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Mortality Table: Definition, Types, and Uses

The Intricacies of Mortality Tables and Insurance PoliciesHave you ever wondered how insurance companies determine the rates for their policies? Or how they manage their liabilities?

If so, you’re in the right place. In this article, we will explore the fascinating world of mortality tables, life tables, and actuarial tables.

We will also delve into the factors that influence insurance policies, such as age, gender, smoking status, occupation, socio-economic class, and weight. So, let’s dive in!

Mortality Tables and Insurance Policies

Understanding Mortality Tables

At the heart of insurance calculations lie mortality tables, also known as life tables or actuarial tables. These tables provide invaluable insights into the rate of deaths within a given population.

By examining the survival rates at various ages, insurance companies can estimate the probability of death and structure their policies accordingly. Mortality tables are derived from historical data and refined over time to reflect changing demographics and medical advancements.

The Role of Mortality Tables in Insurance Policies

Now that we grasp the significance of mortality tables, let’s explore how insurance companies utilize this information. By studying mortality patterns, insurers can determine the appropriate rates for their policies.

The higher the probability of death at a certain age, the higher the premium for coverage. For example, individuals with pre-existing medical conditions may have higher premiums due to an increased risk of mortality.

These tables also aid in liability management, with insurers balancing their exposure to payouts with the revenue generated from premiums.

Factors Influencing Insurance Policies

Factored Variables and Probability of Death

When calculating insurance rates, insurers consider a variety of factors that contribute to the probability of death. These variables encompass the characteristics of the individuals they insure and the collective traits of the population they belong to.

By analyzing the interplay of these factors, actuaries can formulate accurate predictions on mortality rates, enabling insurance companies to offer appropriate coverage and pricing.

Examining the Influential Factors

Let’s now explore some of the key factors that influence insurance policies. First and foremost is age, as mortality rates generally increase with advancing years.

Gender is another influential factor, with statistics showing that women tend to live longer than men. Smoking status also plays a significant role, as tobacco use is strongly associated with numerous health complications.

Occupation and socio-economic class are additional factors taken into account, as certain professions and living conditions may impact mortality rates. Lastly, weight, or body mass index (BMI), is considered, as obesity can lead to a variety of health issues.


In this article, we have uncovered the intricacies of how insurance companies determine their rates and manage their liabilities. By utilizing mortality tables, insurers can make informed decisions when pricing policies to ensure a proper balance between risk and affordability.

Additionally, the various factors explored, including age, gender, smoking status, occupation, socio-economic class, and weight, contribute to the determination of insurance premiums. Armed with this knowledge, you can now better understand the factors at play when obtaining insurance coverage.

Life Insurance Industry and Coverage Policies

The Role of the U.S. Social Security Administration

When it comes to understanding the intricacies of mortality tables and life insurance coverage, the U.S. Social Security Administration (SSA) plays a vital role. The SSA collects extensive data on mortality rates from the general population, enabling insurance companies to make informed decisions.

These statistics provide valuable insights into the expected lifespan of individuals at different ages and serve as a foundation for determining coverage policies. By utilizing the data collected by the SSA, insurance companies can accurately assess risk and establish appropriate rates for life insurance policies.

Raymond Pearl and Ecological Studies

Raymond Pearl, an American biologist, made significant contributions to the field of mortality studies. Through his pioneering work in ecological studies, Pearl developed methods to understand and predict mortality patterns within populations.

His research focused on understanding the various factors that influence mortality rates, including age, health conditions, and lifestyle choices. By examining the relationships between these factors and mortality rates, Pearl provided valuable insights that have contributed to the development of mortality tables and insurance policies.

Period Life Table and Cohort Life Table

Understanding the Period Life Table

A period life table is a type of mortality table that provides valuable information about mortality rates during a specific time period. The table presents data on the number of people alive in a population at each age and the probability of dying at each age.

By examining a period life table, insurance companies gain a comprehensive understanding of mortality rates for a given population within a specific time frame.

