited by the characteristic value of human life ?, ie about 104 years. According to a study by biologists Bryan G. Hughes and Siegfried Hekimi, there is no evidence for the age limit of humans.
Variations over time
The following information is from 1961 EncyclopÃÆ'Â|dia Britannica and other sources, some with questionable accuracy. Unless otherwise stated, it represents the expected life expectancy of the world population as a whole. In many instances, life expectancy varies by class and sex.
Life expectancy at birth takes into account infant mortality but not prenatal death.
Life expectancy increases with age as individuals survive with higher mortality rates associated with childhood. For example, the table above lists the life expectancy at birth among 13th-century English nobles at the age of 30. Having survived until the age of 21, a male member of the British aristocracy during this period may wish to live:
- 1200-1300: until age 64
- 1300-1400: until the age of 45 (due to bubonic disease)
- 1400-1500: until the age of 69
- 1500-1550: until the age of 71
The 17th century British life expectancy is only about 35 years old, mainly because infant and child mortality remains high. Life expectancy under 25 years in early Virginia Colony, and in the 17th century in New England, about 40 percent died before reaching adulthood. During the Industrial Revolution, the life expectancy of children increased dramatically. The under five year mortality rate in London declined from 745 in 1730-1749 to 318 in 1810-1829.
Public health measures are credited with many recent increases in life expectancy. During the 20th century, despite the brief decline of the 1918 flu pandemic that began around that time, the average lifespan in the United States increased over 30 years, where 25 years could be attributed to advances in public health.
Area variation
There is a huge variation in life expectancy between different parts of the world, largely due to differences in public health, medical care, and diet. The impact of AIDS on life expectancy is very important in many African countries. According to the projection made by the United Nations (UN) in 2002, life expectancy at birth for 2010-2015 (if HIV/AIDS does not exist) is:
- 70.7 years, not 31.6 years Botswana
- 69.9 years old, not 41.5 years South Africa
- 70.5 years, not 31.8 years Zimbabwe
The real life expectancy in Botswana declined from 65 in 1990 to 49 in 2000 before rising to 66 in 2011. In South Africa, life expectancy was 63 in 1990, 57 in 2000, and 58 in 2011. And at Zimbabwe, life expectancy is 60 years. 1990, 43 years 2000, and 54 of 2011.
Over the past 200 years, African countries generally do not have the same increase in mortality rates that have been enjoyed by countries in Asia, Latin America and Europe.
In the United States, African-Americans have a shorter life expectancy than their European-American counterparts. For example, white Americans born in 2010 are expected to live up to the age of 78.9, but American blacks are only up to age 75.1. This 3.8 year gap, however, is the lowest since 1975 at the latest. The biggest difference was 7.1 years in 1993. In contrast, Asian-American women live the longest of all ethnic groups in the United States, with an 85.8-year life expectancy. The Hispanic American life expectancy is 81.2 years.
Cities also experience life expectancy based on environmental damage. This is largely due to the economic clustering and poverty conditions that tend to associate by geographic location. The multi-generational poverty found in the struggling environment also contributes. In US cities like Cincinnati, the life expectancy gap between low-income and high-income neighborhoods touches 20 years.
Economic situation
The economic situation also affects life expectancy. For example, in the UK, life expectancy in the richest and wealthiest regions 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 diseases tend not to get rich or live in affluent areas. In Glasgow, disparity is one of the highest in the world: life expectancy for men in the very poor Calton region stands at 54, which is 28 years less than in the rich area of ​​Lenzie, which is only 8 km away.
A 2013 study found a clear link between economic inequality and life expectancy. However, a study by JosÃÆ'Â © 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 depression in general. The authors suggest that when people work extra hard during good economic times, they experience more stress, exposure to pollution, and the possibility of injury among other lifesaving factors.
Life expectancy also tends to be influenced by exposure to highway air pollution levels or industrial air pollution. This is one way that work can have a major impact on life expectancy. Coal miners (and in previous generations, asbestos cutters) often have lower life expectancy than average mean life expectancy. Other factors that affect one's life expectancy are genetic disorders, drug use, tobacco smoking, excessive alcohol consumption, obesity, access to health care, diet and exercise.
Gender differences
In the womb, the male fetus has a higher mortality rate (infants are in an estimated ratio of 107 to 170 men to 100 women, but the ratio at birth in the United States is only 105 men to 100 women). Among the smallest premature infants (who are under 2 pounds or 900 g), females once again have higher survival rates. At the other extreme, about 90% of individuals aged 110 are women. The life expectancy difference between men and women in the United States fell 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 showed a gap in life expectancy between men and women decreases in the future. This may be due to the effects of infant death and the death rate of young adults.
