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Actuarial tables are statistical charts providing information about life expectancy in a given population, usually separated by risk factors to provide more meaningful data. Commonly, the charts split the information between men and women but they may also consider factors like smoking history or socioeconomic class. People use actuarial tables in a variety of ways, ranging from studying a population to determining how much to charge for insurance.
The table offers a list of ages along one axis, and data about each age along the other. The chart will also note the year the actuarial table refers to, as life expectancy can vary, depending on the era people are examining. A historian compiling tables for the Middle Ages, for example, would have a very different result than an insurance company looking at life expectancy in 2020.
Actuarial tables list the number of people per 100,000 likely to be alive at any given age and how many more years of life they have left, statistically. The probability of death for any given age cohort can fluctuate, as some age ranges tend to be more dangerous than others. For example, infants in their first year of life have a higher death probability than two year olds. Some charts also consider the number of years people can expect to live without a disability.
Also known as life or mortality tables, these documents can be very useful. Policymakers often need to think about life expectancy when they are developing proposals for changes in policies surrounding retirement ages and government benefits to retirees. Social scientists are often interested in comparing charts for different races and other groups, while insurance companies use actuarial tables to make decisions about what kinds of policies to write and for whom. Historical tables are often of interest to people looking at quality of life and the makeup of society in different eras. Record-keeping was variable at different points in history, but it is often possible to assemble very detailed and accurate mortality tables for older human societies with some work.
These charts represent only statistical probability. In any given group of 100,000 people, there will be some deviations from an actuarial table. Some people may have multiple risk factors that could make them difficult to categorize on a table, and drilling the data down too far can be difficult. Actuarial tables may do something like breaking smokers down by gender and race to evaluate life expectancy, but the number of fields necessary to convey the information can quickly become overwhelming.
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