Mortality tables analyze these factors and provide highly accurate predictions for large populations, but they only offer statistical estimates for individuals. For example, the life expectancy of two people of the same age and gender may differ significantly if one is a smoker or suffers from a chronic illness. While these predictions help determine insurance premiums and retirement planning, they do not account for random events or all potential health changes. Life expectancy calculations are averages or probabilities, not guarantees or precise predictions of an individual’s lifespan.

Family medical history, including conditions affecting parents and grandparents, as well as genetic predispositions to diseases like cancer, heart disease, and diabetes, also significantly influences life expectancy estimates. Lifestyle choices, such as smoking, alcohol and drug use, diet, exercise, and engagement in risky activities, also play a significant role in determining life expectancy and influence insurance premiums, both in terms of value and duration. High-risk occupations, such as mining, construction, and aviation, as well as dangerous hobbies like diving and horse racing, elevate the risk of death and factor into life expectancy calculations. Also, lower socioeconomic status is often linked to reduced life expectancy, primarily due to limited access to healthcare and increased exposure to health risks.

Questionnaires, medical examinations, and statistical models are commonly used to estimate an individual’s life expectancy and determine insurance premiums. Half a century ago, I conducted a calculation using specific tables that assigned points to various factors. The result of that calculation suggested I could live to be 96. I recently repeated the experiment, and the outcome was nearly the same. This is because my health, habits, and lifestyle have remained relatively unchanged over the years!