In the past, the mortality rate for women in the fertile age group was higher than that of men of the same age. This is no longer the case, and women's life expectancy is much higher than men's. The reasons for this are not entirely certain. Traditional arguments tend to support sociological-environmental factors: historically, men generally consume more tobacco, alcohol, and drugs than women in most societies, and are more likely to die from various associated diseases such as lung cancer, tuberculosis, and cirrhosis heart. Men are also more likely to die of injury, whether accidental (such as work accidents, wars or cars) or deliberate (suicide). Men are also more likely to die from most of the major causes of death (some already mentioned above) than women. Some of them in the United States include: respiratory system cancer, motor vehicle accidents, suicide, liver cirrhosis, emphysema, prostate cancer, and coronary heart disease. This is far greater than the death rate of women from breast cancer and cervical cancer.
Some argue that the shorter male life expectancy is just another manifestation of the general rule, seen in all mammal species, that larger (size) individuals (in a species) tend to, on average, have shorter lives. These biological differences occur because women are more resistant to infections and degenerative diseases.
In his extensive review of the existing literature, Kalben concludes that the fact that women live longer than men is observed at least as far back as 1750 and that, with relatively equal treatment, today men in all parts of the world experience greater death than women.. However, the Kalben study is limited to data in Western Europe only, where the demographic transition occurs relatively early. In countries like Hungary, Bulgaria, India and China, men continue to live longer than women into the twentieth century. Of the 72 causes of death selected, only 6 resulted in a greater female mortality rate than men in 1998 in the United States. With the exception of birds, for almost all animal species studied, males have a higher mortality rate than women. The evidence suggests that the difference in the rate of sex death in humans is due to risk factors and biological/genetic and environmental/behavioral factors.
There is a recent suggestion that mitochondrial mutations that shorten age continue to be expressed in men (but less in women) because mitochondria are inherited only through the mother. In contrast, natural selection removes mitochondria that reduce women's survival; therefore such mitochondria are less likely to be passed on to the next generation. Thus it shows that women tend to live longer than men. The authors claim that this is a partial explanation.
In developed countries, beginning around 1880, mortality rates declined more rapidly among women, leading to differences in mortality rates between men and women. Before the death of 1880 was the same. In people born after 1900, the death rate of men 50 to 70 years is twice that of women of the same age. Cardiovascular disease is the leading cause of higher mortality rates among men. Men may be more susceptible to cardiovascular disease than women, but this vulnerability is evident only after death from other causes, such as infection, begins to decline.
Centenarian
In developed countries, the number of centenarians increases by about 5.5% per year, which means doubling the centenarian population every 13 years, pushing it from about 455,000 in 2009 to 4.1 million by 2050. Japan is the country with the highest centenarian ratio. (347 for every 1 million residents in September 2010). Shimane Prefecture is estimated to have 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).
Mental illness
Mental illness is reported to occur in about 18% of the average American population.
Serious mental illness has a 10 to 25 year reduction in life expectancy. Lifecycle reductions have been studied and documented.
Greater deaths from people with mental disorders may be due to death from injury, from comorbid conditions, or from drug side effects. Psychiatric drugs can increase the likelihood of developing diabetes. Psychiatric drugs can also cause Agranulocytosis. Psychiatric drugs also affect the stomach, where mentally ill people have a fourfold risk of gastrointestinal disease.
Other diseases
The life expectancy of people with diabetes, ie 9.3% of the US population, is reduced by about ten to twenty years. Other demographics that tend to have lower life expectancy than average include transplant recipients, and obesity.
Maps Life expectancy
Evolution and aging rate
Various species of plants and animals, including humans, have different life spans. The theory of evolution suggests that organisms that, by their defense or lifestyle, live for a long time and avoid accidents, illness, predation, etc. Tend to have genes that encode slow aging, which often translates into good cellular improvements. One theory is that if accidental predation or death prevent most individuals from living to old age, there will be less natural selection to increase intrinsic lifespan. The discovery was supported in a classic study of opossum by Austad; However, the opposite relationship is found in studies of the same guppies stand out by Reznick.