The Applicability of Cohort Life Table to Actuarialism

In contrast to the period life table, a cohort life table examines the mortality rates of a specific group of individuals born within a particular time frame, or cohort. This type of table allows insurance companies to analyze the mortality rates of a generation throughout their entire lifespan.

The cohort life table accounts for the changes in mortality rates that occur over time due to factors such as medical advancements, lifestyle changes, and socioeconomic developments. By using a cohort life table, insurers can tailor their policies more accurately to the specific needs and risks of different generations.


In this expanded article, we have delved deeper into the topics of the life insurance industry and coverage policies. We have explored the role of the U.S. Social Security Administration in providing valuable data for mortality analysis, as well as the contributions of Raymond Pearl to ecological studies and mortality research.

Additionally, we have examined the significance of both period and cohort life tables in understanding mortality rates for insurance purposes. Armed with this knowledge, individuals can better understand the factors that influence coverage policies and make informed decisions regarding their life insurance needs.

Characteristics and Probabilities in Mortality Tables

Understanding the Characteristics and Probabilities

Mortality tables are comprehensive tools used in the insurance industry to determine the rates for life insurance policies. These tables take into account various characteristics, such as gender and age, to calculate the probabilities of death per thousand individuals within a specific population.

By analyzing these probabilities, insurance companies can accurately assess the risks associated with different policyholders and set appropriate premiums. Gender is one crucial characteristic that influences mortality rates.

Statistics consistently show that women tend to live longer than men, leading to differences in mortality probabilities between the two genders. Age is another essential factor.

As individuals grow older, the likelihood of mortality increases. Mortality tables provide insight into these age-specific probabilities, which enable insurance companies to tailor their policies and premiums accordingly.

The Role of Mortality Tables in Premiums and Solvency

Mortality tables play a critical role in determining premiums for life insurance policies. By using these tables and their associated probabilities, insurance companies can calculate the appropriate rates based on the potential risks.

For example, if the mortality probabilities indicate higher risks associated with a particular demographic group, such as older individuals, insurance premiums for that group may be higher. Furthermore, mortality tables are essential tools for ensuring the solvency of insurance companies.

Insurers rely heavily on actuarial science to manage their risks and liabilities. By analyzing mortality rates, insurers can estimate the number of deaths expected per thousand individuals and project their financial obligations accurately.

This information allows insurance companies to balance their payout commitments with the revenue generated from premiums, ensuring the long-term stability and solvency of the industry.

Life Expectancy and Mortality Tables

Newborn Males and Life Expectancy

Life expectancy is a crucial concept derived from mortality tables that provides insights into the expected lifespan of individuals from birth. In the case of newborn males, life expectancy is an estimate of the average number of years they are expected to live based on current mortality rates.

This information is vital for both individuals and insurance companies in determining appropriate coverage and premiums.

From 119-Year-Old Man to Mortality Tables

At the other end of the age spectrum, mortality tables play a significant role in understanding the life expectancy of individuals who have already surpassed the average lifespan. In 2005, a man named Henry Allingham, at the remarkable age of 113, was included in the UK’s national mortality tables.

This demonstrates how mortality tables are a dynamic tool that researchers utilize to capture the changing trends in life expectancy and mortality rates. The data collected from individuals like Henry Allingham contributes to the ongoing refinement of mortality tables.

For instance, the U.S. Social Security Administration collects vast amounts of data on mortality rates from individuals throughout their lives, providing valuable insights into life expectancy. These statistics help insurers make accurate projections and assess the long-term risks associated with life insurance policies.


In this expanded article, we have explored the characteristics and probabilities considered in mortality tables, highlighting the importance of gender and age in determining mortality rates. We have discussed how mortality tables play a crucial role in setting premiums for life insurance policies and ensuring the solvency of insurance companies.

Additionally, we have examined the significance of mortality tables in estimating life expectancies, from newborn males to individuals who have surpassed the average lifespan. By utilizing the information from mortality tables, insurance companies can offer appropriate coverage and premiums while maintaining their financial stability.

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