Actuarial tables provide statistical information on life expectancy in a given population, separated by risk factors. They are used by policymakers, social scientists, and insurance companies to make decisions about retirement ages, government benefits, and insurance policies. However, they represent statistical probability only and may not accurately reflect individual circumstances.
Actuarial tables are statistical charts that provide information on life expectancy in a given population, generally separated by risk factors to provide more meaningful data. Typically, the charts divide the information between men and women, but may also consider factors such as smoking history or socioeconomic class. People use actuarial tables in a variety of ways, from studying a population to determining how much to charge for insurance.
The table provides a list of ages along one axis, and data for each age along the other. The chart will also indicate the year to which the actuarial table refers, as life expectancy can vary, depending on the time when people are being tested. 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 age and how many more years to live they have, statistically. The probability of death for any age cohort can fluctuate, as some age ranges tend to be more dangerous than others. For example, babies in their first year of life have a higher chance of death 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 helpful. Policymakers often need to think about life expectancy when developing proposals for policy changes related to retirement ages and government benefits for retirees. Social scientists are often interested in comparing cadres across different races and other groups, while insurance companies use actuarial tables to make decisions about what types of policies to write and for whom. Historical tables are often of interest to people looking at the quality of life and the composition of society at different times. Record keeping was variable at different times in history, but it is often possible to put together very detailed and accurate death tables for the oldest human societies with some work.
These plots represent statistical probability only. In any group of 100,000 people, there will be some deviations from an actuarial table. Some people may have multiple risk factors that could make it difficult to categorize them in a table, and going too deep into the data can be difficult. Actuarial tables can do something like break down smokers by gender and race to assess life expectancy, but the number of fields needed to convey the information can quickly become overwhelming.
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