Life expectancy is the average number of years of life remaining at a given age. Life expectancy is heavily dependent on the criteria used to select the group. In countries with high infant mortality rates, the life expectancy at birth is highly sensitive to the rate of death in the first few years of life. In these cases, another measure such as life expectancy at age 5 (e5) can be used to exclude the effects of infant mortality to reveal the effects of causes of death other than early childhood causes.
See also List of countries by life expectancy
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Humans live on average 31.99 years in Swaziland and on average 82 years in Japan (2008 est.). The oldest confirmed recorded age for any human is 122 years, though some people are reported to have lived longer. Although there are several longevity myths mostly in different stories that were spread in some cultures, there is no scientific evidence of a human living for hundreds of years at any point of time. The following information is derived from the Encyclopaedia Britannica, 1961, as well as other sources:
Humans by Era | Average Lifespan at Birth (years) |
Comment |
---|---|---|
Neanderthal | 20 | Homo neanderthalensis supposedly was a separate species from modern humans but were members of the genus Homo, to which humans belong. |
Upper Paleolithic | 33 | At age 15: 39 (to age 54)[1][2] |
Neolithic | 20 | |
Bronze Age[3] | 18 | |
Classical Greece[4] | 20-30 | |
Classical Rome[5][6] | 20-30 | |
Pre-Columbian North America[7] | 25-35 | |
Medieval Islamic Caliphate[8] | 35+ | The average lifespans of the scholarly class were 59–84.3 years in the Middle East[9][10] and 69–75 in Islamic Spain.[11] |
Medieval Britain[12][13] | 20-30 | |
Early 20th Century[14][15] | 30-40 | |
Current world average[16][17] | 66.12 (2008 est.) |
These represent the life expectancies of the population as a whole. In many instances life expectancy varied considerably according to class and gender. Life expectancy rises sharply in all cases for those who reach puberty. All statistics include infant mortality, but not miscarriage or abortion. This table also rejects certain beliefs based on myths that the old age man had a higher life expectancy. The sharp drop in life expectancy with the advent of the Neolithic mirrors the evidence that the advent of agriculture actually marked a sharp drop in life expectancy that humans are only recovering from in more recent times, mainly in affluent nations.
There are great variations in life expectancy worldwide, mostly caused by differences in public health, medical care and diet from country to country. Climate and location may also have an effect, and the way data is collected may also be an important influence. According to the U.S. Census Bureau, Andorra has the world's longest life expectancy of 83.5 years.
There are also variations between groups within single countries. Significant differences still remain in life expectancy between men and women in France and other developed countries, with women outliving men by five years or more. These gender differences have been lessening in recent years, with men's life expectancy improving at a faster rate than women's. Poverty, in particular, has a very substantial effect on life expectancy. In the United Kingdom life expectancy in the wealthiest areas is on average ten years longer than the poorest areas and the gap appears to be increasing as life expectancy for the prosperous continues to increase while in more deprived communities there is little increase.[18] However, in Glasgow the disparity is among the highest in the world with life expectancy for males in the heavily deprived Calton standing at fifty-four — twenty-eight years less than in the affluent area of Lenzie, which is only eight kilometres away.[19][20]
Life expectancy may also be reduced for people exposed to high levels of highway air pollution or industrial air pollution. Occupation may also have a major effect on life expectancy. Well-educated professionals working in offices have a high life expectancy, while coal miners (and in prior generations, asbestos cutters) do not. Other factors affecting an individual's life expectancy are genetic disorders, obesity, access to health care, diet, exercise, tobacco smoking, and excessive drug and alcohol use.
As pointed out above, AIDS has recently had a negative effect on life expectancy, especially in Sub-Saharan Africa.
The differing lifespans within various species of plants and animals, including humans, raises the question of why such lifespans are observed.
The evolutionary theory states that organisms that are able by virtue of their defenses or lifestyle to live for long periods whilst avoiding accidents, disease, predation etc. are likely to have genes that code for slow aging - good repair.
This is so because if a random genetic trait found in the organism increases its survivability, it is more likely to pass on its genes to the next generation. Thus, a member of the population with genes that lend to increased survivability will tend to reproduce more and have more successors. This gene which increases survivability will thus be increasingly spread throughout the species, increasing the survivability of the species as a whole.
Conversely a change to the environment that means that organisms die younger from a common disease or a new threat from a predator will mean that organisms that have genes that code for putting more energy into reproduction than repair will do better.