One well-known and very popular theory states that age can be extended by a strict budget for food energy called calorie restriction. The calorie restriction observed in many animals (especially rats and mice) shows almost twice the lifespan of a very limited caloric intake. Support for the theory has been supported by several new studies linking lower basal metabolic rates to improve life expectancy. That is the key to why animals such as giant tortoises can live for so long. Studies in humans with a lifespan of at least 100 indicate association with decreased thyroid activity, thereby lowering their metabolic rate.
In a broad survey of zoo animals, no relationship was found between the fertility of the animal and its life span.
Calculation
The starting point for calculating life expectancy is the age-specific mortality rate of members of the population. If large amounts of data are available, statistical populations can be made that allow age-specific mortality to be taken for granted because death rates are actually experienced at every age (the number of deaths divided by the number of years "exposed to risk" in each data cell). However, it is common to apply smoothing to ironing, as much as possible, random statistical fluctuations from one year to the next. In the past, the very simple model used for this purpose was the Gompertz function, but more sophisticated methods are now used.
This is the most common method now used for that purpose:
- to match mathematical formulas, such as extension of Gompertz function, to data,
- for a relatively small amount of data, to see the established mortality table previously lowered for a larger population and make a simple adjustment to it (as multiplied by a constant factor) to fit the data.
- with large amounts of data, one looks at the actual mortality rate experienced by each age, and applies the smoothing (as with cubic splines).
While the data required are easily identifiable in human cases, the calculation of life expectancy of industrial and wild products involves more indirect techniques. Life expectancy and demographics of wild animals are often estimated by capturing, marking, and reclaiming them. The life of a product, more often called shelf life, is also calculated using a similar method. In the case of long-lived components, such as those used in critical applications: in an airplane, methods such as accelerated aging are used to model component life expectancies.
Age-specific mortality rates are calculated separately for separate data sets believed to have different mortality rates (such as males and females, and possibly smokers and nonsmokers if data are available separately for these groups) and then used to calculate life tables from where one can calculate the probability of survival for each age. In actuarial notes, possibly saved from for notes and the probability of death during age (between the ages and ) is denoted . For example, if 10% of a group of people living on their 90th birthday died before their 91st birthday, the probability of age-specific mortality at 90 would be 10%. That is the probability, not the death rate.
Mengganti dalam penjumlahan dan penyederhanaan memberikan rumus yang setara: Jika asumsi dibuat bahwa rata-rata, orang-orang hidup setengah tahun di tahun kematian, harapan lengkap masa depan di usia adalah .
Life expectancy by definition is the arithmetic mean. This can also be calculated by integrating the survival curve from 0 to positive infinity (or equivalent to the maximum age, sometimes called 'omega'). For extinct or complete cohorts (everyone born in 1850, for example), it can, of course, be calculated by the average age at death. For a cohort with some survivors, it is estimated by using the experience of death in recent years. Estimates are called life expectancy cohorts.
It is important to note that statistics are usually based on past experience of death and assume that the same age-specific mortality rate will continue into the future. Thus, such life expectancy needs to be adjusted for temporal trends before calculating how long a person living at this time from a certain age is expected to live. Life expectancy remains a commonly used statistic to summarize the health status of a population today.
However, for some purposes, such as retirement calculations, it usually adjusts the life table used by assuming that age-specific mortality will continue to decline over the years, as has usually been done in the past. It is often done simply by extrapolating past trends; but some models exist to explain the evolution of mortality like the Lee-Carter model.
As discussed above, individually, a number of factors correlate with a longer life. Factors related to life expectancy variation include family history, marital status, economic status, physical, exercise, diet, drug use including smoking and alcohol consumption, disposition, education, environment, sleep, climate, and health care.
Healthy life expectancy
To assess the quality of these extra years of life, 'healthy life expectancy' has been calculated over 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 a person can expect to live in "full health" excluding years living less than full health due to illness and/or injury. Since 2004, Eurostat published an annual statistic called Healthy Life Years (HLY) based on reported activity limitations. The United States uses similar indicators in the context of national health promotion and disease prevention plan of "Healthy People 2010". More countries are using health expectation indicators to monitor the health of their inhabitants.
Forecasting
Estimating life expectancy and death is an important part of demography. Future trends in life expectancy have major implications for old-age support programs such as US Social Security and pensions as the cash flows in this system depend on the number of surviving recipients (along with the investment rate or rate tax in the pay-as-you- go). With longer life expectancy, the system sees an increase in cash outflow; if the system underestimates the increase in life expectancy, they will be unprepared for the big payouts that will happen, because humans live longer and longer.
