Understanding life expectancy
Life expectancy is a statistical measure that indicates the average number of years an individual is expected to live based on current mortality rates. This measurement is often utilized to assess and compare the health and economic conditions of populations, as it can highlight disparities between different geographic areas, ethnic groups, and socioeconomic statuses. Factors influencing life expectancy include healthcare quality, environmental conditions, and lifestyle behaviors such as smoking or physical activity. For instance, in the United States, a newborn female's life expectancy was approximately 80.2 years, compared to about 74.8 years for newborn males in recent estimates.
Life expectancy is not limited to humans; it is also applied to products and machinery to determine their average lifespan and inform warranty periods. Actuarial tables and statistical methods are essential for accurately calculating life expectancy, especially in populations where complete data may not be available. Historical data shows that life expectancy has improved significantly over the past century, although recent events such as the COVID-19 pandemic have caused notable declines. Understanding life expectancy is crucial for informing public health policies and improving overall community well-being.
Understanding life expectancy
- SUMMARY: Estimating life expectancy in present populations relies on actuarial tables.
Life expectancy for an individual is the average number of years remaining until death. It is often used to quantify risk of certain characteristics or behaviors as well as to evaluate and compare populations in terms of economics and health. For example, according to the Center for Disease Control (CDC), the life expectancy for a female in the United States is 80.2 years old. Life expectancy can also be applied to machines or appliances, for product development, to manufacturing quality control, and for the determination of warranty periods. Most incandescent light bulb packages have the life expectancy printed on the packaging. A typical value is 900 hours of use. In this type of application, life expectancy is used as a measure of quality. The calculation of life expectancies can be as simple as taking averages, but normally it uses more advanced mathematics or sampling.
Human Life Expectancy
For human populations, factors affecting life expectancy include resource availability, sanitary practices, healthcare quality, war and sociopolitical factors, cultural and behavior factors, genetic and demographic factors, environmental factors, and epidemics. An increase or decrease in life expectancy may be quoted to describe the risk of a behavior or activity. As an example of using mathematics to make decisions, mathematician James Stein provides the statistic that each hour driven on an interstate highway decreases life expectancy by nineteen minutes, while each hour flying decreases life expectancy by only thirteen minutes, thus illustrating that flying may be a safer mode of transportation. To quantify the risk in smoking, the U.S. Centers for Disease Control and Prevention (CDC) states that the average life expectancy for a smoker is approximately fourteen years less than a nonsmoker.
In the United States, various organizations predict and project life expectancy aside from the CDC, including the Congressional Budget Office (CBO), the Census Bureau, and the Social Security Administration (SSA). In 2024, the CBO estimated life expectancy to be 78.7 years, the SSA estimated it at 78.9 years, and the Census Bureau had the highest estimate for life expectancy at 79.9 years old.
Comparing Populations
The life expectancy of newborns is often quoted to compare the relative health of populations in different geographic areas as well as for differences between ethnic or socioeconomic groups, sexes, historical periods, or age groups. The populations being compared may differ in time, geographic region, or demographic characteristics. To compare populations from different time periods, the life expectancy of a newborn in the United States in the early 1900s was about 47 years, improving to about 60 years by the mid-1930s, and further improving to about 78 years by 2009. By 2018, life expectancy of a newborn was 78.7. The 2020s saw a decrease in life expectancy, and in 2022, life expectancy at birth was 77.5 years according to the CDC. The decline was due to the COVID-19 pandemic, which killed around 16 million people worldwide according to the Global Burden of Disease Study 2021, which was published in 2024.
Life expectancy can vary by gender and race. Historically, females have typically exhibited a higher life expectancy than males. As mentioned, the life expectancy of a newborn female in the United States was estimated to be 80.2 years in 2021, compared to 74.8 years for a newborn male. Also in 2021, a newborn White male had a life expectancy of 74 years, compared to 67.6 years for a newborn Black male. According to the United Nations World Population Prospects 2019 Revision, the world life expectancy for a newborn in 2015–20 was estimated at 72.6 years. Central African Republic exhibited the lowest life expectancy at birth for an individual country—approximately 52 years. The latter was attributed to the high HIV/AIDS mortality and poor healthcare and socioeconomic conditions in sub-Saharan Africa.
For populations that lived in the past, the life expectancy can be calculated by taking the average of the age at death for all of the individuals who lived in the population of interest. For this type of calculation, one normally needs detailed records of dates of births and deaths for the entire population. The first life tables constructed in this way are attributed to John Graunt (1620–1674), who also provided estimated life expectancies in his tables. Following Graunt, a notable life table constructed from birth and funeral data for the purpose of determining life annuity values was published in 1693 by Edmund Halley (Halley’s Comet is named after him) for the city of Breslaw, Poland. Halley used this city for his table because he thought Breslaw was representative of an average European population at the time. Interestingly, Halley provided his own definition of “life expectancy” in describing the third use of his table. In Halley’s description, the expected future years a person of a certain age can reasonably expect to live is the proposed number of years upon which an even wager, which is a bet with a 50-50 chance of being won, can be made that the person arrives at that age before he dies. Halley’s description is that of the median future lifetime, which differs mathematically from the more modern definition of life expectancy.
Sampling and Estimation
In the absence of complete data, modern statistical methods, including sampling, are used to estimate the average age at death. Similar statistical methods are used to estimate the life expectancy of appliances, components, and machines. In the case of inanimate objects, life expectancy may be interpreted as the average time to failure. To estimate the average time to failure, a sample may be taken and tested in a laboratory environment, or failure statistics may be kept after the product goes to market. The failure rates obtained from such data not only provide a basis for determining the life expectancy of the product, but also can be used in determining the cost of a warranty or guarantee issued by the manufacturer.
In modern populations, actuarial tables are developed that estimate the probability of death at any particular age. These probabilities are used to calculate the life expectancy for an individual at his or her current age. For example, suppose a male age 96 is within a population whose mortality table indicates the probability of a male age 96 dying before age 97 is 0.45; the probability of surviving to age 97 and dying before age 98 is 0.35; and the probability of surviving to age 98 and dying before age 99 is 0.2. Then the expected age at death is calculated as the expected value,
96(0.45) + 97(0.35) + 98(0.1) + ½ = 97.25.
Hence, the life expectancy is 1.25 years. The term “1/2” in the expected age at death calculation reflects the assumption that the individual dying within the year lives on average one-half the year.
Bibliography
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