The people from “Our World in Data” have produced yet another insightful chart. It illustrates well the importance of “life expectancy” measures.
The first thing that jumps out is that even in 1790 if you lived to the age of 45 you had a fifty-fifty chance of making it to 70. The carnage of child mortality produces a low average life expectancy. In 1800 only 46% of newborns did not make it to their fifth birthday. ( It was a very bad year). If you could survive to the age of 45 you would have a reasonable life expectancy.
For men that life expectancy stays almost flat until 1950 or even 1960. Only then does the impact of modern medicines and a focus on the diseases of the old, make a difference. My father was born in 1918 so his was the first generation to benefit from this change. Child mortality by 1960 had dropped to 3.5%. By 2021 it was 5.4 deaths per 1000 children. There is a real danger of being blinded by the averages.
We have to work hard to understand societies then. Children died routinely in large numbers. Families were large. Those that survived to reach adulthood had reasonable life expectancies.Today this situation is very different. With fertility of less than two there are many families with only one child. The loss of that child is different.
What do we Mean by Life Expectancy?
The media is full of stories about how we are all living healthier for longer. The justification is often “Life Expectancy” data. It is easy to slip into the assumption that Life Expectancy is a forecast. This is because the media fail to differentiate between the Period and Cohort measures.
Governments need life expectancy data for two different purposes. They want to measure the success of their health and social care plans. Separately they need to know the future structure of Society so that they can plan. My fathers’ generation has gone. For them we can calculate exactly how long they lived. Most of that US data in the chart was based on death tables and the age at death. Most of my generation is still alive. How then do we create useful measures?
Cohort Life Expectancy
We know that modern medicines, lifestyles, and nutrition have extended longevity significantly. Year after year medical science is tackling diseases. As each is “beaten” our life expectancy improves. If we are to forecast the life span of an individual born in 2023, how would we do it? We would look at all the data for children born in previous years. We would forecast life expectancy based on what we know today. We would then need to adjust for the improvement in medicine and health that will take place during that child’s life. We would assume that things would get better. The result is a cohort life expectancy.
Period Life Expectancy
These are the numbers most often quoted in those articles about longevity and the ageing population. It is an index of success for Governments and shows how well they have done in improving health. The Period Life Expectancy of a child born this year assumes no improvement in medical science, nutrition, and lifestyle for the rest of that child’s life. It uses the probabilities of living to different ages based on 2023. They are frozen.
It is not designed as a forecast. It is a retrospective index. It is much easier to measure than cohort expectancy. There is no standardized way of forecasting those health improvements in the cohort numbers. It is difficult therefore to make comparisons across countries and at different times. Forecasting health science adds complexity to the measure.
More Time to Enjoy Life.
The UK Office of National Statistics calculates the Period and Cohort life expectancies at any age. The impact is large. For a baby boy born in 2020, his period life expectancy is 78.4 years. We can compare this with the 56 years in 1920 to show much improvement has been made. In a hundred years we have added 22 to the average males’ life.
If we allow for health improvements during the boy’s lifetime his cohort life expectancy is 87.3 years. Nearly ten years more. Women tend to live longer. The period life expectancy of a baby girl is 82.4 but their cohort expectancy is 90.2. These are huge differences.
If we calculate a period life expectancy at 65, we are adding 65 years of health improvement. The accuracy of a cohort forecast for a 65-year-old is higher. The length of the forecast is much shorter. A 65-year-old woman today has a period life expectancy of 20.6 more years. She has a fifty- fifty chance of reaching the age of 85. If we include the forecasted improvement in medical science and health management this jumps to 87. The difference is smaller for the 65-year-olds than the newborns. There is less time for health improvements to have an impact. The Office of National Statistics offers a Cohort Life expectancy calculator based on their latest model. My cohort life expectancy is 87. However, I have a one on four chance of reaching 92 and a one in ten chance of making it to 96. If you want to try click here:
Cohort Life Expectancy It is under tab 4.
These are the overall averages. In these Newsletters we have looked at many different variables that impact on our lifespan. Deprivation, loneliness, attitudes towards ageing, education can all have an impact. My odds are probably better.
Do not be depressed by the “life expectancies” you see in the media. The period numbers understate the amount of time you have left to enjoy life. They were never intended to be forecasts.