Life expectancy

• 1. Defining The Measure

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  Human life expectancy is a statistical measure of the estimate of the average remaining years of life at a given age. The most commonly used metric is life expectancy at birth, often denoted as e0 in demographic notation. This figure represents the mean length of life for a hypothetical cohort exposed to current mortality rates from birth through death. National agencies and international organizations report these figures as estimates of period life expectancy rather than actual historical data. A different approach called cohort life expectancy measures the mean length of life for all individuals born in a specific year. This calculation can only be performed once every member of that birth group has died. Such cohorts must be born so long ago that their entire lifespan is complete history.

• 2. Historical Evolution

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  Human remains from the early Bronze Age indicate an LEB of 24 years. In 2019, world LEB reached 73.3 years according to global health data. A combination of high infant mortality and deaths in young adulthood significantly lowers this average number before modern medicine was widely available. For example, a society with a LEB of 40 would have relatively few people dying at exactly 40. Most will die before 30 or after 55 due to accidents, epidemics, plagues, wars, and childbirth. Life expectancy at age 5 provides a simple measure of overall mortality rates other than in early childhood. Pre-modern societies had universally higher mortality rates and lower life expectancies at every age for both males and females. The earliest documented work on life expectancy dates back to the 1660s by John Graunt, Christiaan Huygens, and Lodewijck Huygens. During the Industrial Revolution, the life expectancy of children increased dramatically in many regions.

• 3. Regional Disparities

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  Human beings are expected to live on average 60 years in Eswatini and 82.6 years in Japan. An analysis published in 2011 in The Lancet attributes Japanese life expectancy to equal opportunities, excellent public health, and a healthy diet. The World Health Organization announced that the COVID-19 pandemic reversed the trend of steady gain in life expectancy at birth. The pandemic wiped out nearly a decade of progress in improving life expectancy globally. In Africa, countries have generally not had the same improvements in mortality rates enjoyed by nations in Asia, Latin America, and Europe over the last 200 years. This is most apparent by the impact of AIDS on many African countries. According to projections made by the United Nations in 2002, the life expectancy at birth for 2010, 2015 would have been 70.7 years instead of 31.6 years in Botswana if HIV/AIDS did not exist. Eastern Europeans tend to live shorter lives than their western counterparts due to poor health habits and environmental factors like high air pollution.

• 4. Biological And Genetic Factors

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  The heritability of lifespan is estimated to be less than 10%, meaning the majority of variation in lifespan is attributable to differences in environment rather than genetic variation. Researchers have identified regions of the genome which can influence the length of life and the number of years lived in good health. A genome-wide association study of 1 million lifespans found 12 genetic loci which influenced lifespan by modifying susceptibility to cardiovascular and smoking-related disease. The locus with the largest effect is APOE. Carriers of the APOE ε4 allele live approximately one year less than average per copy of the ε4 allele. In July 2020, scientists identified 10 genomic loci with consistent effects across multiple lifespan-related traits including healthspan and longevity. These genes affected haem metabolism as a promising candidate for further research within the field. One recent suggestion is that mitochondrial mutations which shorten lifespan continue to be expressed in males because mitochondria are inherited only through the mother.

• 5. Societal Determinants

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  Mental illness is reported to occur in approximately 18% of the American population. The mentally ill have been shown to have a 10- to 25-year reduction in life expectancy compared to the mentally stable population. The greater mortality of people with mental disorders may be due to death from injury, co-morbid conditions, or medication side effects. For instance, psychiatric medications can increase the risk of developing diabetes. Education on all levels has been strongly associated with increased life expectancy. According to a paper from 2015, the mortality rate for the Caucasian population in the United States from 1993 to 2001 is four times higher for those who did not complete high school compared to those with at least 16 years of education. Preschool education also plays a large role in life expectancy as found by analyzing results of the Carolina Abecedarian Project. Economic circumstances affect life expectancy significantly where disparities exist between wealthy and poor areas.

• 6. Demographic Forecasting

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  Forecasting life expectancy and mortality form an important subdivision of demography used for policy planning regarding old-age support programs like Social Security and pensions. Future trends in life expectancy have huge implications since cash flow in these systems depends on the number of recipients still living. Life expectancy forecasting usually relies on one of two different approaches involving time-series extrapolation procedures or age-specific death rates. The most important approach in this group is the Lee, Carter model which uses singular value decomposition on transformed age-specific mortality rates. This method reduces dimensionality to a single time series before recovering full sets of age-specific mortality rates from that forecasted value. Software includes Professor Rob J. Hyndman's R package called 'demography' and UC Berkeley's LCFIT system. As of 2025, some AI apps claim to be able to predict individual life expectancy through population statistics and individual factors.