Life expectancy forecasting is usually based on two different approaches:
- Estimates live life expectancy, generally using ARIMA or other time series extrapolation procedures: which have the advantage of simplicity, but can not account for changes in mortality at any given age, and the prediction number can not be used to obtain the results of the life table others. Analysis and forecast using this approach can be done with regular statistical/math software packages, such as EViews, R, SAS, Stata, Matlab, or SPSS.
- Estimating age-specific mortality rates and calculating life expectancy from outcomes by life table method: which is usually more complex than simply estimating life expectancy as analysts have to deal with related age-specific mortality rates, but seem stronger than the one-dimensional time dimension approach simple. It also produces a set of age-specific levels that can be used to decrease other measures, such as survival curves or life expectancy at different ages. The most important approach in this group is the Lee-Carter model, which uses the singular value decomposition in a set of specific age mortality rates that change to reduce their dimensions to a time series, predict the timing sequence and then rediscover the full set of age-specific mortality rates from estimated value. The software includes Professor Rob J. Hyndman R's package called `demographic` and the UC Berkeley LCFIT system.
Policy use
Life expectancy is one factor in measuring Human Development Index (HDI) of each country along with adult literacy, education, and living standards.
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 the life insurance policy being sold for cash assets.
The gaps in life expectancy are often cited as indicating the need for better medical care or increased social support. A strongly related indirect measure is income inequality. For the top 21 industrialized countries, if everyone is calculated the same, life expectancy is lower in a more unequal country (r = -0.907). There is a similar relationship among states in the US (r = -0.620).
Life expectancy vs. lifetime
Life expectancy differs from the maximum life span. Life expectancy is the average for everyone in the population - including those who die soon after birth, those who die in early adulthood (eg childbirth, war), and those who live unhindered to old age. Age is an individual-specific concept - the maximum age because it is the upper limit of the average.
However, these two terms often confuse each other until when people hear "life expectancy is 35 years" they often interpret this as meaning that people in that time or place have a short maximum life span. One example can be seen in the In Search... episode of "People Who Will not Die" (About Count of St. Germain) where stated "Recent evidence found in the British Museum shows that St. Germain may have been the third son lost from RÃÆ'¡kÃÆ'³czi born in Transylvania in 1694. If he died in Germany in 1784, he lived for 90 years. The average life expectancy in the 18th century was 35 years. is a mature old age. Ninety ... forever. "
In fact, there are other examples of people who live significantly longer than their life expectancy, such as Socrates, Saint Anthony, Michelangelo, and Benjamin Franklin.
It can be said that it is better to compare the life expectancy of the post-childhood period to get a better handle on life span. Life expectancy can change dramatically after childhood, as shown by the Hope Life table of Rome where at birth , life expectancy is 21, but at the age of 5, it jumps to 42. Studies such as Plymouth Plantation; "Dead at Forty" and Life Expectancy by Age, 1850-2004 alike show a dramatic increase in life expectancy as adults are achieved.
See also
Increasing life expectancy
Note
A. ^ ^ In the standard actuarial note, e < sub> x refers to the expected future of (x) throughout the year, while e x with circles above e shows the expected full future of (x) , including fraction.
References
Further reading
- Leonid A. Gavrilov & amp; Natalia S. Gavrilova (1991), Life Span Biology: A Quantitative Approach . New York: Harwood Academic Publisher, ISBN 3-7186-4983-7
- Kochanek, Kenneth D., Elizabeth Arias, and Robert N. Anderson (2013), How Did The Causes of Death Contribute to Racial Differences in Life Expectations in the United States in 2010? . Hyattsville, Md.: US Department of Health and Human Services, Center for Disease Control and Prevention, National Center for Health Statistics.
External links
- Charts for all countries
- Our World In Data - Life Expectancy - The visualization of how life expectancy around the world has changed historically (by Max Roser). Includes life expectancy for different age groups. Diagrams for all countries, world maps, and links to more data sources.
- Global Agewatch has the most internationally comparable statistics on the life expectancy of 195 countries.
- Ranking order - Life expectancy at birth of the CIA World Factbook.
- CDC year-on-year life expectancy for the US from the US Centers for Disease Control and Prevention, National Center for Health Statistics.
- Life expectancy in Roman times from the University of Texas.
- Animal lifespan: Animal Range from Tesarta Online (Internet Archive); Range of Animal Life from the Site of All Creatures Dr. Bob.
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