The support for this theory includes the fact that better defended animals, for example small birds that can fly away from danger live for a decade or more whereas mice which cannot, die of old age in a year or two. Tortoises and turtles are very well defended indeed and can live for over a hundred years. A classic study comparing opossums on a protected island with unprotected opossums also supports this theory.
But there are also counterexamples, suggesting that there is more to the story. Guppies in predator-free habitats evolve shorter life spans than nearby populations of guppies where predators exact a large toll. A broad survey of mammals indicates many more exceptions. The theory of evolution of aging may be in flux.
Another main counterexample is that the evolutionary traits best for short term survival may be detrimental to long term survival. For example, a hummingbird's extremely fast wings allow it to escape from predators and to find mates, assuring that the genetic trait for fast wings is passed on, explained by natural selection. However, these fast wings can be detrimental to the hummingbird's long term health, as the wings consume vast amounts of Adenosine triphosphate (cellular energy molecules) and cause the hummingbird's heart to deteriorate with permanent and long-term wear. This allows for hummingbirds to effectively survive and reproduce, however as a result, hummingbirds usually die shortly after reproducing.
Short term survival traits are usually those that are most commonly passed on in natural selection. However, humans with technology have prioritized their traits to improve long term survival, as they have already developed short term survival to a significant extent by ensuring their dominance of the food chain. This is known as artificial selection.
If one does not consider the many women who die while giving birth or in pregnancy, the female human life expectancy is considerably higher than those of men, who, on average, consume more tobacco, alcohol and drugs than females in most societies. In most countries many more men than women commit suicide. In general, men are more likely to be murdered. In wars, many men die in combat as soldiers. Men tend to take more risks than females when driving motor vehicles. [1]
Some argue that shorter male life expectancy is merely another manifestation of the general rule, seen in all mammal species, that larger individuals tend on average to have shorter lives. [2][21] If small body size is a result of poor nutrition and not of genetics, then the rule is the other way around: better nourished people are taller and live longer. [3]
There is significantly more research and awareness for women's health than men's health. For example there are seven breast cancer drugs for every one prostate cancer drug. In respect to US federal funding, there is twice as much money dedicated to breast cancer than to prostate cancer. However,it must be noted that breast cancer is well known to be a much more aggressive disease with a poorer prognosis when compared with prostate cancer. Prostate cancer may not always manifest as a 'life-impacting' disease in the lifetime of the man concerned, due to it's slower progress and propensity to be diagnosed much later in life when compared with breast cancer. It is also a point of interest that there remains no real clarity in whether or not screening of the general male population for prostate cancer is beneficial or harmful. Breast cancer screening programmes have improved mortality rates for breast cancer worldwide, and continue to do so.[4] The United States has an office dedicated to women's health while there is not one for men. The situation is mirrored in other industrialized countries.
Persons with serious Mental illness die, on average, 25 years earlier than the general public.
Mental illnesses such as schizophrenia, bipolar disorder and major depression. Three out of five mentally ill die from mostly preventable physical diseases. Diseases such as Heart/Cardiovascular disease, Diabetes, Dyslipidaemia, Respiratory ailments, Pneumonia, Influenza.
The starting point for calculating life expectancies is the age-specific death rates of the population members. For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, then the age-specific death rate at age 90 would be 10%.
These values are then used to calculate a life table, from which one can calculate the probability of surviving to each age. In actuarial notation the probability of surviving from age x to age x+n is denoted and the probability of dying during age x (i.e. between ages x and x+1) is denoted .
The life expectancy at age x, denoted , is then calculated by adding up the probabilities to survive to every age. This is the expected number of complete years lived (one may think of it as the number of birthdays they celebrate).
Because age is rounded down to the last birthday, on average people live half a year beyond their final birthday, so half a year is added to the life expectancy to calculate the full life expectancy.
Life expectancy is by definition an arithmetic mean. It can be calculated also by integrating the survival curve from ages 0 to positive infinity (the maximum lifespan, sometimes called 'omega'). For an extinct cohort (all people born in year 1850, for example), of course, it can simply be calculated by averaging the ages at death. For cohorts with some survivors it is estimated by using mortality experience in recent years.
Note that no allowance has been made in this calculation for expected changes in life expectancy in the future. Usually when life expectancy figures are quoted, they have been calculated like this with no allowance for expected future changes. This means that quoted life expectancy figures are not generally appropriate for calculating how long any given individual of a particular age is expected to live, as they effectively assume that current death rates will be "frozen" and not change in the future. Instead, life expectancy figures can be thought of as a useful statistic to summarize the current health status of a population. Some models do exist to account for the evolution of mortality (e.g., the Lee-Carter model[22]).