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Everything about Life Expectancy totally explained

Life expectancy is a statistical measure of the average life span (average length of survival) of a specified population. It most often refers to the expected age to be reached before death for a given human population (by nation, by current age, or by other demographic variables). Life expectancy may also refer to the expected time remaining to live, and that too can be calculated for any age or for any group.
   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

Life expectancy over human history

Life expectancy is the average number of years a human has before death, conventionally calculated from the time of birth, but also can be calculated from any specified age.
   One of the biggest jumps in life expectancy coincided with the introduction of sewers, which greatly reduced the spread of disease. In the last few centuries a strong statistical effect was caused by the near elimination of infant mortality in the Western world and elsewhere. Average life expectancy before the health transition of the modern era is thought to have varied between about 20 years and 40 years. It is important to note that most people who quote pre-modern life expectancies include infant mortality in their calculations. Also, the life expectancy for women was lower throughout history than it was for men; because, until modern medicine, one in four women died in childbirth. If you survived childhood you could expect to live into your old age in any time throughout history. It has been suggested that life expectancy fell with the introduction of plant and animal domestication because of:
  • higher infection rates caused by the quick increase in human settlement size and density,
  • poorer nutrition due to low dietary variety.
Advances in sanitation, nutrition, and medical knowledge made possible incredible changes in life expectancy in the United States and throughout the world, providing subjects for study as well as the need to study them. In the United States, only 50 percent of children born in 1900 could reasonably hope to reach the age of 50; life expectancy today is approximately 77 years of age. But note that there's a big discrepancy between males and females, 73.6 years for men and 79.4 years for women. Life expectancy is lower for African Americans; 67.2 years for men and 74.7 years for women (Hoyert, Kochanek, and Murphy, 1999).
   Life expectancy recovered somewhat, but it's only in recent centuries that it has dramatically increased. These changes are the result of a combination of factors including nutrition and public health, and medicine only marginally. The most important single factor in the increase is the reduction of death in infancy.
   The greatest improvements have been in the richest parts of the world. Life expectancy increased dramatically in the 20th century. Life expectancy at birth in the United States in 1900 was 47 years. Life expectancy in India at mid-century was around 32, by 2000 it had risen to 64 years. According to the 2006 WHO Report, due to HIV/AIDS and other health related issues today's life expectancy in poorer nations is almost half that of the industrialized, richer nations (External Link).
   Calculating life expectancy from birth emphasizes contributions to improvement in health at lower ages; low pre-modern life expectancy is influenced by high infant and childhood mortality. If a person did make it to the age of forty they'd an average of another twenty years to live. Improvements in sanitation, public health, and nutrition have mainly increased the numbers of people living beyond childhood, with less effect on overall average lifetimes.
   The major exception to this general pattern of improvement has been in countries most affected by AIDS, especially Sub-Saharan Africa, which have seen significant decrements in life expectancy. Another exception is Russia and some other former USSR republics after the collapse of the Soviet Union - in 1999 life expectancy of men dropped to 59.9 years (below the official retirement age), and the life expectancy of women dropped to 72.43 years. The commonly offered hypothesis for this decrease isn't related to AIDS/HIV but rather to an increase in alcohol and drug abuse.
   In recent years, obesity-related diseases have become a major public health issue in many countries. The prevalence of obesity is thought to have reduced life expectancy by contributing to the rise of cancers, heart disease and diabetes in the developed world. However, recent studies in the developed world have found "that people who are modestly overweight have a lower risk of death than those of normal weight." It remains to be determined whether this epidemic will have negative effect on the life expectancy of developed countries. Most continue to have improving life expectancies.

Timeline for humans

Homo sapiens live on average 32.6 years in Swaziland and on average 81 years in Australia. 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's no scientific proof 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 is a similar species of modern humans but is still in any case a fellow member of the genus Homo.
Upper Paleolithic 33 At age 15: 39 (to age 54)
Neolithic 20  
Bronze Age 18  
Classical Greece 20-30  
Classical Rome 20-30  
Pre-Columbian North America 25-35  
Medieval Britain 20-30  
Early 20th Century 30-40  
Current world average 67
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 raises 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 affluent nations today.

Variations in life expectancy in the world today

There are great variations in life expectancy worldwide, mostly caused by differences in public health, medicine and nutrition from country to country.
   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. In France, significant differences in life expectancy between different racial and ethnic groups have persisted, though they've lessened somewhat. Poverty, in particular, has a very substantial effect on life expectancy. In the United Kingdom life expectancy in the wealthiest areas is 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's little increase.
   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.

Evolution and aging rate

The different lifespans of different plants and animals, including humans, raises the question of why such lifespans are found.
   The evolutionary theory is 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 change to the organism (for example a bird might evolve stronger wings) may mean that it's exceptionally capable of escaping from predation, then it'll live longer, and typically die of old age. It will also be more likely to survive to reproduce, so these genes will spread through the gene pool. Thus, a member of the population with the better wings who by chance also has genes that code for better repair will spend a longer time than its contemporaries in the best reproductive years and have more successors. Its genes will tend to dominate more and more of the gene pool and genes for slower aging and by a similar argument a slower reproduction rate, will dominate.
   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's 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 bird'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've already developed short term survival to a significant extent by ensuring their dominance of the food chain. This is known as artificial selection.

Higher female life expectancy

If one doesn't 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 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 they drive cars or motorcycles. (External Link) 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's twice as much money dedicated breast cancer than to prostate cancer. (External Link) The United States has an office dedicated to women's health while there isn't one for men. The situation is mirrored in other industrialized countries.
   Some argue that shorter male life expectancy is merely another manifestation of the general rule, in all mammal species, that larger individuals tend on average to have shorter lives. (External Link) 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. (External Link)
  • Small dog breeds like poodles and dachshunds can reach 15 years of age, while the big breeds like German shepherds seldom reach 10 years of age. (External Link) In their menstruation cycle females regularly lose some blood, which rids them of toxic heavy metals and of iron, which causes oxidative stress. Human females have two X-Chromosomes while males have only one, thus males are more prone for X-linked hereditary diseases than females.

    Lower life expectancy in people with serious mental illness

    Persons with serious Mental illness die 25 years earlier than the general public.
  • PDF Morbidity and Mortality in People with Serious Mental Illness
  • Serious Mental Illness Suffer From Lack of Integrated Care, Psychiatry News January 5, 2007 Volume 42, Number 1, page 5 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.

    Calculating life expectancies

    The starting points for calculating life expectancies is the age-specific death rates of the population members. For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, then the age-specific death rate at age 90 would be 10%.
       These values are then used to calculate a life table, from which one can calculate the probability of surviving to each age. In actuarial notation the probability of surviving from age x to age x+n is denoted ,_np_x! and the probability of dying during age x (for example between ages x and x+1) is denoted q_x!.
       The life expectancy at age x, denoted ,e_x!, is then calculated by adding up the probabilities to survive to every age. This is the expected number of complete years lived (one may think of it as the number of birthdays they celebrate). » e_x =sum_

    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's 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've 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 (for example, the Lee-Carter model).

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